nanosensor-calibration-manager

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Nanosensor characterization skill for calibration, sensitivity analysis, and selectivity validation

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# 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 ```json { "sensor_id": "string", "analyte": "string", "concentration_range": {"min": "number", "max": "number", "unit": "string"}, "interferents": ["string"], "matrix": "buffer|serum|environmental" } ``` ## Output Schema ```json { "calibration": { "equation": "string", "r_squared": "number", "linear_range": {"min": "number", "max": "number"} }, "performance": { "lod": "number", "loq": "number", "sensitivity": "number", "response_time": "number...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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