DSA Process Controller
SkillDev toolsDirected Self-Assembly skill for block copolymer lithography and nanoparticle templating
Use DSA Process Controller in Claude, ChatGPT or Ahel Desktop
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Then ask your AI: use the DSA Process Controller skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/dsa-process-controller/SKILL.md and read by Ahel’s review.
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
-
BCP Selection
- Match pitch to target
- Consider chi-N product
- Select morphology (lamellar, cylindrical)
-
Annealing Optimization
- Choose thermal vs solvent vapor
- Optimize temperature/time
- Achieve equilibrium morphology
-
Defect Analysis
- Classify defect types
- Quantify defect density
- Identify root causes
Process Integration
- Directed Self-Assembly Process Development
- Nanolithography Process Development
Input Schema
{
"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
{
"annealing_protocol": {
"method": "thermal|svA",
"temperature": "number (C)",
"time": "number (hours)",
"solvent": "string (optional)"
},
"achieved_pitch": "number (nm)",
"defect_density": "number (defects/um2)",
"correlation_length": "number (nm)",
"pattern_quality": "string"
}
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
dsa-process-controller- Source
- github.com/a5c-ai/babysitter