nanoparticle-synthesis-optimizer

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Synthesis parameter optimization skill for metal, semiconductor, and oxide nanoparticle production with automated protocol generation and reproducibility validation

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# Nanoparticle Synthesis Optimizer ## Purpose The Nanoparticle Synthesis Optimizer skill provides systematic optimization of synthesis parameters for metal, semiconductor, and oxide nanoparticle production, enabling reproducible synthesis protocols with controlled size, morphology, and surface chemistry. ## Capabilities - Precursor stoichiometry calculation - Reaction temperature/time optimization - Surfactant and capping agent selection - Nucleation and growth kinetics modeling - Size distribution targeting - Batch reproducibility assessment ## Usage Guidelines ### Synthesis Parameter Optimization 1. **Precursor Selection** - Match precursor reactivity to desired kinetics - Consider thermal decomposition temperatures - Evaluate purity requirements 2. **Temperature Programming** - Optimize nucleation temperature for burst nucleation - Control growth temperature for size focusing - Manage heating ramp rates 3. **Surfactant Systems** - Balance steric vs electrostatic stabilization - Consider binding affinity to specific facets - Optimize surfactant-to-precursor ratios ## Process Integration - Nanoparticle Synthesis Protocol Development - Nanomaterial Scale-Up and Process Transfer - Green Synthesis Route Development ## Input Schema ```json { "target_material": "string", "target_size": "number (nm)", "target_morphology": "sphere|rod|cube|plate", "size_tolerance": "number (%)", "synthesis_method": "thermal_decomposition|hot_injecti...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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