AMORPH: A statistical program for characterizing amorphous materials by X-ray diffraction

TL;DR

AMORPH introduces a Bayesian statistical method for analyzing X-ray diffraction data, enabling accurate quantification and characterization of amorphous and crystalline components in materials, with reduced user bias.

Contribution

It presents a novel Bayesian approach for interpreting X-ray diffraction patterns that simultaneously infers parameters and quantifies uncertainties, improving reproducibility and analysis of amorphous materials.

Findings

Effective quantification of amorphous content in volcanic samples

Simultaneous inference of crystalline and amorphous properties

Reduced user bias in X-ray diffraction analysis

Abstract

AMORPH utilizes a new Bayesian statistical approach to interpreting X-ray diffraction results of samples with both crystalline and amorphous components. AMORPH fits X-ray diffraction patterns with a mixture of narrow and wide components, simultaneously inferring all of the model parameters and quantifying their uncertainties. The program simulates background patterns previously applied manually, providing reproducible results, and significantly reducing inter- and intra-user biases. This approach allows for the quantification of amorphous and crystalline materials and for the characterization of the amorphous component, including properties such as the centre of mass, width, skewness, and nongaussianity of the amorphous component. Results demonstrate the applicability of this program for calculating amorphous contents of volcanic materials and independently modeling their properties in compositionally variable materials.