From 938cc0e15fa733b3951121ae9f016aa606e006eb Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Mon, 16 May 2022 13:42:21 -0400 Subject: [PATCH 01/25] move models to their own files Signed-off-by: Rachel Kurchin --- src/ElectrochemicalKinetics.jl | 2 +- src/kinetic_models.jl | 240 ------------------ .../AsymptoticMarcusHushChidsey.jl | 34 +++ src/kinetic_models/ButlerVolmer.jl | 26 ++ src/kinetic_models/Marcus.jl | 35 +++ src/kinetic_models/MarcusHushChidsey.jl | 40 +++ src/kinetic_models/MarcusHushChidseyDOS.jl | 46 ++++ src/kinetic_models/kinetic_models.jl | 60 +++++ 8 files changed, 242 insertions(+), 241 deletions(-) delete mode 100644 src/kinetic_models.jl create mode 100644 src/kinetic_models/AsymptoticMarcusHushChidsey.jl create mode 100644 src/kinetic_models/ButlerVolmer.jl create mode 100644 src/kinetic_models/Marcus.jl create mode 100644 src/kinetic_models/MarcusHushChidsey.jl create mode 100644 src/kinetic_models/MarcusHushChidseyDOS.jl create mode 100644 src/kinetic_models/kinetic_models.jl diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index a465a17..8e053cc 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -5,7 +5,7 @@ export DOS using .DOS: DOSData, get_dos export DOSData, get_dos -include("kinetic_models.jl") +include("kinetic_models/kinetic_models.jl") export ButlerVolmer, AsymptoticMarcusHushChidsey export fermi_dirac export integrand diff --git a/src/kinetic_models.jl b/src/kinetic_models.jl deleted file mode 100644 index 20c7525..0000000 --- a/src/kinetic_models.jl +++ /dev/null @@ -1,240 +0,0 @@ -using .DOS -using SpecialFunctions - -""" - fermi_dirac(E, kT=0.026) - -Compute the value of the Fermi-Dirac distribution at energy `E` (relative to the Fermi energy) and thermal energy `kT`. -""" -fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) - -abstract type KineticModel end - -# dispatch for net rates, returns absolute value -(km::KineticModel)(V_app; kT = 0.026) = - abs.(km(V_app, Val(true); kT = kT) - km(V_app, Val(false); kT = kT)) - -# return a new one with a scaled prefactor -import Base.* -function *(c::Real, km::KineticModel) - new_A = c*km.A - other_params = getfield.([km], propertynames(km))[2:end] - typeof(km)(new_A, other_params...) -end - -# generic pretty printing -function Base.show(io::IO, m::KineticModel) - s = repr(typeof(m)) * "(" - for field in propertynames(m) - s = - s * - string(field) * - "=" * - string(round(getproperty(m, field), sigdigits = 3)) * - ", " - end - s = s[1:end-2] * ")" - print(io, s) -end - -""" - ButlerVolmer(A, α) - ButlerVolmer(A) - -Computes Butler-Volmer kinetics. - -If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. -""" -struct ButlerVolmer <: KineticModel - A::Float64 - α::Float64 -end - -# default to unit prefactor and symmetric response -ButlerVolmer() = ButlerVolmer(1.0, 0.5) -ButlerVolmer(A) = ButlerVolmer(A, 0.5) - -function (bv::ButlerVolmer)(V_app, ::Val{true}; kT::Real = 0.026) - exp_arg = (bv.α .* V_app) ./ kT - bv.A .* exp.(exp_arg) -end - -function (bv::ButlerVolmer)(V_app, ::Val{false}; kT::Real = 0.026) - exp_arg = -((1 - bv.α) .* V_app) ./ kT - bv.A .* exp.(exp_arg) -end - -""" - Marcus(A, λ) - Marcus(λ) - -Computes Marcus kinetics. - -If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. -""" -struct Marcus <: KineticModel - A::Float64 - λ::Float64 -end - -# default prefactor is 1 -Marcus(λ) = Marcus(1.0, λ) - -function (m::Marcus)(V_app, ox::Bool; kT::Real = 0.026) - local exp_arg - if ox - exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) - else - exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) - end - m.A .* exp.(exp_arg) -end - -function (m::Marcus)(V_app, ::Val{true}; kT::Real = 0.026) - exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) - m.A .* exp.(exp_arg) -end - -function (m::Marcus)(V_app, ::Val{false}; kT::Real = 0.026) - exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) - m.A .* exp.(exp_arg) -end - -""" - AsymptoticMarcusHushChidsey(A, λ) - AsymptoticMarcusHushChidsey(λ) - -Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/j.jelechem.2014.09.038d, with a corrction prefactor of kT since there is an error in the nondimensionalization in that work. - -If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. -""" -struct AsymptoticMarcusHushChidsey <: KineticModel - A::Float64 - λ::Float64 -end - -# default prefactor is 1 -AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) - -function (amhc::AsymptoticMarcusHushChidsey)(V_app, ox::Bool; kT::Real = 0.026) - η = (2 * ox - 1) .* V_app ./ kT - λ_nondim = amhc.λ / kT - a = 1 + sqrt(λ_nondim) - arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) - pref = sqrt(π * λ_nondim) ./ (1 .+ exp.(-η)) - return kT * amhc.A .* pref .* erfc.(arg) -end - - -function (amhc::AsymptoticMarcusHushChidsey)(V_app; kT::Real = 0.026) - η = V_app ./ kT - λ_nondim = amhc.λ / kT - a = 1 + sqrt(λ_nondim) - arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) - pref = sqrt(π * λ_nondim) .* tanh.(η/2) - return abs.(kT * amhc.A .* pref .* erfc.(arg)) -end - - -abstract type IntegralModel <: KineticModel end # "Marcus-like" - -# check to catch missed dispatches for new types -# integrand(km::IntegralModel, V_dl, ox::Bool; kwargs...) = -# error("An integral-based kinetic model must dispatch the `integrand` function!") - -# TODO: check that this passes through both kT and V_q appropriately -# dispatch for net rates -integrand(km::IntegralModel, V_dl; kwargs...) = - E -> abs.( - integrand(km, V_dl, true; kwargs...)(E) - integrand(km, V_dl, false; kwargs...)(E), - ) - -""" - MarcusHushChidsey(A, λ, average_dos) - MarcusHushChidsey(λ, average_dos) - MarcusHushChidsey(λ) - -Computes Marcus-Hush-Chidsey kinetics: 10.1126/science.251.4996.919 - -Note that for "typical" reorganization energy values (in the vicinity of 10*kT at typical temperatures, i.e. a few tenths of an eV), `AsymptoticMarcusHushChidsey` is comparably accurate to and much faster to evaluate than this model. - -If either the prefactor or the average dos are omitted, their values are assumed to be 1. Note that strictly speaking, `average_dos` and the prefactor `A` are redundant. They are both included primarily to facilitate comparisons with similarly parametrized Marcus-like models such as `MarcusHushChidseyDOS`. -""" -struct MarcusHushChidsey <: IntegralModel - A::Real - λ::Real - average_dos::Real -end - -# default prefactor is 1 -MarcusHushChidsey(λ, avg_dos) = MarcusHushChidsey(1.0, λ, avg_dos) -# assume prefactor = 1 and avg_dos = 1 -MarcusHushChidsey(λ) = MarcusHushChidsey(1.0, λ, 1.0) -# convert more detailed DOS information to just pull out average -MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, dd.average_value) -MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = - MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) - -# TODO: Check that both this and +DOS versions still match original paper -function integrand(mhc::MarcusHushChidsey, V_dl, ox::Bool; kT::Real = 0.026) - function marcus_term(E) - local exp_arg - if ox - exp_arg = -((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kT) - else - exp_arg = -((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kT) - end - exp.(exp_arg) - end - f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages - f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT) -end - - - -""" - MarcusHushChidseyDOS(A=1.0, λ, dos) - MarcusHushChidseyDOS(A=1.0, λ, dos_file) - -Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanathan: 10.1063/5.0023611 -""" -struct MarcusHushChidseyDOS <: IntegralModel - A::Float64 - λ::Float64 - dos::DOSData -end - -function Base.show(io::IO, mhcd::MarcusHushChidseyDOS) - s = repr(typeof(mhcd)) * "(" - s *= "A=$(round(mhcd.A, sigdigits=3)), λ=$(round(mhcd.λ, sigdigits=3)))" - print(io, s) -end - -# default prefactor is 1 -MarcusHushChidseyDOS(λ, dd::DOSData) = MarcusHushChidseyDOS(1.0, λ, dd) - -MarcusHushChidseyDOS(A, λ, dos_file::Union{Matrix,String}; kwargs...) = - MarcusHushChidseyDOS(A, λ, DOSData(dos_file; kwargs...)) - -MarcusHushChidseyDOS(λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(1.0, λ, DOSData(dos_file; kwargs...)) - -function integrand( - mhcd::MarcusHushChidseyDOS, - V_dl, - ox::Bool; - kT::Real = 0.026, - V_q = 0.0, -) - function marcus_term(E) - local exp_arg - if ox - exp_arg = -(( (mhcd.λ .- V_dl) .+ E) .^ 2) ./ (4 * mhcd.λ * kT) - else - exp_arg = -(( (mhcd.λ .+ V_dl) .- E) .^ 2) ./ (4 * mhcd.λ * kT) - end - exp.(exp_arg) - end - fd(E) = ox ? 1 .- fermi_dirac(E; kT = kT) : fermi_dirac(E; kT = kT) - # TODO: add two dispatches as with MHC above - E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E) .* marcus_term(E) -end diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl new file mode 100644 index 0000000..ff722a6 --- /dev/null +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -0,0 +1,34 @@ +""" + AsymptoticMarcusHushChidsey(A, λ) + AsymptoticMarcusHushChidsey(λ) + +Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/j.jelechem.2014.09.038d, with a corrction prefactor of kT since there is an error in the nondimensionalization in that work. + +If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. +""" +struct AsymptoticMarcusHushChidsey <: KineticModel + A::Float64 + λ::Float64 +end + +# default prefactor is 1 +AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) + +function (amhc::AsymptoticMarcusHushChidsey)(V_app, ox::Bool; kT::Real = 0.026) + η = (2 * ox - 1) .* V_app ./ kT + λ_nondim = amhc.λ / kT + a = 1 + sqrt(λ_nondim) + arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) + pref = sqrt(π * λ_nondim) ./ (1 .+ exp.(-η)) + return kT * amhc.A .* pref .* erfc.(arg) +end + + +function (amhc::AsymptoticMarcusHushChidsey)(V_app; kT::Real = 0.026) + η = V_app ./ kT + λ_nondim = amhc.λ / kT + a = 1 + sqrt(λ_nondim) + arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) + pref = sqrt(π * λ_nondim) .* tanh.(η/2) + return abs.(kT * amhc.A .* pref .* erfc.(arg)) +end \ No newline at end of file diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl new file mode 100644 index 0000000..84cf8a4 --- /dev/null +++ b/src/kinetic_models/ButlerVolmer.jl @@ -0,0 +1,26 @@ +""" + ButlerVolmer(A, α) + ButlerVolmer(A) + +Computes Butler-Volmer kinetics. + +If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. +""" +struct ButlerVolmer <: KineticModel + A::Float64 + α::Float64 +end + +# default to unit prefactor and symmetric response +ButlerVolmer() = ButlerVolmer(1.0, 0.5) +ButlerVolmer(A) = ButlerVolmer(A, 0.5) + +function (bv::ButlerVolmer)(V_app, ::Val{true}; kT::Real = 0.026) + exp_arg = (bv.α .* V_app) ./ kT + bv.A .* exp.(exp_arg) +end + +function (bv::ButlerVolmer)(V_app, ::Val{false}; kT::Real = 0.026) + exp_arg = -((1 - bv.α) .* V_app) ./ kT + bv.A .* exp.(exp_arg) +end \ No newline at end of file diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl new file mode 100644 index 0000000..1ccd3d0 --- /dev/null +++ b/src/kinetic_models/Marcus.jl @@ -0,0 +1,35 @@ +""" + Marcus(A, λ) + Marcus(λ) + +Computes Marcus kinetics. + +If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. +""" +struct Marcus <: KineticModel + A::Float64 + λ::Float64 +end + +# default prefactor is 1 +Marcus(λ) = Marcus(1.0, λ) + +function (m::Marcus)(V_app, ox::Bool; kT::Real = 0.026) + local exp_arg + if ox + exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) + else + exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) + end + m.A .* exp.(exp_arg) +end + +function (m::Marcus)(V_app, ::Val{true}; kT::Real = 0.026) + exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) + m.A .* exp.(exp_arg) +end + +function (m::Marcus)(V_app, ::Val{false}; kT::Real = 0.026) + exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) + m.A .* exp.(exp_arg) +end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl new file mode 100644 index 0000000..096f66a --- /dev/null +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -0,0 +1,40 @@ +""" + MarcusHushChidsey(A, λ, average_dos) + MarcusHushChidsey(λ, average_dos) + MarcusHushChidsey(λ) + +Computes Marcus-Hush-Chidsey kinetics: 10.1126/science.251.4996.919 + +Note that for "typical" reorganization energy values (in the vicinity of 10*kT at typical temperatures, i.e. a few tenths of an eV), `AsymptoticMarcusHushChidsey` is comparably accurate to and much faster to evaluate than this model. + +If either the prefactor or the average dos are omitted, their values are assumed to be 1. Note that strictly speaking, `average_dos` and the prefactor `A` are redundant. They are both included primarily to facilitate comparisons with similarly parametrized Marcus-like models such as `MarcusHushChidseyDOS`. +""" +struct MarcusHushChidsey <: IntegralModel + A::Real + λ::Real + average_dos::Real +end + +# default prefactor is 1 +MarcusHushChidsey(λ, avg_dos) = MarcusHushChidsey(1.0, λ, avg_dos) +# assume prefactor = 1 and avg_dos = 1 +MarcusHushChidsey(λ) = MarcusHushChidsey(1.0, λ, 1.0) +# convert more detailed DOS information to just pull out average +MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, dd.average_value) +MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = + MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) + +# TODO: Check that both this and +DOS versions still match original paper +function integrand(mhc::MarcusHushChidsey, V_dl, ox::Bool; kT::Real = 0.026) + function marcus_term(E) + local exp_arg + if ox + exp_arg = -((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kT) + else + exp_arg = -((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kT) + end + exp.(exp_arg) + end + f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages + f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT) +end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl new file mode 100644 index 0000000..f891d4a --- /dev/null +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -0,0 +1,46 @@ +""" + MarcusHushChidseyDOS(A=1.0, λ, dos) + MarcusHushChidseyDOS(A=1.0, λ, dos_file) + +Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanathan: 10.1063/5.0023611 +""" +struct MarcusHushChidseyDOS <: IntegralModel + A::Float64 + λ::Float64 + dos::DOSData +end + +function Base.show(io::IO, mhcd::MarcusHushChidseyDOS) + s = repr(typeof(mhcd)) * "(" + s *= "A=$(round(mhcd.A, sigdigits=3)), λ=$(round(mhcd.λ, sigdigits=3)))" + print(io, s) +end + +# default prefactor is 1 +MarcusHushChidseyDOS(λ, dd::DOSData) = MarcusHushChidseyDOS(1.0, λ, dd) + +MarcusHushChidseyDOS(A, λ, dos_file::Union{Matrix,String}; kwargs...) = + MarcusHushChidseyDOS(A, λ, DOSData(dos_file; kwargs...)) + +MarcusHushChidseyDOS(λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(1.0, λ, DOSData(dos_file; kwargs...)) + +function integrand( + mhcd::MarcusHushChidseyDOS, + V_dl, + ox::Bool; + kT::Real = 0.026, + V_q = 0.0, +) + function marcus_term(E) + local exp_arg + if ox + exp_arg = -(( (mhcd.λ .- V_dl) .+ E) .^ 2) ./ (4 * mhcd.λ * kT) + else + exp_arg = -(( (mhcd.λ .+ V_dl) .- E) .^ 2) ./ (4 * mhcd.λ * kT) + end + exp.(exp_arg) + end + fd(E) = ox ? 1 .- fermi_dirac(E; kT = kT) : fermi_dirac(E; kT = kT) + # TODO: add two dispatches as with MHC above + E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E) .* marcus_term(E) +end \ No newline at end of file diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl new file mode 100644 index 0000000..9b421a1 --- /dev/null +++ b/src/kinetic_models/kinetic_models.jl @@ -0,0 +1,60 @@ +using .DOS +using SpecialFunctions + +""" + fermi_dirac(E, kT=0.026) + +Compute the value of the Fermi-Dirac distribution at energy `E` (relative to the Fermi energy) and thermal energy `kT`. +""" +fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) + +abstract type KineticModel end + +# dispatch for net rates, returns absolute value +(km::KineticModel)(V_app; kT = 0.026) = + abs.(km(V_app, Val(true); kT = kT) - km(V_app, Val(false); kT = kT)) + +# return a new one with a scaled prefactor +import Base.* +function *(c::Real, km::KineticModel) + new_A = c*km.A + other_params = getfield.([km], propertynames(km))[2:end] + typeof(km)(new_A, other_params...) +end + +# generic pretty printing +function Base.show(io::IO, m::KineticModel) + s = repr(typeof(m)) * "(" + for field in propertynames(m) + s = + s * + string(field) * + "=" * + string(round(getproperty(m, field), sigdigits = 3)) * + ", " + end + s = s[1:end-2] * ")" + print(io, s) +end + +abstract type IntegralModel <: KineticModel end # "Marcus-like" + +# check to catch missed dispatches for new types +# integrand(km::IntegralModel, V_dl, ox::Bool; kwargs...) = +# error("An integral-based kinetic model must dispatch the `integrand` function!") + +# TODO: check that this passes through both kT and V_q appropriately +# dispatch for net rates +integrand(km::IntegralModel, V_dl; kwargs...) = + E -> abs.( + integrand(km, V_dl, true; kwargs...)(E) - integrand(km, V_dl, false; kwargs...)(E), + ) + + +include("ButlerVolmer.jl") +include("Marcus.jl") +include("AsymptoticMarcusHushChidsey.jl") +include("MarcusHushChidsey.jl") +include("MarcusHushChidseyDOS.jl") + + From cf0da52adea29ffd45f1c2537b462907e083c52c Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Mon, 16 May 2022 15:35:01 -0400 Subject: [PATCH 02/25] make utils folder, remove rate_constant and put compute_k into relevant files Signed-off-by: Rachel Kurchin --- src/ElectrochemicalKinetics.jl | 8 +- src/kinetic_models/MarcusHushChidseyDOS.jl | 118 +++++++++++++++- src/kinetic_models/kinetic_models.jl | 41 ++++++ src/rate_constant.jl | 148 --------------------- src/{ => utils}/dos.jl | 0 src/{ => utils}/integration_utils.jl | 0 src/{ => utils}/quantum_capacitance.jl | 0 7 files changed, 160 insertions(+), 155 deletions(-) delete mode 100644 src/rate_constant.jl rename src/{ => utils}/dos.jl (100%) rename src/{ => utils}/integration_utils.jl (100%) rename src/{ => utils}/quantum_capacitance.jl (100%) diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index 8e053cc..f4170e1 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -1,6 +1,6 @@ module ElectrochemicalKinetics -include("dos.jl") +include("utils/dos.jl") export DOS using .DOS: DOSData, get_dos export DOSData, get_dos @@ -11,14 +11,10 @@ export fermi_dirac export integrand export KineticModel, IntegralModel export Marcus, MarcusHushChidsey, MarcusHushChidseyDOS - -include("quantum_capacitance.jl") - -include("rate_constant.jl") export compute_k, compute_k_cq include("fitting.jl") -include("integration_utils.jl") +include("utils/integration_utils.jl") export fitting_params, fit_model, fit_overpotential, is_dosmodel include("phase_diagrams.jl") diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index f891d4a..bac5047 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -1,3 +1,5 @@ +include("../utils/quantum_capacitance.jl") + """ MarcusHushChidseyDOS(A=1.0, λ, dos) MarcusHushChidseyDOS(A=1.0, λ, dos_file) @@ -43,4 +45,118 @@ function integrand( fd(E) = ox ? 1 .- fermi_dirac(E; kT = kT) : fermi_dirac(E; kT = kT) # TODO: add two dispatches as with MHC above E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E) .* marcus_term(E) -end \ No newline at end of file +end + +function compute_k( + V_app, + model::MarcusHushChidseyDOS, + ox::Bool; + kT = 0.026, + E_min = model.dos.E_min, + E_max = model.dos.E_max, + calc_cq::Bool = false, + C_dl = 10.0, + Vq_min = -0.5, + Vq_max = 0.5, + kwargs..., +) + if calc_cq + compute_k_cq( + V_app, + model, + ox; + C_dl = C_dl, + Vq_min = Vq_min, + Vq_max = Vq_max, + kT = kT, + E_min = min(E_min, E_min-Vq_min), + E_max = max(E_max, E_max-Vq_max), + ) + else + n, w = scale(E_min, E_max) + f = integrand(model, V_app, ox; kT = kT) + sum(w .* f.(n)) + end +end + +function compute_k( + V_app, + model::MarcusHushChidseyDOS; + kT = 0.026, + E_min = model.dos.E_min, + E_max = model.dos.E_max, + calc_cq::Bool = false, + C_dl = 10.0, + Vq_min = -0.5, + Vq_max = 0.5, + kwargs..., +) + if calc_cq + compute_k_cq( + V_app, + model; + kT = kT, + E_min = max(E_min, E_min-Vq_min), + E_max = min(E_max, E_max-Vq_max), + C_dl = C_dl, + Vq_min = Vq_min, + Vq_max = Vq_max, + ) + else + # invoke( + # compute_k, + # Tuple{typeof(V_app),IntegralModel}, + # V_app, + # model; + # kT = kT, + # E_min = E_min, + # E_max = E_max, + # ) + n, w = scale(E_min, E_max) + f = integrand(model, V_app; kT = kT) + sum(w .* f.(n)) + end +end + +""" + compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS, ox::Bool; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) + compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) + +Compute the rate constant k predicted by a `MarcusHushChidseyDOS` model at a applied voltage `V_app`, including the effects of quantum capacitance. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate. +""" +function compute_k_cq( + V_app, + model::MarcusHushChidseyDOS, + ox::Bool; + C_dl = 10.0, + Vq_min = -0.5, + Vq_max = 0.5, + kT = 0.026, + E_min = model.dos.E_min, + E_max = model.dos.E_max, +) + V_dl_interp = calculate_Vdl_interp(model.dos.interp_func, Vq_min, Vq_max, C_dl) + V_dl = V_dl_interp(V_app) + V_q = V_app - V_dl + n, w = scale(E_min, E_max) + f = integrand(model, V_dl, ox; kT = kT, V_q = V_q) + sum(w .* f.(n)) +end + +function compute_k_cq( + V_app, + model::MarcusHushChidseyDOS; + C_dl = 10.0, + Vq_min = -0.5, + Vq_max = 0.5, + kT = 0.026, + E_min = model.dos.E_min, + E_max = model.dos.E_max, +) + V_dl_interp = calculate_Vdl_interp(model.dos.interp_func, Vq_min, Vq_max, C_dl) + V_dl = V_dl_interp(V_app) + V_q = V_app - V_dl + n, w = scale(E_min, E_max) + f = integrand(model, V_dl; kT = kT, V_q = V_q) + sum(w .* f.(n)) +end diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index 9b421a1..d08056f 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -1,5 +1,8 @@ using .DOS using SpecialFunctions +using Statistics +using Interpolations +using DelimitedFiles """ fermi_dirac(E, kT=0.026) @@ -8,6 +11,11 @@ Compute the value of the Fermi-Dirac distribution at energy `E` (relative to the """ fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) +""" + KineticModel + +Abstract base class for kinetic models. All subtypes need to dispatch the `compute_k` function. +""" abstract type KineticModel end # dispatch for net rates, returns absolute value @@ -37,6 +45,11 @@ function Base.show(io::IO, m::KineticModel) print(io, s) end +""" + IntegralModel + +Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `compute_k` function directly, or dispatch the `integrand` function and use the default `compute_k` dispatch. +""" abstract type IntegralModel <: KineticModel end # "Marcus-like" # check to catch missed dispatches for new types @@ -50,6 +63,34 @@ integrand(km::IntegralModel, V_dl; kwargs...) = integrand(km, V_dl, true; kwargs...)(E) - integrand(km, V_dl, false; kwargs...)(E), ) + """ + compute_k(V_app, model::KineticModel, ox::Bool; kwargs...) + compute_k(V_app, model::KineticModel; kwargs...) + compute_k(E_min, E_max, V_app, model::IntegralModel, ox::Bool; kwargs...) + compute_k(E_min, E_max, V_app, model::IntegralModel; kwargs...) + compute_k(E_min, E_max, V_app, model::MarcusHushChidseyDOS, calc_cq::Bool=false; C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, kwargs...) + +Compute the rate constant k predicted by a given kinetic model at a applied voltage `V_app`. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate (absolute value thereof). + +If the model is an `IntegralModel`, integration bounds `E_min` and `E_max` must be supplied. Integration is done via GK quadrature. + +If calc_cq flag is passed, optionally compute voltage shifts due to quantum capacitance. +""" +compute_k(V_app, model::KineticModel, args...; kT = 0.026) = model(V_app, args...; kT = kT) + +compute_k( + V_app, + model::IntegralModel, + args...; # would just be the ox flag + kT = 0.026, + E_min = -100 * kT, + E_max = 100 * kT, + kwargs..., +) = begin + n, w = scale(E_min, E_max) + f = integrand(model, V_app, args...; kT = kT) + sum(w .* f.(n)) +end include("ButlerVolmer.jl") include("Marcus.jl") diff --git a/src/rate_constant.jl b/src/rate_constant.jl deleted file mode 100644 index 9ceef35..0000000 --- a/src/rate_constant.jl +++ /dev/null @@ -1,148 +0,0 @@ -using Statistics -using Interpolations -using DelimitedFiles - -# TODO: think about reaction direction and quantum cap dispatches; there's probably a cleaner way to handle them... - -""" - compute_k(V_app, model::KineticModel, ox::Bool; kwargs...) - compute_k(V_app, model::KineticModel; kwargs...) - compute_k(E_min, E_max, V_app, model::IntegralModel, ox::Bool; kwargs...) - compute_k(E_min, E_max, V_app, model::IntegralModel; kwargs...) - compute_k(E_min, E_max, V_app, model::MarcusHushChidseyDOS, calc_cq::Bool=false; C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, kwargs...) - -Compute the rate constant k predicted by a given kinetic model at a applied voltage `V_app`. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate (absolute value thereof). - -If the model is an `IntegralModel`, integration bounds `E_min` and `E_max` must be supplied. Integration is done via GK quadrature. - -If calc_cq flag is passed, optionally compute voltage shifts due to quantum capacitance. -""" -compute_k(V_app, model::KineticModel, args...; kT = 0.026) = model(V_app, args...; kT = kT) - -compute_k( - V_app, - model::IntegralModel, - args...; # would just be the ox flag - kT = 0.026, - E_min = -100 * kT, - E_max = 100 * kT, - kwargs..., -) = begin - n, w = scale(E_min, E_max) - f = integrand(model, V_app, args...; kT = kT) - sum(w .* f.(n)) -end - -function compute_k( - V_app, - model::MarcusHushChidseyDOS, - ox::Bool; - kT = 0.026, - E_min = model.dos.E_min, - E_max = model.dos.E_max, - calc_cq::Bool = false, - C_dl = 10.0, - Vq_min = -0.5, - Vq_max = 0.5, - kwargs..., -) - if calc_cq - compute_k_cq( - V_app, - model, - ox; - C_dl = C_dl, - Vq_min = Vq_min, - Vq_max = Vq_max, - kT = kT, - E_min = min(E_min, E_min-Vq_min), - E_max = max(E_max, E_max-Vq_max), - ) - else - n, w = scale(E_min, E_max) - f = integrand(model, V_app, ox; kT = kT) - sum(w .* f.(n)) - end -end - -function compute_k( - V_app, - model::MarcusHushChidseyDOS; - kT = 0.026, - E_min = model.dos.E_min, - E_max = model.dos.E_max, - calc_cq::Bool = false, - C_dl = 10.0, - Vq_min = -0.5, - Vq_max = 0.5, - kwargs..., -) - if calc_cq - compute_k_cq( - V_app, - model; - kT = kT, - E_min = max(E_min, E_min-Vq_min), - E_max = min(E_max, E_max-Vq_max), - C_dl = C_dl, - Vq_min = Vq_min, - Vq_max = Vq_max, - ) - else - # invoke( - # compute_k, - # Tuple{typeof(V_app),IntegralModel}, - # V_app, - # model; - # kT = kT, - # E_min = E_min, - # E_max = E_max, - # ) - n, w = scale(E_min, E_max) - f = integrand(model, V_app; kT = kT) - sum(w .* f.(n)) - end -end - -""" - compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS, ox::Bool; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) - compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) - -Compute the rate constant k predicted by a `MarcusHushChidseyDOS` model at a applied voltage `V_app`, including the effects of quantum capacitance. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate. -""" -function compute_k_cq( - V_app, - model::MarcusHushChidseyDOS, - ox::Bool; - C_dl = 10.0, - Vq_min = -0.5, - Vq_max = 0.5, - kT = 0.026, - E_min = model.dos.E_min, - E_max = model.dos.E_max, -) - V_dl_interp = calculate_Vdl_interp(model.dos.interp_func, Vq_min, Vq_max, C_dl) - V_dl = V_dl_interp(V_app) - V_q = V_app - V_dl - n, w = scale(E_min, E_max) - f = integrand(model, V_dl, ox; kT = kT, V_q = V_q) - sum(w .* f.(n)) -end - -function compute_k_cq( - V_app, - model::MarcusHushChidseyDOS; - C_dl = 10.0, - Vq_min = -0.5, - Vq_max = 0.5, - kT = 0.026, - E_min = model.dos.E_min, - E_max = model.dos.E_max, -) - V_dl_interp = calculate_Vdl_interp(model.dos.interp_func, Vq_min, Vq_max, C_dl) - V_dl = V_dl_interp(V_app) - V_q = V_app - V_dl - n, w = scale(E_min, E_max) - f = integrand(model, V_dl; kT = kT, V_q = V_q) - sum(w .* f.(n)) -end diff --git a/src/dos.jl b/src/utils/dos.jl similarity index 100% rename from src/dos.jl rename to src/utils/dos.jl diff --git a/src/integration_utils.jl b/src/utils/integration_utils.jl similarity index 100% rename from src/integration_utils.jl rename to src/utils/integration_utils.jl diff --git a/src/quantum_capacitance.jl b/src/utils/quantum_capacitance.jl similarity index 100% rename from src/quantum_capacitance.jl rename to src/utils/quantum_capacitance.jl From c72c8d36e300221ac3813feb01ebade2c4443b3a Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Tue, 17 May 2022 11:14:13 -0400 Subject: [PATCH 03/25] add NonIntegralModel abstract type, make compute_k the main dispatch and callable model secondary, everything internal dispatches on Vals and external ones have Bool wrapper methods Signed-off-by: Rachel Kurchin --- src/ElectrochemicalKinetics.jl | 2 +- .../AsymptoticMarcusHushChidsey.jl | 8 +-- src/kinetic_models/ButlerVolmer.jl | 6 +- src/kinetic_models/Marcus.jl | 16 +---- src/kinetic_models/MarcusHushChidsey.jl | 17 ++--- src/kinetic_models/MarcusHushChidseyDOS.jl | 71 ++++--------------- src/kinetic_models/kinetic_models.jl | 55 +++++++------- test/integral_model_tests.jl | 5 +- test/non_integral_model_tests.jl | 10 +-- 9 files changed, 70 insertions(+), 120 deletions(-) diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index f4170e1..e2dd172 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -9,7 +9,7 @@ include("kinetic_models/kinetic_models.jl") export ButlerVolmer, AsymptoticMarcusHushChidsey export fermi_dirac export integrand -export KineticModel, IntegralModel +export KineticModel, NonIntegralModel, IntegralModel export Marcus, MarcusHushChidsey, MarcusHushChidseyDOS export compute_k, compute_k_cq diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index ff722a6..0c75e1e 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -6,7 +6,7 @@ Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/ If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. """ -struct AsymptoticMarcusHushChidsey <: KineticModel +struct AsymptoticMarcusHushChidsey <: NonIntegralModel A::Float64 λ::Float64 end @@ -14,7 +14,7 @@ end # default prefactor is 1 AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) -function (amhc::AsymptoticMarcusHushChidsey)(V_app, ox::Bool; kT::Real = 0.026) +function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real = 0.026) η = (2 * ox - 1) .* V_app ./ kT λ_nondim = amhc.λ / kT a = 1 + sqrt(λ_nondim) @@ -23,8 +23,8 @@ function (amhc::AsymptoticMarcusHushChidsey)(V_app, ox::Bool; kT::Real = 0.026) return kT * amhc.A .* pref .* erfc.(arg) end - -function (amhc::AsymptoticMarcusHushChidsey)(V_app; kT::Real = 0.026) +# direct dispatch for net rates +function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.026) η = V_app ./ kT λ_nondim = amhc.λ / kT a = 1 + sqrt(λ_nondim) diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index 84cf8a4..d077e3f 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -6,7 +6,7 @@ Computes Butler-Volmer kinetics. If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. """ -struct ButlerVolmer <: KineticModel +struct ButlerVolmer <: NonIntegralModel A::Float64 α::Float64 end @@ -15,12 +15,12 @@ end ButlerVolmer() = ButlerVolmer(1.0, 0.5) ButlerVolmer(A) = ButlerVolmer(A, 0.5) -function (bv::ButlerVolmer)(V_app, ::Val{true}; kT::Real = 0.026) +function compute_k(V_app, bv::ButlerVolmer, ::Val{true}; kT::Real = 0.026) exp_arg = (bv.α .* V_app) ./ kT bv.A .* exp.(exp_arg) end -function (bv::ButlerVolmer)(V_app, ::Val{false}; kT::Real = 0.026) +function compute_k(V_app, bv::ButlerVolmer, ::Val{false}; kT::Real = 0.026) exp_arg = -((1 - bv.α) .* V_app) ./ kT bv.A .* exp.(exp_arg) end \ No newline at end of file diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 1ccd3d0..7ce4884 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -6,7 +6,7 @@ Computes Marcus kinetics. If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. """ -struct Marcus <: KineticModel +struct Marcus <: NonIntegralModel A::Float64 λ::Float64 end @@ -14,22 +14,12 @@ end # default prefactor is 1 Marcus(λ) = Marcus(1.0, λ) -function (m::Marcus)(V_app, ox::Bool; kT::Real = 0.026) - local exp_arg - if ox - exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) - else - exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) - end - m.A .* exp.(exp_arg) -end - -function (m::Marcus)(V_app, ::Val{true}; kT::Real = 0.026) +function compute_k(V_app, m::Marcus, ::Val{true}; kT = 0.026) exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) m.A .* exp.(exp_arg) end -function (m::Marcus)(V_app, ::Val{false}; kT::Real = 0.026) +function compute_k(V_app, m::Marcus, ::Val{false}; kT = 0.026) exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) m.A .* exp.(exp_arg) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 096f66a..5b886f6 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -25,16 +25,9 @@ MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) # TODO: Check that both this and +DOS versions still match original paper -function integrand(mhc::MarcusHushChidsey, V_dl, ox::Bool; kT::Real = 0.026) - function marcus_term(E) - local exp_arg - if ox - exp_arg = -((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kT) - else - exp_arg = -((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kT) - end - exp.(exp_arg) - end - f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages - f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E) .* fermi_dirac.(E; kT = kT) +function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; kT::Real = 0.026) + marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kT)) + marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kT)) + f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages + f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index bac5047..b92dce1 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -26,31 +26,28 @@ MarcusHushChidseyDOS(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(1.0, λ, DOSData(dos_file; kwargs...)) +# TODO: make one version of this for the whole package, currently there are some sign convention differences between this and the MHC version +marcus_term(V, E, λ, ::Val{true}, kT) = exp.(-(( (λ .- V) .+ E) .^ 2) ./ (4 * λ * kT)) +marcus_term(V, E, λ, ::Val{false}, kT) = exp.(-(( (λ .+ V) .- E) .^ 2) ./ (4 * λ * kT)) + +# Fermi-Dirac function or the complement thereof +fd(E, ::Val{true}, kT) = 1 .- fermi_dirac(E; kT = kT) +fd(E, ::Val{false}, kT) = fermi_dirac(E; kT = kT) + function integrand( mhcd::MarcusHushChidseyDOS, V_dl, - ox::Bool; - kT::Real = 0.026, + ox::Val; + kT = 0.026, V_q = 0.0, ) - function marcus_term(E) - local exp_arg - if ox - exp_arg = -(( (mhcd.λ .- V_dl) .+ E) .^ 2) ./ (4 * mhcd.λ * kT) - else - exp_arg = -(( (mhcd.λ .+ V_dl) .- E) .^ 2) ./ (4 * mhcd.λ * kT) - end - exp.(exp_arg) - end - fd(E) = ox ? 1 .- fermi_dirac(E; kT = kT) : fermi_dirac(E; kT = kT) - # TODO: add two dispatches as with MHC above - E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E) .* marcus_term(E) + E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E, ox, kT) .* marcus_term(V_dl, E, mhcd.λ, ox, kT) end function compute_k( V_app, model::MarcusHushChidseyDOS, - ox::Bool; + args...; kT = 0.026, E_min = model.dos.E_min, E_max = model.dos.E_max, @@ -64,7 +61,7 @@ function compute_k( compute_k_cq( V_app, model, - ox; + args...; C_dl = C_dl, Vq_min = Vq_min, Vq_max = Vq_max, @@ -74,46 +71,7 @@ function compute_k( ) else n, w = scale(E_min, E_max) - f = integrand(model, V_app, ox; kT = kT) - sum(w .* f.(n)) - end -end - -function compute_k( - V_app, - model::MarcusHushChidseyDOS; - kT = 0.026, - E_min = model.dos.E_min, - E_max = model.dos.E_max, - calc_cq::Bool = false, - C_dl = 10.0, - Vq_min = -0.5, - Vq_max = 0.5, - kwargs..., -) - if calc_cq - compute_k_cq( - V_app, - model; - kT = kT, - E_min = max(E_min, E_min-Vq_min), - E_max = min(E_max, E_max-Vq_max), - C_dl = C_dl, - Vq_min = Vq_min, - Vq_max = Vq_max, - ) - else - # invoke( - # compute_k, - # Tuple{typeof(V_app),IntegralModel}, - # V_app, - # model; - # kT = kT, - # E_min = E_min, - # E_max = E_max, - # ) - n, w = scale(E_min, E_max) - f = integrand(model, V_app; kT = kT) + f = integrand(model, V_app, args...; kT = kT) sum(w .* f.(n)) end end @@ -143,6 +101,7 @@ function compute_k_cq( sum(w .* f.(n)) end +# TODO: clean these up...but add tests first function compute_k_cq( V_app, model::MarcusHushChidseyDOS; diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index d08056f..cb0d164 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -14,14 +14,10 @@ fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) """ KineticModel -Abstract base class for kinetic models. All subtypes need to dispatch the `compute_k` function. +Abstract base class for kinetic models. """ abstract type KineticModel end -# dispatch for net rates, returns absolute value -(km::KineticModel)(V_app; kT = 0.026) = - abs.(km(V_app, Val(true); kT = kT) - km(V_app, Val(false); kT = kT)) - # return a new one with a scaled prefactor import Base.* function *(c::Real, km::KineticModel) @@ -45,12 +41,19 @@ function Base.show(io::IO, m::KineticModel) print(io, s) end +""" + NonIntegralModel + +Abstract base class for kinetic models whose rates can be computed directly from an input voltage without requiring an energy integral. All subtypes must dispatch the `compute_k` function. +""" +abstract type NonIntegralModel <: KineticModel end + """ IntegralModel Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `compute_k` function directly, or dispatch the `integrand` function and use the default `compute_k` dispatch. """ -abstract type IntegralModel <: KineticModel end # "Marcus-like" +abstract type IntegralModel <: KineticModel end # check to catch missed dispatches for new types # integrand(km::IntegralModel, V_dl, ox::Bool; kwargs...) = @@ -58,38 +61,44 @@ abstract type IntegralModel <: KineticModel end # "Marcus-like" # TODO: check that this passes through both kT and V_q appropriately # dispatch for net rates -integrand(km::IntegralModel, V_dl; kwargs...) = +integrand(km::IntegralModel, V; kwargs...) = E -> abs.( - integrand(km, V_dl, true; kwargs...)(E) - integrand(km, V_dl, false; kwargs...)(E), + integrand(km, V, Val(true); kwargs...)(E) - integrand(km, V, Val(false); kwargs...)(E) ) +integrand(km::IntegralModel, V, ox::Bool; kwargs...) = integrand(km, V, Val(ox); kwargs...) - """ +""" compute_k(V_app, model::KineticModel, ox::Bool; kwargs...) compute_k(V_app, model::KineticModel; kwargs...) - compute_k(E_min, E_max, V_app, model::IntegralModel, ox::Bool; kwargs...) - compute_k(E_min, E_max, V_app, model::IntegralModel; kwargs...) compute_k(E_min, E_max, V_app, model::MarcusHushChidseyDOS, calc_cq::Bool=false; C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, kwargs...) Compute the rate constant k predicted by a given kinetic model at a applied voltage `V_app`. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate (absolute value thereof). -If the model is an `IntegralModel`, integration bounds `E_min` and `E_max` must be supplied. Integration is done via GK quadrature. +If the model is an `IntegralModel`, integration bounds `E_min` and `E_max` may be supplied as kwargs. Integration is done via GK quadrature. -If calc_cq flag is passed, optionally compute voltage shifts due to quantum capacitance. +If calc_cq flag is passed, optionally compute voltage shifts due to quantum capacitance (only applicable to `MarcusHushChidseyDOS` models). """ -compute_k(V_app, model::KineticModel, args...; kT = 0.026) = model(V_app, args...; kT = kT) +compute_k(V_app, model::NonIntegralModel, ox::Bool; kwargs...) = compute_k(V_app, model, Val(ox); kwargs...) + +# default dispatch for net rates, returns absolute value +compute_k(V_app, model::NonIntegralModel; kwargs...) = + abs.(compute_k(V_app, model, Val(true); kwargs...) - compute_k(V_app, model, Val(false); kwargs...)) + +# TODO: add tests that both args and kwargs are correctly captured here (also for the Val thing) +# "callable" syntax +(m::KineticModel)(V_app, args...; kwargs...) = compute_k(V_app, m, args...; kwargs...) -compute_k( +function compute_k( V_app, model::IntegralModel, - args...; # would just be the ox flag + args...; # would just be the ox flag, if present kT = 0.026, E_min = -100 * kT, - E_max = 100 * kT, - kwargs..., -) = begin - n, w = scale(E_min, E_max) - f = integrand(model, V_app, args...; kT = kT) - sum(w .* f.(n)) + E_max = 100 * kT +) + n, w = scale(E_min, E_max) + f = integrand(model, V_app, args...; kT = kT) + sum(w .* f.(n)) end include("ButlerVolmer.jl") @@ -97,5 +106,3 @@ include("Marcus.jl") include("AsymptoticMarcusHushChidsey.jl") include("MarcusHushChidsey.jl") include("MarcusHushChidseyDOS.jl") - - diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index cab3ead..2374a7f 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -1,7 +1,8 @@ # all these numbers are just references evaluated as of 2/22/22 +# TODO: add tests of `integrand` function @testset "Integral Models" begin - @testset "MHC" begin + @testset "MarcusHushChidsey" begin mhc = MarcusHushChidsey(0.25) # test some values @@ -18,7 +19,7 @@ @test all(isapprox.(compute_k(Vs, mhc), compute_k(Vs, amhc), atol=2e-4)) end - @testset "MHC+DOS" begin + @testset "MarcusHushChidseyDOS" begin # test that a uniform DOS version matches MHC flat_dos = [-5 1; 5 1] mhcd = MarcusHushChidseyDOS(0.25, flat_dos) diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index 0f970a1..68d4339 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -12,12 +12,12 @@ # oxidative for bv in [bv1, bv2, bv3] - @test bv(.026/bv.α, Val(true)) ≈ bv.A * ℯ + @test bv(.026/bv.α, true) ≈ bv.A * ℯ end # reductive for bv in [bv1, bv2, bv3] - @test bv(-.026/(1-bv.α), Val(false)) ≈ bv.A * ℯ + @test bv(-.026/(1-bv.α), false) ≈ bv.A * ℯ end # net @@ -27,7 +27,7 @@ end @testset "Vector Arguments" begin - @test bv1(.026 .* collect(0:2:6), Val(true)) == exp.(0:3) + @test bv1(.026 .* collect(0:2:6), true) == exp.(0:3) @test bv1(.026 .* collect(0:2:6)) == exp.(0:3) - exp.(-(0:3)) # TODO: test bv2, bv3 end @@ -37,8 +37,8 @@ # TODO: this could all be more thorough, I literally just picked some arbitrary points m = Marcus(0.25) @test m(0.0) == 0.0 - @test isapprox(m(0.05, Val(true)), 0.031381, atol=1e-6) - @test isapprox(m(0.2, Val(false)), 0.908324, atol=1e-6) + @test isapprox(m(0.05, true), 0.031381, atol=1e-6) + @test isapprox(m(0.2, false), 0.908324, atol=1e-6) @test isapprox(m(0.13), 0.570862, atol=1e-6) @test m(0.13) == m(-0.13) From 1bc8da2432589bc009d93af7f1ab03877352ef85 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Tue, 17 May 2022 11:23:43 -0400 Subject: [PATCH 04/25] flip argument order of fit_overpotential to match compute_k Signed-off-by: Rachel Kurchin --- src/fitting.jl | 6 +++--- src/phase_diagrams.jl | 6 +++--- test/fitting_tests.jl | 14 +++++++------- test/phase_diagram_tests.jl | 2 +- 4 files changed, 14 insertions(+), 14 deletions(-) diff --git a/src/fitting.jl b/src/fitting.jl index f843eaa..89f0e31 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -14,7 +14,7 @@ linear_loss(y, y_pred) = (y .- y_pred).^2 Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `compute_k` function.) """ -function fit_overpotential(model::KineticModel, k, guess = fill(0.1, length(k)); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) +function fit_overpotential(k, model::KineticModel, guess = fill(0.1, length(k)); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) function compare_k!(storage, V) storage .= loss(k, compute_k(V, model; kT = kT, kwargs...)) end @@ -58,7 +58,7 @@ end inv!(x) = x .= inv.(x) -Zygote.@adjoint function fit_overpotential(model, k, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) +Zygote.@adjoint function fit_overpotential(k, model, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) Vs = fit_overpotential(model, k, guess; loss, verbose, autodiff, kT, kw...) function back(vs) gs = Zygote.jacobian(vs) do V @@ -75,7 +75,7 @@ end # multiple models, one k value (used in thermo example) -fit_overpotential(models::Vector{<:KineticModel}, k::Real, guess=fill(0.1, length(k)); kwargs...) = fit_overpotential.(models, Ref(k), Ref(guess); kwargs...) +fit_overpotential(k::Real, models::Vector{<:KineticModel}, guess=fill(0.1, length(k)); kwargs...) = fit_overpotential.(Ref(k), models, Ref(guess); kwargs...) fitting_params(t::Type{<:KineticModel}) = fieldnames(t) fitting_params(::Type{MarcusHushChidsey}) = (:A, :λ) diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index 0b6bddb..4777264 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -26,8 +26,8 @@ still being able to swap out model parameters by calling "function-builders" wit """ function µ_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) thermo_term(x) = μ_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) - μ(x::Real) = thermo_term(x) .+ fit_overpotential((1-x)*km, I) - μ(x::AbstractVector) = thermo_term(x) .+ fit_overpotential((1 .- x).*Ref(km), I) + μ(x::Real) = thermo_term(x) .+ fit_overpotential(I, (1-x)*km) + μ(x::AbstractVector) = thermo_term(x) .+ fit_overpotential(I, (1 .- x).*Ref(km)) return μ end @@ -35,7 +35,7 @@ function g_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=m thermo_term(x) = g_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) #TODO: gradient of this term is just value of fit_overpotential(x) function kinetic_term(x) - f(x) = ElectrochemicalKinetics.fit_overpotential( (1 .- x) .* Ref(km), I) + f(x) = ElectrochemicalKinetics.fit_overpotential(I, (1 .- x) .* Ref(km)) n, w = ElectrochemicalKinetics.scale(zero.(x), x) map((w, n) -> sum(w .* f(n)), eachcol(w), eachcol(n)) end diff --git a/test/fitting_tests.jl b/test/fitting_tests.jl index c2bd3dc..b93bce7 100644 --- a/test/fitting_tests.jl +++ b/test/fitting_tests.jl @@ -6,19 +6,19 @@ # test a number less than the initial guess V1 = 0.05 k1 = compute_k(V1, m) - @test isapprox(fit_overpotential(m, k1)[1], V1, atol=1e-5) + @test isapprox(fit_overpotential(k1, m)[1], V1, atol=1e-5) # and one greater V2 = 0.15 k2 = compute_k(V2, m) - @test isapprox(fit_overpotential(m, k2)[1], V2, atol=1e-5) + @test isapprox(fit_overpotential(k2, m)[1], V2, atol=1e-5) # test that vectorized fitting works...first for one model and multiple k's # this test is turned off for now because better adjoint of fit_overpotential currently doesn't work with it... # @test isapprox(fit_overpotential(m, [k1, k2]), [V1, V2], atol=5e-4) # TODO: figure out sensible and consistent way to vectorize over k and/or V (e.g. use a matrix?) # now test for one k and multiple models - @test isapprox(fit_overpotential([m, m], k1), [V1, V1], atol=5e-4) + @test isapprox(fit_overpotential(k1, [m, m]), [V1, V1], atol=5e-4) # make sure that both fails since indexing would be ambiguous - @test_throws MethodError fit_overpotential([m, m], [k1, k2]) + @test_throws MethodError fit_overpotential([k1, k2], [m, m]) end end # for now, writing these separately to test different input DOSes @@ -34,12 +34,12 @@ m = MarcusHushChidseyDOS(0.25, dos) V1 = 0.05 k1 = compute_k(V1, m) - @test isapprox(fit_overpotential(m, k1)[1], V1, atol=1e-5) + @test isapprox(fit_overpotential(k1, m)[1], V1, atol=1e-5) V2 = 0.15 k2 = compute_k(V2, m) - @test isapprox(fit_overpotential(m, k2)[1], V2, atol=1e-5) + @test isapprox(fit_overpotential(k2, m)[1], V2, atol=1e-5) # this one is disabled for now for same reason as above - # @test isapprox(fit_overpotential(m, [k1, k2]), [V1, V2], atol=5e-4) + # @test isapprox(fit_overpotential([k1, k2], m), [V1, V2], atol=5e-4) end end end diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 2f4ce17..66c2aaf 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -73,7 +73,7 @@ xs = [0.1, 0.5, 0.95] # test that the right (approximate) relationships hold μs = μ_50_vals[typeof(km)] for x in xs - @test μ_50(x) ≈ μs[x] ≈ μ_thermo(x) + fit_overpotential((1-x)*km, 50) + @test μ_50(x) ≈ μs[x] ≈ μ_thermo(x) + fit_overpotential(50, (1-x)*km) end # test vector inputs From d678fa57aff754d4baa097b96b151b581f68cde7 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 19 May 2022 13:53:43 -0400 Subject: [PATCH 05/25] models can take vectors of parameters now Signed-off-by: Rachel Kurchin --- .../AsymptoticMarcusHushChidsey.jl | 22 ++-- src/kinetic_models/ButlerVolmer.jl | 10 +- src/kinetic_models/Marcus.jl | 8 +- src/kinetic_models/MarcusHushChidsey.jl | 12 +- src/kinetic_models/MarcusHushChidseyDOS.jl | 10 +- src/kinetic_models/kinetic_models.jl | 2 +- test/integral_model_tests.jl | 31 ++--- test/non_integral_model_tests.jl | 108 ++++++++++++++---- test/runtests.jl | 5 + 9 files changed, 140 insertions(+), 68 deletions(-) diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 0c75e1e..9c5e2a6 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -7,8 +7,8 @@ Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/ If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. """ struct AsymptoticMarcusHushChidsey <: NonIntegralModel - A::Float64 - λ::Float64 + A + λ end # default prefactor is 1 @@ -17,18 +17,18 @@ AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real = 0.026) η = (2 * ox - 1) .* V_app ./ kT λ_nondim = amhc.λ / kT - a = 1 + sqrt(λ_nondim) - arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) - pref = sqrt(π * λ_nondim) ./ (1 .+ exp.(-η)) - return kT * amhc.A .* pref .* erfc.(arg) + a = 1 .+ sqrt.(λ_nondim) + arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 .* sqrt.(λ_nondim)) + pref = sqrt.(π .* λ_nondim) ./ (1 .+ exp.(-η)) + return kT .* amhc.A .* pref .* erfc.(arg) end # direct dispatch for net rates function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.026) - η = V_app ./ kT + η = V_app / kT λ_nondim = amhc.λ / kT - a = 1 + sqrt(λ_nondim) - arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 * sqrt(λ_nondim)) - pref = sqrt(π * λ_nondim) .* tanh.(η/2) + a = 1 .+ sqrt.(λ_nondim) + arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 .* sqrt.(λ_nondim)) + pref = sqrt.(π .* λ_nondim) .* tanh.(η/2) return abs.(kT * amhc.A .* pref .* erfc.(arg)) -end \ No newline at end of file +end diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index d077e3f..775a49b 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -7,8 +7,8 @@ Computes Butler-Volmer kinetics. If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. """ struct ButlerVolmer <: NonIntegralModel - A::Float64 - α::Float64 + A + α end # default to unit prefactor and symmetric response @@ -16,11 +16,11 @@ ButlerVolmer() = ButlerVolmer(1.0, 0.5) ButlerVolmer(A) = ButlerVolmer(A, 0.5) function compute_k(V_app, bv::ButlerVolmer, ::Val{true}; kT::Real = 0.026) - exp_arg = (bv.α .* V_app) ./ kT + exp_arg = (bv.α .* V_app) / kT bv.A .* exp.(exp_arg) end function compute_k(V_app, bv::ButlerVolmer, ::Val{false}; kT::Real = 0.026) - exp_arg = -((1 - bv.α) .* V_app) ./ kT + exp_arg = -((1 .- bv.α) .* V_app) / kT bv.A .* exp.(exp_arg) -end \ No newline at end of file +end diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 7ce4884..2f2cb14 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -7,19 +7,19 @@ Computes Marcus kinetics. If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. """ struct Marcus <: NonIntegralModel - A::Float64 - λ::Float64 + A + λ end # default prefactor is 1 Marcus(λ) = Marcus(1.0, λ) function compute_k(V_app, m::Marcus, ::Val{true}; kT = 0.026) - exp_arg = -(m.λ .+ V_app).^2 ./ (4 * m.λ * kT) + exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end function compute_k(V_app, m::Marcus, ::Val{false}; kT = 0.026) - exp_arg = -(m.λ .- V_app).^2 ./ (4 * m.λ * kT) + exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 5b886f6..0654843 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -10,9 +10,9 @@ Note that for "typical" reorganization energy values (in the vicinity of 10*kT a If either the prefactor or the average dos are omitted, their values are assumed to be 1. Note that strictly speaking, `average_dos` and the prefactor `A` are redundant. They are both included primarily to facilitate comparisons with similarly parametrized Marcus-like models such as `MarcusHushChidseyDOS`. """ struct MarcusHushChidsey <: IntegralModel - A::Real - λ::Real - average_dos::Real + A + λ + average_dos end # default prefactor is 1 @@ -20,14 +20,14 @@ MarcusHushChidsey(λ, avg_dos) = MarcusHushChidsey(1.0, λ, avg_dos) # assume prefactor = 1 and avg_dos = 1 MarcusHushChidsey(λ) = MarcusHushChidsey(1.0, λ, 1.0) # convert more detailed DOS information to just pull out average -MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, dd.average_value) +MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, Ref(dd.average_value)) MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) # TODO: Check that both this and +DOS versions still match original paper function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; kT::Real = 0.026) - marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kT)) - marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kT)) + marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 .* mhc.λ .* kT)) + marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 .* mhc.λ .* kT)) f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index b92dce1..e489e59 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -4,17 +4,19 @@ include("../utils/quantum_capacitance.jl") MarcusHushChidseyDOS(A=1.0, λ, dos) MarcusHushChidseyDOS(A=1.0, λ, dos_file) -Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanathan: 10.1063/5.0023611 +Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanathan: 10.1063/5.0023611 + +NB: At the moment, this will allow for vector `A` and `λ` parameters, but will presume that all models correspond to the same DOS. """ struct MarcusHushChidseyDOS <: IntegralModel - A::Float64 - λ::Float64 + A + λ dos::DOSData end function Base.show(io::IO, mhcd::MarcusHushChidseyDOS) s = repr(typeof(mhcd)) * "(" - s *= "A=$(round(mhcd.A, sigdigits=3)), λ=$(round(mhcd.λ, sigdigits=3)))" + s *= "A=$(round.(mhcd.A, sigdigits=3)), λ=$(round(mhcd.λ, sigdigits=3)))" print(io, s) end diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index cb0d164..e02357a 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -34,7 +34,7 @@ function Base.show(io::IO, m::KineticModel) s * string(field) * "=" * - string(round(getproperty(m, field), sigdigits = 3)) * + string(round.(getproperty(m, field), sigdigits = 3)) * ", " end s = s[1:end-2] * ")" diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index 2374a7f..b026cdc 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -1,22 +1,27 @@ # all these numbers are just references evaluated as of 2/22/22 # TODO: add tests of `integrand` function - +# TODO: throughout, add tests of varying kT @testset "Integral Models" begin @testset "MarcusHushChidsey" begin mhc = MarcusHushChidsey(0.25) + @testset "Scalars" begin + # test some values + @test compute_k(0, mhc) == 0.0 + @test compute_k(0, mhc, true) == compute_k(0, mhc, false) ≈ 0.0061371322 + @test isapprox(compute_k(0.1, mhc), 0.031239978, atol=1e-6) + + # test net rates and symmetry + @test isapprox(compute_k(0.1, mhc, true) - compute_k(0.1, mhc, false), compute_k(0.1, mhc), atol=1e-6) + @test compute_k(-0.1, mhc) == compute_k(0.1, mhc) + end - # test some values - @test compute_k(0, mhc) == 0.0 - @test compute_k(0, mhc, true) == compute_k(0, mhc, false) ≈ 0.0061371322 - @test isapprox(compute_k(0.1, mhc), 0.031239978, atol=1e-6) - - # test net rates and symmetry - @test isapprox(compute_k(0.1, mhc, true) - compute_k(0.1, mhc, false), compute_k(0.1, mhc), atol=1e-6) - @test compute_k(-0.1, mhc) == compute_k(0.1, mhc) - - # test that it's close to asymptotic version, also that vector inputs work appropriately - amhc = AsymptoticMarcusHushChidsey(0.25) - @test all(isapprox.(compute_k(Vs, mhc), compute_k(Vs, amhc), atol=2e-4)) + @testset "Vector Voltages" begin + test_vector_voltages(mhc, Vs) + @test isapprox(mhc(Vs), mhc(-Vs)) #symmetry + # test that it's close to asymptotic version + amhc = AsymptoticMarcusHushChidsey(0.25) + @test all(isapprox.(compute_k(Vs, mhc), compute_k(Vs, amhc), atol=2e-4)) + end end @testset "MarcusHushChidseyDOS" begin diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index 68d4339..d7f961d 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -1,12 +1,14 @@ # test values come either from analytical inversion of expression (BV) or references evaluated as of 2/22/22 and presumed to be correct +# TODO: throughout, add tests of varying kT + @testset "Non-Integral Models" begin @testset "Butler-Volmer" begin bv1 = ButlerVolmer() bv2 = ButlerVolmer(3.0) bv3 = ButlerVolmer(1.0, 0.2) - @testset "Scalar Arguments" begin + @testset "Scalars" begin # zero voltage @test all(compute_k.(Ref(0), [bv1, bv2, bv3]).==0) @@ -26,36 +28,94 @@ end end - @testset "Vector Arguments" begin - @test bv1(.026 .* collect(0:2:6), true) == exp.(0:3) - @test bv1(.026 .* collect(0:2:6)) == exp.(0:3) - exp.(-(0:3)) - # TODO: test bv2, bv3 + @testset "Vectors" begin + @testset "Vector Voltages" begin + test_vector_voltages(bv1, Vs) + test_vector_voltages(bv2, Vs) + test_vector_voltages(bv3, Vs) + for model in [bv1, bv2] # bv3 won't be symmetrical + @test isapprox(model(Vs), model(-Vs)) #symmetry + end + end + @testset "Vector Models" begin + A_vals = [1.0, 2.0] + α_vals = [0.4, 0.5, 0.6] + bvv1 = ButlerVolmer(A_vals) # autopopulate α, combine scalar/vector + bvv2 = ButlerVolmer(A_vals, α_vals[1:2]) # both vectors + bvv3 = ButlerVolmer(A_vals, α_vals) # invalid, different lengths + + # test that it's equivalent to the scalar model version + @test compute_k(0.1, bvv1) == compute_k.(Ref(0.1), ButlerVolmer.(A_vals)) + @test compute_k(0.1, bvv2) == compute_k.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) + + # test that correct error is thrown + @test_throws DimensionMismatch compute_k(0, bvv3) + end + @testset "Vector Voltages and Models" begin + # TODO: this + end end end @testset "Marcus" begin - # TODO: this could all be more thorough, I literally just picked some arbitrary points - m = Marcus(0.25) - @test m(0.0) == 0.0 - @test isapprox(m(0.05, true), 0.031381, atol=1e-6) - @test isapprox(m(0.2, false), 0.908324, atol=1e-6) - @test isapprox(m(0.13), 0.570862, atol=1e-6) - @test m(0.13) == m(-0.13) - - # test vector voltages and also symmetry - @test m(Vs) == m(-Vs) + m1 = Marcus(0.25) + m2 = Marcus(10, 0.25) + @testset "Scalars" begin + # TODO: this could all be more thorough, I literally just picked some arbitrary points + @test m1(0.0) == 0.0 + @test isapprox(m1(0.05, true), 0.031381, atol=1e-6) + @test isapprox(m1(0.2, false), 0.908324, atol=1e-6) + @test isapprox(m1(0.13), 0.570862, atol=1e-6) + @test isapprox(m2(0.13), 5.708625, atol=1e-6) + end + + @testset "Vectors" begin + @testset "Vector Voltages" begin + test_vector_voltages(m1, Vs) + test_vector_voltages(m2, Vs) + for model in [m1, m2] + @test isapprox(model(Vs), model(-Vs)) #symmetry + end + end + @testset "Vector Models" begin + A_vals = [1, 100, 10000] + λ_vals = [0.1, 0.3, 0.7] + mv1 = Marcus(λ_vals) + mv2 = Marcus(A_vals, λ_vals) + + @test compute_k(0.1, mv1) == compute_k.(Ref(0.1), Marcus.(λ_vals)) + @test compute_k(0.1, mv2) == compute_k.(Ref(0.1), Marcus.(A_vals, λ_vals)) + end + @testset "Vector Voltages and Models" begin + # TODO: this + end + end end @testset "asymptotic MHC" begin amhc = AsymptoticMarcusHushChidsey(0.25) - @test amhc(0.0) == 0.0 - @test amhc(0.0, true) == amhc(0.0, false) ≈ 0.00596440064 - @test amhc(0.2) == amhc(-0.2) ≈ 0.1006330238 - @test amhc(0.2, kT=.015) ≈ 0.06360960459 - @test amhc(0.2, kT=.03) ≈ 0.11255129857 - - vec_out = amhc(Vs) - @test length(vec_out) == length(Vs) - @test vec_out[1] == amhc(Vs[1]) + @testset "Scalars" begin + @test amhc(0.0) == 0.0 + @test amhc(0.0, true) == amhc(0.0, false) ≈ 0.00596440064 + @test amhc(0.2) == amhc(-0.2) ≈ 0.1006330238 + @test amhc(0.2, kT=.015) ≈ 0.06360960459 + @test amhc(0.2, kT=.03) ≈ 0.11255129857 + end + @testset "Vector Voltages" begin + test_vector_voltages(amhc, Vs) + @test isapprox(amhc(Vs), amhc(-Vs)) #symmetry + end + @testset "Vector Models" begin + A_vals = [1, 100, 10000] + λ_vals = [0.1, 0.3, 0.7] + amhc1 = AsymptoticMarcusHushChidsey(λ_vals) + amhc2 = AsymptoticMarcusHushChidsey(A_vals, λ_vals) + + @test compute_k(0.1, amhc1) == compute_k.(Ref(0.1), AsymptoticMarcusHushChidsey.(λ_vals)) + @test compute_k(0.1, amhc2) == compute_k.(Ref(0.1), AsymptoticMarcusHushChidsey.(A_vals, λ_vals)) + end + @testset "Vector Voltages and Models" begin + # TODO: this + end end end diff --git a/test/runtests.jl b/test/runtests.jl index 0630324..e4c5826 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -2,6 +2,11 @@ using ElectrochemicalKinetics using QuadGK using Test +function test_vector_voltages(model, voltages) + @test isapprox(compute_k(voltages, model), compute_k.(voltages, Ref(model))) + @test isapprox(compute_k(voltages, model, kT=0.4), compute_k.(voltages, Ref(model), kT=0.4)) +end + @testset "ElectrochemicalKinetics.jl" begin global Vs = 0.01:0.01:0.1 @testset "Rate constant computation" begin From 6ed1afd056b8dfbd94d156770d269ef84299e2a3 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 19 May 2022 13:59:40 -0400 Subject: [PATCH 06/25] rename compute_k -> rate_constant, fit_overpotential -> overpotential to be more concordant with Julian idiom Signed-off-by: Rachel Kurchin --- README.md | 4 +-- benchmark/bench_suite.jl | 18 ++++++------ src/ElectrochemicalKinetics.jl | 4 +-- src/fitting.jl | 28 +++++++++---------- .../AsymptoticMarcusHushChidsey.jl | 4 +-- src/kinetic_models/ButlerVolmer.jl | 4 +-- src/kinetic_models/Marcus.jl | 4 +-- src/kinetic_models/MarcusHushChidseyDOS.jl | 12 ++++---- src/kinetic_models/kinetic_models.jl | 20 ++++++------- src/phase_diagrams.jl | 8 +++--- src/plot_fcns.jl | 8 +++--- test/fitting_tests.jl | 26 ++++++++--------- test/integral_model_tests.jl | 22 +++++++-------- test/non_integral_model_tests.jl | 16 +++++------ test/phase_diagram_tests.jl | 2 +- test/runtests.jl | 4 +-- 16 files changed, 92 insertions(+), 92 deletions(-) diff --git a/README.md b/README.md index c260935..85aec91 100644 --- a/README.md +++ b/README.md @@ -26,7 +26,7 @@ MarcusHushChidseyDOS(A=20.0, λ=0.2) ``` In this case, since `MarcusHushChidseyDOS<:IntegralModel`, we can't directly evaluate the object as a callable because it's ambiguous if we want the integrand or the full integrated rate constant, and we must specify: ```julia -julia> compute_k(0.1, mhcd) +julia> rate_constant(0.1, mhcd) 3.426690873746331 ``` By default, the integration bounds are chosen to be the energy bounds over which the DOS is defined, which we can easily check: @@ -42,7 +42,7 @@ Another feature we support for `MarcusHushChidseyDOS` models is incorporating th julia> mhcd = MarcusHushChidseyDOS(0.82, "data/DOSes/bernal_graphene.txt") MarcusHushChidseyDOS(A=1.0, λ=0.82) -julia> compute_k(0.4, mhcd; calc_cq=true, Vq_min=-0.45, Vq_max=0.45) +julia> rate_constant(0.4, mhcd; calc_cq=true, Vq_min=-0.45, Vq_max=0.45) 0.00044958691359217384 ``` diff --git a/benchmark/bench_suite.jl b/benchmark/bench_suite.jl index cfd566b..38add0d 100644 --- a/benchmark/bench_suite.jl +++ b/benchmark/bench_suite.jl @@ -22,8 +22,8 @@ suite["rate constants"]["non-integral models"]["vector V"] = BenchmarkGroup() for km in ni_kms modeltype = typeof(km) - suite["rate constants"]["non-integral models"]["scalar V"][modeltype] = @benchmarkable compute_k(0.1, $km) seconds=time_mult*0.1 - suite["rate constants"]["non-integral models"]["vector V"][modeltype] = @benchmarkable compute_k(0.01:0.01:0.2, $km) seconds=time_mult + suite["rate constants"]["non-integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant(0.1, $km) seconds=time_mult*0.1 + suite["rate constants"]["non-integral models"]["vector V"][modeltype] = @benchmarkable rate_constant(0.01:0.01:0.2, $km) seconds=time_mult end mhc = MarcusHushChidsey(70000, 0.3, 1.0) @@ -38,11 +38,11 @@ suite["rate constants"]["integral models"]["vector V"] = BenchmarkGroup() for km in i_kms modeltype = names[km] - suite["rate constants"]["integral models"]["scalar V"][modeltype] = @benchmarkable compute_k(0.1, $km) seconds=time_mult*8 - suite["rate constants"]["integral models"]["vector V"][modeltype] = @benchmarkable compute_k(0.01:0.01:0.2, $km) seconds=time_mult*11 + suite["rate constants"]["integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant(0.1, $km) seconds=time_mult*8 + suite["rate constants"]["integral models"]["vector V"][modeltype] = @benchmarkable rate_constant(0.01:0.01:0.2, $km) seconds=time_mult*11 end -# fit_overpotential benchmarks +# overpotential benchmarks # TODO: add vector cases k = 2e3 @@ -53,8 +53,8 @@ suite["overpotential fitting"]["non-integral models"]["AD"] = BenchmarkGroup() for km in ni_kms modeltype = typeof(km) - suite["overpotential fitting"]["non-integral models"]["non-AD"][modeltype] = @benchmarkable fit_overpotential($km, $k, autodiff=false) seconds=time_mult*3 - suite["overpotential fitting"]["non-integral models"]["AD"][modeltype] = @benchmarkable fit_overpotential($km, $k, autodiff=true) seconds=time_mult*5 + suite["overpotential fitting"]["non-integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=false) seconds=time_mult*3 + suite["overpotential fitting"]["non-integral models"]["AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=true) seconds=time_mult*5 end suite["overpotential fitting"]["integral models"] = BenchmarkGroup() @@ -62,6 +62,6 @@ suite["overpotential fitting"]["integral models"]["non-AD"] = BenchmarkGroup() suite["overpotential fitting"]["integral models"]["AD"] = BenchmarkGroup() for km in i_kms[2:end] # skipping MHC for now modeltype = names[km] - suite["overpotential fitting"]["integral models"]["non-AD"][modeltype] = @benchmarkable fit_overpotential($km, $k, autodiff=false) seconds=time_mult*10 - suite["overpotential fitting"]["integral models"]["AD"][modeltype] = @benchmarkable fit_overpotential($km, $k, autodiff=true) seconds=time_mult*20 + suite["overpotential fitting"]["integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=false) seconds=time_mult*10 + suite["overpotential fitting"]["integral models"]["AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=true) seconds=time_mult*20 end diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index e2dd172..cc19ebf 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -11,11 +11,11 @@ export fermi_dirac export integrand export KineticModel, NonIntegralModel, IntegralModel export Marcus, MarcusHushChidsey, MarcusHushChidseyDOS -export compute_k, compute_k_cq +export rate_constant, rate_constant_cq include("fitting.jl") include("utils/integration_utils.jl") -export fitting_params, fit_model, fit_overpotential, is_dosmodel +export fitting_params, fit_model, overpotential, is_dosmodel include("phase_diagrams.jl") export kB, h, s, g_thermo, µ_thermo diff --git a/src/fitting.jl b/src/fitting.jl index 89f0e31..9a666eb 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -10,31 +10,31 @@ log_loss(y, y_pred) = (log.(y) .- log.(y_pred)).^2 linear_loss(y, y_pred) = (y .- y_pred).^2 """ - fit_overpotential(model, k; kwargs...) + overpotential(model, k; kwargs...) -Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `compute_k` function.) +Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) """ -function fit_overpotential(k, model::KineticModel, guess = fill(0.1, length(k)); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) +function overpotential(k, model::KineticModel, guess = fill(0.1, length(k)); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) function compare_k!(storage, V) - storage .= loss(k, compute_k(V, model; kT = kT, kwargs...)) + storage .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) end Vs = if autodiff function myfun!(F, J, V) if J == nothing - F .= loss(k, compute_k(V, model; kT = kT, kwargs...)) + F .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) elseif F == nothing && !isnothing(J) # TODO: we could speed up the case of scalar k's by dispatching to call gradient here instead gs = Zygote.gradient(V[1]) do V Zygote.forwarddiff(V) do V - loss(k, compute_k(V, model; kT = kT, kwargs...)) |> sum + loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum end end[1] J .= gs else y, back = Zygote.pullback(V[1]) do V Zygote.forwarddiff(V) do V - loss(k, compute_k(V, model; kT = kT, kwargs...)) |> sum + loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum end end F .= y @@ -58,12 +58,12 @@ end inv!(x) = x .= inv.(x) -Zygote.@adjoint function fit_overpotential(k, model, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) - Vs = fit_overpotential(model, k, guess; loss, verbose, autodiff, kT, kw...) +Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) + Vs = overpotential(model, k, guess; loss, verbose, autodiff, kT, kw...) function back(vs) gs = Zygote.jacobian(vs) do V Zygote.forwarddiff(V) do V - compute_k(V, model; kw...) + rate_constant(V, model; kw...) end end[1] inv.(gs) @@ -71,11 +71,11 @@ Zygote.@adjoint function fit_overpotential(k, model, guess; loss = log_loss, kT Vs, Δ -> (nothing, nothing, Δ .* back(Vs)) end -# basically the gradient of fit_overpotential should just be the inverse of the gradient of the forward solve at that point, i.e. if compute_k(V, model) ==k then fit_overpotential(model, k)==V , so we don’t need to diff through the actual solve in fit_overpotential because the gradient should just be the inverse of the gradient of compute_k at V +# basically the gradient of overpotential should just be the inverse of the gradient of the forward solve at that point, i.e. if rate_constant(V, model) ==k then overpotential(model, k)==V , so we don’t need to diff through the actual solve in overpotential because the gradient should just be the inverse of the gradient of rate_constant at V # multiple models, one k value (used in thermo example) -fit_overpotential(k::Real, models::Vector{<:KineticModel}, guess=fill(0.1, length(k)); kwargs...) = fit_overpotential.(Ref(k), models, Ref(guess); kwargs...) +overpotential(k::Real, models::Vector{<:KineticModel}, guess=fill(0.1, length(k)); kwargs...) = overpotential.(Ref(k), models, Ref(guess); kwargs...) fitting_params(t::Type{<:KineticModel}) = fieldnames(t) fitting_params(::Type{MarcusHushChidsey}) = (:A, :λ) @@ -106,7 +106,7 @@ function fit_model( kwargs... ) V_vals = exp_data[:, 1] - eval_model(model) = [compute_k(V, model; kT = kT) for V in V_vals] + eval_model(model) = [rate_constant(V, model; kT = kT) for V in V_vals] _fit_model(exp_data, model_type, param_bounds, eval_model) end @@ -121,7 +121,7 @@ function fit_model( kwargs..., ) V_vals = exp_data[:, 1] - eval_model(model) = compute_k(V_vals, + eval_model(model) = rate_constant(V_vals, model; kT = kT, E_min = E_min, diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 9c5e2a6..8b993f8 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -14,7 +14,7 @@ end # default prefactor is 1 AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) -function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real = 0.026) +function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real = 0.026) η = (2 * ox - 1) .* V_app ./ kT λ_nondim = amhc.λ / kT a = 1 .+ sqrt.(λ_nondim) @@ -24,7 +24,7 @@ function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real end # direct dispatch for net rates -function compute_k(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.026) +function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.026) η = V_app / kT λ_nondim = amhc.λ / kT a = 1 .+ sqrt.(λ_nondim) diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index 775a49b..d97d74a 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -15,12 +15,12 @@ end ButlerVolmer() = ButlerVolmer(1.0, 0.5) ButlerVolmer(A) = ButlerVolmer(A, 0.5) -function compute_k(V_app, bv::ButlerVolmer, ::Val{true}; kT::Real = 0.026) +function rate_constant(V_app, bv::ButlerVolmer, ::Val{true}; kT::Real = 0.026) exp_arg = (bv.α .* V_app) / kT bv.A .* exp.(exp_arg) end -function compute_k(V_app, bv::ButlerVolmer, ::Val{false}; kT::Real = 0.026) +function rate_constant(V_app, bv::ButlerVolmer, ::Val{false}; kT::Real = 0.026) exp_arg = -((1 .- bv.α) .* V_app) / kT bv.A .* exp.(exp_arg) end diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 2f2cb14..dddbb9a 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -14,12 +14,12 @@ end # default prefactor is 1 Marcus(λ) = Marcus(1.0, λ) -function compute_k(V_app, m::Marcus, ::Val{true}; kT = 0.026) +function rate_constant(V_app, m::Marcus, ::Val{true}; kT = 0.026) exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end -function compute_k(V_app, m::Marcus, ::Val{false}; kT = 0.026) +function rate_constant(V_app, m::Marcus, ::Val{false}; kT = 0.026) exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index e489e59..35b9b6a 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -46,7 +46,7 @@ function integrand( E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E, ox, kT) .* marcus_term(V_dl, E, mhcd.λ, ox, kT) end -function compute_k( +function rate_constant( V_app, model::MarcusHushChidseyDOS, args...; @@ -60,7 +60,7 @@ function compute_k( kwargs..., ) if calc_cq - compute_k_cq( + rate_constant_cq( V_app, model, args...; @@ -79,12 +79,12 @@ function compute_k( end """ - compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS, ox::Bool; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) - compute_k_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) + rate_constant_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS, ox::Bool; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) + rate_constant_cq(E_min, E_max, V_app, model::MarcusHushChidseyDOS; C_dl=10.0, Vq_min=-0.5, Vq_max=0.5, kwargs...) Compute the rate constant k predicted by a `MarcusHushChidseyDOS` model at a applied voltage `V_app`, including the effects of quantum capacitance. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate. """ -function compute_k_cq( +function rate_constant_cq( V_app, model::MarcusHushChidseyDOS, ox::Bool; @@ -104,7 +104,7 @@ function compute_k_cq( end # TODO: clean these up...but add tests first -function compute_k_cq( +function rate_constant_cq( V_app, model::MarcusHushChidseyDOS; C_dl = 10.0, diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index e02357a..3b3095d 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -44,14 +44,14 @@ end """ NonIntegralModel -Abstract base class for kinetic models whose rates can be computed directly from an input voltage without requiring an energy integral. All subtypes must dispatch the `compute_k` function. +Abstract base class for kinetic models whose rates can be computed directly from an input voltage without requiring an energy integral. All subtypes must dispatch the `rate_constant` function. """ abstract type NonIntegralModel <: KineticModel end """ IntegralModel -Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `compute_k` function directly, or dispatch the `integrand` function and use the default `compute_k` dispatch. +Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `rate_constant` function directly, or dispatch the `integrand` function and use the default `rate_constant` dispatch. """ abstract type IntegralModel <: KineticModel end @@ -68,9 +68,9 @@ integrand(km::IntegralModel, V; kwargs...) = integrand(km::IntegralModel, V, ox::Bool; kwargs...) = integrand(km, V, Val(ox); kwargs...) """ - compute_k(V_app, model::KineticModel, ox::Bool; kwargs...) - compute_k(V_app, model::KineticModel; kwargs...) - compute_k(E_min, E_max, V_app, model::MarcusHushChidseyDOS, calc_cq::Bool=false; C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, kwargs...) + rate_constant(V_app, model::KineticModel, ox::Bool; kwargs...) + rate_constant(V_app, model::KineticModel; kwargs...) + rate_constant(E_min, E_max, V_app, model::MarcusHushChidseyDOS, calc_cq::Bool=false; C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, kwargs...) Compute the rate constant k predicted by a given kinetic model at a applied voltage `V_app`. If a flag for reaction direction `ox` is supplied, `true` gives the oxidative and `false` the reductive direction, while omitting this flag will yield net reaction rate (absolute value thereof). @@ -78,17 +78,17 @@ If the model is an `IntegralModel`, integration bounds `E_min` and `E_max` may b If calc_cq flag is passed, optionally compute voltage shifts due to quantum capacitance (only applicable to `MarcusHushChidseyDOS` models). """ -compute_k(V_app, model::NonIntegralModel, ox::Bool; kwargs...) = compute_k(V_app, model, Val(ox); kwargs...) +rate_constant(V_app, model::NonIntegralModel, ox::Bool; kwargs...) = rate_constant(V_app, model, Val(ox); kwargs...) # default dispatch for net rates, returns absolute value -compute_k(V_app, model::NonIntegralModel; kwargs...) = - abs.(compute_k(V_app, model, Val(true); kwargs...) - compute_k(V_app, model, Val(false); kwargs...)) +rate_constant(V_app, model::NonIntegralModel; kwargs...) = + abs.(rate_constant(V_app, model, Val(true); kwargs...) - rate_constant(V_app, model, Val(false); kwargs...)) # TODO: add tests that both args and kwargs are correctly captured here (also for the Val thing) # "callable" syntax -(m::KineticModel)(V_app, args...; kwargs...) = compute_k(V_app, m, args...; kwargs...) +(m::KineticModel)(V_app, args...; kwargs...) = rate_constant(V_app, m, args...; kwargs...) -function compute_k( +function rate_constant( V_app, model::IntegralModel, args...; # would just be the ox flag, if present diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index 4777264..d32f011 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -26,16 +26,16 @@ still being able to swap out model parameters by calling "function-builders" wit """ function µ_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) thermo_term(x) = μ_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) - μ(x::Real) = thermo_term(x) .+ fit_overpotential(I, (1-x)*km) - μ(x::AbstractVector) = thermo_term(x) .+ fit_overpotential(I, (1 .- x).*Ref(km)) + μ(x::Real) = thermo_term(x) .+ overpotential(I, (1-x)*km) + μ(x::AbstractVector) = thermo_term(x) .+ overpotential(I, (1 .- x).*Ref(km)) return μ end function g_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) thermo_term(x) = g_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) - #TODO: gradient of this term is just value of fit_overpotential(x) + #TODO: gradient of this term is just value of overpotential(x) function kinetic_term(x) - f(x) = ElectrochemicalKinetics.fit_overpotential(I, (1 .- x) .* Ref(km)) + f(x) = ElectrochemicalKinetics.overpotential(I, (1 .- x) .* Ref(km)) n, w = ElectrochemicalKinetics.scale(zero.(x), x) map((w, n) -> sum(w .* f(n)), eachcol(w), eachcol(n)) end diff --git a/src/plot_fcns.jl b/src/plot_fcns.jl index 1381f3e..1836f32 100644 --- a/src/plot_fcns.jl +++ b/src/plot_fcns.jl @@ -9,7 +9,7 @@ Plot predicted rate constants for each model in the provided list. # Keyword Arguments * V_min and V_max: bounds of voltage, defaults to +/- 1.0 * plot_title -* kwargs for compute_k function +* kwargs for rate_constant function """ function plot_models( models::Vector{<:KineticModel}; @@ -20,7 +20,7 @@ function plot_models( ) V_range = range(V_min, V_max, length = 200) xs = repeat([V_range], length(models)) - ys = map(model -> [compute_k(V, model; kwargs...) for V in V_range], models) + ys = map(model -> [rate_constant(V, model; kwargs...) for V in V_range], models) plot( xs, ys, @@ -42,7 +42,7 @@ Plot predicted rate constants for each model in the provided list. # Keyword Arguments * V_min and V_max: bounds of voltage, defaults to +/- 1.0 * plot_title -* kwargs for compute_k function +* kwargs for rate_constant function """ function plot_exp_and_models( exp_data::Matrix, @@ -56,7 +56,7 @@ function plot_exp_and_models( xs = Vector[V, repeat([V_range], length(models))...] ys = Vector[ exp_data[:, 2], - map(model -> compute_k(V_range, model; kwargs...), models)..., + map(model -> rate_constant(V_range, model; kwargs...), models)..., ] # scatter plot of experimental data, lines for fits diff --git a/test/fitting_tests.jl b/test/fitting_tests.jl index b93bce7..700daea 100644 --- a/test/fitting_tests.jl +++ b/test/fitting_tests.jl @@ -5,20 +5,20 @@ m = model_type(params[model_type]...) # test a number less than the initial guess V1 = 0.05 - k1 = compute_k(V1, m) - @test isapprox(fit_overpotential(k1, m)[1], V1, atol=1e-5) + k1 = rate_constant(V1, m) + @test isapprox(overpotential(k1, m)[1], V1, atol=1e-5) # and one greater V2 = 0.15 - k2 = compute_k(V2, m) - @test isapprox(fit_overpotential(k2, m)[1], V2, atol=1e-5) + k2 = rate_constant(V2, m) + @test isapprox(overpotential(k2, m)[1], V2, atol=1e-5) # test that vectorized fitting works...first for one model and multiple k's - # this test is turned off for now because better adjoint of fit_overpotential currently doesn't work with it... - # @test isapprox(fit_overpotential(m, [k1, k2]), [V1, V2], atol=5e-4) + # this test is turned off for now because better adjoint of overpotential currently doesn't work with it... + # @test isapprox(overpotential(m, [k1, k2]), [V1, V2], atol=5e-4) # TODO: figure out sensible and consistent way to vectorize over k and/or V (e.g. use a matrix?) # now test for one k and multiple models - @test isapprox(fit_overpotential(k1, [m, m]), [V1, V1], atol=5e-4) + @test isapprox(overpotential(k1, [m, m]), [V1, V1], atol=5e-4) # make sure that both fails since indexing would be ambiguous - @test_throws MethodError fit_overpotential([k1, k2], [m, m]) + @test_throws MethodError overpotential([k1, k2], [m, m]) end end # for now, writing these separately to test different input DOSes @@ -33,13 +33,13 @@ for dos in [flat_dos, smooth_dos] m = MarcusHushChidseyDOS(0.25, dos) V1 = 0.05 - k1 = compute_k(V1, m) - @test isapprox(fit_overpotential(k1, m)[1], V1, atol=1e-5) + k1 = rate_constant(V1, m) + @test isapprox(overpotential(k1, m)[1], V1, atol=1e-5) V2 = 0.15 - k2 = compute_k(V2, m) - @test isapprox(fit_overpotential(k2, m)[1], V2, atol=1e-5) + k2 = rate_constant(V2, m) + @test isapprox(overpotential(k2, m)[1], V2, atol=1e-5) # this one is disabled for now for same reason as above - # @test isapprox(fit_overpotential([k1, k2], m), [V1, V2], atol=5e-4) + # @test isapprox(overpotential([k1, k2], m), [V1, V2], atol=5e-4) end end end diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index b026cdc..37e6824 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -6,13 +6,13 @@ mhc = MarcusHushChidsey(0.25) @testset "Scalars" begin # test some values - @test compute_k(0, mhc) == 0.0 - @test compute_k(0, mhc, true) == compute_k(0, mhc, false) ≈ 0.0061371322 - @test isapprox(compute_k(0.1, mhc), 0.031239978, atol=1e-6) + @test rate_constant(0, mhc) == 0.0 + @test rate_constant(0, mhc, true) == rate_constant(0, mhc, false) ≈ 0.0061371322 + @test isapprox(rate_constant(0.1, mhc), 0.031239978, atol=1e-6) # test net rates and symmetry - @test isapprox(compute_k(0.1, mhc, true) - compute_k(0.1, mhc, false), compute_k(0.1, mhc), atol=1e-6) - @test compute_k(-0.1, mhc) == compute_k(0.1, mhc) + @test isapprox(rate_constant(0.1, mhc, true) - rate_constant(0.1, mhc, false), rate_constant(0.1, mhc), atol=1e-6) + @test rate_constant(-0.1, mhc) == rate_constant(0.1, mhc) end @testset "Vector Voltages" begin @@ -20,7 +20,7 @@ @test isapprox(mhc(Vs), mhc(-Vs)) #symmetry # test that it's close to asymptotic version amhc = AsymptoticMarcusHushChidsey(0.25) - @test all(isapprox.(compute_k(Vs, mhc), compute_k(Vs, amhc), atol=2e-4)) + @test all(isapprox.(rate_constant(Vs, mhc), rate_constant(Vs, amhc), atol=2e-4)) end end @@ -28,10 +28,10 @@ # test that a uniform DOS version matches MHC flat_dos = [-5 1; 5 1] mhcd = MarcusHushChidseyDOS(0.25, flat_dos) - @test isapprox(compute_k(0, mhcd), 0.0, atol=1e-6) + @test isapprox(rate_constant(0, mhcd), 0.0, atol=1e-6) mhc = MarcusHushChidsey(0.25) - mhcd_k = compute_k(Vs, mhcd) - mhc_k = compute_k(Vs, mhc) + mhcd_k = rate_constant(Vs, mhcd) + mhc_k = rate_constant(Vs, mhc) @test all(isapprox.(mhc_k, mhcd_k, atol=1e-6)) # make some cartoon smooth DOSes... @@ -41,11 +41,11 @@ dos = hcat(Es, gaussian.(0.7 .*(Es .- 2)) .+ gaussian.(0.7 .*(Es .+ 2))) mhcd = MarcusHushChidseyDOS(0.25, dos) # this should be symmetric - @test all(isapprox.(compute_k(Vs, mhcd), compute_k(-Vs, mhcd), atol=1e-6)) + @test all(isapprox.(rate_constant(Vs, mhcd), rate_constant(-Vs, mhcd), atol=1e-6)) # now try an asymmetric one dos = hcat(Es .+ 1, dos[:,2]) mhcd = MarcusHushChidseyDOS(0.25, dos) - @test all(compute_k(-Vs, mhcd) .> compute_k(Vs, mhcd)) + @test all(rate_constant(-Vs, mhcd) .> rate_constant(Vs, mhcd)) end @testset "Quantum Capacitance" begin diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index d7f961d..ce7c0af 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -10,7 +10,7 @@ @testset "Scalars" begin # zero voltage - @test all(compute_k.(Ref(0), [bv1, bv2, bv3]).==0) + @test all(rate_constant.(Ref(0), [bv1, bv2, bv3]).==0) # oxidative for bv in [bv1, bv2, bv3] @@ -45,11 +45,11 @@ bvv3 = ButlerVolmer(A_vals, α_vals) # invalid, different lengths # test that it's equivalent to the scalar model version - @test compute_k(0.1, bvv1) == compute_k.(Ref(0.1), ButlerVolmer.(A_vals)) - @test compute_k(0.1, bvv2) == compute_k.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) + @test rate_constant(0.1, bvv1) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals)) + @test rate_constant(0.1, bvv2) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) # test that correct error is thrown - @test_throws DimensionMismatch compute_k(0, bvv3) + @test_throws DimensionMismatch rate_constant(0, bvv3) end @testset "Vector Voltages and Models" begin # TODO: this @@ -83,8 +83,8 @@ mv1 = Marcus(λ_vals) mv2 = Marcus(A_vals, λ_vals) - @test compute_k(0.1, mv1) == compute_k.(Ref(0.1), Marcus.(λ_vals)) - @test compute_k(0.1, mv2) == compute_k.(Ref(0.1), Marcus.(A_vals, λ_vals)) + @test rate_constant(0.1, mv1) == rate_constant.(Ref(0.1), Marcus.(λ_vals)) + @test rate_constant(0.1, mv2) == rate_constant.(Ref(0.1), Marcus.(A_vals, λ_vals)) end @testset "Vector Voltages and Models" begin # TODO: this @@ -111,8 +111,8 @@ amhc1 = AsymptoticMarcusHushChidsey(λ_vals) amhc2 = AsymptoticMarcusHushChidsey(A_vals, λ_vals) - @test compute_k(0.1, amhc1) == compute_k.(Ref(0.1), AsymptoticMarcusHushChidsey.(λ_vals)) - @test compute_k(0.1, amhc2) == compute_k.(Ref(0.1), AsymptoticMarcusHushChidsey.(A_vals, λ_vals)) + @test rate_constant(0.1, amhc1) == rate_constant.(Ref(0.1), AsymptoticMarcusHushChidsey.(λ_vals)) + @test rate_constant(0.1, amhc2) == rate_constant.(Ref(0.1), AsymptoticMarcusHushChidsey.(A_vals, λ_vals)) end @testset "Vector Voltages and Models" begin # TODO: this diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 66c2aaf..79dce54 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -73,7 +73,7 @@ xs = [0.1, 0.5, 0.95] # test that the right (approximate) relationships hold μs = μ_50_vals[typeof(km)] for x in xs - @test μ_50(x) ≈ μs[x] ≈ μ_thermo(x) + fit_overpotential(50, (1-x)*km) + @test μ_50(x) ≈ μs[x] ≈ μ_thermo(x) + overpotential(50, (1-x)*km) end # test vector inputs diff --git a/test/runtests.jl b/test/runtests.jl index e4c5826..052d1fa 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -3,8 +3,8 @@ using QuadGK using Test function test_vector_voltages(model, voltages) - @test isapprox(compute_k(voltages, model), compute_k.(voltages, Ref(model))) - @test isapprox(compute_k(voltages, model, kT=0.4), compute_k.(voltages, Ref(model), kT=0.4)) + @test isapprox(rate_constant(voltages, model), rate_constant.(voltages, Ref(model))) + @test isapprox(rate_constant(voltages, model, kT=0.4), rate_constant.(voltages, Ref(model), kT=0.4)) end @testset "ElectrochemicalKinetics.jl" begin From 0539cbdfc83392867fda662fb0d89e1f45f2a6f6 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Wed, 6 Jul 2022 16:46:16 -0400 Subject: [PATCH 07/25] add type parameters, fix tests Signed-off-by: Rachel Kurchin --- .../AsymptoticMarcusHushChidsey.jl | 10 ++++-- src/kinetic_models/ButlerVolmer.jl | 11 ++++-- src/kinetic_models/Marcus.jl | 10 ++++-- src/kinetic_models/MarcusHushChidsey.jl | 14 +++++--- src/kinetic_models/MarcusHushChidseyDOS.jl | 10 ++++-- src/kinetic_models/kinetic_models.jl | 4 ++- src/utils/misc.jl | 20 +++++++++++ test/non_integral_model_tests.jl | 5 +-- test/phase_diagram_tests.jl | 36 +++++++++---------- 9 files changed, 80 insertions(+), 40 deletions(-) create mode 100644 src/utils/misc.jl diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 8b993f8..a12e368 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -6,9 +6,13 @@ Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/ If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. """ -struct AsymptoticMarcusHushChidsey <: NonIntegralModel - A - λ +struct AsymptoticMarcusHushChidsey{T} <: NonIntegralModel + A::T + λ::T + function AsymptoticMarcusHushChidsey(A, λ) + ps = consistent_params(Float64.(A), Float64.(λ)) + new{typeof(ps[1])}(ps...) + end end # default prefactor is 1 diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index d97d74a..713e1d4 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -6,9 +6,14 @@ Computes Butler-Volmer kinetics. If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. """ -struct ButlerVolmer <: NonIntegralModel - A - α +struct ButlerVolmer{T} <: NonIntegralModel + A::T + α::T + function ButlerVolmer(A, α) + @assert all(α .<= 1.0 .&& α .>=0.0) "Electron transfer coefficient must be in [0,1]" + ps = consistent_params(Float64.(A), Float64.(α)) + new{typeof(ps[1])}(ps...) + end end # default to unit prefactor and symmetric response diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index dddbb9a..60954b0 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -6,9 +6,13 @@ Computes Marcus kinetics. If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. """ -struct Marcus <: NonIntegralModel - A - λ +struct Marcus{T} <: NonIntegralModel + A::T + λ::T + function Marcus(A, λ) + ps = consistent_params(Float64.(A), Float64.(λ)) + new{typeof(ps[1])}(ps...) + end end # default prefactor is 1 diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 0654843..0d87f40 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -9,10 +9,14 @@ Note that for "typical" reorganization energy values (in the vicinity of 10*kT a If either the prefactor or the average dos are omitted, their values are assumed to be 1. Note that strictly speaking, `average_dos` and the prefactor `A` are redundant. They are both included primarily to facilitate comparisons with similarly parametrized Marcus-like models such as `MarcusHushChidseyDOS`. """ -struct MarcusHushChidsey <: IntegralModel - A - λ - average_dos +struct MarcusHushChidsey{T} <: IntegralModel + A::T + λ::T + average_dos::T + function MarcusHushChidsey(A, λ, average_dos) + ps = consistent_params(Float64.(A), Float64.(λ), Float64.(average_dos)) + new{typeof(ps[1])}(ps...) + end end # default prefactor is 1 @@ -20,7 +24,7 @@ MarcusHushChidsey(λ, avg_dos) = MarcusHushChidsey(1.0, λ, avg_dos) # assume prefactor = 1 and avg_dos = 1 MarcusHushChidsey(λ) = MarcusHushChidsey(1.0, λ, 1.0) # convert more detailed DOS information to just pull out average -MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, Ref(dd.average_value)) +MarcusHushChidsey(A, λ, dd::DOSData) = MarcusHushChidsey(A, λ, dd.average_value) MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index 35b9b6a..4e2a6e6 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -8,10 +8,14 @@ Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanat NB: At the moment, this will allow for vector `A` and `λ` parameters, but will presume that all models correspond to the same DOS. """ -struct MarcusHushChidseyDOS <: IntegralModel - A - λ +struct MarcusHushChidseyDOS{T} <: IntegralModel + A::T + λ::T dos::DOSData + function MarcusHushChidseyDOS(A, λ, dos) + ps = consistent_params(Float64.(A), Float64.(λ)) + new{typeof(ps[1])}(ps..., dos) + end end function Base.show(io::IO, mhcd::MarcusHushChidseyDOS) diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index 3b3095d..f5b905d 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -4,6 +4,8 @@ using Statistics using Interpolations using DelimitedFiles +include("../utils/misc.jl") + """ fermi_dirac(E, kT=0.026) @@ -23,7 +25,7 @@ import Base.* function *(c::Real, km::KineticModel) new_A = c*km.A other_params = getfield.([km], propertynames(km))[2:end] - typeof(km)(new_A, other_params...) + eval(nameof(typeof(km)))(new_A, other_params...) end # generic pretty printing diff --git a/src/utils/misc.jl b/src/utils/misc.jl new file mode 100644 index 0000000..370f106 --- /dev/null +++ b/src/utils/misc.jl @@ -0,0 +1,20 @@ +# make a list of parameters into a list of vectors of the same length +function consistent_params(ps...) + lengths = Set(length.(ps)) + if length(lengths) == 1 # they're already the same length + return ps + elseif (length(lengths)==2 && 1 in lengths) + len = [l for l in lengths if l!=1][1] + new_ps = [] + for p in ps + if length(p) == len + push!(new_ps, p) + else + push!(new_ps, repeat([p], len)) + end + end + return new_ps + else + throw(DimensionMismatch("Mixed length fields...they must be all the same length, or a combination of one length and length one ;)")) + end +end diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index ce7c0af..88c3f7c 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -42,14 +42,11 @@ α_vals = [0.4, 0.5, 0.6] bvv1 = ButlerVolmer(A_vals) # autopopulate α, combine scalar/vector bvv2 = ButlerVolmer(A_vals, α_vals[1:2]) # both vectors - bvv3 = ButlerVolmer(A_vals, α_vals) # invalid, different lengths + @test_throws DimensionMismatch ButlerVolmer(A_vals, α_vals) # invalid, different lengths # test that it's equivalent to the scalar model version @test rate_constant(0.1, bvv1) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals)) @test rate_constant(0.1, bvv2) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) - - # test that correct error is thrown - @test_throws DimensionMismatch rate_constant(0, bvv3) end @testset "Vector Voltages and Models" begin # TODO: this diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 79dce54..3524bf6 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -42,28 +42,28 @@ xs = [0.1, 0.5, 0.95] @testset "Kinetic μ" begin # all these numbers are just references evaluated as of 2/24/22 μ_50_vals = Dict( - ButlerVolmer=>Dict( + :ButlerVolmer=>Dict( 0.1 => 0.0383864736, 0.5 => 0.01862765755, 0.95 => 0.06237022288), - Marcus=>Dict( + :Marcus=>Dict( 0.1 => 0.02841242588577, 0.5 => 0.01928206795, 0.95 => 0.07492901629449), - AsymptoticMarcusHushChidsey=>Dict( + :AsymptoticMarcusHushChidsey=>Dict( 0.1 => 0.0389118763, 0.5 => 0.0195713281175, 0.95 => 0.0735097011) ) μ_200_vals = Dict( - ButlerVolmer=>[0.0524237924, 0.04250974, 0.13058880458], - Marcus=>[0.054009696387679, 0.045881168639779, 0.212205862750], - AsymptoticMarcusHushChidsey=>[0.05451269755, 0.046343172588, 0.17452291988558] + :ButlerVolmer=>[0.0524237924, 0.04250974, 0.13058880458], + :Marcus=>[0.054009696387679, 0.045881168639779, 0.212205862750], + :AsymptoticMarcusHushChidsey=>[0.05451269755, 0.046343172588, 0.17452291988558] ) μ_100_T400_vals = Dict( - ButlerVolmer=>[0.02384219096, 0.02702875, 0.1212749347], - Marcus=>[0.024573427974, 0.028429814254, 0.1529930329757], - AsymptoticMarcusHushChidsey=>[0.024890385314, 0.028908839244, 0.14468140815] + :ButlerVolmer=>[0.02384219096, 0.02702875, 0.1212749347], + :Marcus=>[0.024573427974, 0.028429814254, 0.1529930329757], + :AsymptoticMarcusHushChidsey=>[0.024890385314, 0.028908839244, 0.14468140815] ) for km in kms @testset "$(typeof(km))" begin @@ -71,25 +71,25 @@ xs = [0.1, 0.5, 0.95] μ_200 = μ_kinetic(200, km) μ_100_T400 = μ_kinetic(100, km, T=400) # test that the right (approximate) relationships hold - μs = μ_50_vals[typeof(km)] + μs = μ_50_vals[typeof(km).name.name] for x in xs @test μ_50(x) ≈ μs[x] ≈ μ_thermo(x) + overpotential(50, (1-x)*km) end # test vector inputs - @test μ_200(xs) ≈ μ_200_vals[typeof(km)] - @test μ_100_T400(xs) == μ_100_T400.(xs) ≈ μ_100_T400_vals[typeof(km)] + @test μ_200(xs) ≈ μ_200_vals[typeof(km).name.name] + @test μ_100_T400(xs) == μ_100_T400.(xs) ≈ μ_100_T400_vals[typeof(km).name.name] end end end @testset "Kinetic g" begin g_200_T400_vals = Dict( - ButlerVolmer => [0.0205857425, 0.037693617, 0.06661696], - Marcus => [0.02073470111, 0.03874647481, 0.07399607032], - AsymptoticMarcusHushChidsey => [0.0207838185, 0.0390031065, 0.0729910686] + :ButlerVolmer => [0.0205857425, 0.037693617, 0.06661696], + :Marcus => [0.02073470111, 0.03874647481, 0.07399607032], + :AsymptoticMarcusHushChidsey => [0.0207838185, 0.0390031065, 0.0729910686] ) - g_50_2_vals = Dict(ButlerVolmer=>0.03519728018258, Marcus=>0.03395267141265, AsymptoticMarcusHushChidsey=>0.0347968044) + g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018258, :Marcus=>0.03395267141265, :AsymptoticMarcusHushChidsey=>0.0347968044) for km in kms @testset "$(typeof(km))" begin μ_50 = μ_kinetic(50, km) @@ -102,10 +102,10 @@ end # check scalar input works @test g_50(xs[2]) == g_50(xs)[2] - @test isapprox(g_50(xs)[2], g_50_2_vals[typeof(km)], atol=1e-5) + @test isapprox(g_50(xs)[2], g_50_2_vals[typeof(km).name.name], atol=1e-5) # check a few other values - @test all(isapprox.(g_200_T400(xs), g_200_T400_vals[typeof(km)], atol=1e-5)) + @test all(isapprox.(g_200_T400(xs), g_200_T400_vals[typeof(km).name.name], atol=1e-5)) end end end From 6d1af53592aeb3a138969148c8a5fb36fd7909d2 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Wed, 6 Jul 2022 17:12:44 -0400 Subject: [PATCH 08/25] fix typo, update benchmark syntax Signed-off-by: Rachel Kurchin --- benchmark/bench_suite.jl | 16 ++++++++-------- src/fitting.jl | 2 +- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/benchmark/bench_suite.jl b/benchmark/bench_suite.jl index 38add0d..c3186e7 100644 --- a/benchmark/bench_suite.jl +++ b/benchmark/bench_suite.jl @@ -22,8 +22,8 @@ suite["rate constants"]["non-integral models"]["vector V"] = BenchmarkGroup() for km in ni_kms modeltype = typeof(km) - suite["rate constants"]["non-integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant(0.1, $km) seconds=time_mult*0.1 - suite["rate constants"]["non-integral models"]["vector V"][modeltype] = @benchmarkable rate_constant(0.01:0.01:0.2, $km) seconds=time_mult + suite["rate constants"]["non-integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant($0.1, $km) seconds=time_mult*0.1 + suite["rate constants"]["non-integral models"]["vector V"][modeltype] = @benchmarkable rate_constant($0.01:0.01:0.2, $km) seconds=time_mult end mhc = MarcusHushChidsey(70000, 0.3, 1.0) @@ -38,8 +38,8 @@ suite["rate constants"]["integral models"]["vector V"] = BenchmarkGroup() for km in i_kms modeltype = names[km] - suite["rate constants"]["integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant(0.1, $km) seconds=time_mult*8 - suite["rate constants"]["integral models"]["vector V"][modeltype] = @benchmarkable rate_constant(0.01:0.01:0.2, $km) seconds=time_mult*11 + suite["rate constants"]["integral models"]["scalar V"][modeltype] = @benchmarkable rate_constant($0.1, $km) seconds=time_mult*8 + suite["rate constants"]["integral models"]["vector V"][modeltype] = @benchmarkable rate_constant($0.01:0.01:0.2, $km) seconds=time_mult*11 end # overpotential benchmarks @@ -53,8 +53,8 @@ suite["overpotential fitting"]["non-integral models"]["AD"] = BenchmarkGroup() for km in ni_kms modeltype = typeof(km) - suite["overpotential fitting"]["non-integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=false) seconds=time_mult*3 - suite["overpotential fitting"]["non-integral models"]["AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=true) seconds=time_mult*5 + suite["overpotential fitting"]["non-integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=false) seconds=time_mult*3 + suite["overpotential fitting"]["non-integral models"]["AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=true) seconds=time_mult*5 end suite["overpotential fitting"]["integral models"] = BenchmarkGroup() @@ -62,6 +62,6 @@ suite["overpotential fitting"]["integral models"]["non-AD"] = BenchmarkGroup() suite["overpotential fitting"]["integral models"]["AD"] = BenchmarkGroup() for km in i_kms[2:end] # skipping MHC for now modeltype = names[km] - suite["overpotential fitting"]["integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=false) seconds=time_mult*10 - suite["overpotential fitting"]["integral models"]["AD"][modeltype] = @benchmarkable overpotential($km, $k, autodiff=true) seconds=time_mult*20 + suite["overpotential fitting"]["integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=false) seconds=time_mult*10 + suite["overpotential fitting"]["integral models"]["AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=true) seconds=time_mult*20 end diff --git a/src/fitting.jl b/src/fitting.jl index 9a666eb..d2f44bd 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -10,7 +10,7 @@ log_loss(y, y_pred) = (log.(y) .- log.(y_pred)).^2 linear_loss(y, y_pred) = (y .- y_pred).^2 """ - overpotential(model, k; kwargs...) + overpotential(k, model; kwargs...) Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) 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zQ;5q-N1$VO9lYtMf$oVM%H1*(UAu+Tcqb1b~lv>aB(b0WhN34EyfaY1*L4A(OAn!&oA90BCtKm>G lY(WpU7qd8CdDRMerS&lN51yjB$NG6$&NtGG_0D1>e*yi>N(BG_ literal 0 HcmV?d00001 From fdb7454bc08af1c7286fd425b81f94b507a53ba1 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Wed, 6 Jul 2022 18:11:18 -0400 Subject: [PATCH 10/25] fix vector cases - add type parameter to abstract types to make dispatch easier in case we need it later - fix scalar-specific AD stuff in overpotential...this may have caused a performance penalty, but long vectors still win - it's often getting the wrong sign of the potential now, so I'll remove the absolute value again next Signed-off-by: Rachel Kurchin --- src/fitting.jl | 22 +++++++------------ .../AsymptoticMarcusHushChidsey.jl | 2 +- src/kinetic_models/ButlerVolmer.jl | 2 +- src/kinetic_models/Marcus.jl | 2 +- src/kinetic_models/MarcusHushChidsey.jl | 2 +- src/kinetic_models/MarcusHushChidseyDOS.jl | 2 +- src/kinetic_models/kinetic_models.jl | 9 +++++--- 7 files changed, 19 insertions(+), 22 deletions(-) diff --git a/src/fitting.jl b/src/fitting.jl index d2f44bd..314953d 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -14,31 +14,30 @@ linear_loss(y, y_pred) = (y .- y_pred).^2 Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) """ -function overpotential(k, model::KineticModel, guess = fill(0.1, length(k)); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) +function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) function compare_k!(storage, V) storage .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) end Vs = if autodiff function myfun!(F, J, V) - if J == nothing + if isnothing(J) F .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) - elseif F == nothing && !isnothing(J) - # TODO: we could speed up the case of scalar k's by dispatching to call gradient here instead - gs = Zygote.gradient(V[1]) do V + elseif isnothing(F) && !isnothing(J) + gs = Zygote.gradient(V) do V Zygote.forwarddiff(V) do V loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum end end[1] - J .= gs + J .= diagm(gs) else - y, back = Zygote.pullback(V[1]) do V + y, back = Zygote.pullback(V) do V Zygote.forwarddiff(V) do V loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum end end F .= y - J .= back(one.(y))[1] + J .= diagm(back(one.(y))[1]) end end Vs = nlsolve(only_fj!(myfun!), guess, show_trace=verbose) @@ -48,12 +47,7 @@ function overpotential(k, model::KineticModel, guess = fill(0.1, length(k)); kT if !converged(Vs) @warn "Overpotential fit not fully converged...you may have fed in an unreachable reaction rate!" end - # this is janky but the broadcast doesn't work otherwise - if typeof(k) <: Array - Vs.zero - else - Vs.zero[1] - end + Vs.zero end inv!(x) = x .= inv.(x) diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index a12e368..2c35338 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -6,7 +6,7 @@ Computes asymptotic solution to MHC model, as described in Zeng et al.: 10.1016/ If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor to 1.0. """ -struct AsymptoticMarcusHushChidsey{T} <: NonIntegralModel +struct AsymptoticMarcusHushChidsey{T} <: NonIntegralModel{T} A::T λ::T function AsymptoticMarcusHushChidsey(A, λ) diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index 713e1d4..9030708 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -6,7 +6,7 @@ Computes Butler-Volmer kinetics. If initialized with one argument, assumes symmetric electron transfer (α=0.5) and sets this to be the prefactor A. Note that this prefactor implicitly contains information about equilibrium activation energies, as well as geometric information. """ -struct ButlerVolmer{T} <: NonIntegralModel +struct ButlerVolmer{T} <: NonIntegralModel{T} A::T α::T function ButlerVolmer(A, α) diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 60954b0..17f09c7 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -6,7 +6,7 @@ Computes Marcus kinetics. If initialized with one argument, assumes this to be the reorganization energy λ and sets the prefactor A to 1.0. """ -struct Marcus{T} <: NonIntegralModel +struct Marcus{T} <: NonIntegralModel{T} A::T λ::T function Marcus(A, λ) diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 0d87f40..7202557 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -9,7 +9,7 @@ Note that for "typical" reorganization energy values (in the vicinity of 10*kT a If either the prefactor or the average dos are omitted, their values are assumed to be 1. Note that strictly speaking, `average_dos` and the prefactor `A` are redundant. They are both included primarily to facilitate comparisons with similarly parametrized Marcus-like models such as `MarcusHushChidseyDOS`. """ -struct MarcusHushChidsey{T} <: IntegralModel +struct MarcusHushChidsey{T} <: IntegralModel{T} A::T λ::T average_dos::T diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index 4e2a6e6..d7da536 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -8,7 +8,7 @@ Computes Marcus-Hush-Chidsey + DOS kinetics as described in Kurchin and Viswanat NB: At the moment, this will allow for vector `A` and `λ` parameters, but will presume that all models correspond to the same DOS. """ -struct MarcusHushChidseyDOS{T} <: IntegralModel +struct MarcusHushChidseyDOS{T} <: IntegralModel{T} A::T λ::T dos::DOSData diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index f5b905d..101ad08 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -22,12 +22,15 @@ abstract type KineticModel end # return a new one with a scaled prefactor import Base.* -function *(c::Real, km::KineticModel) +function *(c, km::KineticModel) new_A = c*km.A other_params = getfield.([km], propertynames(km))[2:end] eval(nameof(typeof(km)))(new_A, other_params...) end +import Base.length +length(km::KineticModel) = length(km.A) + # generic pretty printing function Base.show(io::IO, m::KineticModel) s = repr(typeof(m)) * "(" @@ -48,14 +51,14 @@ end Abstract base class for kinetic models whose rates can be computed directly from an input voltage without requiring an energy integral. All subtypes must dispatch the `rate_constant` function. """ -abstract type NonIntegralModel <: KineticModel end +abstract type NonIntegralModel{T} <: KineticModel end """ IntegralModel Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `rate_constant` function directly, or dispatch the `integrand` function and use the default `rate_constant` dispatch. """ -abstract type IntegralModel <: KineticModel end +abstract type IntegralModel{T} <: KineticModel end # check to catch missed dispatches for new types # integrand(km::IntegralModel, V_dl, ox::Bool; kwargs...) = From a3a0dd8a843105736c287a41237c46e5638a4e47 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Wed, 6 Jul 2022 19:00:19 -0400 Subject: [PATCH 11/25] remove absolute value, fix Marcus sign error, fix tests Signed-off-by: Rachel Kurchin --- src/fitting.jl | 15 ++++++++++++++- .../AsymptoticMarcusHushChidsey.jl | 2 +- src/kinetic_models/Marcus.jl | 4 ++-- src/kinetic_models/MarcusHushChidsey.jl | 2 +- src/kinetic_models/kinetic_models.jl | 14 ++++++-------- test/fitting_tests.jl | 16 ++++++++-------- test/integral_model_tests.jl | 8 ++++---- test/non_integral_model_tests.jl | 12 ++++++------ test/phase_diagram_tests.jl | 4 ++-- 9 files changed, 44 insertions(+), 33 deletions(-) diff --git a/src/fitting.jl b/src/fitting.jl index 314953d..496c576 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -9,12 +9,23 @@ log_loss(y, y_pred) = (log.(y) .- log.(y_pred)).^2 # sum of squares loss in linear coordinates linear_loss(y, y_pred) = (y .- y_pred).^2 +# one that works for both signs +function janky_log_loss(y, y_pred) + if all(y .* y_pred .> 0) + return log_loss(abs.(y), abs.(y_pred)) + else + # @warn "Values have different signs...defaulting to squared error" + # this should be fine to (hopefully) push things into the right region... + return linear_loss(y, y_pred) + end +end + """ overpotential(k, model; kwargs...) Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) """ -function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); kT = 0.026, loss = log_loss, autodiff = true, verbose=false, kwargs...) +function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); kT = 0.026, loss = janky_log_loss, autodiff = true, verbose=false, kwargs...) function compare_k!(storage, V) storage .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) end @@ -50,6 +61,8 @@ function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), Vs.zero end +overpotential(k::Real, model::KineticModel{T}, guess=0.1; kwargs...) where T<:Real = overpotential([k], model, [0.1]; kwargs...)[1] + inv!(x) = x .= inv.(x) Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 2c35338..0fb4baa 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -34,5 +34,5 @@ function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.02 a = 1 .+ sqrt.(λ_nondim) arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 .* sqrt.(λ_nondim)) pref = sqrt.(π .* λ_nondim) .* tanh.(η/2) - return abs.(kT * amhc.A .* pref .* erfc.(arg)) + return kT * amhc.A .* pref .* erfc.(arg) end diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 17f09c7..ab7bbfe 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -19,11 +19,11 @@ end Marcus(λ) = Marcus(1.0, λ) function rate_constant(V_app, m::Marcus, ::Val{true}; kT = 0.026) - exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kT) + exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end function rate_constant(V_app, m::Marcus, ::Val{false}; kT = 0.026) - exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kT) + exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kT) m.A .* exp.(exp_arg) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 7202557..4ea2f93 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -33,5 +33,5 @@ function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; kT::Real = 0.026) marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 .* mhc.λ .* kT)) marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 .* mhc.λ .* kT)) f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages - f(E::Real) = (mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT) + f(E::Real) = (mhc.A .* mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT) end \ No newline at end of file diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index 101ad08..fad5096 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -18,7 +18,7 @@ fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) Abstract base class for kinetic models. """ -abstract type KineticModel end +abstract type KineticModel{T} end # return a new one with a scaled prefactor import Base.* @@ -51,14 +51,14 @@ end Abstract base class for kinetic models whose rates can be computed directly from an input voltage without requiring an energy integral. All subtypes must dispatch the `rate_constant` function. """ -abstract type NonIntegralModel{T} <: KineticModel end +abstract type NonIntegralModel{T} <: KineticModel{T} end """ IntegralModel Abstract base class for "Marcus-like" kinetic models that require computation of an energy integral. All subtypes need to dispatch the `rate_constant` function directly, or dispatch the `integrand` function and use the default `rate_constant` dispatch. """ -abstract type IntegralModel{T} <: KineticModel end +abstract type IntegralModel{T} <: KineticModel{T} end # check to catch missed dispatches for new types # integrand(km::IntegralModel, V_dl, ox::Bool; kwargs...) = @@ -67,9 +67,7 @@ abstract type IntegralModel{T} <: KineticModel end # TODO: check that this passes through both kT and V_q appropriately # dispatch for net rates integrand(km::IntegralModel, V; kwargs...) = - E -> abs.( - integrand(km, V, Val(true); kwargs...)(E) - integrand(km, V, Val(false); kwargs...)(E) - ) + E -> integrand(km, V, Val(true); kwargs...)(E) - integrand(km, V, Val(false); kwargs...)(E) integrand(km::IntegralModel, V, ox::Bool; kwargs...) = integrand(km, V, Val(ox); kwargs...) """ @@ -85,9 +83,9 @@ If calc_cq flag is passed, optionally compute voltage shifts due to quantum capa """ rate_constant(V_app, model::NonIntegralModel, ox::Bool; kwargs...) = rate_constant(V_app, model, Val(ox); kwargs...) -# default dispatch for net rates, returns absolute value +# dispatch for net rates rate_constant(V_app, model::NonIntegralModel; kwargs...) = - abs.(rate_constant(V_app, model, Val(true); kwargs...) - rate_constant(V_app, model, Val(false); kwargs...)) + rate_constant(V_app, model, Val(true); kwargs...) - rate_constant(V_app, model, Val(false); kwargs...) # TODO: add tests that both args and kwargs are correctly captured here (also for the Val thing) # "callable" syntax diff --git a/test/fitting_tests.jl b/test/fitting_tests.jl index 700daea..67082d7 100644 --- a/test/fitting_tests.jl +++ b/test/fitting_tests.jl @@ -6,17 +6,17 @@ # test a number less than the initial guess V1 = 0.05 k1 = rate_constant(V1, m) - @test isapprox(overpotential(k1, m)[1], V1, atol=1e-5) + @test isapprox(overpotential(k1, m), V1, atol=1e-5) # and one greater V2 = 0.15 k2 = rate_constant(V2, m) - @test isapprox(overpotential(k2, m)[1], V2, atol=1e-5) - # test that vectorized fitting works...first for one model and multiple k's - # this test is turned off for now because better adjoint of overpotential currently doesn't work with it... - # @test isapprox(overpotential(m, [k1, k2]), [V1, V2], atol=5e-4) - # TODO: figure out sensible and consistent way to vectorize over k and/or V (e.g. use a matrix?) - # now test for one k and multiple models - @test isapprox(overpotential(k1, [m, m]), [V1, V1], atol=5e-4) + @test isapprox(overpotential(k2, m), V2, atol=1e-5) + # test that vectorized fitting works, both for scalar k and vector model and vice versa + # TODO: figure out why this doesn't work for integral models + if model_type != MarcusHushChidsey + @test isapprox(overpotential([k1, k2], m), [V1, V2], atol=5e-4) + @test isapprox(overpotential(k1, [1,1]*m), [V1, V1], atol=5e-4) + end # make sure that both fails since indexing would be ambiguous @test_throws MethodError overpotential([k1, k2], [m, m]) end diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index 37e6824..e8220fa 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -12,12 +12,12 @@ # test net rates and symmetry @test isapprox(rate_constant(0.1, mhc, true) - rate_constant(0.1, mhc, false), rate_constant(0.1, mhc), atol=1e-6) - @test rate_constant(-0.1, mhc) == rate_constant(0.1, mhc) + @test -rate_constant(-0.1, mhc) == rate_constant(0.1, mhc) end @testset "Vector Voltages" begin test_vector_voltages(mhc, Vs) - @test isapprox(mhc(Vs), mhc(-Vs)) #symmetry + @test isapprox(mhc(Vs), -mhc(-Vs)) #symmetry # test that it's close to asymptotic version amhc = AsymptoticMarcusHushChidsey(0.25) @test all(isapprox.(rate_constant(Vs, mhc), rate_constant(Vs, amhc), atol=2e-4)) @@ -41,11 +41,11 @@ dos = hcat(Es, gaussian.(0.7 .*(Es .- 2)) .+ gaussian.(0.7 .*(Es .+ 2))) mhcd = MarcusHushChidseyDOS(0.25, dos) # this should be symmetric - @test all(isapprox.(rate_constant(Vs, mhcd), rate_constant(-Vs, mhcd), atol=1e-6)) + @test all(isapprox.(rate_constant(Vs, mhcd), -rate_constant(-Vs, mhcd), atol=1e-6)) # now try an asymmetric one dos = hcat(Es .+ 1, dos[:,2]) mhcd = MarcusHushChidseyDOS(0.25, dos) - @test all(rate_constant(-Vs, mhcd) .> rate_constant(Vs, mhcd)) + @test all(-rate_constant(-Vs, mhcd) .> rate_constant(Vs, mhcd)) end @testset "Quantum Capacitance" begin diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index 88c3f7c..160cffe 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -34,7 +34,7 @@ test_vector_voltages(bv2, Vs) test_vector_voltages(bv3, Vs) for model in [bv1, bv2] # bv3 won't be symmetrical - @test isapprox(model(Vs), model(-Vs)) #symmetry + @test isapprox(model(Vs), -model(-Vs)) #symmetry end end @testset "Vector Models" begin @@ -60,8 +60,8 @@ @testset "Scalars" begin # TODO: this could all be more thorough, I literally just picked some arbitrary points @test m1(0.0) == 0.0 - @test isapprox(m1(0.05, true), 0.031381, atol=1e-6) - @test isapprox(m1(0.2, false), 0.908324, atol=1e-6) + @test isapprox(m1(0.05, false), 0.031381, atol=1e-6) + @test isapprox(m1(0.2, true), 0.908324, atol=1e-6) @test isapprox(m1(0.13), 0.570862, atol=1e-6) @test isapprox(m2(0.13), 5.708625, atol=1e-6) end @@ -71,7 +71,7 @@ test_vector_voltages(m1, Vs) test_vector_voltages(m2, Vs) for model in [m1, m2] - @test isapprox(model(Vs), model(-Vs)) #symmetry + @test isapprox(model(Vs), -model(-Vs)) #symmetry end end @testset "Vector Models" begin @@ -94,13 +94,13 @@ @testset "Scalars" begin @test amhc(0.0) == 0.0 @test amhc(0.0, true) == amhc(0.0, false) ≈ 0.00596440064 - @test amhc(0.2) == amhc(-0.2) ≈ 0.1006330238 + @test amhc(0.2) == -amhc(-0.2) ≈ 0.1006330238 @test amhc(0.2, kT=.015) ≈ 0.06360960459 @test amhc(0.2, kT=.03) ≈ 0.11255129857 end @testset "Vector Voltages" begin test_vector_voltages(amhc, Vs) - @test isapprox(amhc(Vs), amhc(-Vs)) #symmetry + @test isapprox(amhc(Vs), -amhc(-Vs)) #symmetry end @testset "Vector Models" begin A_vals = [1, 100, 10000] diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 3524bf6..74ddaee 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -47,7 +47,7 @@ xs = [0.1, 0.5, 0.95] 0.5 => 0.01862765755, 0.95 => 0.06237022288), :Marcus=>Dict( - 0.1 => 0.02841242588577, + 0.1 => 0.0387445526862, 0.5 => 0.01928206795, 0.95 => 0.07492901629449), :AsymptoticMarcusHushChidsey=>Dict( @@ -89,7 +89,7 @@ end :Marcus => [0.02073470111, 0.03874647481, 0.07399607032], :AsymptoticMarcusHushChidsey => [0.0207838185, 0.0390031065, 0.0729910686] ) - g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018258, :Marcus=>0.03395267141265, :AsymptoticMarcusHushChidsey=>0.0347968044) + g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018258, :Marcus=>0.03542169346909, :AsymptoticMarcusHushChidsey=>0.03552448666) for km in kms @testset "$(typeof(km))" begin μ_50 = μ_kinetic(50, km) From b30e824fed2c4aa95df0b806e701fbac6bedf344 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 7 Jul 2022 11:25:11 -0400 Subject: [PATCH 12/25] ease tolerances and reduce integration nodes, didn't need that precision and want the speed Signed-off-by: Rachel Kurchin --- src/phase_diagrams.jl | 20 ++++---------------- src/utils/integration_utils.jl | 13 ++----------- test/phase_diagram_tests.jl | 6 +++--- 3 files changed, 9 insertions(+), 30 deletions(-) diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index d32f011..8702ced 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -9,8 +9,6 @@ const room_T = 298 const muoA_default = 0.02 const muoB_default = 0.03 const Ω_default = 0.1 -N = 1000 -quadfun = gausslegendre # our familiar thermodynamic functions h(x;Ω=Ω_default) = @. x*(1-x)*Ω # enthalpy of mixing @@ -36,7 +34,7 @@ function g_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=m #TODO: gradient of this term is just value of overpotential(x) function kinetic_term(x) f(x) = ElectrochemicalKinetics.overpotential(I, (1 .- x) .* Ref(km)) - n, w = ElectrochemicalKinetics.scale(zero.(x), x) + n, w = ElectrochemicalKinetics.scale_coarse(zero.(x), x) map((w, n) -> sum(w .* f(n)), eachcol(w), eachcol(n)) end g(x) = thermo_term(x) .+ kinetic_term(vec(x)) @@ -53,6 +51,7 @@ function common_tangent(x::Vector, I, km::KineticModel; Ω=Ω_default, muoA=muoA end # case where we want to check many points at once (shape of x should be N x 2) +# TODO: test this...may not really be able to save much time function common_tangent(x::Array, I, km::KineticModel; kwargs...) g = g_kinetic(I, km; kwargs...) µ = µ_kinetic(I, km; kwargs...) @@ -63,7 +62,7 @@ function common_tangent(x::Array, I, km::KineticModel; kwargs...) hcat(Δg ./ Δx .- μ1, Δμ) end -function find_phase_boundaries(I, km::KineticModel; quadfun=quadfun, N=N, kwargs...) +function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], verbose=false, kwargs...) function myct!(storage, x) res = common_tangent(x, I, km; kwargs...) @@ -71,21 +70,10 @@ function find_phase_boundaries(I, km::KineticModel; quadfun=quadfun, N=N, kwargs storage[2] = res[2] end # TODO: grad! here from AD - x1 = nlsolve(myct!, [0.05 0.95]) + x1 = nlsolve(myct!, guess, show_trace=verbose, ftol=1e-6, xtol=1e-6) x1.zero end function phase_diagram(km::KineticModel; kwargs...) # TODO: write this, lol end - -# bv = ButlerVolmer(300) -# I_vals = 10 .^ (1.1:0.025:3.1) - - -# this line takes a few seconds with B-V but aaages with anything else... -# pbs = [find_phase_boundaries(I, bv, T=330) for I in I_vals] - -# plot(vcat(pbs...), hcat(I_vals, I_vals), label="phase boundary") -# xlabel!("x") -# ylabel!("I") diff --git a/src/utils/integration_utils.jl b/src/utils/integration_utils.jl index 43995bb..925910d 100644 --- a/src/utils/integration_utils.jl +++ b/src/utils/integration_utils.jl @@ -16,14 +16,5 @@ function setup_integration(f, N) end end -const scale = setup_integration(gausslegendre, 1000) - -# Can't get this to broadcast correctly - but this is the right sort of -# approach to take here. Of note - this is 2x faster in the forwards pass -# and about 10x faster in the backwards pass compared to the other method -# function scale_integration_nodes2(unscaled_x, unscaled_w, lb, ub) -# w_scale = @. 0.5 * (ub - lb) -# x_scale = @. 0.5 * (ub + lb) + 0.5 * (ub - lb) -# unscaled_x * x_scale', unscaled_w * w_scale' -# # x_scale * unscaled_x, unscaled_w * w_scale' -# end +const scale = setup_integration(gausslegendre, 500) +const scale_coarse = setup_integration(gausslegendre, 50) diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 74ddaee..c804565 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -128,9 +128,9 @@ end @test v3[2] < v1[2] # test actual numerical values too - @test isapprox(v1, [0.04584 0.839942], atol=1e-6) - @test isapprox(v2, [0.0837787 0.795035], atol=1e-6) - @test isapprox(v3, [0.107585 0.675948], atol=1e-6) + @test isapprox(v1, [0.04584, 0.839942], atol=1e-5) + @test isapprox(v2, [0.0837787, 0.795035], atol=1e-5) + @test isapprox(v3, [0.107585, 0.675948], atol=1e-5) # TODO: next for multiple currents at once (may require some syntax tweaks) From a5bf5a628d665b847dfc027c52bf9a5bc4318e8a Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 7 Jul 2022 13:21:58 -0400 Subject: [PATCH 13/25] single precision Signed-off-by: Rachel Kurchin --- src/fitting.jl | 6 +-- .../AsymptoticMarcusHushChidsey.jl | 2 +- src/kinetic_models/ButlerVolmer.jl | 2 +- src/kinetic_models/Marcus.jl | 2 +- src/kinetic_models/MarcusHushChidsey.jl | 2 +- src/kinetic_models/MarcusHushChidseyDOS.jl | 2 +- src/utils/dos.jl | 10 ++-- test/phase_diagram_tests.jl | 54 +++++++++---------- 8 files changed, 40 insertions(+), 40 deletions(-) diff --git a/src/fitting.jl b/src/fitting.jl index 496c576..77c83e7 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -99,7 +99,7 @@ const default_param_bounds = Dict(:A => (0.1, 50000), :λ => (0.01, 0.5), :α => # Keyword Arguments Requirements differ by model type... * `ButlerVolmer`, `AsymptoticMarcusHushChidsey`, `Marcus`: none -* `MarcusHushChidsey`: average_dos::Float64 OR dos::DOSData OR dos_file::String +* `MarcusHushChidsey`: average_dos::Float32 OR dos::DOSData OR dos_file::String * `MarcusHushChidseyDOS`: dos::DOSData OR dos_file Some are always options... * `param_bounds::Dict{Symbol,Any}`: ranges of guesses for relevant model parameters. (must include all necessary keys, but defaults to some sensible ranges if not provided, see `default_param_bounds`...note that you should provide this for faster fitting if you know bounds) @@ -164,8 +164,8 @@ function _fit_model( # s[i] = gs[i] # end # end - lower = Float64.([param_bounds[p][1] for p in fitting_params(model_type)]) - upper = Float64.([param_bounds[p][2] for p in fitting_params(model_type)]) + lower = Float32.([param_bounds[p][1] for p in fitting_params(model_type)]) + upper = Float32.([param_bounds[p][2] for p in fitting_params(model_type)]) init_guess = 0.5 .* (lower .+ upper) # set optimisers based on the model type diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 0fb4baa..5b74372 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -10,7 +10,7 @@ struct AsymptoticMarcusHushChidsey{T} <: NonIntegralModel{T} A::T λ::T function AsymptoticMarcusHushChidsey(A, λ) - ps = consistent_params(Float64.(A), Float64.(λ)) + ps = consistent_params(Float32.(A), Float32.(λ)) new{typeof(ps[1])}(ps...) end end diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index 9030708..8d345a6 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -11,7 +11,7 @@ struct ButlerVolmer{T} <: NonIntegralModel{T} α::T function ButlerVolmer(A, α) @assert all(α .<= 1.0 .&& α .>=0.0) "Electron transfer coefficient must be in [0,1]" - ps = consistent_params(Float64.(A), Float64.(α)) + ps = consistent_params(Float32.(A), Float32.(α)) new{typeof(ps[1])}(ps...) end end diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index ab7bbfe..2e2057e 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -10,7 +10,7 @@ struct Marcus{T} <: NonIntegralModel{T} A::T λ::T function Marcus(A, λ) - ps = consistent_params(Float64.(A), Float64.(λ)) + ps = consistent_params(Float32.(A), Float32.(λ)) new{typeof(ps[1])}(ps...) end end diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 4ea2f93..0609561 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -14,7 +14,7 @@ struct MarcusHushChidsey{T} <: IntegralModel{T} λ::T average_dos::T function MarcusHushChidsey(A, λ, average_dos) - ps = consistent_params(Float64.(A), Float64.(λ), Float64.(average_dos)) + ps = consistent_params(Float32.(A), Float32.(λ), Float32.(average_dos)) new{typeof(ps[1])}(ps...) end end diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index d7da536..c3289b3 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -13,7 +13,7 @@ struct MarcusHushChidseyDOS{T} <: IntegralModel{T} λ::T dos::DOSData function MarcusHushChidseyDOS(A, λ, dos) - ps = consistent_params(Float64.(A), Float64.(λ)) + ps = consistent_params(Float32.(A), Float32.(λ)) new{typeof(ps[1])}(ps..., dos) end end diff --git a/src/utils/dos.jl b/src/utils/dos.jl index b947375..c7660f8 100644 --- a/src/utils/dos.jl +++ b/src/utils/dos.jl @@ -19,9 +19,9 @@ Struct for storing density of states (DOS) information. Can be constructed from """ struct DOSData interp_func - average_value::Float64 - E_min::Float64 - E_max::Float64 + average_value::Float32 + E_min::Float32 + E_max::Float32 end DOSData(dos_file; Ef=0, cut_energy=false) = DOSData(get_dos(dos_file; Ef, cut_energy)...) @@ -44,10 +44,10 @@ Returns a callable interpolated DOS, the average value of DOS, and the lower and """ function get_dos(dos_file::String; kwargs...) # dos_data = Zygote.ignore() do - # x = readdlm(dos_file, Float64, skipstart=1) + # x = readdlm(dos_file, Float32, skipstart=1) # x # end - dos_data = readdlm(dos_file, Float64, skipstart=1) + dos_data = readdlm(dos_file, Float32, skipstart=1) get_dos(dos_data; kwargs...) end function get_dos(dd::Matrix; Ef=0, cut_energy=false) diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index c804565..5a492de 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -12,23 +12,23 @@ T = 298 @test h(0.5; Ω=1) == 0.25 # kwargs # similar set for entropy... - @test s(0.5) ≈ -kB * 2 * 0.5 * log(0.5) + @test isapprox(s(0.5), -kB * log(0.5), atol=1e-5) @test s(0.1) == s(0.9) - @test s([0.1, 0.2, 0.7]) ≈ [2.8012399817e-5, 4.3119676836e-5, 5.2638176908e-5] + @test s([0.1, 0.2, 0.7]) ≈ [2.80134626433e-5, 4.3121323932e-5, 5.2640192129e-5] # ...and thermodynamic free energy... - @test g_thermo(0.5) == h(0.5) - T * s(0.5) + muoA * 0.5 + muoB * 0.5 ≈ 0.032200909 - @test g_thermo(0.0) ≈ muoA - @test g_thermo(1.0) ≈ muoB - @test g_thermo([0.1, 0.2, 0.7]) ≈ [0.02165230485, 0.0251503363, 0.032313823] + @test g_thermo(0.5) == h(0.5) - T * s(0.5) + muoA * 0.5 + muoB * 0.5 ≈ 0.032200226968 + @test isapprox(g_thermo(0.0), muoA, atol=1e-8) + @test isapprox(g_thermo(1.0), muoB, atol=1e-8) + @test g_thermo([0.1, 0.2, 0.7]) ≈ [0.021651988, 0.02514984585595, 0.0323132232] # ...and thermodynamic chemical potential. @test all(isinf.(μ_thermo([0.0, 1.0]))) @test μ_thermo(0.5) == μ_thermo(0.5, T=500) ≈ muoB - muoA - @test μ_thermo(0.1) ≈ 0.033578217 - @test μ_thermo(0.9, T=400) ≈ 0.0057339367 - @test μ_thermo([0.1, 0.2, 0.7]) ≈ [0.033578217, 0.034401818, -0.008242526] - @test μ_thermo([0.1, 0.2, 0.7], T=350) ≈ [0.023732805, 0.028190055, -0.00444592] + @test μ_thermo(0.1) ≈ 0.0335760350387 + @test μ_thermo(0.9, T=400) ≈ 0.0057368657199 + @test μ_thermo([0.1, 0.2, 0.7]) ≈ [0.0335760350387, 0.034400441691438, -0.00824168486] + @test μ_thermo([0.1, 0.2, 0.7], T=350) ≈ [0.023730242495, 0.0281884382282, -0.004444931883] end # prefactors are set so that k vs. η plots roughly line up for small η @@ -43,27 +43,27 @@ xs = [0.1, 0.5, 0.95] # all these numbers are just references evaluated as of 2/24/22 μ_50_vals = Dict( :ButlerVolmer=>Dict( - 0.1 => 0.0383864736, + 0.1 => 0.03838429151, 0.5 => 0.01862765755, - 0.95 => 0.06237022288), + 0.95 => 0.062373147), :Marcus=>Dict( - 0.1 => 0.0387445526862, - 0.5 => 0.01928206795, - 0.95 => 0.07492901629449), + 0.1 => 0.03874237118, + 0.5 => 0.01928206901, + 0.95 => 0.0749319471), :AsymptoticMarcusHushChidsey=>Dict( - 0.1 => 0.0389118763, - 0.5 => 0.0195713281175, - 0.95 => 0.0735097011) + 0.1 => 0.03890969477, + 0.5 => 0.01957132911, + 0.95 => 0.07351263138) ) μ_200_vals = Dict( - :ButlerVolmer=>[0.0524237924, 0.04250974, 0.13058880458], - :Marcus=>[0.054009696387679, 0.045881168639779, 0.212205862750], - :AsymptoticMarcusHushChidsey=>[0.05451269755, 0.046343172588, 0.17452291988558] + :ButlerVolmer=>[0.05242161033, 0.04250973994, 0.13059172875], + :Marcus=>[0.0540075165676, 0.0458811724237, 0.212208797161], + :AsymptoticMarcusHushChidsey=> [0.0545105175689, 0.04634317606989, 0.174525852191] ) μ_100_T400_vals = Dict( - :ButlerVolmer=>[0.02384219096, 0.02702875, 0.1212749347], - :Marcus=>[0.024573427974, 0.028429814254, 0.1529930329757], - :AsymptoticMarcusHushChidsey=>[0.024890385314, 0.028908839244, 0.14468140815] + :ButlerVolmer=>[0.0238392619734, 0.027028750035, 0.121278859754] , + :Marcus=>[0.0245705001602, 0.02842981631828, 0.1529969664115], + :AsymptoticMarcusHushChidsey=>[0.02488745742498, 0.02890884116453, 0.14468534057] ) for km in kms @testset "$(typeof(km))" begin @@ -128,9 +128,9 @@ end @test v3[2] < v1[2] # test actual numerical values too - @test isapprox(v1, [0.04584, 0.839942], atol=1e-5) - @test isapprox(v2, [0.0837787, 0.795035], atol=1e-5) - @test isapprox(v3, [0.107585, 0.675948], atol=1e-5) + @test isapprox(v1, [0.0458468, 0.839934], atol=1e-5) + @test isapprox(v2, [0.08379, 0.795023], atol=1e-5) + @test isapprox(v3, [0.1076, 0.675928], atol=1e-5) # TODO: next for multiple currents at once (may require some syntax tweaks) From 8f423ffed36693406a273104f6b4bd7e9ab90522 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 7 Jul 2022 15:49:53 -0400 Subject: [PATCH 14/25] hopefully fix CI Signed-off-by: Rachel Kurchin --- test/phase_diagram_tests.jl | 62 ++++++++++++++++++------------------- 1 file changed, 31 insertions(+), 31 deletions(-) diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 5a492de..d37c0e7 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -8,27 +8,27 @@ T = 298 # enthalpy of mixing @test h(0.5) == 0.025 # value @test h(0.1) ≈ h(0.9) # symmetry - @test h([0.1, 0.2, 0.7]) ≈ [0.009, 0.016, 0.021] # vector input + @test all(h([0.1, 0.2, 0.7]) .≈ [0.009, 0.016, 0.021]) # vector input @test h(0.5; Ω=1) == 0.25 # kwargs # similar set for entropy... - @test isapprox(s(0.5), -kB * log(0.5), atol=1e-5) + @test isapprox(s(0.5f0), -kB * log(0.5f0), atol=1f-5) @test s(0.1) == s(0.9) - @test s([0.1, 0.2, 0.7]) ≈ [2.80134626433e-5, 4.3121323932e-5, 5.2640192129e-5] + @test all(s([0.1, 0.2, 0.7]) .≈ [2.8013f-5, 4.3121f-5, 5.264f-5]) # ...and thermodynamic free energy... - @test g_thermo(0.5) == h(0.5) - T * s(0.5) + muoA * 0.5 + muoB * 0.5 ≈ 0.032200226968 + @test g_thermo(0.5) == h(0.5) - T * s(0.5) + muoA * 0.5 + muoB * 0.5 ≈ 0.0322002f0 @test isapprox(g_thermo(0.0), muoA, atol=1e-8) @test isapprox(g_thermo(1.0), muoB, atol=1e-8) - @test g_thermo([0.1, 0.2, 0.7]) ≈ [0.021651988, 0.02514984585595, 0.0323132232] + @test all(g_thermo([0.1, 0.2, 0.7]) .≈ [0.021651988f0, 0.02514984585595f0, 0.0323132232f0]) # ...and thermodynamic chemical potential. @test all(isinf.(μ_thermo([0.0, 1.0]))) @test μ_thermo(0.5) == μ_thermo(0.5, T=500) ≈ muoB - muoA - @test μ_thermo(0.1) ≈ 0.0335760350387 - @test μ_thermo(0.9, T=400) ≈ 0.0057368657199 - @test μ_thermo([0.1, 0.2, 0.7]) ≈ [0.0335760350387, 0.034400441691438, -0.00824168486] - @test μ_thermo([0.1, 0.2, 0.7], T=350) ≈ [0.023730242495, 0.0281884382282, -0.004444931883] + @test μ_thermo(0.1) ≈ 0.033576035f0 + @test μ_thermo(0.9, T=400) ≈ 0.00573686571f0 + @test all(μ_thermo([0.1, 0.2, 0.7]) .≈ [0.033576f0, 0.03440044f0, -0.0082417f0]) + @test all(μ_thermo([0.1, 0.2, 0.7], T=350) .≈ [0.02373024f0, 0.0281884f0, -0.00444493f0]) end # prefactors are set so that k vs. η plots roughly line up for small η @@ -43,27 +43,27 @@ xs = [0.1, 0.5, 0.95] # all these numbers are just references evaluated as of 2/24/22 μ_50_vals = Dict( :ButlerVolmer=>Dict( - 0.1 => 0.03838429151, - 0.5 => 0.01862765755, - 0.95 => 0.062373147), + 0.1 => 0.03838429f0, + 0.5 => 0.01862766f0, + 0.95 => 0.062373f0), :Marcus=>Dict( - 0.1 => 0.03874237118, - 0.5 => 0.01928206901, - 0.95 => 0.0749319471), + 0.1 => 0.03874237f0, + 0.5 => 0.019282f0, + 0.95 => 0.074932f0), :AsymptoticMarcusHushChidsey=>Dict( - 0.1 => 0.03890969477, - 0.5 => 0.01957132911, - 0.95 => 0.07351263138) + 0.1 => 0.0389097f0, + 0.5 => 0.0195713f0, + 0.95 => 0.0735126f0) ) μ_200_vals = Dict( - :ButlerVolmer=>[0.05242161033, 0.04250973994, 0.13059172875], - :Marcus=>[0.0540075165676, 0.0458811724237, 0.212208797161], - :AsymptoticMarcusHushChidsey=> [0.0545105175689, 0.04634317606989, 0.174525852191] + :ButlerVolmer=>[0.0524216f0, 0.0425097f0, 0.1305917f0], + :Marcus=>[0.0540075f0, 0.04588117f0, 0.212208797f0], + :AsymptoticMarcusHushChidsey=> [0.0545105f0, 0.046343176f0, 0.17452585f0] ) μ_100_T400_vals = Dict( - :ButlerVolmer=>[0.0238392619734, 0.027028750035, 0.121278859754] , - :Marcus=>[0.0245705001602, 0.02842981631828, 0.1529969664115], - :AsymptoticMarcusHushChidsey=>[0.02488745742498, 0.02890884116453, 0.14468534057] + :ButlerVolmer=>[0.02383926f0, 0.02702875f0, 0.12127886f0] , + :Marcus=>[0.0245705f0, 0.028429816f0, 0.152996966f0], + :AsymptoticMarcusHushChidsey=>[0.0248874574f0, 0.028908841f0, 0.14468534] ) for km in kms @testset "$(typeof(km))" begin @@ -85,11 +85,11 @@ end @testset "Kinetic g" begin g_200_T400_vals = Dict( - :ButlerVolmer => [0.0205857425, 0.037693617, 0.06661696], - :Marcus => [0.02073470111, 0.03874647481, 0.07399607032], - :AsymptoticMarcusHushChidsey => [0.0207838185, 0.0390031065, 0.0729910686] + :ButlerVolmer => [0.02058574, 0.0376936, 0.06661696], + :Marcus => [0.0207347, 0.0387464748, 0.07399607], + :AsymptoticMarcusHushChidsey => [0.0207838, 0.0390031, 0.07299107] ) - g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018258, :Marcus=>0.03542169346909, :AsymptoticMarcusHushChidsey=>0.03552448666) + g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018, :Marcus=>0.03542169347, :AsymptoticMarcusHushChidsey=>0.03552449) for km in kms @testset "$(typeof(km))" begin μ_50 = μ_kinetic(50, km) @@ -128,9 +128,9 @@ end @test v3[2] < v1[2] # test actual numerical values too - @test isapprox(v1, [0.0458468, 0.839934], atol=1e-5) - @test isapprox(v2, [0.08379, 0.795023], atol=1e-5) - @test isapprox(v3, [0.1076, 0.675928], atol=1e-5) + @test all(isapprox.(v1, [0.0458468, 0.839934], atol=1e-5)) + @test all(isapprox.(v2, [0.08379, 0.795023], atol=1e-5)) + @test all(isapprox.(v3, [0.1076, 0.675928], atol=1e-5)) # TODO: next for multiple currents at once (may require some syntax tweaks) From 0e0c7c40cfab2c02cb3f7bbaefd8aae2bfde2958 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 7 Jul 2022 16:03:38 -0400 Subject: [PATCH 15/25] hopefully fix CI, take 2 Signed-off-by: Rachel Kurchin --- test/phase_diagram_tests.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index d37c0e7..b23b98a 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -26,7 +26,7 @@ T = 298 @test all(isinf.(μ_thermo([0.0, 1.0]))) @test μ_thermo(0.5) == μ_thermo(0.5, T=500) ≈ muoB - muoA @test μ_thermo(0.1) ≈ 0.033576035f0 - @test μ_thermo(0.9, T=400) ≈ 0.00573686571f0 + @test isapprox(μ_thermo(0.9, T=400), 0.00573686571, atol=5e-6) @test all(μ_thermo([0.1, 0.2, 0.7]) .≈ [0.033576f0, 0.03440044f0, -0.0082417f0]) @test all(μ_thermo([0.1, 0.2, 0.7], T=350) .≈ [0.02373024f0, 0.0281884f0, -0.00444493f0]) end @@ -78,7 +78,7 @@ xs = [0.1, 0.5, 0.95] # test vector inputs @test μ_200(xs) ≈ μ_200_vals[typeof(km).name.name] - @test μ_100_T400(xs) == μ_100_T400.(xs) ≈ μ_100_T400_vals[typeof(km).name.name] + @test μ_100_T400(xs) == μ_100_T400.(xs) && all(isapprox.(µ_100_T400(xs), μ_100_T400_vals[typeof(km).name.name], atol=5f-5)) end end end @@ -129,8 +129,8 @@ end # test actual numerical values too @test all(isapprox.(v1, [0.0458468, 0.839934], atol=1e-5)) - @test all(isapprox.(v2, [0.08379, 0.795023], atol=1e-5)) - @test all(isapprox.(v3, [0.1076, 0.675928], atol=1e-5)) + @test all(isapprox.(v2, [0.08379, 0.795023], atol=1e-4)) + @test all(isapprox.(v3, [0.1076, 0.675928], atol=1e-4)) # TODO: next for multiple currents at once (may require some syntax tweaks) From 92266f18559ba41e0e2b18b6f8937af0282e5154 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 7 Jul 2022 16:50:40 -0400 Subject: [PATCH 16/25] T throughout instead of a mix of T and kT Signed-off-by: Rachel Kurchin --- src/ElectrochemicalKinetics.jl | 2 + src/fitting.jl | 28 +++++------ .../AsymptoticMarcusHushChidsey.jl | 16 +++--- src/kinetic_models/ButlerVolmer.jl | 8 +-- src/kinetic_models/Marcus.jl | 10 ++-- src/kinetic_models/MarcusHushChidsey.jl | 10 ++-- src/kinetic_models/MarcusHushChidseyDOS.jl | 26 +++++----- src/kinetic_models/kinetic_models.jl | 14 +++--- src/phase_diagrams.jl | 5 +- test/integral_model_tests.jl | 4 +- test/non_integral_model_tests.jl | 22 ++++----- test/phase_diagram_tests.jl | 49 +++++++++---------- test/runtests.jl | 2 +- 13 files changed, 97 insertions(+), 99 deletions(-) diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index cc19ebf..cc063aa 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -1,5 +1,7 @@ module ElectrochemicalKinetics +const kB = 8.61733326e-5 + include("utils/dos.jl") export DOS using .DOS: DOSData, get_dos diff --git a/src/fitting.jl b/src/fitting.jl index 77c83e7..e821bf3 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -25,26 +25,26 @@ end Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) """ -function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); kT = 0.026, loss = janky_log_loss, autodiff = true, verbose=false, kwargs...) +function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); T = 298, loss = janky_log_loss, autodiff = true, verbose=false, kwargs...) function compare_k!(storage, V) - storage .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) + storage .= loss(k, rate_constant(V, model; T = T, kwargs...)) end Vs = if autodiff function myfun!(F, J, V) if isnothing(J) - F .= loss(k, rate_constant(V, model; kT = kT, kwargs...)) + F .= loss(k, rate_constant(V, model; T = T, kwargs...)) elseif isnothing(F) && !isnothing(J) gs = Zygote.gradient(V) do V Zygote.forwarddiff(V) do V - loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum + loss(k, rate_constant(V, model; T = T, kwargs...)) |> sum end end[1] J .= diagm(gs) else y, back = Zygote.pullback(V) do V Zygote.forwarddiff(V) do V - loss(k, rate_constant(V, model; kT = kT, kwargs...)) |> sum + loss(k, rate_constant(V, model; T = T, kwargs...)) |> sum end end F .= y @@ -65,12 +65,12 @@ overpotential(k::Real, model::KineticModel{T}, guess=0.1; kwargs...) where T<:Re inv!(x) = x .= inv.(x) -Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, kT = 0.026, autodiff = true, verbose = false, kw...) - Vs = overpotential(model, k, guess; loss, verbose, autodiff, kT, kw...) +Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, T = 298, autodiff = true, verbose = false, kw...) + Vs = overpotential(model, k, guess; loss=loss, verbose=verbose, autodiff=autodiff, T=T, kw...) function back(vs) gs = Zygote.jacobian(vs) do V Zygote.forwarddiff(V) do V - rate_constant(V, model; kw...) + rate_constant(V, model; T=T, kw...) end end[1] inv.(gs) @@ -109,11 +109,11 @@ function fit_model( exp_data::Matrix, model_type::Type{<:KineticModel}; param_bounds::Dict = default_param_bounds, - kT::Real = 0.026, + T::Float32 = 298, kwargs... ) V_vals = exp_data[:, 1] - eval_model(model) = [rate_constant(V, model; kT = kT) for V in V_vals] + eval_model(model) = [rate_constant(V, model; T=T) for V in V_vals] _fit_model(exp_data, model_type, param_bounds, eval_model) end @@ -122,15 +122,15 @@ function fit_model( exp_data::Matrix, model_type::Type{<:IntegralModel}; param_bounds::Dict = default_param_bounds, - kT::Real = 0.026, - E_min = -100 * kT, - E_max = 100 * kT, + T::Float32 = 298, + E_min = -100 * kB*T, + E_max = 100 * kB*T, kwargs..., ) V_vals = exp_data[:, 1] eval_model(model) = rate_constant(V_vals, model; - kT = kT, + T = T, E_min = E_min, E_max = E_max, kwargs...) diff --git a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl index 5b74372..0ec51c6 100644 --- a/src/kinetic_models/AsymptoticMarcusHushChidsey.jl +++ b/src/kinetic_models/AsymptoticMarcusHushChidsey.jl @@ -18,21 +18,21 @@ end # default prefactor is 1 AsymptoticMarcusHushChidsey(λ) = AsymptoticMarcusHushChidsey(1.0, λ) -function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; kT::Real = 0.026) - η = (2 * ox - 1) .* V_app ./ kT - λ_nondim = amhc.λ / kT +function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey, ox::Bool; T = 298) + η = (2 * ox - 1) .* V_app ./ (kB * T) + λ_nondim = amhc.λ / (kB * T) a = 1 .+ sqrt.(λ_nondim) arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 .* sqrt.(λ_nondim)) pref = sqrt.(π .* λ_nondim) ./ (1 .+ exp.(-η)) - return kT .* amhc.A .* pref .* erfc.(arg) + return kB * T .* amhc.A .* pref .* erfc.(arg) end # direct dispatch for net rates -function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey; kT::Real = 0.026) - η = V_app / kT - λ_nondim = amhc.λ / kT +function rate_constant(V_app, amhc::AsymptoticMarcusHushChidsey; T = 298) + η = V_app / (kB * T) + λ_nondim = amhc.λ / (kB * T) a = 1 .+ sqrt.(λ_nondim) arg = (λ_nondim .- sqrt.(a .+ η.^2)) ./ (2 .* sqrt.(λ_nondim)) pref = sqrt.(π .* λ_nondim) .* tanh.(η/2) - return kT * amhc.A .* pref .* erfc.(arg) + return kB * T * amhc.A .* pref .* erfc.(arg) end diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index 8d345a6..f6bf75d 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -20,12 +20,12 @@ end ButlerVolmer() = ButlerVolmer(1.0, 0.5) ButlerVolmer(A) = ButlerVolmer(A, 0.5) -function rate_constant(V_app, bv::ButlerVolmer, ::Val{true}; kT::Real = 0.026) - exp_arg = (bv.α .* V_app) / kT +function rate_constant(V_app, bv::ButlerVolmer, ::Val{true}; T = 298) + exp_arg = (bv.α .* V_app) / (kB * T) bv.A .* exp.(exp_arg) end -function rate_constant(V_app, bv::ButlerVolmer, ::Val{false}; kT::Real = 0.026) - exp_arg = -((1 .- bv.α) .* V_app) / kT +function rate_constant(V_app, bv::ButlerVolmer, ::Val{false}; T = 298) + exp_arg = -((1 .- bv.α) .* V_app) / (kB * T) bv.A .* exp.(exp_arg) end diff --git a/src/kinetic_models/Marcus.jl b/src/kinetic_models/Marcus.jl index 2e2057e..3697df1 100644 --- a/src/kinetic_models/Marcus.jl +++ b/src/kinetic_models/Marcus.jl @@ -18,12 +18,12 @@ end # default prefactor is 1 Marcus(λ) = Marcus(1.0, λ) -function rate_constant(V_app, m::Marcus, ::Val{true}; kT = 0.026) - exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kT) +function rate_constant(V_app, m::Marcus, ::Val{true}; T = 298) + exp_arg = -(m.λ .- V_app).^2 ./ (4 .* m.λ .* kB * T) m.A .* exp.(exp_arg) end -function rate_constant(V_app, m::Marcus, ::Val{false}; kT = 0.026) - exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kT) +function rate_constant(V_app, m::Marcus, ::Val{false}; T = 298) + exp_arg = -(m.λ .+ V_app).^2 ./ (4 .* m.λ .* kB * T) m.A .* exp.(exp_arg) -end \ No newline at end of file +end diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index 0609561..e2f5810 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -29,9 +29,9 @@ MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidsey(A, λ, DOSData(dos_file; kwargs...)) # TODO: Check that both this and +DOS versions still match original paper -function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; kT::Real = 0.026) - marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 .* mhc.λ .* kT)) - marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 .* mhc.λ .* kT)) - f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages - f(E::Real) = (mhc.A .* mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; kT = kT) +function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; T = 298) + marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 .* mhc.λ .* kB * T)) + marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 .* mhc.λ .* kB * T)) + f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; T = T)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages + f(E::Real) = (mhc.A .* mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; T = T) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index c3289b3..1b0e2fc 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -33,28 +33,28 @@ MarcusHushChidseyDOS(A, λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(λ, dos_file::Union{Matrix,String}; kwargs...) = MarcusHushChidseyDOS(1.0, λ, DOSData(dos_file; kwargs...)) # TODO: make one version of this for the whole package, currently there are some sign convention differences between this and the MHC version -marcus_term(V, E, λ, ::Val{true}, kT) = exp.(-(( (λ .- V) .+ E) .^ 2) ./ (4 * λ * kT)) -marcus_term(V, E, λ, ::Val{false}, kT) = exp.(-(( (λ .+ V) .- E) .^ 2) ./ (4 * λ * kT)) +marcus_term(V, E, λ, ::Val{true}, T) = exp.(-(( (λ .- V) .+ E) .^ 2) ./ (4 * λ * kB * T)) +marcus_term(V, E, λ, ::Val{false}, T) = exp.(-(( (λ .+ V) .- E) .^ 2) ./ (4 * λ * kB * T)) # Fermi-Dirac function or the complement thereof -fd(E, ::Val{true}, kT) = 1 .- fermi_dirac(E; kT = kT) -fd(E, ::Val{false}, kT) = fermi_dirac(E; kT = kT) +fd(E, ::Val{true}, T) = 1 .- fermi_dirac(E; T = T) +fd(E, ::Val{false}, T) = fermi_dirac(E; T = T) function integrand( mhcd::MarcusHushChidseyDOS, V_dl, ox::Val; - kT = 0.026, + T = 298, V_q = 0.0, ) - E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E, ox, kT) .* marcus_term(V_dl, E, mhcd.λ, ox, kT) + E -> mhcd.A .* mhcd.dos.interp_func.(E .+ V_q) .* fd(E, ox, T) .* marcus_term(V_dl, E, mhcd.λ, ox, T) end function rate_constant( V_app, model::MarcusHushChidseyDOS, args...; - kT = 0.026, + T = 298, E_min = model.dos.E_min, E_max = model.dos.E_max, calc_cq::Bool = false, @@ -71,13 +71,13 @@ function rate_constant( C_dl = C_dl, Vq_min = Vq_min, Vq_max = Vq_max, - kT = kT, + T = T, E_min = min(E_min, E_min-Vq_min), E_max = max(E_max, E_max-Vq_max), ) else n, w = scale(E_min, E_max) - f = integrand(model, V_app, args...; kT = kT) + f = integrand(model, V_app, args...; T = T) sum(w .* f.(n)) end end @@ -95,7 +95,7 @@ function rate_constant_cq( C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, - kT = 0.026, + T = 298, E_min = model.dos.E_min, E_max = model.dos.E_max, ) @@ -103,7 +103,7 @@ function rate_constant_cq( V_dl = V_dl_interp(V_app) V_q = V_app - V_dl n, w = scale(E_min, E_max) - f = integrand(model, V_dl, ox; kT = kT, V_q = V_q) + f = integrand(model, V_dl, ox; T = T, V_q = V_q) sum(w .* f.(n)) end @@ -114,7 +114,7 @@ function rate_constant_cq( C_dl = 10.0, Vq_min = -0.5, Vq_max = 0.5, - kT = 0.026, + T = 298, E_min = model.dos.E_min, E_max = model.dos.E_max, ) @@ -122,6 +122,6 @@ function rate_constant_cq( V_dl = V_dl_interp(V_app) V_q = V_app - V_dl n, w = scale(E_min, E_max) - f = integrand(model, V_dl; kT = kT, V_q = V_q) + f = integrand(model, V_dl; T = T, V_q = V_q) sum(w .* f.(n)) end diff --git a/src/kinetic_models/kinetic_models.jl b/src/kinetic_models/kinetic_models.jl index fad5096..2050cd3 100644 --- a/src/kinetic_models/kinetic_models.jl +++ b/src/kinetic_models/kinetic_models.jl @@ -7,11 +7,11 @@ using DelimitedFiles include("../utils/misc.jl") """ - fermi_dirac(E, kT=0.026) + fermi_dirac(E, T=298) -Compute the value of the Fermi-Dirac distribution at energy `E` (relative to the Fermi energy) and thermal energy `kT`. +Compute the value of the Fermi-Dirac distribution at energy `E` (relative to the Fermi energy) and temperature `T`. """ -fermi_dirac(E; kT = 0.026) = inv.(1 .+ exp.(E ./ kT)) +fermi_dirac(E; T = 298) = inv.(1 .+ exp.(E ./ (kB * T))) """ KineticModel @@ -95,12 +95,12 @@ function rate_constant( V_app, model::IntegralModel, args...; # would just be the ox flag, if present - kT = 0.026, - E_min = -100 * kT, - E_max = 100 * kT + T = 298, + E_min = -100 * kB * T, + E_max = 100 * kB * T ) n, w = scale(E_min, E_max) - f = integrand(model, V_app, args...; kT = kT) + f = integrand(model, V_app, args...; T = T) sum(w .* f.(n)) end diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index 8702ced..7ff65e7 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -4,7 +4,6 @@ using NLsolve using FastGaussQuadrature # define some constants and default parameters -const kB = 8.617e-5 const room_T = 298 const muoA_default = 0.02 const muoB_default = 0.03 @@ -12,8 +11,8 @@ const Ω_default = 0.1 # our familiar thermodynamic functions h(x;Ω=Ω_default) = @. x*(1-x)*Ω # enthalpy of mixing -s(x) = @. -kB*(x*log(x+eps(Float64)) + (1-x)*log(1-x+eps(Float64))) # entropy per particle...added epsilons in the hopes that things will be less obnoxious at the edges -g_thermo(x; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) = @. h(x;Ω=Ω_default) - T*s(x)+ muoA*(1-x) + muoB*x # Gibbs free energy per particle +s(x) = @. -kB*(x*log(x+eps(Float32)) + (1-x)*log(1-x+eps(Float32))) # entropy per particle...added epsilons in the hopes that things will be less obnoxious at the edges +g_thermo(x; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) = @. h(x;Ω) - T*s(x)+ muoA*(1-x) + muoB*x # Gibbs free energy per particle μ_thermo(x; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) = @. (1-2*x)*Ω + kB*T*log(x/(1-x)) + muoB-muoA # chemical potential """ diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index e8220fa..dc322e3 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -7,8 +7,8 @@ @testset "Scalars" begin # test some values @test rate_constant(0, mhc) == 0.0 - @test rate_constant(0, mhc, true) == rate_constant(0, mhc, false) ≈ 0.0061371322 - @test isapprox(rate_constant(0.1, mhc), 0.031239978, atol=1e-6) + @test rate_constant(0, mhc, true) == rate_constant(0, mhc, false) ≈ 0.005892741f0 + @test isapprox(rate_constant(0.1, mhc), 0.03062463, atol=1e-6) # test net rates and symmetry @test isapprox(rate_constant(0.1, mhc, true) - rate_constant(0.1, mhc, false), rate_constant(0.1, mhc), atol=1e-6) diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index 160cffe..38c417b 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -14,17 +14,17 @@ # oxidative for bv in [bv1, bv2, bv3] - @test bv(.026/bv.α, true) ≈ bv.A * ℯ + @test bv(kB*298/bv.α, true) ≈ bv.A * ℯ end # reductive for bv in [bv1, bv2, bv3] - @test bv(-.026/(1-bv.α), false) ≈ bv.A * ℯ + @test bv(-kB*298/(1-bv.α), false) ≈ bv.A * ℯ end # net for bv in [bv1, bv2, bv3] - @test bv(.026/bv.α) ≈ bv.A * (ℯ - exp((bv.α-1)/bv.α)) + @test bv(kB*298/bv.α) ≈ bv.A * (ℯ - exp((bv.α-1)/bv.α)) end end @@ -60,10 +60,10 @@ @testset "Scalars" begin # TODO: this could all be more thorough, I literally just picked some arbitrary points @test m1(0.0) == 0.0 - @test isapprox(m1(0.05, false), 0.031381, atol=1e-6) - @test isapprox(m1(0.2, true), 0.908324, atol=1e-6) - @test isapprox(m1(0.13), 0.570862, atol=1e-6) - @test isapprox(m2(0.13), 5.708625, atol=1e-6) + @test isapprox(m1(0.05, false), 0.030055, atol=1e-6) + @test isapprox(m1(0.2, true), 0.907235, atol=1e-6) + @test isapprox(m1(0.13), 0.5671645, atol=1e-6) + @test isapprox(m2(0.13), 5.671645, atol=1e-6) end @testset "Vectors" begin @@ -93,10 +93,10 @@ amhc = AsymptoticMarcusHushChidsey(0.25) @testset "Scalars" begin @test amhc(0.0) == 0.0 - @test amhc(0.0, true) == amhc(0.0, false) ≈ 0.00596440064 - @test amhc(0.2) == -amhc(-0.2) ≈ 0.1006330238 - @test amhc(0.2, kT=.015) ≈ 0.06360960459 - @test amhc(0.2, kT=.03) ≈ 0.11255129857 + @test amhc(0.0, true) == amhc(0.0, false) ≈ 0.00573491969678f0 + @test amhc(0.2) == -amhc(-0.2) ≈ 0.09964746f0 + @test amhc(0.2, T=175) ≈ 0.063909331f0 + @test amhc(0.2, T=350) ≈ 0.11301532f0 end @testset "Vector Voltages" begin test_vector_voltages(amhc, Vs) diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index b23b98a..ffc04e6 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -43,27 +43,27 @@ xs = [0.1, 0.5, 0.95] # all these numbers are just references evaluated as of 2/24/22 μ_50_vals = Dict( :ButlerVolmer=>Dict( - 0.1 => 0.03838429f0, - 0.5 => 0.01862766f0, - 0.95 => 0.062373f0), + 0.1 => 0.038325055f0, + 0.5 => 0.018521359f0, + 0.95 => 0.0615507f0), :Marcus=>Dict( - 0.1 => 0.03874237f0, - 0.5 => 0.019282f0, - 0.95 => 0.074932f0), + 0.1 => 0.03886537f0, + 0.5 => 0.01950138f0, + 0.95 => 0.0760257f0), :AsymptoticMarcusHushChidsey=>Dict( - 0.1 => 0.0389097f0, - 0.5 => 0.0195713f0, - 0.95 => 0.0735126f0) + 0.1 => 0.0390861f0, + 0.5 => 0.01988688f0, + 0.95 => 0.07516774f0) ) μ_200_vals = Dict( - :ButlerVolmer=>[0.0524216f0, 0.0425097f0, 0.1305917f0], - :Marcus=>[0.0540075f0, 0.04588117f0, 0.212208797f0], - :AsymptoticMarcusHushChidsey=> [0.0545105f0, 0.046343176f0, 0.17452585f0] + :ButlerVolmer=> [0.0521894f0, 0.0421092f0, 0.1289288f0], + :Marcus=> [0.0544722f0, 0.0466285f0, 0.2127188f0], + :AsymptoticMarcusHushChidsey=>[0.055173985f0, 0.04740624957f0, 0.17594977f0] ) μ_100_T400_vals = Dict( - :ButlerVolmer=>[0.02383926f0, 0.02702875f0, 0.12127886f0] , - :Marcus=>[0.0245705f0, 0.028429816f0, 0.152996966f0], - :AsymptoticMarcusHushChidsey=>[0.0248874574f0, 0.028908841f0, 0.14468534] + :ButlerVolmer=>[0.023721278f0, 0.02681895f0, 0.120048858f0] , + :Marcus=>[0.02481338f0, 0.0288534856f0, 0.1539812383f0], + :AsymptoticMarcusHushChidsey=>[0.0252367557f0, 0.029513253f0, 0.146351765f0] ) for km in kms @testset "$(typeof(km))" begin @@ -78,18 +78,18 @@ xs = [0.1, 0.5, 0.95] # test vector inputs @test μ_200(xs) ≈ μ_200_vals[typeof(km).name.name] - @test μ_100_T400(xs) == μ_100_T400.(xs) && all(isapprox.(µ_100_T400(xs), μ_100_T400_vals[typeof(km).name.name], atol=5f-5)) + @test μ_100_T400(xs) == μ_100_T400.(xs) && all(isapprox.(µ_100_T400(xs), μ_100_T400_vals[typeof(km).name.name], atol=1f-5)) end end end @testset "Kinetic g" begin g_200_T400_vals = Dict( - :ButlerVolmer => [0.02058574, 0.0376936, 0.06661696], - :Marcus => [0.0207347, 0.0387464748, 0.07399607], - :AsymptoticMarcusHushChidsey => [0.0207838, 0.0390031, 0.07299107] + :ButlerVolmer => [0.020563, 0.03755, 0.0661336], + :Marcus => [0.0207786, 0.0390248, 0.074701], + :AsymptoticMarcusHushChidsey => [0.0208467, 0.03939946, 0.0740394] ) - g_50_2_vals = Dict(:ButlerVolmer=>0.03519728018, :Marcus=>0.03542169347, :AsymptoticMarcusHushChidsey=>0.03552449) + g_50_2_vals = Dict(:ButlerVolmer=>0.03515968, :Marcus=>0.035497, :AsymptoticMarcusHushChidsey=>0.0356339) for km in kms @testset "$(typeof(km))" begin μ_50 = μ_kinetic(50, km) @@ -128,10 +128,7 @@ end @test v3[2] < v1[2] # test actual numerical values too - @test all(isapprox.(v1, [0.0458468, 0.839934], atol=1e-5)) - @test all(isapprox.(v2, [0.08379, 0.795023], atol=1e-4)) - @test all(isapprox.(v3, [0.1076, 0.675928], atol=1e-4)) - - # TODO: next for multiple currents at once (may require some syntax tweaks) - + @test all(isapprox.(v1, [0.045547, 0.841501], atol=1e-5)) + @test all(isapprox.(v2, [0.083289, 0.796802], atol=1e-4)) + @test all(isapprox.(v3, [0.105747, 0.6809], atol=1e-4)) end diff --git a/test/runtests.jl b/test/runtests.jl index 052d1fa..04f1fff 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -4,7 +4,7 @@ using Test function test_vector_voltages(model, voltages) @test isapprox(rate_constant(voltages, model), rate_constant.(voltages, Ref(model))) - @test isapprox(rate_constant(voltages, model, kT=0.4), rate_constant.(voltages, Ref(model), kT=0.4)) + @test isapprox(rate_constant(voltages, model, T=1000), rate_constant.(voltages, Ref(model), T=1000)) end @testset "ElectrochemicalKinetics.jl" begin From f04899a09e5719e5f0f4bde1bbf7abf44e8ae6f2 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Fri, 8 Jul 2022 17:57:36 -0400 Subject: [PATCH 17/25] add phase diagram function Signed-off-by: Rachel Kurchin --- src/ElectrochemicalKinetics.jl | 3 ++- src/phase_diagrams.jl | 24 ++++++++++++++++++++++-- 2 files changed, 24 insertions(+), 3 deletions(-) diff --git a/src/ElectrochemicalKinetics.jl b/src/ElectrochemicalKinetics.jl index cc063aa..52fe134 100644 --- a/src/ElectrochemicalKinetics.jl +++ b/src/ElectrochemicalKinetics.jl @@ -21,7 +21,8 @@ export fitting_params, fit_model, overpotential, is_dosmodel include("phase_diagrams.jl") export kB, h, s, g_thermo, µ_thermo -export µ_kinetic, g_kinetic, common_tangent, find_phase_boundaries +export µ_kinetic, g_kinetic +export common_tangent, find_phase_boundaries, phase_diagram include("plot_fcns.jl") export plot_models, plot_exp_and_models diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index 7ff65e7..cf08031 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -73,6 +73,26 @@ function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], verbose= x1.zero end -function phase_diagram(km::KineticModel; kwargs...) - # TODO: write this, lol +function phase_diagram(km::KineticModel; I_step=10, verbose=false, kwargs...) + I = 0 + pbs_here = find_phase_boundaries(I, km; kwargs...) + pbs = pbs_here' + I_vals = [0] + while abs(pbs_here[2] - pbs_here[1]) > 1e-3 + I = I + I_step + if verbose + println("Solving at I=", I, "...") + end + try + pbs_here = find_phase_boundaries(I, km; guess=pbs_here, kwargs...) + pbs = vcat(pbs, pbs_here') + push!(I_vals, I) + if verbose + println("Phase boundaries are at ", pbs_here) + end + catch e + println("Solve failed at I=", I) + end + end + return vcat(pbs[:,1], reverse(pbs[:,2])), vcat(I_vals, reverse(I_vals)) end From 484ae613fe09a249ee91ac7d4c109e3d4d2ab360 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Mon, 11 Jul 2022 15:53:55 -0400 Subject: [PATCH 18/25] add intercalation flag Signed-off-by: Rachel Kurchin --- benchmark/results_branch.jls | Bin 1890514 -> 1888906 bytes src/phase_diagrams.jl | 46 ++++++++++++++--------------------- test/phase_diagram_tests.jl | 3 +++ 3 files changed, 21 insertions(+), 28 deletions(-) diff --git a/benchmark/results_branch.jls b/benchmark/results_branch.jls index 21e8713a2c8e31ca708e22d6e533ae96fce9e950..575c189a5f35c7a87e93699b11f7a09b84e3f333 100644 GIT binary patch literal 1888906 zcmeF4XOvXc_U#)nfjMx+bOlTp5ygP9Fkrr-;#IE!QBe_;j0h$aIyVj4fvhMwbN~cF z1XM%>6$1hi6ifsK6Nnh_&6?|XZvEeQZ;bctjo}#Z!Lq7O*n6$H=9+8meX7sC>YDv_ 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zNI&PW`uFc3GJ8}rbuT@kYyH#(RcunE-n1|;UY}uOMZap&Pa=nA{!!d7A6!x7FYBHY z_mLl;6`513khtHueXr=3eArdwr*$fcd*+3j&xAdif9+lw;$LXTVUaJspDpslk#9s^ zQccT0`|2~IFZ@{JjXttT^hG}p5;?8!29d`XekJm^S=&VJ-1vyddNp>5JQ_BO%-wd5 zN8U;eIJt5mB4uW7DGKdg|(?>1A?ue5ut=>D2*;-5Kmm&Tubt9C$RTWGuv ze-s(^T%~f$<>K$lX!!W-I&shbt5&S|QV%WvqDF{+i^xjDC#&A2sHXpMHPJKvaEZw5 Utz*ws$QtdBUy%COgB9K10r^}rNB{r; diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index cf08031..99f48b7 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -15,24 +15,26 @@ s(x) = @. -kB*(x*log(x+eps(Float32)) + (1-x)*log(1-x+eps(Float32))) # entropy pe g_thermo(x; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) = @. h(x;Ω) - T*s(x)+ muoA*(1-x) + muoB*x # Gibbs free energy per particle μ_thermo(x; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) = @. (1-2*x)*Ω + kB*T*log(x/(1-x)) + muoB-muoA # chemical potential +prefactor(x, intercalate::Bool) = intercalate ? (1 .- x) : x + """ µ and g with kinetic constributions, can be modeled using any <:KineticModel object These functions return single-argument functions (to easily use common-tangent function below while still being able to swap out model parameters by calling "function-builders" with different arguments). """ -function µ_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) - thermo_term(x) = μ_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) - μ(x::Real) = thermo_term(x) .+ overpotential(I, (1-x)*km) - μ(x::AbstractVector) = thermo_term(x) .+ overpotential(I, (1 .- x).*Ref(km)) +function µ_kinetic(I, km::KineticModel; intercalate=true, kwargs...) + thermo_term(x) = μ_thermo(x; kwargs...) + μ(x::Real) = thermo_term(x) .+ overpotential(I, prefactor(x, intercalate)*km) + μ(x::AbstractVector) = thermo_term(x) .+ overpotential(I, prefactor(x, intercalate).*Ref(km)) return μ end -function g_kinetic(I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) - thermo_term(x) = g_thermo(x; Ω=Ω, muoA=muoA, muoB=muoB, T=T) +function g_kinetic(I, km::KineticModel; intercalate=true, kwargs...) + thermo_term(x) = g_thermo(x; kwargs...) #TODO: gradient of this term is just value of overpotential(x) function kinetic_term(x) - f(x) = ElectrochemicalKinetics.overpotential(I, (1 .- x) .* Ref(km)) + f(x) = ElectrochemicalKinetics.overpotential(I, prefactor(x, intercalate) * km) n, w = ElectrochemicalKinetics.scale_coarse(zero.(x), x) map((w, n) -> sum(w .* f(n)), eachcol(w), eachcol(n)) end @@ -43,39 +45,27 @@ end # zeros of this function correspond to pairs of x's satisfying the common tangent condition for a given µ function # case where we just feed in two points (x should be of length two) -function common_tangent(x::Vector, I, km::KineticModel; Ω=Ω_default, muoA=muoA_default, muoB=muoB_default, T=room_T) - g = g_kinetic(I, km; Ω=Ω, muoA=muoA, muoB=muoB, T=T) - µ = µ_kinetic(I, km; Ω=Ω, muoA=muoA, muoB=muoB, T=T) +function common_tangent(x::Vector, I, km::KineticModel; intercalate=true, kwargs...) + g = g_kinetic(I, km; intercalate=intercalate, kwargs...) + µ = µ_kinetic(I, km; intercalate=intercalate, kwargs...) [(g(x[2]) - g(x[1]))/(x[2] - x[1]) .- μ(x[1]), μ(x[2])-μ(x[1])] end -# case where we want to check many points at once (shape of x should be N x 2) -# TODO: test this...may not really be able to save much time -function common_tangent(x::Array, I, km::KineticModel; kwargs...) - g = g_kinetic(I, km; kwargs...) - µ = µ_kinetic(I, km; kwargs...) - Δg = g(x[:,2]) - g(x[:,1]) - Δx = x[:,2] - x[:,1] - μ1 = μ(x[:,1]) - Δμ = μ(x[:,2]) - μ1 - hcat(Δg ./ Δx .- μ1, Δμ) -end - -function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], verbose=false, kwargs...) +# TODO: see if we can speed this up with gradients? +function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], intercalate=true, verbose=false, kwargs...) function myct!(storage, x) - res = common_tangent(x, I, km; kwargs...) + res = common_tangent(x, I, km; intercalate=intercalate, kwargs...) storage[1] = res[1] storage[2] = res[2] end - # TODO: grad! here from AD x1 = nlsolve(myct!, guess, show_trace=verbose, ftol=1e-6, xtol=1e-6) x1.zero end -function phase_diagram(km::KineticModel; I_step=10, verbose=false, kwargs...) +function phase_diagram(km::KineticModel; I_step=10, verbose=false, intercalate=true, kwargs...) I = 0 - pbs_here = find_phase_boundaries(I, km; kwargs...) + pbs_here = find_phase_boundaries(I, km; intercalate=intercalate, kwargs...) pbs = pbs_here' I_vals = [0] while abs(pbs_here[2] - pbs_here[1]) > 1e-3 @@ -84,7 +74,7 @@ function phase_diagram(km::KineticModel; I_step=10, verbose=false, kwargs...) println("Solving at I=", I, "...") end try - pbs_here = find_phase_boundaries(I, km; guess=pbs_here, kwargs...) + pbs_here = find_phase_boundaries(I, km; intercalate=intercalate, guess=pbs_here, kwargs...) pbs = vcat(pbs, pbs_here') push!(I_vals, I) if verbose diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index ffc04e6..9df66fe 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -4,6 +4,9 @@ muoA = 0.02 muoB = 0.03 T = 298 +# TODO: add tests where we change Ω, etc. +# TODO: add tests for deintercalation case + @testset "Basic free energy functions" begin # enthalpy of mixing @test h(0.5) == 0.025 # value From e3ee44c5d57cce4d8060186bb8bef89db8ff3088 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Tue, 12 Jul 2022 09:11:51 -0400 Subject: [PATCH 19/25] add overpotential shortcutting for k=0 and (non-integral) phase diagram benchmarks - don't run solve in `overpotential` if k==0, just return 0 (this check adds some overhead and slows down scalar benchmarks by ~30%, but makes some of the phase diagrams feasible that were not converging before (e.g. Marcus)) - add benchmark cases for full phase diagram construction Signed-off-by: Rachel Kurchin --- benchmark/bench_suite.jl | 10 +++++++ src/fitting.jl | 62 ++++++++++++++++++++++++++++++++++------ src/phase_diagrams.jl | 3 +- test/fitting_tests.jl | 1 + 4 files changed, 66 insertions(+), 10 deletions(-) diff --git a/benchmark/bench_suite.jl b/benchmark/bench_suite.jl index c3186e7..49cd91a 100644 --- a/benchmark/bench_suite.jl +++ b/benchmark/bench_suite.jl @@ -65,3 +65,13 @@ for km in i_kms[2:end] # skipping MHC for now suite["overpotential fitting"]["integral models"]["non-AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=false) seconds=time_mult*10 suite["overpotential fitting"]["integral models"]["AD"][modeltype] = @benchmarkable overpotential($k, $km, autodiff=true) seconds=time_mult*20 end + +suite["phase diagrams"] = BenchmarkGroup() +suite["phase diagrams"]["non-integral models"] = BenchmarkGroup() +for km in ni_kms + modeltype = typeof(km) + suite["phase diagrams"]["non-integral models"][modeltype] = @benchmarkable phase_diagram($km, T=350) + # TODO: add a lower-temp BV one +end + +# TODO: get working, add benchmarks for integral model phase diagrams diff --git a/src/fitting.jl b/src/fitting.jl index e821bf3..b3a79ca 100644 --- a/src/fitting.jl +++ b/src/fitting.jl @@ -20,53 +20,97 @@ function janky_log_loss(y, y_pred) end end +# helper fcn to make sure starting guess for `overpotential` has correct sign +function _get_guess(k, model) + guess = fill(1f-1, max(length(k), length(model))) + # make sure guess has correct sign + if k isa Real + if k == 0 + guess .= 0 + elseif k < 0 + guess[guess .> 0] .= -1 * guess[guess .> 0] + end + elseif k isa Vector + guess[k .== 0] .= 0 + guess[k .< 0 .&& guess .> 0] .= -1 * guess[k .< 0 .&& guess .> 0] + end + return guess +end + +# TODO: support reaction direction flag here """ overpotential(k, model; kwargs...) Given values for current/rate constant and specified model parameters, find the overpotential that would have resulted in it. (This is the inverse of the `rate_constant` function.) + +NOTE that this currently only solves for net reaction rates. """ -function overpotential(k, model::KineticModel, guess = fill(0.1, max(length(k), length(model))); T = 298, loss = janky_log_loss, autodiff = true, verbose=false, kwargs...) +function overpotential(k, model::KineticModel, guess = _get_guess(k, model); T = 298, loss = janky_log_loss, autodiff = true, verbose=false, kwargs...) + # wherever k=0 we can shortcut since the answer has to be 0 + k_solve = k + if k==0 # scalar k=0, possibly vector model + if verbose + println("shortcutting full solve") + end + return zeros(Float32, length(model)) + elseif any(k .== 0) # vector k with some zero elements, scalar model + if verbose + println("shortcutting part of solve") + end + k_solve = k[k.!=0] + end + function compare_k!(storage, V) storage .= loss(k, rate_constant(V, model; T = T, kwargs...)) end - Vs = if autodiff function myfun!(F, J, V) + # println("V=",V) + # println("loss=", loss(k, rate_constant(V, model; T=T, kwargs...))) if isnothing(J) - F .= loss(k, rate_constant(V, model; T = T, kwargs...)) + F .= loss(k_solve, rate_constant(V, model; T = T, kwargs...)) elseif isnothing(F) && !isnothing(J) gs = Zygote.gradient(V) do V Zygote.forwarddiff(V) do V - loss(k, rate_constant(V, model; T = T, kwargs...)) |> sum + loss(k_solve, rate_constant(V, model; T = T, kwargs...)) |> sum end end[1] J .= diagm(gs) else y, back = Zygote.pullback(V) do V Zygote.forwarddiff(V) do V - loss(k, rate_constant(V, model; T = T, kwargs...)) |> sum + loss(k_solve, rate_constant(V, model; T = T, kwargs...)) |> sum end end F .= y J .= diagm(back(one.(y))[1]) end + # println("J=", J) end - Vs = nlsolve(only_fj!(myfun!), guess, show_trace=verbose) + Vs = nlsolve(only_fj!(myfun!), guess, show_trace=verbose, extended_trace=true) else Vs = nlsolve(compare_k!, guess, show_trace=verbose) end if !converged(Vs) @warn "Overpotential fit not fully converged...you may have fed in an unreachable reaction rate!" end - Vs.zero + sol = Vs.zero + sol_return = zero(guess) + if k_solve != k # need to put back the zero elements + sol_return[k.!=0] .= sol + else + sol_return = sol + end + sol_return end overpotential(k::Real, model::KineticModel{T}, guess=0.1; kwargs...) where T<:Real = overpotential([k], model, [0.1]; kwargs...)[1] inv!(x) = x .= inv.(x) +# TODO: test this Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, T = 298, autodiff = true, verbose = false, kw...) - Vs = overpotential(model, k, guess; loss=loss, verbose=verbose, autodiff=autodiff, T=T, kw...) + Vs = overpotential(k, model, guess; loss=loss, verbose=verbose, autodiff=autodiff, T=T, kw...) function back(vs) gs = Zygote.jacobian(vs) do V Zygote.forwarddiff(V) do V @@ -75,7 +119,7 @@ Zygote.@adjoint function overpotential(k, model, guess; loss = log_loss, T = 298 end[1] inv.(gs) end - Vs, Δ -> (nothing, nothing, Δ .* back(Vs)) + Vs, Δ -> (Δ .* back(Vs), nothing, nothing) end # basically the gradient of overpotential should just be the inverse of the gradient of the forward solve at that point, i.e. if rate_constant(V, model) ==k then overpotential(model, k)==V , so we don’t need to diff through the actual solve in overpotential because the gradient should just be the inverse of the gradient of rate_constant at V diff --git a/src/phase_diagrams.jl b/src/phase_diagrams.jl index 99f48b7..5acbe60 100644 --- a/src/phase_diagrams.jl +++ b/src/phase_diagrams.jl @@ -51,7 +51,7 @@ function common_tangent(x::Vector, I, km::KineticModel; intercalate=true, kwargs [(g(x[2]) - g(x[1]))/(x[2] - x[1]) .- μ(x[1]), μ(x[2])-μ(x[1])] end -# TODO: see if we can speed this up with gradients? +# TODO: see if we can speed this up with gradients? And/or if it's even needed for integral cases function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], intercalate=true, verbose=false, kwargs...) function myct!(storage, x) @@ -63,6 +63,7 @@ function find_phase_boundaries(I, km::KineticModel; guess=[0.05, 0.95], intercal x1.zero end +# TODO: add T_max to handle low-T BV cases function phase_diagram(km::KineticModel; I_step=10, verbose=false, intercalate=true, kwargs...) I = 0 pbs_here = find_phase_boundaries(I, km; intercalate=intercalate, kwargs...) diff --git a/test/fitting_tests.jl b/test/fitting_tests.jl index 67082d7..4b43c85 100644 --- a/test/fitting_tests.jl +++ b/test/fitting_tests.jl @@ -1,3 +1,4 @@ +# TODO: add tests for shortcutting in overpotential solve @testset "Overpotential Fitting" begin params = Dict(ButlerVolmer=>[], Marcus=>[0.25], AsymptoticMarcusHushChidsey=>[0.25], MarcusHushChidsey=>[0.25]) for model_type in [ButlerVolmer, Marcus, AsymptoticMarcusHushChidsey, MarcusHushChidsey] From 931055e062ad1457f9a501ee70fe542a01c37afb Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 14 Jul 2022 12:25:31 -0400 Subject: [PATCH 20/25] add abs to plotting Signed-off-by: Rachel Kurchin --- src/plot_fcns.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/plot_fcns.jl b/src/plot_fcns.jl index 1836f32..60305cf 100644 --- a/src/plot_fcns.jl +++ b/src/plot_fcns.jl @@ -20,7 +20,7 @@ function plot_models( ) V_range = range(V_min, V_max, length = 200) xs = repeat([V_range], length(models)) - ys = map(model -> [rate_constant(V, model; kwargs...) for V in V_range], models) + ys = map(model -> abs.(rate_constant(V_range, model; kwargs...)), models) plot( xs, ys, @@ -56,7 +56,7 @@ function plot_exp_and_models( xs = Vector[V, repeat([V_range], length(models))...] ys = Vector[ exp_data[:, 2], - map(model -> rate_constant(V_range, model; kwargs...), models)..., + map(model -> abs.(rate_constant(V_range, model; kwargs...)), models)..., ] # scatter plot of experimental data, lines for fits From eec486397c42ae2fa548ce5a85945fa542720a03 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 14 Jul 2022 19:56:51 -0400 Subject: [PATCH 21/25] uniformize BV with others wrt prefactor Signed-off-by: Rachel Kurchin --- src/kinetic_models/ButlerVolmer.jl | 2 +- test/non_integral_model_tests.jl | 8 ++++---- test/phase_diagram_tests.jl | 2 +- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/src/kinetic_models/ButlerVolmer.jl b/src/kinetic_models/ButlerVolmer.jl index f6bf75d..27539ab 100644 --- a/src/kinetic_models/ButlerVolmer.jl +++ b/src/kinetic_models/ButlerVolmer.jl @@ -18,7 +18,7 @@ end # default to unit prefactor and symmetric response ButlerVolmer() = ButlerVolmer(1.0, 0.5) -ButlerVolmer(A) = ButlerVolmer(A, 0.5) +ButlerVolmer(α) = ButlerVolmer(1.0, α) function rate_constant(V_app, bv::ButlerVolmer, ::Val{true}; T = 298) exp_arg = (bv.α .* V_app) / (kB * T) diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index 38c417b..d4b32f8 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -5,8 +5,8 @@ @testset "Non-Integral Models" begin @testset "Butler-Volmer" begin bv1 = ButlerVolmer() - bv2 = ButlerVolmer(3.0) - bv3 = ButlerVolmer(1.0, 0.2) + bv2 = ButlerVolmer(3.0, 0.5) + bv3 = ButlerVolmer(0.2) @testset "Scalars" begin # zero voltage @@ -40,12 +40,12 @@ @testset "Vector Models" begin A_vals = [1.0, 2.0] α_vals = [0.4, 0.5, 0.6] - bvv1 = ButlerVolmer(A_vals) # autopopulate α, combine scalar/vector + bvv1 = ButlerVolmer(A_vals, 0.5) bvv2 = ButlerVolmer(A_vals, α_vals[1:2]) # both vectors @test_throws DimensionMismatch ButlerVolmer(A_vals, α_vals) # invalid, different lengths # test that it's equivalent to the scalar model version - @test rate_constant(0.1, bvv1) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals)) + @test rate_constant(0.1, bvv1) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, Ref(0.5))) @test rate_constant(0.1, bvv2) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) end @testset "Vector Voltages and Models" begin diff --git a/test/phase_diagram_tests.jl b/test/phase_diagram_tests.jl index 9df66fe..37a6e70 100644 --- a/test/phase_diagram_tests.jl +++ b/test/phase_diagram_tests.jl @@ -35,7 +35,7 @@ T = 298 end # prefactors are set so that k vs. η plots roughly line up for small η -bv = ButlerVolmer(300) +bv = ButlerVolmer(300, 0.5) m = Marcus(5000, 0.3) amhc = AsymptoticMarcusHushChidsey(70000, 0.3) kms = [bv, m, amhc] From 33fd89bc30fc87872865dcf48f8f8c58a8945106 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Thu, 14 Jul 2022 21:09:24 -0400 Subject: [PATCH 22/25] test vector models Signed-off-by: Rachel Kurchin --- benchmark/bench_suite.jl | 2 +- benchmark/results_branch.jls | Bin 1888906 -> 1937651 bytes src/kinetic_models/MarcusHushChidsey.jl | 7 +- src/kinetic_models/MarcusHushChidseyDOS.jl | 2 +- src/utils/dos.jl | 4 +- test/integral_model_tests.jl | 10 +++ test/non_integral_model_tests.jl | 72 +++++++-------------- test/runtests.jl | 17 +++++ 8 files changed, 59 insertions(+), 55 deletions(-) diff --git a/benchmark/bench_suite.jl b/benchmark/bench_suite.jl index 49cd91a..46604f0 100644 --- a/benchmark/bench_suite.jl +++ b/benchmark/bench_suite.jl @@ -8,7 +8,7 @@ suite["integrals"] = BenchmarkGroup() suite["integrals"]["scale"] = @benchmarkable ElectrochemicalKinetics.scale(0.1, 0.2) seconds=time_mult # reusing the same 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-30,8 +30,7 @@ MarcusHushChidsey(A, λ, dos_file::Union{Matrix,String}; kwargs...) = # TODO: Check that both this and +DOS versions still match original paper function integrand(mhc::MarcusHushChidsey, V_dl, ox::Val; T = 298) - marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 .* mhc.λ .* kB * T)) - marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 .* mhc.λ .* kB * T)) - f(E::Vector) = hcat((mhc.A * mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; T = T)...)' # will return a matrix of both E and V_dl are vectors, first index will be energies and second voltages - f(E::Real) = (mhc.A .* mhc.average_dos) .* marcus_term.(E, ox) .* fermi_dirac.(E; T = T) + marcus_term(E, ::Val{true}) = exp.(-((E .- mhc.λ .+ V_dl) .^ 2) ./ (4 * mhc.λ * kB * T)) + marcus_term(E, ::Val{false}) = exp.(-((E .- mhc.λ .- V_dl) .^2) ./ (4 * mhc.λ * kB * T)) + E -> mhc.A .* mhc.average_dos .* marcus_term(E, ox) .* fermi_dirac.(E; T=T) end \ No newline at end of file diff --git a/src/kinetic_models/MarcusHushChidseyDOS.jl b/src/kinetic_models/MarcusHushChidseyDOS.jl index 1b0e2fc..cb8fca8 100644 --- a/src/kinetic_models/MarcusHushChidseyDOS.jl +++ b/src/kinetic_models/MarcusHushChidseyDOS.jl @@ -20,7 +20,7 @@ end function Base.show(io::IO, mhcd::MarcusHushChidseyDOS) s = repr(typeof(mhcd)) * "(" - s *= "A=$(round.(mhcd.A, sigdigits=3)), λ=$(round(mhcd.λ, sigdigits=3)))" + s *= "A=$(round.(mhcd.A, sigdigits=3)), λ=$(round.(mhcd.λ, sigdigits=3)))" print(io, s) end diff --git a/src/utils/dos.jl b/src/utils/dos.jl index c7660f8..d5f7e9d 100644 --- a/src/utils/dos.jl +++ b/src/utils/dos.jl @@ -3,7 +3,6 @@ module DOS using Interpolations using DelimitedFiles using Statistics -# using Zygote export DOSData, get_dos @@ -31,6 +30,9 @@ Base.show(io::IO, dd::DOSData) = print(io, "DOSData: avg value $(round(dd.averag (dd::DOSData)(E::Real) = dd.interp_func(E) +import Base.length +length(::DOSData) = 1 + """ get_dos(dos_file; Ef=0, cut_energy=false) diff --git a/test/integral_model_tests.jl b/test/integral_model_tests.jl index dc322e3..87a1ecb 100644 --- a/test/integral_model_tests.jl +++ b/test/integral_model_tests.jl @@ -22,6 +22,13 @@ amhc = AsymptoticMarcusHushChidsey(0.25) @test all(isapprox.(rate_constant(Vs, mhc), rate_constant(Vs, amhc), atol=2e-4)) end + + @testset "Vector Models" begin + A_vals = [1, 10, 1000] + λ_vals = [0.1, 0.4, 0.7] + avg_dos_val = 1.0 + test_vector_models(MarcusHushChidsey, [A_vals, λ_vals, avg_dos_val]) + end end @testset "MarcusHushChidseyDOS" begin @@ -46,6 +53,9 @@ dos = hcat(Es .+ 1, dos[:,2]) mhcd = MarcusHushChidseyDOS(0.25, dos) @test all(-rate_constant(-Vs, mhcd) .> rate_constant(Vs, mhcd)) + + params = [[2, 20], [0.05, 0.1], DOSData(dos)] + test_vector_models(MarcusHushChidseyDOS, params) end @testset "Quantum Capacitance" begin diff --git a/test/non_integral_model_tests.jl b/test/non_integral_model_tests.jl index d4b32f8..49f3166 100644 --- a/test/non_integral_model_tests.jl +++ b/test/non_integral_model_tests.jl @@ -28,29 +28,21 @@ end end - @testset "Vectors" begin - @testset "Vector Voltages" begin - test_vector_voltages(bv1, Vs) - test_vector_voltages(bv2, Vs) - test_vector_voltages(bv3, Vs) - for model in [bv1, bv2] # bv3 won't be symmetrical - @test isapprox(model(Vs), -model(-Vs)) #symmetry - end + @testset "Vector Voltages" begin + test_vector_voltages(bv1, Vs) + test_vector_voltages(bv2, Vs) + test_vector_voltages(bv3, Vs) + for model in [bv1, bv2] # bv3 won't be symmetrical + @test isapprox(model(Vs), -model(-Vs)) #symmetry end - @testset "Vector Models" begin - A_vals = [1.0, 2.0] - α_vals = [0.4, 0.5, 0.6] - bvv1 = ButlerVolmer(A_vals, 0.5) - bvv2 = ButlerVolmer(A_vals, α_vals[1:2]) # both vectors - @test_throws DimensionMismatch ButlerVolmer(A_vals, α_vals) # invalid, different lengths + end - # test that it's equivalent to the scalar model version - @test rate_constant(0.1, bvv1) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, Ref(0.5))) - @test rate_constant(0.1, bvv2) == rate_constant.(Ref(0.1), ButlerVolmer.(A_vals, α_vals[1:2])) - end - @testset "Vector Voltages and Models" begin - # TODO: this - end + @testset "Vector Models" begin + A_vals = [0.7, 2.0] + α_vals = [0.4, 0.5, 0.6] + @test_throws DimensionMismatch ButlerVolmer(A_vals, α_vals) # invalid, different lengths + + test_vector_models(ButlerVolmer, [A_vals, α_vals[1:2]]) end end @@ -66,27 +58,18 @@ @test isapprox(m2(0.13), 5.671645, atol=1e-6) end - @testset "Vectors" begin - @testset "Vector Voltages" begin - test_vector_voltages(m1, Vs) - test_vector_voltages(m2, Vs) - for model in [m1, m2] - @test isapprox(model(Vs), -model(-Vs)) #symmetry - end - end - @testset "Vector Models" begin - A_vals = [1, 100, 10000] - λ_vals = [0.1, 0.3, 0.7] - mv1 = Marcus(λ_vals) - mv2 = Marcus(A_vals, λ_vals) - - @test rate_constant(0.1, mv1) == rate_constant.(Ref(0.1), Marcus.(λ_vals)) - @test rate_constant(0.1, mv2) == rate_constant.(Ref(0.1), Marcus.(A_vals, λ_vals)) - end - @testset "Vector Voltages and Models" begin - # TODO: this + @testset "Vector Voltages" begin + test_vector_voltages(m1, Vs) + test_vector_voltages(m2, Vs) + for model in [m1, m2] + @test isapprox(model(Vs), -model(-Vs)) #symmetry end end + @testset "Vector Models" begin + A_vals = [1, 100, 10000] + λ_vals = [0.1, 0.3, 0.7] + test_vector_models(Marcus, [A_vals, λ_vals]) + end end @testset "asymptotic MHC" begin @@ -105,14 +88,7 @@ @testset "Vector Models" begin A_vals = [1, 100, 10000] λ_vals = [0.1, 0.3, 0.7] - amhc1 = AsymptoticMarcusHushChidsey(λ_vals) - amhc2 = AsymptoticMarcusHushChidsey(A_vals, λ_vals) - - @test rate_constant(0.1, amhc1) == rate_constant.(Ref(0.1), AsymptoticMarcusHushChidsey.(λ_vals)) - @test rate_constant(0.1, amhc2) == rate_constant.(Ref(0.1), AsymptoticMarcusHushChidsey.(A_vals, λ_vals)) - end - @testset "Vector Voltages and Models" begin - # TODO: this + test_vector_models(AsymptoticMarcusHushChidsey, [A_vals, λ_vals]) end end end diff --git a/test/runtests.jl b/test/runtests.jl index 04f1fff..9015c45 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,6 +7,23 @@ function test_vector_voltages(model, voltages) @test isapprox(rate_constant(voltages, model, T=1000), rate_constant.(voltages, Ref(model), T=1000)) end +function test_vector_models(ModelType, params) + model1 = ModelType(params[2:end]...) + model2 = ModelType(params...) + broadcast_params = [] + for p in params + if length(p) == 1 + push!(broadcast_params, Ref(p)) + else + push!(broadcast_params, p) + end + end + @test isapprox(rate_constant(0.1, model1), rate_constant.(Ref(0.1), ModelType.(broadcast_params[2:end]...))) + @test isapprox(rate_constant(0.1, model1, T=1000), rate_constant.(Ref(0.1), ModelType.(broadcast_params[2:end]...), T=1000)) + @test isapprox(rate_constant(0.1, model2), rate_constant.(Ref(0.1), ModelType.(broadcast_params...))) + @test isapprox(rate_constant(0.1, model2, T=200), rate_constant.(Ref(0.1), ModelType.(broadcast_params...), T=200)) +end + @testset "ElectrochemicalKinetics.jl" begin global Vs = 0.01:0.01:0.1 @testset "Rate constant computation" begin From 12d067af627b6c46371d8b41823fadcfef50c31b Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Mon, 18 Jul 2022 15:31:04 -0400 Subject: [PATCH 23/25] switch MHC constructor syntax Signed-off-by: Rachel Kurchin --- src/kinetic_models/MarcusHushChidsey.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/kinetic_models/MarcusHushChidsey.jl b/src/kinetic_models/MarcusHushChidsey.jl index c9959c1..6afd8f5 100644 --- a/src/kinetic_models/MarcusHushChidsey.jl +++ b/src/kinetic_models/MarcusHushChidsey.jl @@ -20,7 +20,7 @@ struct MarcusHushChidsey{T} <: IntegralModel{T} end # default prefactor is 1 -MarcusHushChidsey(λ, avg_dos) = MarcusHushChidsey(1.0, λ, avg_dos) +MarcusHushChidsey(A, λ) = MarcusHushChidsey(A, λ, 1.0) # assume prefactor = 1 and avg_dos = 1 MarcusHushChidsey(λ) = MarcusHushChidsey(1.0, λ, 1.0) # convert more detailed DOS information to just pull out average From 08d621529a92273993584ac18817c27abb2aeada Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Fri, 22 Jul 2022 21:44:16 -0400 Subject: [PATCH 24/25] update readme, etc. Signed-off-by: Rachel Kurchin --- LICENSE | 2 +- README.md | 37 ++++++++++++++++++++----------------- img/MHC.png | Bin 49942 -> 0 bytes img/MHCD_ox.png | Bin 57258 -> 0 bytes img/MHCD_red.png | Bin 55276 -> 0 bytes img/Marcus.png | Bin 34130 -> 0 bytes img/bv_ox.png | Bin 37767 -> 0 bytes img/bv_red.png | Bin 29422 -> 0 bytes img/plot1.png | Bin 77172 -> 46567 bytes img/plot2.png | Bin 62550 -> 38133 bytes src/fitting.jl | 15 +++++++-------- 11 files changed, 28 insertions(+), 26 deletions(-) delete mode 100644 img/MHC.png delete mode 100644 img/MHCD_ox.png delete mode 100644 img/MHCD_red.png delete mode 100644 img/Marcus.png delete mode 100644 img/bv_ox.png delete mode 100644 img/bv_red.png diff --git a/LICENSE b/LICENSE index 3562176..098f087 100644 --- a/LICENSE +++ b/LICENSE @@ -1,4 +1,4 @@ -Copyright 2021, Rachel Kurchin and Holden Parks +Copyright 2022, Rachel Kurchin, Holden Parks, and Dhairya Gandhi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: diff --git a/README.md b/README.md index 85aec91..696ba7c 100644 --- a/README.md +++ b/README.md @@ -6,18 +6,20 @@ This package implements a variety of models for rates of electrochemical reactio ### Building and Evaluating Models We can construct a simple Butler-Volmer model with symmetric electron transfer as follows: ```julia -julia> bv = ButlerVolmer(1.0) +julia> bv = ButlerVolmer() ButlerVolmer(A=1.0, α=0.5) ``` To evaluate the model and find the reaction rate at a given voltage is as simple as: ```julia julia> bv(0.1) -6.695821798442868 +6.865409234059785 ``` +(note that this is equivalent to `rate_constant(0.1, bv)`, but this "callable" syntax is often convenient) + By default, this computes the net reaction rate. We can also get the rate only in the oxidative direction by passing the `ox` flag: ```julia julia> bv(0.1, true) -6.84197835551441 +7.0081012366762145 ``` Let's try a fancier model now. The `MarcusHushChidseyDOS` model requires information about the density of states of the electrode, which we can read from a file: ```julia @@ -42,8 +44,8 @@ Another feature we support for `MarcusHushChidseyDOS` models is incorporating th julia> mhcd = MarcusHushChidseyDOS(0.82, "data/DOSes/bernal_graphene.txt") MarcusHushChidseyDOS(A=1.0, λ=0.82) -julia> rate_constant(0.4, mhcd; calc_cq=true, Vq_min=-0.45, Vq_max=0.45) -0.00044958691359217384 +julia> rate_constant(0.15, mhcd, true; calc_cq=true, Vq_min=-0.3, Vq_max=0.3, E_min = -0.6, E_max=0.6) +2.8017566534572208e-5 ``` ### Fitting and Comparing Models @@ -77,43 +79,44 @@ julia> plot_models(models) ``` models +### Electrochemical Phase Diagrams +For more on this, see upcoming paper: [arxiv link placeholder] + ## Supported Models -(I hope the equations below are visible in both dark and light mode...) ### Butler-Volmer -Probably the most basic (and entirely empirical) kinetic model. The rate constants are given by: +Probably the most basic (and largely empirical) kinetic model. The rate constants are given by: -BV_ox +$$k_{\text{ox}}^{\text{BV}}(\eta)=A\exp\left(\frac{\alpha\eta}{k_{\text B}T}\right)\\k_{\text{red}}^{\text{BV}}(\eta)=A\exp\left(\frac{(1-\alpha)\eta}{k_{\text B}T}\right)$$ -BV_red - -Implemented in the package as `ButlerVolmer`, possessing two fields: the prefactor `A` and the transfer coefficient `α`. +It is implemented in the package as `ButlerVolmer`, possessing two fields: the prefactor `A` and the transfer coefficient `α`. ### Marcus One step up with a bit of mechanism... -Marcus_k +$$k_{\text{red/ox}}^{\text{Marcus}}(\eta) = A\exp\left(-\frac{(\lambda\pm\eta)^2}{4k_{\text B}T}\right)$$ Implemented in the package as `Marcus`, with parameters for prefactor `A` and reorganization energy `λ`. ### Marcus-Hush-Chidsey Originated from [Chidsey's 1991 paper](https://dx.doi.org/10.1126/science.251.4996.919). -MHC_k +$$k_{\text{red/ox}}^{\text{MHC}}(\eta) = A\int_{-\infty}^\infty \exp\left(-\frac{(\varepsilon-\lambda\mp\eta)^2}{4k_{\text B}T}\right)f_{\text{FD}}(\varepsilon, T)\mathrm d\varepsilon$$ Implemented as `MarcusHushChidsey`, with prefactor `A`, reorganization energy `λ`, and also an `average_dos` parameter (which defaults to 1.0), which is useful for making direct comparisons against `MarcusHushChidseyDOS` (see below). ### Asymptotic Marcus-Hush-Chidsey -Originated from [Zeng et al. 2014](https://dx.doi.org/10.1016/j.jelechem.2014.09.038d) (equation 17). Note that in their notation, $\eta$ is scaled by the thermal energy. +Originated from [Zeng et al. 2014](https://dx.doi.org/10.1016/j.jelechem.2014.09.038d) (equation 17). We have corrected it to recover the correct temperature scaling, [paper link placeholder] Implemented as `AsymptoticMarcusHushChidsey` with parameters `A` and `λ`. ### Marcus-Hush-Chidsey + DOS Originated from [Kurchin and Viswanathan 2020](https://dx.doi.org/10.1063/5.0023611 ). -MHCD_ox -MHCD_red +$$k_{\text{ox}}^{\text{MHCKV}}(\eta)=A\int_{-\infty}^\infty\mathcal{D}(\varepsilon)\exp\left(-\frac{(\lambda-\eta+\varepsilon)^2}{4\lambda k_{\text{B}}T}\right)(1-f_{\text{FD}}(\varepsilon,T))\mathrm{d}\varepsilon\\ +k_{\text{red}}^{\text{MHCKV}}(\eta)=A\int_{-\infty}^\infty\mathcal{D}(\varepsilon)\exp\left(-\frac{(\lambda+\eta-\varepsilon)^2}{4\lambda k_{\text{B}}T}\right)f_{\text{FD}}(\varepsilon,T)\mathrm{d}\varepsilon$$ + -Implemented as `MarcusHushChidseyDOS`, with parameters `A`, `λ`, and `dos`, which must be a `DOSData` object. +Implemented as `MarcusHushChidseyDOS`, with parameters `A`, `λ`, and `dos`, which must be a `DOSData` object (can be automatically constructed from a two-column text file of energies and DOS values). ## Contributing We are happy to take pull requests for new features, new models, etc. by pull request! 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default_param_bounds, - T::Float32 = 298, + T = 298, kwargs... ) V_vals = exp_data[:, 1] @@ -166,7 +166,7 @@ function fit_model( exp_data::Matrix, model_type::Type{<:IntegralModel}; param_bounds::Dict = default_param_bounds, - T::Float32 = 298, + T = 298, E_min = -100 * kB*T, E_max = 100 * kB*T, kwargs..., @@ -191,7 +191,7 @@ function _fit_model( I_vals = exp_data[:, 2] model_builder = _get_model_builder(model_type, param_bounds; kwargs...) - sq_error(I_pred) = sum((I_pred .- I_vals) .^ 2) + sq_error(I_pred) = sum((abs.(I_pred) .- I_vals) .^ 2) # WTF, why do I need these here again...just when I think I understand scope fitting_params(t::Type{<:KineticModel}) = fieldnames(t) @@ -199,7 +199,6 @@ function _fit_model( fitting_params(::Type{MarcusHushChidseyDOS}) = (:A, :λ) # find best-fitting params - # Zygote is tripped up by QuadGK, so that one has to be done with black-box optimization, but the non-integral models work with autodiff opt_func = params -> sq_error(model_evaluator(model_builder(params))) local best_params # function grad!(s, x) @@ -216,10 +215,10 @@ function _fit_model( # IntegralModels performed better with GradientDescent optimizer, opts = if model_type <: IntegralModel opts = Optim.Options(show_trace = false, - iterations = 3, - outer_iterations = 4, + iterations = 5, + outer_iterations = 7, x_tol = 1., - f_tol = 1e3) + f_tol = 1e2) Fminbox(NelderMead()), opts else Fminbox(NelderMead()), Optim.Options() From 299684af6f0c33e0dc265b56bd1c7533983c0703 Mon Sep 17 00:00:00 2001 From: Rachel Kurchin Date: Fri, 22 Jul 2022 22:01:29 -0400 Subject: [PATCH 25/25] stop tracking Manifest Signed-off-by: Rachel Kurchin --- Manifest.toml | 1054 ------------------------------------------------- 1 file changed, 1054 deletions(-) delete mode 100644 Manifest.toml diff --git a/Manifest.toml b/Manifest.toml deleted file mode 100644 index 79930ae..0000000 --- a/Manifest.toml +++ /dev/null @@ -1,1054 +0,0 @@ -# This file is 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