home / skills / a5c-ai / babysitter / xrd-crystallography-analyzer

This skill analyzes X-ray diffraction data to identify phases, estimate crystallite size, and refine structures for nanomaterial characterization.

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SKILL.md
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---
name: xrd-crystallography-analyzer
description: X-ray Diffraction skill for crystal structure, phase identification, and crystallite size analysis of nanomaterials
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Bash
metadata:
  specialization: nanotechnology
  domain: science
  category: spectroscopy
  priority: high
  phase: 6
  tools-libraries:
    - HighScore
    - JADE
    - GSAS-II
    - FullProf
    - PDFgui
---

# XRD Crystallography Analyzer

## Purpose

The XRD Crystallography Analyzer skill provides crystallographic characterization of nanomaterials through X-ray diffraction analysis, enabling phase identification, crystallite size determination, and structural refinement.

## Capabilities

- Phase identification and Rietveld refinement
- Crystallite size (Scherrer equation)
- Lattice parameter calculation
- Preferred orientation analysis
- In-situ XRD capabilities
- PDF (Pair Distribution Function) analysis

## Usage Guidelines

### XRD Analysis

1. **Phase Identification**
   - Match peaks to database entries
   - Identify multiple phases
   - Assess phase purity

2. **Crystallite Size**
   - Apply Scherrer equation: D = Kl/(B cos theta)
   - Account for instrumental broadening
   - Use Williamson-Hall for strain

3. **Structural Refinement**
   - Perform Rietveld refinement
   - Extract lattice parameters
   - Quantify phase fractions

## Process Integration

- Multi-Modal Nanomaterial Characterization Pipeline
- Structure-Property Correlation Analysis
- Nanoparticle Synthesis Protocol Development

## Input Schema

```json
{
  "diffraction_file": "string",
  "analysis_type": "phase_id|crystallite_size|refinement|pdf",
  "wavelength": "number (Angstrom)",
  "expected_phases": ["string"]
}
```

## Output Schema

```json
{
  "phases": [{
    "name": "string",
    "pdf_number": "string",
    "weight_fraction": "number"
  }],
  "crystallite_size": {
    "value": "number (nm)",
    "method": "string"
  },
  "lattice_parameters": {
    "a": "number",
    "b": "number",
    "c": "number",
    "space_group": "string"
  },
  "refinement_quality": {
    "Rwp": "number",
    "chi_squared": "number"
  }
}
```

Overview

This skill provides X-ray diffraction analysis for nanomaterials to identify phases, estimate crystallite sizes, and refine crystal structures. It delivers practical outputs such as phase lists, lattice parameters, crystallite size estimates, and refinement quality metrics. The focus is on fast, reproducible characterization for research and quality control workflows.

How this skill works

The skill ingests diffraction files and runs peak matching against databases to propose phase IDs and weight fractions. It computes crystallite size using the Scherrer equation and optional Williamson–Hall strain analysis, and performs Rietveld-style structural refinement to extract lattice parameters and refinement statistics. Outputs follow a clear schema so downstream pipelines can consume phases, sizes, lattice info, and fit quality metrics.

When to use it

  • Initial phase identification after synthesis or processing
  • Quantifying phase fractions in multiphase samples
  • Estimating average crystallite size for nanoparticles
  • Refining lattice parameters or checking structural models
  • Integrating XRD results into multimodal characterization pipelines

Best practices

  • Provide accurate wavelength and instrument broadening data to correct peak widths
  • Supply expected phases to guide matching and reduce false positives
  • Pre-process diffraction files to remove artifacts and background before analysis
  • Validate automated phase matches with expert inspection for unusual chemistries
  • Report refinement statistics (Rwp, chi_squared) and inspect difference plots for fit quality

Example use cases

  • Identify and quantify phases in a mixed-oxide nanoparticle sample
  • Estimate crystallite size changes across a thermal annealing series
  • Refine lattice parameters to detect dopant-induced lattice shifts
  • Combine XRD outputs with TEM and spectroscopy for structure–property studies
  • Run in-situ XRD analysis to monitor phase transitions during heating

FAQ

What input formats are supported?

Provide standard diffraction text files (2θ vs intensity). Ensure the file includes correct wavelength metadata when possible.

How is crystallite size calculated?

Primary method is the Scherrer equation with optional instrumental broadening correction. Williamson–Hall analysis is available to separate strain contributions.

How reliable are automated phase identifications?

Automated matching accelerates screening but should be confirmed for complex chemistries. Supplying expected phases improves accuracy.