dsa-process-controller

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Directed Self-Assembly skill for block copolymer lithography and nanoparticle templating

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# DSA Process Controller ## Purpose The DSA Process Controller skill provides directed self-assembly process control for block copolymer lithography and nanoparticle templating, enabling sub-lithographic patterning through controlled polymer phase separation. ## Capabilities - Block copolymer selection and design - Annealing protocol optimization - Defect density analysis - Pattern transfer protocols - Graphoepitaxy and chemoepitaxy - Long-range order characterization ## Usage Guidelines ### DSA Process Control 1. **BCP Selection** - Match pitch to target - Consider chi-N product - Select morphology (lamellar, cylindrical) 2. **Annealing Optimization** - Choose thermal vs solvent vapor - Optimize temperature/time - Achieve equilibrium morphology 3. **Defect Analysis** - Classify defect types - Quantify defect density - Identify root causes ## Process Integration - Directed Self-Assembly Process Development - Nanolithography Process Development ## Input Schema ```json { "bcp_system": "string (e.g., PS-b-PMMA)", "target_pitch": "number (nm)", "morphology": "lamellar|cylindrical|spherical", "guiding_type": "graphoepitaxy|chemoepitaxy", "substrate_pattern": "string" } ``` ## Output Schema ```json { "annealing_protocol": { "method": "thermal|svA", "temperature": "number (C)", "time": "number (hours)", "solvent": "string (optional)" }, "achieved_pitch": "number (nm)", "defect_density": "number (defects/um2)...

Details

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

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