mat-amorphization

What problem does it solve?

Producing realistic amorphous (disordered) atomic structures from crystalline starting points without manually tuning many simulation details.

Core Features & Use Cases

• Melt-quench MD protocol: Generates disorder by heating above a melting threshold and rapidly cooling to a target temperature.
• Multi-stage validation: Verifies amorphous character using RDF (radial distribution function) and coordination-number analysis.
• Supercell preparation: Builds sufficiently large conventional supercells to reduce spurious periodicity and support >~100-atom amorphous behavior.
• Common research use case: Preparing amorphous inputs for studying structure–property relationships in disordered materials (e.g., disordered phases, glassy states).

Quick Start

Ask the AI to amorphize your input crystal by running a melt to 3000 K, quenching to 300 K, equilibrating, and then producing RDF/coordination plots from the final amorphous structure.