基于材料基因工程的二维MOFs催化材料研究：描述因子挖掘及OER性能预测

开发高性能的OER催化材料是提升下一代能源存储/转换装置效率使其得以广泛应用的基础和关键。本项目针对传统试错型研发模式无法满足快速筛选高效OER催化材料的问题，提出了通过发掘描述因子建立OER过电位与MOFs相关结构参数之间的“桥梁”，进而实现高性能催化材料快速预测的新理念。以二维MOFs为研究对象，以材料基因工程理念为核心思想，通过高通量计算系统地建立起二维MOFs材料催化OER的过电位与结构参数之间的映射关系，获取OER过电位的描述因子，结合高通量实验技术对描述因子进行优化校正，建立具有高OER活性的二维MOFs催化材料的快速筛选方法，合成5-10种兼具高性能、低成本和优异循环稳定性的二维MOFs催化材料。该项目的意义在于通过描述因子建立MOFs微观结构参数与宏观性能的直接关联，为发展基于材料基因工程的MOFs催化材料快速研发模式提供理论基础和实验依据。

The development of high-performance OER catalysts is the basis to improve the efficiency of energy storage/conversion devices and their application. This project sets the two-dimensional MOFs as the research object, based on the material genetic engineering, by means of high-throughput computing system to establish the correlation relationship between overpotential of the two-dimensional MOFs during the OER process and their structural parameters, discovering a description of the overpotential, combining with high throughput experimental technology for the further optimization the correction of the descriptor, establishing a rapid screening method of high-performance two-dimensional MOFs, and finally obtain 5-10 kinds of two-dimensional MOFs equipped with both high OER activity, low cost and good cycle stability. The significance of this project is to establish the direct correlation between the microstructure parameters and the macroscopic properties of MOFs through the description factors, so as to provide theoretical and experimental basis for the development of the MOFs catalytic material rapid development model based on material genetic engineering.