matbinder / fitsnap-example

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FitSnap3 Tantalum example

available at: https://github.com/FitSNAP/FitSNAP

This example will generate a potential for tantalum as published in Thompson, A.P. et. al, J. Comp. Phys. 285 (2015) 316-330. This version of the tantalum potential uses the linear version of SNAP.

Running this example:

To run this example use mybinder:

Binder

Files in this Directory

Ta-example.in

Input file containing parameters to run FitSNAP and generate the tantalum potential

grouplist.in

File that lists all the training groups in the JSON directory, the number of files in each group, and the energy, force, and virial training weights on each group.

JSON/

Directory that contains all the training configurations which are organized into different groups.

Files generated by example:

Ta_pot.snapcoeff

SNAP potential coefficient file that contains all the beta coefficients for this potential. This is one of two files needed to use this potential in LAMMPS

Ta_pot.snapparam

SNAP potential parameters file that contains the hyperparameters and options used during the fit for this potential. This is one of two files needed to use this potential in LAMMPS

Ta_metrics.csv

Contains a variety of error metrics for all the training groups for this fit.

Note that the 19Nov19_Standard/ directory contains sample output for this example

Important input parameters for this example

rcutfac = 4.67637 : Radial cutoff (hyperparameters) chosen for this potential wj1 = 1.0 : Elemental weight on tantalum for density expansion radelem1 = 0.5 : Tantalum per-element cutoff type1 = Ta : Chemical symbol for element which should match training files in JSON quadraticflag = 0 : Quadratic SNAP is turned off, using linear SNAP

Tantalum data from:

The JSON configurations and hyperparameters used for this example are published in:

Thompson, A. P., Swiler, L. P., Trott, C. R., Foiles, S. M., & Tucker, G. J. (2015). Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials. Journal of Computational Physics, 285, 316-330

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