Agent skill
tem-image-analyzer
Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer
Metadata
Additional technical details for this skill
- phase
- 6
- domain
- science
- category
- microscopy-characterization
- priority
- high
- specialization
- nanotechnology
- tools libraries
-
[ "ImageJ/Fiji", "Gatan DigitalMicrograph", "JEMS", "CryoSPARC" ]
SKILL.md
TEM Image Analyzer
Purpose
The TEM Image Analyzer skill provides comprehensive analysis of transmission electron microscopy data for nanomaterial characterization, enabling automated particle detection, size distribution analysis, and crystallographic structure determination.
Capabilities
- Automated particle detection and sizing
- Morphology classification
- Lattice fringe analysis
- Selected area electron diffraction (SAED) indexing
- High-resolution TEM (HRTEM) analysis
- STEM-HAADF imaging
Usage Guidelines
Image Analysis Workflow
-
Particle Detection
- Apply appropriate thresholding
- Use watershed for touching particles
- Count minimum 200 particles for statistics
-
Size Measurement
- Calibrate pixel size from scale bar
- Measure Feret diameter or equivalent circular diameter
- Report mean, standard deviation, distribution
-
Crystallographic Analysis
- Index SAED patterns to phase
- Measure d-spacings from lattice fringes
- Identify zone axis from HRTEM
Process Integration
- Multi-Modal Nanomaterial Characterization Pipeline
- Statistical Particle Size Distribution Analysis
- In-Situ Characterization Experiment Design
Input Schema
{
"image_path": "string",
"analysis_type": "sizing|morphology|crystallography",
"scale_bar": {"length": "number", "pixels": "number"},
"expected_material": "string (for indexing)"
}
Output Schema
{
"particle_statistics": {
"count": "number",
"mean_size": "number (nm)",
"std_dev": "number (nm)",
"size_distribution": {"bins": [], "counts": []}
},
"morphology": {
"shapes": [{"type": "string", "fraction": "number"}],
"aspect_ratio": "number"
},
"crystallography": {
"phase": "string",
"d_spacings": ["number (nm)"],
"zone_axis": "string"
}
}
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