Electron transfer rules of minerals under pressure informed by machine learning.

ABSTRACT: Electron transfer is the most elementary process in nature, but the existing electron transfer rules are seldom applied to high-pressure situations, such as in the deep Earth. Here we show a deep learning model to obtain the electronegativity of 96 elements under arbitrary pressure, and a regressed unified formula to quantify its relationship with pressure and electronic configuration. The relative work function of minerals is further predicted by electronegativity, presenting a decreasing trend with pressure because of pressure-induced electron delocalization. Using the work function as the case study of electronegativity, it reveals that the driving force behind directional electron transfer results from the enlarged work function difference between compounds with pressure. This well exp

SUBMITTER: Li Y 

PROVIDER: S-EPMC10066309 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature