Heterogeneous electrocatalysis lies at the center of various technologies that could help
enable a sustainable future. However, its complexity makes it challenging to accurately and …

Computational spectroscopy has emerged as a critical tool for researchers looking to
achieve both qualitative and quantitative interpretations of experimental spectra. Over the …

An important yet challenging aspect of atomistic materials modeling is reconciling
experimental and computational results. Conventional approaches involve generating …

Precise determination of atomic structural information in functional materials holds
transformative potential and broad implications for emerging technologies. Spectroscopic …

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide
valuable insights into the atomic structures of materials, yet the inverse prediction of precise …

Machine learning can reveal new insights into X-ray spectroscopy of liquids when the local
atomistic environment is presented to the model in a suitable way. Many unique structural …

Accurate classification of molecular chemical motifs from experimental measurement is an
important problem in molecular physics, chemistry, and biology. In this work, we present …

X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing
the local chemical environment of absorbing atoms. However, analyzing XAS data presents …

One of the most important, and most challenging, aspects of atomistic materials modeling is
to reconcile experimental and computational results. This requires an effective strategy for …

In their recent work published in the Journal of the American Chemical Society, Zhang et al.
introduce a novel approach combining electron diffraction data with computational …