multiscale-materials-modelling-marketplace

Atomistic structure manipulation, file-format conversion, supercells, surfaces, and geometry optimization with ASE

Read and write LAMMPS data and dump files, with LAMMPS/GSD interconversion

Write and debug packmol input files to build initial configurations for MD simulations

Generate atomistic and coarse-grained polymer systems and LAMMPS data files from SMILES

Write, review, and debug LAMMPS input scripts with physics-aware validation

Biomolecular MD setup, execution, and analysis with GROMACS

Molecular HF, DFT, and MP2 calculations in Python with PySCF

Generate, validate, and debug CP2K input files for periodic DFT, AIMD, and geometry optimization

Run pretrained MACE-MP machine-learning potentials for energies, forces, and geometry optimization

Crystal structures, materials file-format conversion, and phase diagrams with pymatgen

Query the Materials Project database for crystal structures and material properties

SMILES/SDF parsing, molecular descriptors, fingerprints, and substructure search with RDKit

Analyze MD trajectories: RDF, MSD, order parameters, structure factor, PMFT, Voronoi, and clustering

Low-level matplotlib plotting and figure customization

Statistical visualizations from pandas DataFrames with seaborn

SHAP values and explanation plots for model feature-importance analysis

Classification, regression, clustering, dimensionality reduction, and pipelines with scikit-learn

Nonlinear dimensionality reduction and embedding visualization with UMAP

Render publication-quality molecular snapshots and animations from simulation trajectories with OVITO

Publication-quality matplotlib figures with APS, Nature, Science, and IEEE journal styling

Bayesian optimization for expensive material and molecular properties using Ax and BoTorch

Create, edit, evaluate, and benchmark Claude Code skills