材料科学
生化工程
催化作用
密度泛函理论
合理设计
计算机科学
多相催化
纳米技术
计算模型
分子
领域(数学)
小分子
计算化学
化学
人工智能
工程类
有机化学
生物化学
数学
纯数学
作者
Geun Ho Gu,Changhyeok Choi,Yeunhee Lee,Andres Bethavan Situmorang,Juhwan Noh,Yong‐Hyun Kim,Yousung Jung
标识
DOI:10.1002/adma.201907865
摘要
Abstract The chemical conversion of small molecules such as H 2 , H 2 O, O 2 , N 2 , CO 2 , and CH 4 to energy and chemicals is critical for a sustainable energy future. However, the high chemical stability of these molecules poses grand challenges to the practical implementation of these processes. In this regard, computational approaches such as density functional theory, microkinetic modeling, data science, and machine learning have guided the rational design of catalysts by elucidating mechanistic insights, identifying active sites, and predicting catalytic activity. Here, the theory and methodologies for heterogeneous catalysis and their applications for small‐molecule activation are reviewed. An overview of fundamental theory and key computational methods for designing catalysts, including the emerging data science techniques in particular, is given. Applications of these methods for finding efficient heterogeneous catalysts for the activation of the aforementioned small molecules are then surveyed. Finally, promising directions of the computational catalysis field for further outlooks are discussed, focusing on the challenges and opportunities for new methods.
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