Code & Data
FPBench
An application-oriented benchmark that decomposes the errors of machine-learned foundation potentials on representative computational tasks—force prediction, energy ranking, and ion migration—exposing reliability gaps that average energy/force errors miss, with open evaluation code and a public leaderboard.
AIMD Diffusion Error Analysis Toolkit
A Python toolkit for diffusion analysis from ab initio molecular dynamics (AIMD) simulations, with a command-line tool for single- and multi-temperature diffusivity and Arrhenius analysis.
npj Comput. Mater. 4, 18 (2018)
Electrochemical & Interface Stability Analysis Toolkit
A Python package for analyzing the thermodynamic stability of solid electrolyte–electrode interfaces in all-solid-state batteries.
ACS Appl. Mater. Interfaces 7, 23685-23693 (2015); J. Mater. Chem. A 4, 3253-3266 (2016); Adv. Sci. 1600517 (2017)
MLIP Performance Analysis
Performance datasets and analysis notebooks for high-dimensional analyses of machine learning interatomic potential (MLIP) performance.
npj Comput. Mater. 10, 159 (2024)
Li-Al MLIP Models & Datasets
Training, validation, and testing datasets for assessing machine learning interatomic potential accuracy on elemental ordering in Li-Al alloys.
Acta Mater. 268, 119742 (2024)
Mixed Ternary Chalcogenide Phase Change Materials
Code for identifying and generating candidate ternary chalcogenide phase-change materials from Materials Project tie-line analysis, through DFT-ready structures.
Silicon MLIP Datasets
Training, validation, and testing datasets for evaluating machine learning interatomic potentials (MLIPs) on silicon defects and diffusion.
npj Comput. Mater. 9, 174 (2023)
Topological Site & Diffusion Analysis for Crystal Structures
A Python library for topological analysis of interstitial sites in oxide and sulfide crystal structures, based on Voronoi analysis.
Adv. Energy Mater. 9, 1902078 (2019)