Computational Chemistry

OpenMM is a molecular simulation toolkit. Its official OpenMM-ML extension connects machine learning potentials to simulations.

Computational Chemistry

ASE is a Python atomistic simulation library connecting conventional codes and external machine learning potentials through a common calculator interface.

Computational Chemistry

SevenNet provides graph neural network interatomic potentials, pretrained models, fine-tuning interfaces and ASE/LAMMPS integration.

Computational Chemistry

MatGL is a materials graph learning library for developing and using property predictors and machine learning potentials.

Computational Chemistry · Materials Discovery

Rowan is a cloud platform for molecular calculations, combining quantum chemistry, machine-learned potentials, property prediction, and protein–ligand workflows through a web interface and Python API.

Computational Chemistry · Quantum Chemistry

A reactive-MD post-processing Skill that guides ReacNetGenerator tool selection, LAMMPS trajectory preparation, reaction-network generation and inspection of existing analysis outputs.

Computational Chemistry

An ASE routing Skill in the computational-chemistry-agent-skills collection that separates workflow preparation from calculator configuration and delegates execution elsewhere.

Computational Chemistry · Materials Discovery

Cantera Skill (K-Dense) provides instructions and a Python helper for homogeneous ignition calculations, with mechanism provenance, conservation diagnostics, and numerical refinement checks.

Computational Chemistry · Process Optimization

ChemAgent (AI4Chem) is a research framework for chemistry and materials tool use, linked to the CheMatAgent paper on tree-search planning, tool execution and ChemToolBench-based training.

Computational Chemistry · Materials Discovery

ChemAgent is a chemical-reasoning research framework that decomposes problems and retrieves reusable memories, with released code for constructing memory pools and running SciBench experiments.

Computational Chemistry

MDCrow is a Python LLM-agent toolset for molecular dynamics workflows, connecting natural-language requests to simulation setup, OpenMM execution, output analysis and scientific information retrieval.

Computational Chemistry

ChemGraph is a Python agent framework that connects natural-language chemistry requests to molecular construction, simulations, analysis, and reporting, with CLI, Python, Streamlit, and MCP interfaces.

Computational Chemistry · Materials Discovery

NovoMCP exposes computational chemistry tools through MCP and REST, combining molecular profiling with configurable simulation services, discovery-funnel orchestration, and tool-call auditing.

Computational Chemistry · Drug Discovery

molSimplify generates inorganic coordination and intermolecular complexes for computational screening, with bundled neural networks for selected properties of octahedral transition metal complexes.

Molecular Generation · Computational Chemistry

DP-GEN is a Python concurrent-learning platform that coordinates molecular simulation, first-principles calculations and DeePMD-kit workflows to generate interatomic potential models.

Computational Chemistry · Materials Discovery

M3GNet is an archived materials graph neural network implementation with three-body interactions, a pretrained interatomic potential, and workflows for crystal relaxation, molecular dynamics and model training.

Computational Chemistry · Materials Discovery

CHGNet is a pretrained, charge-informed neural network potential for crystal structures, predicting energies, forces, stresses and magnetic moments for relaxation and molecular dynamics workflows.

Computational Chemistry · Materials Discovery

GEOM provides 37 million energy- and statistical-weight-annotated molecular conformations for over 450,000 molecules, with MessagePack data, RDKit objects, and loading and analysis tutorials.

Molecular Generation · Computational Chemistry

GeoDiff is a geometric diffusion model for molecular conformation generation, with official code for GEOM-based training, checkpoint sampling, and conformation and property evaluation.

Molecular Generation · Computational Chemistry

GemNet is a PyTorch reference implementation of a geometric message-passing model for molecular energies and atomic forces, with notebooks for training, ASE-based prediction and molecular dynamics.

Molecular Property Prediction · Computational Chemistry