An explainable "family bucket" model for simultaneous prediction of K-edge XANES for multiple light transition metals.

ABSTRACT: X-ray near-edge structure (XANES) is a crucial bridge between the local structures and chemical properties of materials. Although there have been a number of studies devoted to the development of predictive K-edge XANES spectral models, existing methods are usually still limited to separate modeling for a specific absorbing element. Currently, there is a lack of a K-edge XANES spectra prediction model that can be broadly applied to a wide range of elements, which would enable data dispersed in terms of absorbing elements to be integrated and well utilized. In this work, we develop an innovative "family bucket" model based on a multi-head graph attention convolutional neural network by combining a multi-element mixed dataset with a crystal topology approach for the localized environment. Th

SUBMITTER: Huang C 

PROVIDER: S-EPMC12315256 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature