Babysitter nanoimprint-process-controller

Nanoimprint Lithography skill for high-throughput nanopatterning with template management and demolding optimization

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/nanotechnology/skills/nanoimprint-process-controller" ~/.claude/skills/a5c-ai-babysitter-nanoimprint-process-controller && rm -rf "$T"

manifest: library/specializations/domains/science/nanotechnology/skills/nanoimprint-process-controller/SKILL.md

Nanoimprint Process Controller

Purpose

The Nanoimprint Process Controller skill provides comprehensive nanoimprint lithography process control, enabling high-throughput nanopatterning through template design, imprint optimization, and defect management.

Capabilities

Template design and fabrication
Imprint pressure and temperature optimization
UV-NIL and thermal NIL protocols
Demolding force analysis
Residual layer control
Defect inspection and yield analysis

Usage Guidelines

NIL Process Control

Template Preparation
- Design with demolding in mind
- Apply anti-sticking treatment
- Verify pattern fidelity
Imprint Optimization
- Optimize pressure and temperature
- Control residual layer thickness
- Minimize defects
Yield Improvement
- Track defect types
- Optimize demolding conditions
- Implement cleaning protocols

Process Integration

Nanolithography Process Development
Directed Self-Assembly Process Development

Input Schema

{
  "template_id": "string",
  "resist_type": "thermal|uv_curable",
  "target_features": {
    "min_cd": "number (nm)",
    "pitch": "number (nm)",
    "aspect_ratio": "number"
  },
  "substrate": "string"
}

Output Schema

{
  "process_parameters": {
    "temperature": "number (C)",
    "pressure": "number (bar)",
    "time": "number (s)",
    "uv_dose": "number (mJ/cm2)"
  },
  "residual_layer": "number (nm)",
  "demolding_force": "number (N)",
  "defect_density": "number (defects/cm2)",
  "yield": "number (%)"
}