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saxs-waxs-analyzer

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Small/Wide Angle X-ray Scattering skill for nanostructure size, shape, and organization analysis

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How to use this skill

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  2. Copy the prompt below and paste it into your agent.
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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/domains/science/nanotechnology/skills/saxs-waxs-analyzer/SKILL.md

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

SAXS-WAXS Analyzer

Purpose

The SAXS-WAXS Analyzer skill provides structural characterization of nanomaterials through small and wide angle X-ray scattering, enabling determination of size, shape, and spatial organization at the nanoscale.

Capabilities

  • SAXS data reduction and analysis
  • Form factor fitting
  • Guinier and Kratky analysis
  • Pair distance distribution function
  • WAXS crystallinity assessment
  • Self-assembly structure determination

Usage Guidelines

SAXS Analysis

  1. Data Reduction

    • Subtract background
    • Apply transmission correction
    • Merge multiple detector regions

  2. Form Factor Analysis

    • Fit to sphere, cylinder, or other models
    • Extract size distribution
    • Determine shape parameters

  3. Structural Analysis

    • Calculate P(r) function
    • Determine Rg from Guinier
    • Assess folding from Kratky

Process Integration

  • Statistical Particle Size Distribution Analysis
  • Directed Self-Assembly Process Development
  • Structure-Property Correlation Analysis

Input Schema

{
  "data_file": "string",
  "technique": "saxs|waxs|combined",
  "analysis_type": "guinier|form_factor|pdf",
  "expected_shape": "sphere|cylinder|disk|ellipsoid"
}

Output Schema

{
  "guinier": {
    "Rg": "number (nm)",
    "I0": "number",
    "qRg_range": "string"
  },
  "form_factor": {
    "model": "string",
    "radius": "number (nm)",
    "polydispersity": "number",
    "chi_squared": "number"
  },
  "pdf": {
    "Dmax": "number (nm)",
    "p_r_function": {"r": [], "p": []}
  }
}