Agent skill

tem-image-analyzer

Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment

Stars 514
Forks 31

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

  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

json
{
  "image_path": "string",
  "analysis_type": "sizing|morphology|crystallography",
  "scale_bar": {"length": "number", "pixels": "number"},
  "expected_material": "string (for indexing)"
}

Output Schema

json
{
  "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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