Agent skill

nanoimprint-process-controller

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

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/nanotechnology/skills/nanoimprint-process-controller

Metadata

Additional technical details for this skill

phase
6
domain
science
category
fabrication
priority
medium
specialization
nanotechnology
tools libraries
[
    "NIL process simulation",
    "Template design tools"
]

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

  1. Template Preparation

    • Design with demolding in mind
    • Apply anti-sticking treatment
    • Verify pattern fidelity
  2. Imprint Optimization

    • Optimize pressure and temperature
    • Control residual layer thickness
    • Minimize defects
  3. Yield Improvement

    • Track defect types
    • Optimize demolding conditions
    • Implement cleaning protocols

Process Integration

  • Nanolithography Process Development
  • Directed Self-Assembly Process Development

Input Schema

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

Output Schema

json
{
  "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 (%)"
}

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