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XRD Pattern Analysis

Overview

MatPilot provides a complete pipeline for analyzing powder X-ray diffraction patterns. The automated workflow processes raw detector data through background subtraction, Kα2 radiation stripping, and noise reduction to produce clean diffraction patterns ready for peak detection and phase identification.

Scientific Background

X-ray diffraction (XRD) is the primary technique for characterizing crystalline materials. When a monochromatic X-ray beam strikes a polycrystalline sample, the diffracted intensity as a function of 2θ angle reveals the crystal structure through Bragg's Law: nλ = 2d·sin(θ). The measured pattern contains contributions from the sample's crystal structure, instrumental broadening, and experimental noise that must be separated for accurate analysis.

Workflow

1

Upload your XRD data file (XRDML, RAW, XY, CSV, or other formats)

2

Automatic format detection and parsing extracts 2θ and intensity arrays

3

Background correction removes the diffuse scattering component using iterative polynomial fitting

4

Kα2 stripping eliminates the Kα2 wavelength contribution using the Rachinger algorithm

5

Noise reduction smooths the pattern while preserving peak shapes using Savitzky-Golay filtering

6

Peak detection identifies Bragg peaks using second-derivative methods with adaptive thresholds

Input Formats

Bruker RAW
PANalytical XRDML
XY (two-column)
CSV
DAT
TXT

Expected Outputs

Background-corrected diffraction pattern
Kα2-stripped intensity data
Smoothed pattern with preserved peak profiles
Detected peak positions (2θ), intensities, FWHM, and d-spacings
Interactive diffraction pattern chart

Benefits

Automated processing eliminates manual intervention
Multiple format support for universal compatibility
Publication-quality output suitable for journal submission
Interactive chart with zoom, pan, and high-resolution export
Reproducible results with documented processing parameters

Frequently Asked Questions

What file formats are supported?
MatPilot supports Bruker RAW (binary and text), PANalytical XRDML, XY two-column, CSV, DAT, and TXT formats. The parser automatically detects the format upon upload.
How does background correction work?
The algorithm uses an iterative polynomial fitting approach that progressively identifies and excludes peak regions, fitting the background to the remaining points until convergence is achieved.
Can I adjust processing parameters?
Yes, the pipeline allows customization of background polynomial degree, Kα2 stripping parameters, noise reduction window size, and peak detection sensitivity thresholds.
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