Sustainability assessment skill for evaluating and designing environmentally friendly nanomaterial synthesis routes
Scanned 9/2/2026
Install to Claude Code
npx -y skills add a5c-ai/babysitter --skill green-synthesis-evaluator --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: green-synthesis-evaluator
description: Sustainability assessment skill for evaluating and designing environmentally friendly nanomaterial synthesis routes
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: nanotechnology
domain: science
category: synthesis-materials
priority: medium
phase: 6
tools-libraries:
- LCA tools
- Green chemistry databases
- Sustainability metrics calculators
graph:
domains: [domain:nanotechnology]
skillAreas: [skill-area:mathematical-reasoning, skill-area:physics-simulation, skill-area:data-analysis]
workflows: [workflow:experiment-design]
roles: [role:research-engineer]
---
# Green Synthesis Evaluator
## Purpose
The Green Synthesis Evaluator skill provides comprehensive sustainability assessment for nanomaterial synthesis routes, enabling design of environmentally friendly processes through green chemistry metrics and lifecycle analysis.
## Capabilities
- Green chemistry metrics calculation (E-factor, atom economy)
- Lifecycle assessment integration
- Bio-based precursor database
- Solvent sustainability scoring
- Energy consumption estimation
- Waste minimization strategies
## Usage Guidelines
### Sustainability Assessment
1. **Green Chemistry Metrics**
- E-factor = mass waste / mass product
- Atom economy = MW product / MW reactants x 100%
- Process mass intensity (PMI)
2. **Solvent Selection**
- Use GSK solvent selection guide
- Prefer water, ethanol, or bio-solvents
- Avoid chlorinated and aromatic solvents
3. **Energy Optimization**
- Minimize reaction temperatures
- Reduce processing times
- Consider microwave/ultrasonic assistance
## Process Integration
- Green Synthesis Route Development
- Nanoparticle Synthesis Protocol Development
## Input Schema
```json
{
"current_synthesis": {
"precursors": ["string"],
"solvents": ["string"],
"temperatures": ["number"],
"reagent_masses": ["number"]
},
"product_mass": "number (g)",
"product_type": "string"
}
```
## Output Schema
```json
{
"sustainability_metrics": {
"e_factor": "number",
"atom_economy": "number (%)",
"pmi": "number"
},
"solvent_score": "number (1-10)",
"green_alternatives": [{
"change": "string",
"improvement": "string",
"feasibility": "high|medium|low"
}],
"overall_rating": "string"
}
```
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