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mat-diffusion-analysis

Calculate ionic diffusion coefficients and activation energies from ASE .traj trajectories.

144|21|Updated Jan 8, 2026
Search Tags:#diffusion#pymatgen#materials science#molecular dynamics#activation energy#Arrhenius fit
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-diffusion-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mat-diffusion-analysis
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/mat-diffusion-analysis
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-diffusion-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

It calculates ionic diffusion coefficients and activation energies from atomistic molecular dynamics (MD) trajectories, turning raw trajectory data into temperature-dependent transport parameters.

Core Features & Use Cases

  • Diffusivity & MSD extraction: Computes mean square displacement (MSD) and diffusivity for a chosen atomic species from ASE .traj trajectories using pymatgen’s DiffusionAnalyzer.
  • Equilibration-aware analysis: Ignores an initial equilibration period (ignore_ps) so the fitted diffusive regime reflects long-time behavior.
  • Arrhenius activation-energy fitting: Combines per-temperature diffusivity results and performs a weighted Arrhenius fit to obtain activation energy and extrapolated room-temperature conductivity.
  • Deterministic, reproducible scripts: Provides ready-to-run Python scripts and standard output artifacts (plots and JSON results) for downstream reporting.

Quick Start

Run diffusion analysis on an MD trajectory by executing python .agents/skills/mat-diffusion-analysis/scripts/analyze_diffusion.py results/md_600K/trajectory.traj --species Li --temperature 600 --ignore_ps 5.0 --output_dir results/md_600K.

Frequently Asked Questions about mat-diffusion-analysis

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

FAQPage Schema
How do I calculate ionic diffusion coefficients from ASE trajectory files?▼

You can calculate ionic diffusion coefficients from ASE .traj files by computing mean square displacement (MSD) and diffusivity for a chosen atomic species using pymatgen's DiffusionAnalyzer.

How do I determine activation energy from molecular dynamics trajectories across multiple temperatures?▼

Activation energy is determined by combining per-temperature diffusivity results from MD trajectories and performing a weighted Arrhenius fit to obtain the energy barrier and extrapolated room-temperature conductivity.

How do I exclude equilibration time when computing mean square displacement from MD trajectories?▼

You can exclude initial equilibration time from MSD computation by specifying an ignore_ps parameter, ensuring the fitted diffusive regime reflects long-time behavior rather than transient dynamics.

Can I use pymatgen to analyze lithium diffusion in solid electrolytes from MD data?▼

Yes, pymatgen-based MSD and diffusivity computation applies to atomistic transport studies such as analyzing lithium diffusion in solid electrolytes and superionic conductors from MD trajectories.

What is the best way to fit Arrhenius trends from temperature-dependent diffusivity data?▼

The best way to fit Arrhenius trends is using a weighted activation-energy regression on per-temperature diffusivity results, which outputs JSON files and plots suitable for downstream reporting.

Does the diffusion analysis script automatically detect frame intervals from ASE trajectories?▼

The diffusion analysis script supports optional log-based frame interval detection when processing ASE .traj trajectories to compute accurate ionic diffusion coefficients.

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