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Recent Progress in First Principle Calculation and High-Throughput Screening of Electrocatalysts: A Review

机译:最近的第一原理计算和高通量筛选电催化剂的进展情况:综述

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摘要

There are many ongoing efforts to develop sustainable, clean, efficient, and economical pathways to produce renewable energy sources to satisfy worldwide energy demands. Electrochemical conversion processes, such as water splitting, CO2 conversion and N-2 electroreduction, have been considered as successful approaches to solve these energy issues. Over the past decade, combining of theory and experiment has proven to be an innovative strategy, providing a framework for the design of high-performance catalysts and to investigate their mechanisms. This review introduces recent progress in theoretical strategies for state-of-the-art heterogeneous electrocatalysts. Theoretical approaches are essential for grasping the intrinsic nature of the catalytic materials. Various levels of model system, with corresponding descriptions to capture the realistic environment, are addressed. Meanwhile, machine learning using data obtained by high-throughput screening, exploited as a new scientific approach, is discussed. Based on this review, it is expected that theoretical approaches will shed light on the future design of electrocatalysts, allowing for the development of sustainable energy sources.
机译:有许多持续的努力来开发可持续,干净,高效,经济的途径,以生产可再生能源,以满足全球能源需求。电化学转换方法,例如水分解,CO2转化和N-2电导,已被认为是解决这些能源问题的成功方法。在过去的十年中,理论和实验的结合已被证明是一种创新的策略,为高性能催化剂设计提供了一种框架,并调查其机制。本综述介绍了最近的最先进的异质电催化剂的理论策略进展。理论方法对于抓住催化材料的内在性质是必不可少的。解决了各种级别的模型系统,具有相应的描述来捕获现实环境。同时,讨论了使用由高吞吐量筛选获得的数据作为一种新的科学方法获得的机器学习。基于这一综述,预计理论方法将在未来的电催化剂设计上阐明,允许开发可持续能源。

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