a5c-ai/nanoimprint-process-controller
library/specializations/domains/science/nanotechnology/skills/nanoimprint-process-controller/SKILL.md
Nanoimprint Lithography skill for high-throughput nanopatterning with template management and demolding optimization
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter nanoimprint-process-controllerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 2, 2026, 7:46 AM57.8s1 file scanned
SKILL.md
- name:
- nanoimprint-process-controller
- description:
- Nanoimprint Lithography skill for high-throughput nanopatterning with template management and demolding optimization
- specialization:
- nanotechnology
- domain:
- science
- category:
- fabrication
- priority:
- medium
- phase:
- 6
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 (%)"
}
Related Skills
a5c-ai/model-card-generator
development
VerifiedTrustedCommunity
Model documentation skill for generating model cards following Google's model card framework.
680SKILL.mdUpdated Apr 28, 2026
a5c-ai/mlflow-experiment-tracker
development
VerifiedTrustedCommunity
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
680SKILL.mdUpdated Apr 28, 2026
a5c-ai/lime-explainer
data-ai
VerifiedTrustedCommunity
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
680SKILL.mdUpdated Apr 28, 2026
a5c-ai/kubeflow-pipeline-executor
devops
VerifiedTrustedCommunity
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.
680SKILL.mdUpdated Apr 28, 2026