mat-md-probability-density
OfficialTurn MD diffusion into a CHGCAR map
Education & Research#molecular dynamics#materials simulation#ionic diffusion#probability density#CHGCAR#VESTA#solid-state electrolytes
Authorlearningmatter-mit
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It calculates and visualizes the spatial probability density of mobile ions from a molecular dynamics trajectory so you can identify likely conduction pathways and preferred ion sites in a crystal.
Core Features & Use Cases
- Probability density from MD trajectories: Converts time-sampled fractional coordinates of a chosen species into a volumetric grid suitable for CHGCAR output.
- Smoothing and optional log compression: Applies Gaussian smoothing to make sparse hopping visually coherent, and supports logarithmic compression to better reveal continuous diffusion paths from short trajectories.
- VESTA-ready visualization: Produces CHGCAR data that can be opened directly in VESTA for isosurface-based pathway visualization.
Quick Start
Run the probability-density calculation for your MD trajectory using the base-agent environment to generate a CHGCAR that you can open in VESTA.
Dependency Matrix
Required Modules
asenumpypymatgenscipy
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mat-md-probability-density Download link: https://github.com/learningmatter-mit/AtomisticSkills/archive/main.zip#mat-md-probability-density Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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