X-ray Diffraction (XRD): What It Is and How to Interpret a Pattern

X-ray diffraction (XRD) is an analytical technique that identifies crystalline phases in a solid sample by measuring how X-rays scatter from its atomic planes. It works best on powdered, crystalline, or polycrystalline materials; amorphous or very poorly ordered samples produce broad humps rather than sharp peaks, which limits phase identification. This guide explains the physical principle, how to read a pattern, and how to move from raw data to a phase assignment.

What XRD actually measures

When a monochromatic X-ray beam hits a crystalline sample, rays scattered by parallel atomic planes interfere. Constructive interference occurs only at specific angles, described by Bragg's law:

nλ = 2d sinθ

• λ — X-ray wavelength (fixed by the instrument, commonly Cu Kα at ~1.54 Å)
• d — spacing between the diffracting atomic planes
• θ — angle between the beam and the plane
• n — integer order of diffraction

The detector records intensity as a function of the angle 2θ (the angle between incident and diffracted beams). Each crystalline phase has a unique set of d-spacings, so it produces a unique set of peaks. That fingerprint is what makes phase identification possible.

How to read an XRD pattern

A typical pattern plots intensity (y-axis) against 2θ (x-axis). Four features carry most of the information:

Step 1 — Locate the peaks

Identify each peak's 2θ position, ideally after baseline correction. Convert positions to d-spacings using Bragg's law so you can compare against reference data regardless of the wavelength used.

Step 2 — Note relative intensities

Reference databases list peaks with relative intensities (often normalized to the strongest peak = 100). Compare the pattern of intensities, not just individual peaks — a single matching peak is not enough.

Step 3 — Match against reference phases

Search a database for phases whose peak positions and relative intensities fit your observed pattern. A match requires that all major observed peaks are accounted for, and that expected strong peaks are not missing.

Step 4 — Check for multiple phases

Real samples often contain several phases. After assigning the strongest pattern, subtract or mentally account for its peaks and look for remaining unexplained peaks, then repeat the match.

Common practical issues

• Background/baseline: Amorphous scattering, air scatter, and fluorescence raise the baseline. Baseline correction before peak picking improves position accuracy.
• Peak broadening: Small crystallites, microstrain, or instrumental effects widen peaks. Broadening complicates overlap between phases.
• Preferred orientation: Plate-like or needle-like crystals align during sample prep, distorting relative intensities so they no longer match a random-powder reference.
• Sample preparation: Poor packing, surface roughness, and particle size affect peak intensity and position reproducibility.
• Peak overlap: When two phases share similar d-spacings, peaks merge and require deconvolution or careful comparison.

How software and databases help

Manual matching becomes impractical with many peaks or multiple phases. Reference databases (such as RRUFF-style mineral collections) provide curated peak lists and d-spacings for comparison. Analysis platforms can assist with:

• Baseline correction to isolate real peaks from background
• Curve deconvolution to separate overlapping peaks
• Database matching to score candidate phases against the observed pattern
• AI phase unmixing to estimate phase mixtures in complex samples

The RDRS SpectraLib platform (rdrs.uaic.ro) is one example of a web tool that integrates spectral visualization, processing, and database matching across Raman, infrared, and XRD data — useful when you want to compare XRD results alongside complementary vibrational spectra.

A practical workflow

1. Collect the pattern with a known wavelength and record 2θ range.
2. Apply baseline correction and, if needed, smooth the data.
3. Pick peak positions and convert to d-spacings.
4. Search a reference database for candidate phases.
5. Verify that all major peaks are explained and relative intensities are consistent.
6. If peaks remain unexplained, test additional phases and consider deconvolution.
7. Report phases with the caveats (preferred orientation, amorphous content, detection limits).

The key decision point is whether your pattern has sharp, well-separated peaks (straightforward identification) or broad, overlapping features (requires deconvolution and careful database work). Matching peak positions alone is rarely sufficient — relative intensities and completeness of the match determine whether a phase assignment is reliable.