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New defect example ipynb
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lizhenzhupearl committed Mar 30, 2023
1 parent 86cb26b commit 58c2f20
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68 changes: 68 additions & 0 deletions DefectCon_example.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from materials\n",
"import numpy as np\n",
"\n",
"from plot_potential import plot_potential\n",
"\n",
"T = np.linspace(600,1200,100) # K\n",
"P = np.array( np.logspace(1,7,100),ndmin=2).transpose() # Pa\n",
"\n",
"#D_mu_S8 = 1/8*(S8.mu_kJ(T, P) - alpha_S.mu_kJ(T, P))\n",
"mu_S2 = 1/2*S2.mu_kJ(T, P)\n",
"mu_Ss = 1/8 *alpha_S.mu_kJ(T, P)\n",
"mu_S8 = 1/8 * S8.mu_kJ(T, P)\n",
"D_mu = 1/2 * S2.mu_kJ(T, P) - 1/8 *alpha_S.mu_kJ(T, P)\n",
"#D_mu = 1/2* S2.mu_kJ(T, P) - 1/8 * S8.mu_kJ(T, P)\n",
"\n",
"E_Ss = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_Ss) * 0.0103636 + (+2)*(3.15+0.846)\n",
"E_S8 = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_S8) * 0.0103636 + (+2)*(3.15+0.846)\n",
"E_S2 = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_S2) * 0.0103636 + (+2)*(3.15+0.846)\n",
"kbt = (1.380649e-23) * T / (1.6e-19)\n",
"n_S2 = np.log10(1 * 64 * np.exp(-E_S2/kbt))\n",
"n_S8 = np.log10(1 * 64 * np.exp(-E_S8/kbt))\n",
"n_Ss = np.log10(1 * 64 * np.exp(-E_Ss/kbt))\n",
"\n",
"\n",
"n =(- D_mu * 1000 / ((1.380649e-23) * (6.0221408e+23) * T))\n",
"\n",
"D_mu_label = 'ln(n(V$_{S}$)/n(V$_{S(ref)}$))'\n",
"formation = 'V$_{S}$$^{+2}$ formation energy (eV)'\n",
"con_label= 'V$_{S}$$^{+2}$ Defect concentration (log10)'\n",
"scale_range = [0,35]\n",
"\n",
"#plot_potential(T,P,E_S2,formation,scale_range,filename='plots/FormationS2.png')\n",
"plot_potential(T,P,mu_Ss,con_label,scale_range,filename='plots/muSs_y.png')\n",
"plot_potential(T,P,E_S8,con_label,scale_range,filename='plots/E8.png')\n",
"plot_potential(T,P,n_S2,con_label,scale_range,filename='plots/ConcentrationS2_y.png')\n",
"plot_potential(T,P,n_S8,con_label,scale_range,filename='plots/ConcentrationS8_y.png')\n",
"plot_potential(T,P,n_Ss,con_label,scale_range,filename='plots/ConcentrationSs_y.png')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.16 64-bit",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.9.16"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "397704579725e15f5c7cb49fe5f0341eb7531c82d19f2c29d197e8b64ab5776b"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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41 changes: 41 additions & 0 deletions scripts/defect_concentration.py
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def main():
from materials
import numpy as np

from plot_potential import plot_potential

T = np.linspace(600,1200,100) # K
P = np.array( np.logspace(1,7,100),ndmin=2).transpose() # Pa

#D_mu_S8 = 1/8*(S8.mu_kJ(T, P) - alpha_S.mu_kJ(T, P))
mu_S2 = 1/2*S2.mu_kJ(T, P)
mu_Ss = 1/8 *alpha_S.mu_kJ(T, P)
mu_S8 = 1/8 * S8.mu_kJ(T, P)
D_mu = 1/2 * S2.mu_kJ(T, P) - 1/8 *alpha_S.mu_kJ(T, P)
#D_mu = 1/2* S2.mu_kJ(T, P) - 1/8 * S8.mu_kJ(T, P)

E_Ss = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_Ss) * 0.0103636 + (+2)*(3.15+0.846)
E_S8 = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_S8) * 0.0103636 + (+2)*(3.15+0.846)
E_S2 = (-.12378465E+04) - (-.12377738E+04) + (1) * (mu_S2) * 0.0103636 + (+2)*(3.15+0.846)
kbt = (1.380649e-23) * T / (1.6e-19)
n_S2 = np.log10(1 * 64 * np.exp(-E_S2/kbt))
n_S8 = np.log10(1 * 64 * np.exp(-E_S8/kbt))
n_Ss = np.log10(1 * 64 * np.exp(-E_Ss/kbt))


n =(- D_mu * 1000 / ((1.380649e-23) * (6.0221408e+23) * T))

D_mu_label = 'ln(n(V$_{S}$)/n(V$_{S(ref)}$))'
formation = 'V$_{S}$$^{+2}$ formation energy (eV)'
con_label= 'V$_{S}$$^{+2}$ Defect concentration (log10)'
scale_range = [0,35]

#plot_potential(T,P,E_S2,formation,scale_range,filename='plots/FormationS2.png')
plot_potential(T,P,mu_Ss,con_label,scale_range,filename='plots/muSs_y.png')
plot_potential(T,P,E_S8,con_label,scale_range,filename='plots/E8.png')
plot_potential(T,P,n_S2,con_label,scale_range,filename='plots/ConcentrationS2_y.png')
plot_potential(T,P,n_S8,con_label,scale_range,filename='plots/ConcentrationS8_y.png')
plot_potential(T,P,n_Ss,con_label,scale_range,filename='plots/ConcentrationSs_y.png')

if __name__ == "__main__":
main()

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