mat-synthesis-recommendation

Query and rank Materials Project synthesis recipes for target inorganic formulas.

144|21|Updated Jan 8, 2026
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-synthesis-recommendation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mat-synthesis-recommendation
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/mat-synthesis-recommendation
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill mat-synthesis-recommendation

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps researchers and engineers find experimentally validated synthesis routes for a target inorganic material by turning text-mined literature records into ranked, actionable recipe candidates.

Core Features & Use Cases

  • Recipe discovery via Materials Project API: Searches the Materials Project synthesis database for recipes matching a target formula.
  • Practical ranking heuristics: Orders results by fewer precursors (simplicity), lower synthesis temperatures (ease), and preference for common synthesis types.
  • Experiment-oriented outputs: Returns precursors, step-by-step procedures, reaction equations (when available), and DOI links to the source papers.
  • Use case: Given a target cathode or ceramic composition (e.g., LiCoO2), quickly shortlist low-precursor, lower-temperature routes to guide lab planning and procurement.

Quick Start

Run the skill to retrieve up to 10 ranked synthesis recipes for LiFePO4 using the Materials Project API and output them to a JSON file named synthesis_recipes.json.

Frequently Asked Questions about mat-synthesis-recommendation

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

FAQPage Schema
How do I find experimentally validated synthesis routes for an inorganic material from literature?

Find experimentally validated synthesis routes by querying the Materials Project text-mined synthesis database for a target inorganic formula. The Skill searches literature records and returns ranked recipe candidates with precursors, procedures, reaction equations, and DOI references.

How are synthesis recipes ranked when searching for precursor selection and reaction procedures?

Synthesis recipes are ranked using practical heuristics that prioritize fewer precursors for simplicity, lower synthesis temperatures for ease, and common synthesis types. This ordering helps researchers quickly shortlist low-precursor, lower-temperature routes to guide lab planning.

Do I need an MP_API_KEY to retrieve Materials Project synthesis recipes?

Yes, you need an MP_API_KEY configuration to access the Materials Project API. The Skill queries this API to retrieve text-mined synthesis recipes, requiring the key for authentication before returning ranked recipe candidates.

Can I use this for planning battery cathode and ceramic fabrication steps?

Yes, you can use it for planning material fabrication steps in battery cathodes, ceramics, and other inorganic systems. Given a target composition like LiCoO2 or LiFePO4, it shortlists candidate precursors and procedures sourced from literature.

What synthesis recipe information is included in the JSON output?

The JSON output includes up to 10 ranked synthesis recipes containing precursors, step-by-step procedures, reaction equations when available, and DOI links to source papers. This experiment-oriented output provides actionable recipe candidates for lab planning and procurement.

What are the limitations of using text-mined literature records for synthesis planning?

Text-mined literature records depend on the availability and accuracy of the Materials Project synthesis database. Filtering on synthesis type and temperature is limited when such data is unavailable in the source papers, which may affect ranking precision for certain inorganic formulas.