| name | materials-screening |
| description | 材料科学筛选技能。用于固态电解质、催化剂等材料的候选筛选、
属性预测和多目标优化排序。触发词包括"材料筛选"、"materials screening"等。
|
| triggers | ["材料筛选","materials screening","固态电解质","solid electrolyte","材料发现","materials discovery"] |
| domain | materials_science |
| version | 1.0 |
Materials Screening Skill
Overview
AI-powered materials discovery workflow for screening candidate materials based on target properties and constraints.
Trigger Conditions
- User mentions materials screening, discovery
- Solid-state electrolyte research
- Catalyst design tasks
Workflow
Step 1: Define Objectives
Specify target properties and constraints:
- Ionic conductivity (max)
- Formation energy (min)
- Band gap (range)
- Stability threshold
Step 2: Search Candidates
Query materials databases:
- Materials Project
- AFLOW
- OQMD
Script: scripts/search_candidates.py
See: STRUCTURE_FAMILIES.md for common structure families
Step 3: Property Prediction
Use ML models for property prediction:
- GNN-based property prediction
- Formation energy estimation
- Stability assessment
Script: scripts/predict_properties.py
Step 4: Ranking & Selection
Multi-objective optimization:
- Pareto frontier analysis
- Weighted scoring
- Constraint filtering
Script: scripts/rank_materials.py
Output Format
{
"query": "solid electrolyte Li-ion",
"candidates": [
{
"formula": "Li7La3Zr2O12",
"structure_family": "garnet",
"predicted_conductivity": 1e-3,
"formation_energy": -3.2,
"stability": "stable",
"rank": 1
}
],
"total_screened": 1000,
"passed_constraints": 50
}