Graph neural networks and XANES spectroscopy for investigation of the structure of copper centers in Cu-MOR

Abstract

Graph neural networks and XANES spectroscopy for investigation of the structure of copper centers in Cu-MOR

Gladchenko-Djevelekis Ya.N., Kulaev K.D., Ponosova E.E., Babayants A.S., Ermakova A.M., Sukharina G.B., Pryadchenko V.V., Avakyan L.A.

Incoming article date: 09.11.2023

In this paper, the possibility of applying graph neural networks (NN) to study the structure of copper centers of zeolites is considered. The dataset used for NN training was prepared using the FDMNES software based on the finite difference method and included more than 2100 Cu K-XANES spectra for Cu-MOR. The performed study demonstrated the capability of graph neural networks to reproduce the Cu K-XANES spectrum corresponding to a particular model of the copper center in the zeolite framework.

Keywords: zeolite, mordenite, atomic structure, XANES, machine learning, graph neural networks