In Silico Design of Covalent Organic Framework-Based Electrocatalysts.

ABSTRACT: Covalent organic frameworks (COFs) are an emerging type of porous crystalline material for efficient catalysis of the oxygen evolution reaction (OER). However, it remains a grand challenge to address the best candidates from thousands of possible COFs. Here, we report a methodology for the design of the best candidate screened from 100 virtual M-N _x O _y (M = 3d transition metal)-based model catalysts via density functional theory (DFT) and machine learning (ML). The intrinsic descriptors of OER activity of M-N _x O _y were addressed by the machine learning and used for predicting the best structure with OER performances. One of the predicted structures with a Ni-N₂O₂ unit is subsequently employed to

SUBMITTER: Zhou W 

PROVIDER: S-EPMC8479867 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature