X-ray spectroscopy study of hydrocarbon adsorption dynamics on transition metal catalysts by innovative algorithms for data analysis based on artificial intelligence

From 01.10.2020 till 01.10.2022
Grant holder: Alexander Soldatov
Responsible: Oleg Usoltsev

The study of nanocatalysts by X-ray absorption spectroscopy has become widespread in the scientific world as one of the most effective methods for determining the local structure of matter. Among the currently available techniques, the use of machine learning methods for in situ analysis of XANES spectra will make it possible to identify structural parameters previously inaccessible to researchers for a number of materials, for example, the structure of transition metal nanocatalysts during catalytic reactions. The project goal is determination of the structural parameters for transition metal nanoparticles (palladium, platinum, nickel, as well as their alloys) by the exposure of hydrocarbon gases under realistic manufacture conditions. This project will allow experimentally investigating of the transition metal nanoparticles structure based on in situ measurements at synchrotron radiation facilities in the stream of hydrocarbon gases (C2H2, C2H4, CH4 etc.) to study active phases formation and to determine the local structure both on the surface and in the core of the nanoparticles. It will be applied fundamentally new methods of data analysis and it will be constructed the model of transition metal nanoparticles structure evolution using novel structural information for sample characterization.