🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/forum?id=SAT0KPA5UO

A simple and fast python library to handle the data generated from molecular dynamics simulations

This repository contains a suite of scripts designed to automate thermodynamic properties of materials, using MatterSim, a universal machine learning interatomic potential, for geometry optimization and force constant calculations, integrated with Phonopy-QHA for Quasi-Harmonic Approximation.

Reference-audited AI coding-agent skill library for computational chemistry, materials modeling, atomistic simulation, scientific ML, and related workflows.

From metadynamics to machine-learning interatomic potentials — research code and notes.

Committee-based active learning framework for building AENET interatomic potential training datasets