A deep learning package for many-body potential energy representation and molecular dynamics
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Updated
Jul 14, 2026 - Python
A deep learning package for many-body potential energy representation and molecular dynamics
Graphics Processing Units Molecular Dynamics
AI-enhanced computational chemistry
GPU Monte Carlo Simulation Code with a taste of RASPA
GUI for running simulations with universal MLIPs (MACE, CHGNet, SevenNet, Nequix, ORB, MatterSim, UPET, GRACE)
Genarris is a random molecular crystal structure generator.
Accelerating Metadynamics-Based Free-Energy Calculations with Adaptive Machine Learning Potentials
Meta's UMA and Orbital Materials' Orb-v3/OrbMol interatomic potential models, running on Tenstorrent hardware.
Endstate corrections from MM to QML potential
A lightweight Snakemake-based workflow that implements the DP-GEN scheme.
Collection of tools/codes/data used in the article D4DD00265B
Machine learning interatomic potentials and their application to lithium batteries (seminar talk in Spanish).
A minimal package for providing pretrained machine learning force fields (e.g. multi-fidelity M3GNet) for material simulations.
Physics bachelor's thesis project focused on testing the physical adequacy and physical foundations of MLIPs in the context of molecular simulations.
Generative inverse design of Li–P–S solid-electrolyte candidates: MatterGen → self-consistent MLIP stability screen (S.U.N.) → conductivity ranking. Concept validation.
A lightweight agent-callable workflow prototype for AI4Materials simulation analysis.
This is the GitHub repo to support the manuscript "Machine Learning Approaches for Developing Potential Surfaces: Applications to OH−(H2O)n (n = 1 − 3) Complexes"
Code for term project of Molecular Data Science & Informatics (CH5650) course taken at IIT Madras during Jan-May 2022
Companion data and code for Tatsumi et al., "Comparison of Elastic Constants and Surface Energies of β-Sn from Density Functional Theory, Universal Machine Learning Potential, and Empirical Potentials" (Modell. Simul. Mater. Sci. Eng., in review) — OpenMX DFT, PFP v8/Matlantis, and MEAM/LAMMPS inputs, outputs, and analysis scripts.
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