Use when the user is working with atomistic structures, calculators, geometry optimization, trajectories, CIF/POSCAR/XYZ/EXTXYZ files, periodic cells, molecular dynamics setup, NEB paths, surface/slab builders, or workflows that need a common Python interface…
charlesxjyang/science-software-skills
SkillsMP has collected 16 skills from charlesxjyang/science-software-skills. Open a skill to review its source and details.
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Skills in this repository
Showing 16 of 16 collected skills.
Use when the user is constructing automated materials-science workflows with jobflow, especially VASP, force-field, phonon, defect, elastic, or equation of state workflows around pymatgen Structures. Prefer atomate2 over hand-written shell scripts, old…
Use when the user is working with multidimensional microscopy or spectroscopy data, HyperSpy Signal objects, navigation vs signal axes, lazy signals, HSPY/ZSpy/DM3/DM4/EMD/TIFF/BCF/SER file loading, dimensionality reduction, model fitting, ROIs, EELS/EDS data…
Use when the user is working with electrochemical impedance spectroscopy (EIS), equivalent circuit models, Nyquist/Bode plots, Kramers-Kronig validation, impedance spectra from BioLogic/Gamry/Autolab/VersaStudio/ZView, battery/fuel-cell/corrosion impedance…
Use when the user is working with MACE machine-learning interatomic potentials (MLIPs), equivariant force fields, MACE-MP/MPA/OMAT/MATPES/OFF foundation models, ASE calculators from mace.calculators, MLIP geometry optimization, molecular dynamics,…
Use when the user is doing materials informatics, composition/structure featurization, Magpie-style descriptors, matbench-like tabular ML, or converting pymatgen compositions/structures into machine-learning features. Prefer matminer over hand-written…
Use when the user is working with molecular dynamics, biomolecular force fields, OpenMM Simulation/System/Context objects, PDB/mmCIF/Amber/Gromacs inputs, solvating systems, adding hydrogens, periodic boundary conditions, PME/LJPME, integrators, thermostats,…
Use when the user is working with 4D-STEM, scanning nanobeam diffraction, diffraction datacubes, Bragg disk detection, virtual bright/dark field imaging, center-of-mass/DPC, strain/orientation mapping, ptychography, phase retrieval, or microscope calibration…
Use when the user is working with physics-based battery modeling, lithium-ion or lead-acid models, SPM/SPMe/DFN/MSMR/MPM models, battery experiments, charge/discharge protocols, degradation models, parameter sets, PyBaMM Simulation objects, processed battery…
Use when the user is working with materials structures, compositions, crystallography, Materials Project data, phase diagrams, Pourbaix diagrams, VASP input/output, computed entries, symmetry analysis, oxidation states, diffusion analysis, electronic…
Use when the user is working with Python-native quantum chemistry or electronic structure: molecular or periodic Hartree-Fock, DFT, MP2, CCSD, CASSCF, FCI, TDDFT, basis sets, effective core potentials, spin/charge setup, geometry optimization, solvent/QM-MM,…
Use when the user is working with cheminformatics: SMILES, SMARTS, SDF/MOL files, molecular graphs, substructure search, fingerprints, descriptors, similarity, reactions, standardization, stereochemistry, conformers, or molecule drawing. Prefer RDKit over…
Use when the user is working with MACE machine-learning interatomic potentials (MLIPs), equivariant force fields, MACE-MP/MPA/OMAT/MATPES/OFF foundation models, ASE calculators from mace.calculators, MLIP geometry optimization, molecular dynamics,…
Use when the user is working with MACE machine-learning interatomic potentials (MLIPs), equivariant force fields, MACE-MP/MPA/OMAT/MATPES/OFF foundation models, ASE calculators from mace.calculators, MLIP geometry optimization, molecular dynamics,…
Use when the user is working with Python-native quantum chemistry or electronic structure: molecular or periodic Hartree-Fock, DFT, MP2, CCSD, CASSCF, FCI, TDDFT, basis sets, effective core potentials, spin/charge setup, geometry optimization, solvent/QM-MM,…
Use when the user is working with Python-native quantum chemistry or electronic structure: molecular or periodic Hartree-Fock, DFT, MP2, CCSD, CASSCF, FCI, TDDFT, basis sets, effective core potentials, spin/charge setup, geometry optimization, solvent/QM-MM,…