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mat-ionic-substitution

Predict charge-balanced ionic substitution candidates for crystal structures.

144|21|Updated Jan 8, 2026
Search Tags:#materials project#structure search#crystal structure#MLIP relaxation#ionic substitution#oxidation states
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-ionic-substitution
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mat-ionic-substitution
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/mat-ionic-substitution
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-ionic-substitution

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymatgen, mp-api, and includes scripts (resource) components.

What problem does it solve?

Ionic substitution proposes new crystal structures by swapping ions in charge-balanced ways, enabling discovery of candidate materials without running expensive searches from scratch.

Core Features & Use Cases

  • Forward mode (propose): Generate high-probability ion-substituted variants from an existing ordered structure (e.g., NaCoO2 → LiCoO2 and related candidates).
  • Reverse mode (find): Given a target composition, locate known precursor structures in Materials Project whose ion substitutions can produce the target (e.g., Li2ZrCl6 from Li2ZrF6-like families).
  • Actionable outputs: Writes substituted CIF files plus JSON manifests containing substitution maps and probabilities for downstream relaxation and stability ranking.

Quick Start

Run the reverse search for a target composition using the provided script with your MP_API_KEY set, then inspect structure_manifest.json to see which precursor substitutions generate the target candidates.

Frequently Asked Questions about mat-ionic-substitution

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

FAQPage Schema
How do I predict charge-balanced ionic substitution candidates for a crystal structure?▼

Ionic substitution candidates are predicted by mining substitution probabilities trained on inorganic crystal data. The Skill applies forward substitution proposals from an existing ordered structure to generate charge-balanced variants.

Can I find known precursor structures in Materials Project that substitute into a target composition?▼

Yes, reverse structure discovery mode locates known precursor structures in Materials Project whose ionic substitutions produce a target composition. Querying requires setting your MP_API_KEY to find matching charge-balanced candidates.

What input format is required for ionic substitution structure search?▼

Ionic substitution structure search requires oxidation-state-decorated crystal structures as input. Providing ordered structures with explicit oxidation states ensures generated substitutions remain charge-balanced during prediction.

How do I configure probability thresholds for ion-substituted crystal candidates?▼

Probability thresholds filter ion-substituted crystal candidates by their mined substitution likelihoods. Configuring these thresholds limits outputs to high-probability structural variants suitable for downstream screening workflows.

What outputs does the ionic substitution prediction generate for MLIP relaxation?▼

Ionic substitution prediction generates substituted CIF files and JSON manifests containing substitution maps and probabilities. These outputs are structured for direct use in subsequent MLIP relaxation and E_hull evaluation workflows.

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