Create, transform, and analyze crystalline structures with pymatgen.
npx skills add https://github.com/ovachiever/droid-tings --skill pymatgen-ovachiever
Please help me install this Agent Skill. Skill: pymatgen Source: https://github.com/ovachiever/droid-tings/tree/main/skills/pymatgen Command: npx skills add https://github.com/ovachiever/droid-tings --skill pymatgen-ovachiever
Pymatgen is a comprehensive materials-analysis library for creating, transforming, and analyzing crystal structures, files formats, and materials data, enabling streamlined materials research workflows.
Basic structure creation and CIF/POSCAR I/O in minutes.
High-intent search queries and answers about installing and using this skill.
Pymatgen automatically detects and converts between 100+ structure formats including CIF, POSCAR, and XYZ. Load a structure with `Structure.from_file()`, then save it in your target format using `.to()` method, enabling seamless format interoperability for materials workflows.
Yes. Pymatgen provides symmetry analysis tools and local environment analyzers that identify coordination polyhedra, nearest neighbors, and symmetry operations within crystal structures, supporting detailed structural characterization and high-throughput screening.
Pymatgen includes phase diagram and Pourbaix diagram generators that consume thermodynamic data to construct equilibrium diagrams. Integrate with Materials Project data for pre-computed entries, enabling rapid thermodynamic analysis without manual calculations.
Pymatgen's surface generation tools create slabs and interfaces from bulk structures by specifying Miller indices and vacuum thickness. These generated surfaces support catalysis, adsorption, and interface studies in computational materials research.
Yes. Pymatgen integrates directly with the Materials Project API, allowing you to query and retrieve pre-computed structure, thermodynamic, and property data, then manipulate it locally for batch analysis and high-throughput pipelines.
Pymatgen is fully scriptable and designed for batch workflows. Load multiple structure files, apply transformations, compute properties, and export results programmatically, enabling integration into high-throughput computational pipelines and automation.
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