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ALD Process Controller

Atomic Layer Deposition skill for conformal thin film deposition with atomic-level thickness control

Installable skillMITBy a5c-aiUpdated Oct 30, 2026
INTENDED FORClaude CodeCodexOpenClawCursorInstall in a listed agent.

instructions.md

---
name: ald-process-controller-d110b01872f4
description: Atomic Layer Deposition skill for conformal thin film deposition with atomic-level thickness control
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Bash
metadata:
  specialization: nanotechnology
  domain: science
  category: fabrication
  priority: high
  phase: 6
  tools-libraries:
    - ALD process simulators
    - Quartz crystal microbalance analysis
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]
---

# ALD Process Controller

## Purpose

The ALD Process Controller skill provides comprehensive atomic layer deposition process control, enabling conformal thin film growth with atomic-level precision through optimized pulse sequences and in-situ monitoring.

## Capabilities

- Precursor pulse/purge optimization
- Growth per cycle (GPC) characterization
- Film uniformity mapping
- Conformality assessment
- In-situ monitoring integration
- Multi-component film design

## Usage Guidelines

### ALD Process Control

1. **Saturation Studies**
   - Vary pulse times
   - Identify saturation dose
   - Optimize purge times

2. **Process Window**
   - Determine ALD window
   - Optimize temperature
   - Monitor GPC stability

3. **Film Quality**
   - Characterize uniformity
   - Measure conformality
   - Assess impurity levels

## Process Integration

- Thin Film Deposition Process Optimization
- Nanodevice Integration Process Flow

## Input Schema

```json
{
  "material": "string",
  "precursor_a": "string",
  "precursor_b": "string",
  "target_thickness": "number (nm)",
  "substrate": "string",
  "temperature": "number (C)"
}
```

## Output Schema

```json
{
  "optimized_recipe": {
    "precursor_a_pulse": "number (s)",
    "purge_a": "number (s)",
    "precursor_b_pulse": "number (s)",
    "purge_b": "number (s)"
  },
  "gpc": "number (Angstrom/cycle)",
  "cycles_required": "number",
  "uniformity": "number (%)",
  "conformality": "number (% step coverage)"
}
```

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Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.