Babysitter ebl-process-controller

Electron Beam Lithography skill for high-resolution nanopatterning with dose optimization and proximity effect correction

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 "$T/library/specializations/domains/science/nanotechnology/skills/ebl-process-controller" ~/.claude/skills/a5c-ai-babysitter-ebl-process-controller && rm -rf "$T"
manifest: library/specializations/domains/science/nanotechnology/skills/ebl-process-controller/SKILL.md
source content

EBL Process Controller

Purpose

The EBL Process Controller skill provides comprehensive electron beam lithography process control, enabling high-resolution nanopatterning through dose optimization, proximity effect correction, and critical dimension control.

Capabilities

  • Pattern design and fracturing
  • Dose optimization and modulation
  • Proximity effect correction (PEC)
  • Alignment and overlay control
  • Resist processing optimization
  • Critical dimension (CD) control

Usage Guidelines

EBL Process Control

  1. Pattern Preparation

    • Design in CAD software
    • Fracture into write fields
    • Apply beam step size
  2. Dose Optimization

    • Run dose matrices
    • Apply PEC algorithms
    • Account for pattern density
  3. Process Integration

    • Optimize resist thickness
    • Control development conditions
    • Verify feature dimensions

Process Integration

  • Nanolithography Process Development
  • Nanodevice Integration Process Flow

Input Schema

{
  "pattern_file": "string",
  "resist": "string",
  "thickness": "number (nm)",
  "target_cd": "number (nm)",
  "beam_voltage": "number (kV)",
  "beam_current": "number (pA)"
}

Output Schema

{
  "optimized_dose": "number (uC/cm2)",
  "pec_parameters": {
    "alpha": "number",
    "beta": "number",
    "eta": "number"
  },
  "write_time": "number (hours)",
  "expected_cd": "number (nm)",
  "cd_uniformity": "number (3sigma)"
}