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Tem image analyzer

Skill a5c-ai/babysitter/library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer

Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessmentFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill tem-image-analyzer

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SKILL.md

2.5 KB, 438 tokens by cl100k_base, as published. Nobody here has run it

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

  1. Particle Detection

    • Apply appropriate thresholding
    • Use watershed for touching particles
    • Count minimum 200 particles for statistics
  2. Size Measurement

    • Calibrate pixel size from scale bar
    • Measure Feret diameter or equivalent circular diameter
    • Report mean, standard deviation, distribution
  3. 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"
  }
}

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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