ATOMICA: Learning Universal Representations of Intermolecular Interactions

Code for automated fitting of machine learned interatomic potentials.

Chemical intuition for surface science in a package.

Julia implementation of algorithm for counting primitive rings in an atomistic structure. Useful for materials simulations

This repository includes a notebook to run the open-source materials modeling package Quantum Espresso on Google Colab.

Modulated automation of cluster expansion based on atomate2 and Jobflow

KIMERA: A Kinetic Monte Carlo code for Mineral Dissolution

This repository contains the LAMMPS and python scripts created from the ground-up, along with the most important data, to conduct a thorough analysis of the Thermal Rectification (TR) in semi-stochastically generated atomistic models of polycrystalline graphene with graded grain size variation - using Molecular Dynamics & mapping of phonon modes.

ConfRank+: Extending Conformer Ranking to Charged Molecules

A CLI tool for Molecular Dynamics pre- and post-processing, Meant to be used with Large Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS).

Code and experiments accompanying our paper Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties at NeurIPS 2022

ASD2VTK is a Python tool that enables the conversion of output data from UppASD simulations to VTK files for easy visualization and post-processing in Paraview.

Domain ontology for atomistic and electronic modelling