2023/04/28 by Charles Cardot, Cardot, Charles, J. J. Kas +7 · 3 citations
Chemistry · Materials Science · Physics and Astronomy · #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Organometallic Complex Synthesis and Catalysis #Strongly Correlated Electrons (cond-mat.str-el) #X-ray Spectroscopy and Fluorescence Analysis
paper · pdf · doi:10.48550/arxiv.2304.14582
openalex publication_date 2023/04/28 · openalex created_date 2023/05/02 · openalex updated_date 2026/08/01
Recent advances using Density Functional Theory (DFT) to augment Multiplet Ligand Field Theory (MLFT) have led to ab-initio calculations of many formerly empirical parameters. This development makes MLFT more predictive instead of interpretive, thus improving its value for understanding highly correlated 3d, 4d, and f-electron systems. Here, we explore a DFT + MLFT based approach for core-to-core Kα x-ray emission spectra (XES) and evaluate its performance for a range of transition metal systems. We find good agreement between theory and experiment, as well as the ability to capture key spectral trends related to spin and oxidation state. We also discuss limitations of the model in the context of the remaining free parameters and suggest directions forward.