ebl-process-controller
Electron Beam Lithography skill for high-resolution nanopatterning with dose optimization and proximity effect correction
ソース情報
- リポジトリ
- a5c-ai/babysitter
- ソースの最終更新活動
- 2026年6月1日 07:46
- 検出された SKILL.md の言語
- 英語
- スター
- 1,813
- フォーク
- 111
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SKILL.md
ソースの指示 · 読み取り専用プレビュー- name
- ebl-process-controller
- description
- Electron Beam Lithography skill for high-resolution nanopatterning with dose optimization and proximity effect correction
- allowed-tools
- ["Read","Write","Glob","Grep","Bash"]
- metadata
- {"specialization":"nanotechnology","domain":"science","category":"fabrication","priority":"high","phase":6,"tools-libraries":["BEAMER","GenISys TRACER","Raith NanoSuite"]}
- graph
- {"domains":["domain:nanotechnology"],"skillAreas":["skill-area:mathematical-reasoning","skill-area:physics-simulation","skill-area:data-analysis"],"workflows":["workflow:experiment-design"],"roles":["role:research-engineer"]}
# 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
```json
{
"pattern_file": "string",
"resist": "string",
"thickness": "number (nm)",
"target_cd": "number (nm)",
"beam_voltage": "number (kV)",
"beam_current": "number (pA)"
}
```
## Output Schema
```json
{
"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)"
}
```
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