Understanding how nanomaterials work requires identifying their active units, pinpointing active sites, and providing data that inform theoretical models. Two major challenges are the intrinsic heterogeneity of active species and their dynamic restructuring in reactive environments. In the first part of my talk, I will introduce a descriptor-based approach that bridges structure and function...
Machine Learning (ML) techniques offer powerful tools for advancing scientific discoveries and are increasingly integrated into material science, particularly X-ray Absorption Spectroscopy (XAS) studies in situ. These methods enable applications ranging from real-time spectral analysis during catalytic reaction to the prediction of structural parameters [1,2]. As a wide range of spectroscopic...
Hyperspectral X-ray absorption spectra (XAS) imaging implemented at the ROCK-SOLEIL beamline [1] offers a unique opportunity to combine second time-resolution and micrometer spatial resolution for monitoring electronic and local order transformations occurring during a chemical reaction. Individual spectra collected under operando conditions at each raw pixel of hyperspectral cubes have low...