Automatic Differentiation of Interatomic Potentials with Phonons in Julia: ADIP².jl
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Updated
Aug 25, 2021 - Julia
Automatic Differentiation of Interatomic Potentials with Phonons in Julia: ADIP².jl
Сollection of ab initio calculated molecular potential energy surfaces
Modified Embedded Atom Method with Bond Order (MEAM-BO) implementation in LAMMPS
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.
A python package for fast building amorphous solids and liquid mixtures from https://materialsproject.org computed structures and machine learning interatomic potentials
Fitting interatomic potential for molecular dynamics
Molecular dynamics simulations to find the lattice parameters of diamond and 3C-SiC lattices at the equilibrium with different interatomic potentials available in LAMMPS
Ionic Dynamics on GPU (variant of atomistic simulation for ionic crystals like UO2, CaF2, etc.)
Impliment of the ReaxFF-nn mathine learning potential in the GULP package
A Python package for developing machine learning interatomic potentials, based on JAX.
Provide easy-to-use CESMIX-aligned case studies. Integrate the latest developments of the Julia atomistic ecosystem and state-of-the-art tools.
GAP-AL tutorial for the Psi-k ML-IP 2021 tutorial workshop.
Instructions and scripts for adaptive sampling for gas-surface dynamics
A flexible and performant framework for training machine learning potentials.
Webpage for RANN interatomic potential
Generator of polynomial machine learning potentials
FLAME: a library for atomistic modeling environments
An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.
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