GAP-AL tutorial for the Psi-k ML-IP 2021 tutorial workshop.
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Updated
Jan 19, 2022 - Jupyter Notebook
GAP-AL tutorial for the Psi-k ML-IP 2021 tutorial workshop.
An attempt to fit ab-initio materials database (e.g. Materials Project) results to FitSNAP potential.
A parallel molecular dynamics simulation algorithm for studying the thermal stability of nanoalloys.
Molecular dynamics simulations to find the lattice parameters of diamond and 3C-SiC lattices at the equilibrium with different interatomic potentials available in LAMMPS
Impliment of the ReaxFF-nn mathine learning potential in the GULP package
Сollection of ab initio calculated molecular potential energy surfaces
Ionic Dynamics on GPU (variant of atomistic simulation for ionic crystals like UO2, CaF2, etc.)
Instructions and scripts for adaptive sampling for gas-surface dynamics
A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials
Webpage for RANN interatomic potential
Automatic Differentiation of Interatomic Potentials with Phonons in Julia: ADIP².jl
Modified Embedded Atom Method with Bond Order (MEAM-BO) implementation in LAMMPS
A Python library for developing machine learning interatomic potentials, based on Google JAX.
Fitting interatomic potential for molecular dynamics
Provide easy-to-use CESMIX-aligned case studies. Integrate the latest developments of the Julia atomistic ecosystem and state-of-the-art tools.
Generator of polynomial machine learning potentials
Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics
A flexible and performant framework for training machine learning potentials.
PotentialLearning.jl: Optimize your atomistic data and interatomic potential models in your molecular dynamic workflows.
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