TEM Image Analyzer
SkillMediaTransmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the TEM Image Analyzer skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer/SKILL.md and read by ahel’s review.
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"
}
}
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
tem-image-analyzer- Source
- github.com/a5c-ai/babysitter