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SkillsMP hat 21 Skills aus WuGroup-XJTLU/cc-skills-ZhenghaoWu-Group gesammelt. Öffne einen Skill, um Quelle und Details zu prüfen.
Es werden 21 von 21 gesammelten Skills angezeigt.
Use when manipulating atomistic structures, converting between file formats (CIF, POSCAR, XYZ, LAMMPS data), building supercells and surfaces, or running small geometry optimizations with ASE-supported calculators.
Quellsprache: Englisch
Use when optimizing material compositions, polymer sequences, molecular structures, or any expensive-to-evaluate property where each evaluation requires simulation or experiment. Also use when the user mentions Bayesian optimization for materials, black-box…
Quellsprache: Englisch
Use when writing, reviewing, or debugging CP2K input files, choosing DFT methods (GPW, GAPW, functionals, basis sets), setting up calculations (geometry optimization, AIMD, cell optimization, NEB, single-point energy), validating parameters (cutoff, SCF…
Quellsprache: Englisch
Use when code imports `freud` or `freud-analysis`, or user asks to analyze molecular simulation trajectories (RDF, MSD, order parameters, structure factor, PMFT, Voronoi, clustering). Also use when reading LAMMPS dump/data files for freud analysis via…
Quellsprache: Englisch
Use when setting up and running biomolecular MD simulations with GROMACS. Generate topologies, write MDP input files, execute simulations, and perform basic analysis.
Quellsprache: Englisch
Use when writing, reviewing, or debugging LAMMPS input scripts, choosing simulation methods (deformation, equilibration, transport), validating physics parameters (timestep, thermostat, units), or encountering LAMMPS runtime errors (lost atoms, DOF conflicts,…
Quellsprache: Englisch
Use when importing `lammpsio`, reading/writing LAMMPS data/dump files, or converting between LAMMPS and GSD formats.
Quellsprache: Englisch
Use when running machine-learning potential calculations with MACE. Load pretrained MACE-MP models, compute energies and forces, and run geometry optimizations on atomistic structures.
Quellsprache: Englisch
Use when querying the Materials Project database for crystal structures, material properties, or generating phase diagrams. Requires the MP_API_KEY environment variable to be set.
Quellsprache: Englisch
Use when creating matplotlib plots from scratch, customizing plot elements at a low level, or building novel visualization types that seaborn does not support.
Quellsprache: Englisch
Use when code imports `ovito`, or user asks to render molecular snapshots / animations from LAMMPS, XYZ, GSD, PDB, CIF or POSCAR files. Covers headless rendering (Tachyon/OSPRay), coloring, PBC handling, bonds, camera setup, and publication-ready output.
Quellsprache: Englisch
Use when writing, reviewing, debugging, or explaining packmol input files and packing strategies for molecular dynamics simulations.
Quellsprache: Englisch
Use when creating polymer systems, generating LAMMPS data files from SMILES, building atomistic or coarse-grained bead-spring models, setting up polymer simulations (homopolymer, copolymer, ring polymer, polymer solutions), or when user mentions AutoPoly,…
Quellsprache: Englisch
Use when working with crystal structures in Python, converting materials file formats (CIF, POSCAR, XYZ), querying the Materials Project database, or computing phase diagrams and electronic structure properties.
Quellsprache: Englisch
Use when running molecular quantum chemistry calculations in Python. Computes single-point energies, optimized geometries, vibrational frequencies, and population analysis using HF, DFT, or MP2 methods.
Quellsprache: Englisch
Use when parsing SMILES/SDF files, calculating molecular descriptors or fingerprints, performing substructure searches with SMARTS, or generating 2D/3D coordinates in Python.
Quellsprache: Englisch
Use when creating publication-quality matplotlib figures in Python — scientific line plots, scatter, error bars, heatmaps, contour, bar, histogram, 3D, multi-panel, log-scale, twin/inset axes, and colorbars. Applies APS journal styling (Helvetica, 8pt, inward…
Quellsprache: Englisch
Use when training classification or regression models, performing clustering or dimensionality reduction, tuning hyperparameters, or building preprocessing pipelines in Python.
Quellsprache: Englisch
Use when creating statistical visualizations from pandas DataFrames, exploring distributions or categorical comparisons, or producing multi-panel relational plots with minimal code.
Quellsprache: Englisch
Use when computing SHAP values, generating explanation plots (waterfall, beeswarm, bar), or debugging feature importance for tree-based, neural-network, or linear models.
Quellsprache: Englisch
Use when reducing high-dimensional data to 2D/3D for visualization, preprocessing embeddings before clustering with HDBSCAN, or training parametric dimensionality-reduction models.
Quellsprache: Englisch