Design and Synthesis of Electrocatalysts Base on Catalysis-Unit Engineering.

It is a pressing need to develop new energy materials to address the existing energy crisis. However, screening optimal targets out of thousands of materials candidates remains a great challenge. Herein, we propose and validate an alternative concept for highly effective materials screening based on dual-atom salphen catalysis units. Such an approach simplifies the design of catalytic materials and reforms the trial-and-error experimental model into a building-blocks-assembly like process. Firstly, density functional theory (DFT) calculations were performed on a series of potential catalysis units which were possible to synthesize. Then, machine learning (ML) was employed to define the structure-performance relationship and acquire chemical insights. Afterwards, the projected catalysis units were integrated into covalent organic frameworks (COFs) to validate the concept Electrochemical tests confirm that Ni-SalphenCOF and Co-SalphenCOF are promising conductive agent-free oxygen evolution reaction (OER) catalysts. This work provides a fast-tracked strategy for design and development of functional materials, which serves as a potentially workable framework for seamlessly integrating DFT calculations, ML, and experimental approaches. This article is protected by copyright. All rights reserved.