mat-amorphization

Generate amorphous atomic structures via melt-quench molecular dynamics from crystalline inputs.

144|21|Updated Jan 8, 2026

Search Tags:#molecular dynamics #materials modeling #MLIP #amorphization #melt-quench #RDF analysis #coordination number

Ready to run

npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-amorphization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mat-amorphization
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/mat-amorphization
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-amorphization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, matplotlib, ase, pymatgen, and includes scripts (resource) components.

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.

Frequently Asked Questions about mat-amorphization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate amorphous structures from a crystalline input using melt-quench molecular dynamics?▼

Generate amorphous structures by applying a melt-quench molecular dynamics workflow that heats crystalline inputs above a melting threshold, rapidly cools them to a target temperature, and equilibrates the final disordered configuration.

What is the best way to verify the amorphous character of a glassy structure after quenching?▼

Verify amorphous character by performing radial distribution function (RDF) and coordination-number analysis on the final structure to confirm the loss of long-range order and validate the disordered atomic configuration.

Do I need a large supercell to prepare disordered glassy states for materials modeling?▼

Yes, preparing a sufficiently large conventional supercell is required to reduce spurious periodicity and support the behavior of a bulk amorphous phase containing over one hundred atoms.

Can I use ASE and pymatgen structures for molecular dynamics amorphization?▼

Yes, the melt-quench amorphization workflow supports atomistic materials research by utilizing numpy, matplotlib, ase, and pymatgen dependencies to process crystalline structures and generate disordered configurations.

Why does my melt-quench protocol produce structures with spurious periodicity?▼

Spurious periodicity occurs when the initial crystalline supercell is too small, which is why building a sufficiently large conventional supercell is necessary to achieve realistic amorphous behavior.

When do I need to use a melt-quench workflow for molecular dynamics simulations?▼

Use a melt-quench workflow when you need to produce realistic disordered atomic configurations from crystalline starting points for downstream property calculations, benchmarking, or model validation in atomistic materials research.