Work

Effect of data quality on results of Reverse Monte Carlo analysis of EXAFS data

Year: 2023

Type: article

Abstract: Reverse Monte Carlo (RMC) is a computational technique used to generate three-dimensional atomic structural models compatible with a given set of experimental data. RMC is applicable to X-ray absorption fine structure (XAFS) data, which generally show different energy ranges and noise levels depending on the experimental conditions. In this article, we explore the relationship between these effects and the precision of structural results obtained through RMC, by examining two simple molecular cases. In such specific cases (Br2 and BBr3) we have found that the XAFS data range has generally a limited influence on the structural results, except for signals on restricted wave-vector ranges (kmax<8A−1). Different noise levels are shown to affect the precision of the structural results, depending also on how the noise is included in the RMC procedure. As an outcome of this study, we propose general guidelines for best practices in RMC XAFS data-analysis, aiming to improve the accuracy and reliability of atomic structure modeling.

Source: Radiation Physics and Chemistry

DOI: 10.1016/j.radphyschem.2023.111352

Authors: Fabio Iesari, Andrea Di Cicco, Toshihiro Okajima

Institutions: Aichi Synchrotron Radiation Center, Università di Camerino

Language: English

Topic: X-ray Spectroscopy and Fluorescence Analysis

Subfield: Radiation

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,730

Funders: Japan Science and Technology Agency, Core Research for Evolutional Science and Technology