Automated full-pattern-fitting of illite polytypes: Standardizing quantification and uncertainty for Illite Age Analysis
Year: 2026
Type: article
Abstract: Quantitative analysis of illite polytypes is essential for constraining the thermal and burial history of sedimentary rocks and dating fault slip events through Illite Age Analysis (IAA).However, traditional manual full-pattern fitting (FPF) of X-ray diffraction (XRD) data involves subjective interpretation, inconsistent reproducibility, and poor error quantification.To overcome these limitations, we developed a Pythonbased automated algorithm integrating synthetic reference patterns generated by WILDFIRE-© with systematic baseline correction, polytypespecific weighting, Monte Carlo regression, and uncertainty evaluation.The method excludes quartz interference and focuses on diagnostic illite reflections in the 22.5-26° and 27-32.5°2θ (Cu-Kα) ranges.Validation against expert-based FPF results from eight fault gouge samples (YC4, YC5-1, YC5-2, STB1-9, STB8-14, SNN-03, SNN-10) from major Korean fault zones yielded goodness-of-fit R values consistently below 10%.Both linear and asymmetric least squares baseline corrections effectively accommodate compositional variations.Monte Carlo error propagation provides realistic ±1σ uncertainties previously unavailable in manual analyses.Combined with published K-Ar illite ages, the automated FPF-IAA reproduces established age trends and fault reactivation episodes while greatly enhancing reproducibility and transparency.This framework offers a standardized and transparent alternative to proprietary tools, with representative input files, parameter settings, and outputs provided to support reproducibility, advancing clay mineral-based geochronology studies.
Source: Episodes
Authors: Ho Sim, Yungoo Song, Seung-Ik Park, Seongsik Hong
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7167020294
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