DSA Process Controller

SkillDev tools

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

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.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the DSA Process Controller skill

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: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: dsa-process-controller
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter