materials-science
Analyzes material properties including crystal structures, phase diagrams, mechanical/thermal/electronic properties, and supports materials discovery through computational approaches; trigger when users discuss alloys, ceramics, polymers, nanomaterials, or materials characterization.
Best use case
materials-science is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyzes material properties including crystal structures, phase diagrams, mechanical/thermal/electronic properties, and supports materials discovery through computational approaches; trigger when users discuss alloys, ceramics, polymers, nanomaterials, or materials characterization.
Teams using materials-science should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/materials-science/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How materials-science Compares
| Feature / Agent | materials-science | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyzes material properties including crystal structures, phase diagrams, mechanical/thermal/electronic properties, and supports materials discovery through computational approaches; trigger when users discuss alloys, ceramics, polymers, nanomaterials, or materials characterization.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
## When to Trigger Activate this skill when the user mentions: - Crystal structures, lattice parameters, space groups, unit cells - Phase diagrams, phase transitions, thermodynamic stability - Mechanical properties (tensile strength, hardness, elastic modulus) - Electronic properties (band gap, conductivity, dielectric constant) - Materials characterization (XRD, SEM, TEM, AFM) - Nanomaterials, thin films, composites, polymers - Materials databases, high-throughput screening, materials informatics ## Step-by-Step Methodology 1. **Define the materials question** - Specify the material system (elements, compounds), property of interest, and application context (structural, electronic, optical, catalytic). 2. **Database search** - Query Materials Project, AFLOW, ICSD, or OQMD for known structures and computed properties. Check experimental databases (Springer Materials, NIST) for measured values. 3. **Structure analysis** - Identify crystal system, space group, and Wyckoff positions. Compute lattice parameters and density. For disordered systems, characterize using pair distribution functions or radial distribution functions. 4. **Property evaluation** - Retrieve or compute relevant properties: formation energy (thermodynamic stability), band structure (electronic), phonon dispersion (thermal), elastic tensor (mechanical). Compare with target specifications. 5. **Phase diagram analysis** - Construct or retrieve phase diagrams (binary, ternary). Identify stable phases, invariant reactions (eutectic, peritectic), and solid solutions. Use CALPHAD method for complex systems. 6. **Characterization guidance** - Recommend appropriate techniques: XRD for crystal structure, SEM/TEM for microstructure, XPS for surface chemistry, DSC for thermal transitions. Specify expected peaks/features. 7. **Design recommendations** - Suggest composition or processing modifications to achieve target properties. Consider trade-offs between competing properties (strength vs. ductility, conductivity vs. transparency). ## Key Databases and Tools - **Materials Project** - Computed materials properties (DFT) - **AFLOW** - Automatic FLOW for materials discovery - **ICSD** - Inorganic Crystal Structure Database - **NIST Materials Data** - Experimental property data - **Springer Materials** - Curated materials data - **Thermo-Calc / FactSage** - CALPHAD thermodynamic modeling ## Output Format - Crystal structures with space group, lattice parameters (in Angstroms), and atomic positions. - Properties in SI units with comparison to reference values. - Phase diagrams with labeled phases, invariant points, and temperature/composition axes. - Characterization predictions (expected XRD peaks with 2-theta and hkl, expected spectral features). ## Quality Checklist - [ ] Crystal structure validated against experimental data when available - [ ] Property values compared between computational and experimental sources - [ ] Temperature and pressure conditions specified for all properties - [ ] Appropriate computational method noted (DFT functional, basis set) - [ ] Phase diagram includes metastable phases if relevant - [ ] Synthesis feasibility and processing conditions considered - [ ] Units consistent and clearly stated throughout - [ ] Uncertainty or accuracy of computational predictions discussed
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