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name: nanosensor-calibration-manager description: Nanosensor characterization skill for calibration, sensitivity analysis, and selectivity validation allowed-tools:

• Read
• Write
• Glob
• Grep
• Bash metadata: specialization: nanotechnology domain: science category: applications priority: high phase: 6 tools-libraries:
  • Sensor calibration software
  • Data analysis tools 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]

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Nanosensor Calibration Manager

Purpose

The Nanosensor Calibration Manager skill provides comprehensive characterization of nanomaterial-based sensors, enabling systematic calibration, sensitivity optimization, and selectivity validation for analytical applications.

Capabilities

• Calibration curve generation
• Limit of detection (LOD) calculation
• Sensitivity and dynamic range analysis
• Selectivity and interference testing
• Response time characterization
• Long-term stability assessment

Usage Guidelines

Sensor Calibration

1. Calibration Curve

   • Prepare standard solutions
   • Measure sensor response
   • Fit calibration model

2. Performance Metrics

   • Calculate LOD (3 sigma method)
   • Determine linear range
   • Assess sensitivity (slope)

3. Selectivity Testing

   • Test interferents
   • Calculate selectivity coefficients
   • Validate in complex matrices

Process Integration

• Nanosensor Development and Validation Pipeline

Input Schema

{
  "sensor_id": "string",
  "analyte": "string",
  "concentration_range": {"min": "number", "max": "number", "unit": "string"},
  "interferents": ["string"],
  "matrix": "buffer|serum|environmental"
}

Output Schema

{
  "calibration": {
    "equation": "string",
    "r_squared": "number",
    "linear_range": {"min": "number", "max": "number"}
  },
  "performance": {
    "lod": "number",
    "loq": "number",
    "sensitivity": "number",
    "response_time": "number (seconds)"
  },
  "selectivity": [{
    "interferent": "string",
    "selectivity_coefficient": "number"
  }]
}