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solvents interface code #87
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from .bulk import Bulk | ||
from .ion import Ion | ||
from .slab import Slab | ||
from .solvent import Solvent | ||
from .adsorbate import Adsorbate | ||
from .adsorbate_slab_config import AdsorbateSlabConfig | ||
from .multi_adsorbate_slab_config import MultipleAdsorbateSlabConfig | ||
from .complex_solvent_config import ComplexSolventConfig |
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import os | ||
import subprocess | ||
import tempfile | ||
from shutil import which | ||
from typing import List | ||
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import ase.io | ||
import numpy as np | ||
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from ocdata.core import Adsorbate, Ion, MultipleAdsorbateSlabConfig, Slab, Solvent | ||
from ocdata.utils.geometry import BoxGeometry, PlaneBoundTriclinicGeometry | ||
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# Code adapted from https://github.com/henriasv/molecular-builder/tree/master | ||
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class ComplexSolventConfig(MultipleAdsorbateSlabConfig): | ||
""" | ||
Class to represent a solvent, adsorbate, slab, ion config. This class only | ||
returns a fixed combination of adsorbates placed on the surface. Solvent | ||
placement is performed by packmol | ||
(https://m3g.github.io/packmol/userguide.shtml), with the number of solvent | ||
molecules controlled by its corresponding density. Ion placement is random | ||
within the desired volume. | ||
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Arguments | ||
--------- | ||
slab: Slab | ||
Slab object. | ||
adsorbates: List[Adsorbate] | ||
List of adsorbate objects to place on the slab. | ||
solvent: Solvent | ||
Solvent object | ||
ions: List[Ion] = [] | ||
List of ion objects to place | ||
num_sites: int | ||
Number of sites to sample. | ||
num_configurations: int | ||
Number of configurations to generate per slab+adsorbate(s) combination. | ||
This corresponds to selecting different site combinations to place | ||
the adsorbates on. | ||
interstitial_gap: float | ||
Minimum distance, in Angstroms, between adsorbate and slab atoms as | ||
well as the inter-adsorbate distance. | ||
vacuum_size: int | ||
Size of vacuum layer to add to both ends of the resulting atoms object. | ||
solvent_interstitial_gap: float | ||
Minimum distance, in Angstroms, between the solvent environment and the | ||
adsorbate-slab environment. | ||
solvent_depth: float | ||
Volume depth to be used to pack solvents inside. | ||
pbc_shift: float | ||
Cushion to add to the packmol volume to avoid overlapping atoms over pbc. | ||
packmol_tolerance: float | ||
Packmol minimum distance to impose between molecules. | ||
mode: str | ||
"random", "heuristic", or "random_site_heuristic_placement". | ||
This affects surface site sampling and adsorbate placement on each site. | ||
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In "random", we do a Delaunay triangulation of the surface atoms, then | ||
sample sites uniformly at random within each triangle. When placing the | ||
adsorbate, we randomly rotate it along xyz, and place it such that the | ||
center of mass is at the site. | ||
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In "heuristic", we use Pymatgen's AdsorbateSiteFinder to find the most | ||
energetically favorable sites, i.e., ontop, bridge, or hollow sites. | ||
When placing the adsorbate, we randomly rotate it along z with only | ||
slight rotation along x and y, and place it such that the binding atom | ||
is at the site. | ||
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In "random_site_heuristic_placement", we do a Delaunay triangulation of | ||
the surface atoms, then sample sites uniformly at random within each | ||
triangle. When placing the adsorbate, we randomly rotate it along z with | ||
only slight rotation along x and y, and place it such that the binding | ||
atom is at the site. | ||
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In all cases, the adsorbate is placed at the closest position of no | ||
overlap with the slab plus `interstitial_gap` along the surface normal. | ||
""" | ||
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def __init__( | ||
self, | ||
slab: Slab, | ||
adsorbates: List[Adsorbate], | ||
solvent: Solvent, | ||
ions: List[Ion] = None, | ||
num_sites: int = 100, | ||
num_configurations: int = 1, | ||
interstitial_gap: float = 0.1, | ||
vacuum_size: int = 15, | ||
solvent_interstitial_gap: float = 2, | ||
solvent_depth: float = 8, | ||
pbc_shift: float = 0.0, | ||
packmol_tolerance: float = 2, | ||
mode: str = "random_site_heuristic_placement", | ||
): | ||
super().__init__( | ||
slab=slab, | ||
adsorbates=adsorbates, | ||
num_sites=num_sites, | ||
num_configurations=num_configurations, | ||
interstitial_gap=interstitial_gap, | ||
mode=mode, | ||
) | ||
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self.solvent = solvent | ||
self.ions = ions | ||
self.vacuum_size = vacuum_size | ||
self.solvent_depth = solvent_depth | ||
self.solvent_interstitial_gap = solvent_interstitial_gap | ||
self.pbc_shift = pbc_shift | ||
self.packmol_tolerance = packmol_tolerance | ||
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self.n_mol_per_volume = solvent.get_molecules_per_volume | ||
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self.atoms_list, self.metadata_list = self.create_interface_on_sites( | ||
self.atoms_list, self.metadata_list | ||
) | ||
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def create_interface_on_sites(self, atoms_list, metadata_list): | ||
atoms_interface_list = [] | ||
metadata_interface_list = [] | ||
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for atoms, adsorbate_metadata in zip(atoms_list, metadata_list): | ||
cell = atoms.cell.copy() | ||
unit_normal = cell[2] / np.linalg.norm(cell[2]) | ||
cell[2] = self.solvent_depth * unit_normal | ||
volume = cell.volume | ||
n_solvent_mols = int(self.n_mol_per_volume * volume) | ||
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if cell.orthorhombic: | ||
box_length = cell.lengths() | ||
geometry = BoxGeometry( | ||
center=box_length / 2, length=box_length - self.pbc_shift | ||
) | ||
else: | ||
geometry = PlaneBoundTriclinicGeometry(cell, pbc=self.pbc_shift) | ||
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solvent_ions_atoms = self.create_packmol_atoms(geometry, n_solvent_mols) | ||
solvent_ions_atoms.set_cell(cell) | ||
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max_z = atoms.positions[:, 2].max() + self.solvent_interstitial_gap | ||
translation_vec = cell[2] | ||
translation_vec[2] = max_z | ||
solvent_ions_atoms.translate(translation_vec) | ||
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interface_atoms = atoms + solvent_ions_atoms | ||
interface_atoms.center(vacuum=self.vacuum_size, axis=2) | ||
interface_atoms.wrap() | ||
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atoms_interface_list.append(interface_atoms) | ||
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metadata = { | ||
"adsorbates": adsorbate_metadata, | ||
"solvent": self.solvent.name, | ||
"ions": [x.name for x in self.ions], | ||
"ion_concentrations": [ | ||
x.get_ion_concentration(volume) for x in self.ions | ||
], | ||
"solvent_depth": self.solvent_depth, | ||
"solvent_volume": volume, | ||
} | ||
metadata_interface_list.append(metadata) | ||
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return atoms_interface_list, metadata_interface_list | ||
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def create_packmol_atoms(self, geometry, n_solvent_mols): | ||
cell = geometry.cell | ||
with tempfile.TemporaryDirectory() as tmp_dir: | ||
output_path = os.path.join(tmp_dir, "out.pdb") | ||
self.solvent.atoms.write(f"{tmp_dir}/solvent.pdb", format="proteindatabank") | ||
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# When placing a single ion, packmol strangely always places it at | ||
# the boundary of the cell. This hacky fix manually places | ||
# the ion in a random location in the cell. Packmol then will fix | ||
# these atoms and not optimize them during its optimization, only | ||
# optimizing solvent molecules arround the ion. | ||
for i, ion in enumerate(self.ions): | ||
ion_atoms = ion.atoms.copy() | ||
ion_atoms.set_cell(cell) | ||
self.randomize_coords(ion_atoms) | ||
ion_atoms.write(f"{tmp_dir}/ion_{i}.pdb", format="proteindatabank") | ||
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# write packmol input | ||
packmol_input = os.path.join(tmp_dir, "input.inp") | ||
with open(packmol_input, "w") as f: | ||
f.write(f"tolerance {self.packmol_tolerance}\n") | ||
f.write("filetype pdb\n") | ||
f.write(f"output {output_path}\n") | ||
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# write solvent | ||
f.write( | ||
geometry.packmol_structure( | ||
f"{tmp_dir}/solvent.pdb", n_solvent_mols, "inside" | ||
) | ||
) | ||
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for i in range(len(self.ions)): | ||
f.write(f"structure {tmp_dir}/ion_{i}.pdb\n") | ||
f.write(" number 1\n") | ||
f.write(" fixed 0 0 0 0 0 0\n") | ||
f.write("end structure\n\n") | ||
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self.run_packmol(packmol_input) | ||
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solvent_ions_atoms = ase.io.read(output_path, format="proteindatabank") | ||
solvent_ions_atoms.set_pbc(True) | ||
solvent_ions_atoms.set_tags([3] * len(solvent_ions_atoms)) | ||
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return solvent_ions_atoms | ||
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def run_packmol(self, packmol_input): | ||
packmol_cmd = which("packmol") | ||
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try: | ||
ps = subprocess.Popen( | ||
f"{packmol_cmd} < {packmol_input}", | ||
shell=True, | ||
stdout=subprocess.PIPE, | ||
stderr=subprocess.PIPE, | ||
) | ||
out, err = ps.communicate() | ||
except NotImplementedError: | ||
raise OSError("packmol is not found.") | ||
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def randomize_coords(self, atoms): | ||
cell_weights = np.random.rand(3) | ||
cell_weights /= np.sum(cell_weights) | ||
xyz = np.dot(cell_weights, atoms.cell) | ||
atoms.set_center_of_mass(xyz) |
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import pickle | ||
import warnings | ||
from typing import Any, Dict, Tuple | ||
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import ase | ||
import ase.units as units | ||
import numpy as np | ||
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from ocdata.databases.pkls import IONS_PKL_PATH | ||
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class Ion: | ||
""" | ||
Initializes an ion object in one of 2 ways: | ||
- Directly pass in an ase.Atoms object. | ||
- Pass in index of ion to select from ion database. | ||
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Arguments | ||
--------- | ||
ion_atoms: ase.Atoms | ||
ion structure. | ||
ion_id_from_db: int | ||
Index of ion to select. | ||
ion_db_path: str | ||
Path to ion database. | ||
""" | ||
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def __init__( | ||
self, | ||
ion_atoms: ase.Atoms = None, | ||
ion_id_from_db: int = None, | ||
ion_db_path: str = IONS_PKL_PATH, | ||
): | ||
self.ion_id_from_db = ion_id_from_db | ||
self.ion_db_path = ion_db_path | ||
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if ion_atoms is not None: | ||
self.atoms = ion_atoms.copy() | ||
self.name = str(self.atoms.symbols) | ||
elif ion_id_from_db is not None: | ||
ion_db = pickle.load(open(ion_db_path, "rb")) | ||
self._load_ion(ion_db[ion_id_from_db]) | ||
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def __len__(self): | ||
return len(self.atoms) | ||
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def __str__(self): | ||
return self.name | ||
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def _load_ion(self, ion: Dict) -> None: | ||
""" | ||
Saves the fields from an ion stored in a database. Fields added | ||
after the first revision are conditionally added for backwards | ||
compatibility with older database files. | ||
""" | ||
self.atoms = ion["atoms"] | ||
self.name = ion["name"] | ||
self.charge = ion["charge"] | ||
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def get_ion_concentration(self, volume): | ||
""" | ||
Compute the ion concentration units of M, given a volume in units of | ||
Angstrom^3. | ||
""" | ||
return 1e27 / (units._Nav * volume) |
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import pickle | ||
import warnings | ||
from typing import Any, Dict, Tuple | ||
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import ase | ||
import ase.units as units | ||
import numpy as np | ||
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from ocdata.databases.pkls import SOLVENTS_PKL_PATH | ||
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class Solvent: | ||
""" | ||
Initializes a solvent object in one of 2 ways: | ||
- Directly pass in an ase.Atoms object. | ||
- Pass in index of solvent to select from solvent database. | ||
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Arguments | ||
--------- | ||
solvent_atoms: ase.Atoms | ||
Solvent molecule | ||
solvent_id_from_db: int | ||
Index of solvent to select. | ||
solvent_db_path: str | ||
Path to solvent database. | ||
solvent_density: float | ||
Desired solvent density to use. If not specified, the default is used | ||
from the solvent databases. | ||
""" | ||
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def __init__( | ||
self, | ||
solvent_atoms: ase.Atoms = None, | ||
solvent_id_from_db: int = None, | ||
solvent_db_path: str = SOLVENTS_PKL_PATH, | ||
solvent_density: float = None, | ||
): | ||
self.solvent_id_from_db = solvent_id_from_db | ||
self.solvent_db_path = solvent_db_path | ||
self.solvent_density = solvent_density | ||
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if solvent_atoms is not None: | ||
self.atoms = solvent_atoms.copy() | ||
self.name = str(self.atoms.symbols) | ||
elif solvent_id_from_db is not None: | ||
solvent_db = pickle.load(open(solvent_db_path, "rb")) | ||
self._load_solvent(solvent_db[solvent_id_from_db]) | ||
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self.molar_mass = sum(self.atoms.get_masses()) | ||
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def __len__(self): | ||
return len(self.atoms) | ||
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def __str__(self): | ||
return self.name | ||
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def _load_solvent(self, solvent: Dict) -> None: | ||
""" | ||
Saves the fields from an adsorbate stored in a database. Fields added | ||
after the first revision are conditionally added for backwards | ||
compatibility with older database files. | ||
""" | ||
self.atoms = solvent["atoms"] | ||
self.name = solvent["name"] | ||
# use the default density if one is not specified | ||
self.density = ( | ||
solvent["density"] if not self.solvent_density else self.solvent_density | ||
) | ||
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@property | ||
def get_molecules_per_volume(self): | ||
""" | ||
Convert the solvent density in g/cm3 to the number of molecules per | ||
angstrom cubed of volume. | ||
""" | ||
# molecules/mol * grams/cm3 / (1e24 A^3/cm^3 * g/mol) | ||
return units._Nav * self.density / (1e24 * self.molar_mass) |
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Can we think of other metadata we would like to store when we generate the input? Is initial surface charge density something meaningful (i.e.
ion_charge / surface_area
)?cc - @nitishg91
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Yes, initial surface charge would be good to store.