Pinned Repositories
Learning_from_models
The analyses applied on high-dimensional performance data of machine learning interatomic potentials (MLIPs), described in 'Learning from models: high-dimensional analyses on the performance of MLIPs'
Li-Al_MLIP_datasets
Eight datasets (including two training datasets, two validation datasets, and four testing datasets) for the publication "Assessing the accuracy of MLIPs in predicting the elemental ordering: a case study on Li-Al alloys"
Silicon_MLIP_datasets
Training, validation, and testing datasets for the publication "The discrepancies, the extrapolability, and the interpolability of machine learning interatomic potentials on simulating atomic dynamics"
Topological_Analysis
Topological analysis for Li local space, site, pathway in crystal structures
postqe
qeschema
West
WEST code
MechElastic
This python scripts can be used to calculate some important physical properties such as elastic moduli, melting temperature, Debye temperature, elastic wave velocities, and elastic anisotropy for all crystalline systems using the VASP output data for elastic tensor calculation. It can also be used to test the mechanical stability of any bulk system. It reads the elastic matrix written in the OUTCAR file. If not provided by user, this script will read the crystal type from the OUTCAR file.
yliu1240's Repositories
yliu1240/MechElastic
This python scripts can be used to calculate some important physical properties such as elastic moduli, melting temperature, Debye temperature, elastic wave velocities, and elastic anisotropy for all crystalline systems using the VASP output data for elastic tensor calculation. It can also be used to test the mechanical stability of any bulk system. It reads the elastic matrix written in the OUTCAR file. If not provided by user, this script will read the crystal type from the OUTCAR file.