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Article Navigation >  Green Energy&Environment  > 2020  >  5(3): 286-302
Haoxiang Xu, Daojian Cheng. First-principles-aided thermodynamic modeling of transition-metal heterogeneous catalysts: A review. Green Energy&Environment, 2020, 5(3): 286-302. doi: 10.1016/j.gee.2020.07.006
Citation: Haoxiang Xu, Daojian Cheng. First-principles-aided thermodynamic modeling of transition-metal heterogeneous catalysts: A review. Green Energy&Environment, 2020, 5(3): 286-302. doi: 10.1016/j.gee.2020.07.006
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First-principles-aided thermodynamic modeling of transition-metal heterogeneous catalysts: A review

doi: 10.1016/j.gee.2020.07.006

  • State Key Laboratory of Organic-Inorganic Composites and Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China

More Information
  • Corresponding author: E-mail address: chengdj@mail.buct.edu.cn (Daojian Cheng)
  • Received date 23 May 2020, Accepted date 08 July 2020, RevRecd date 08 July 2020, Available online 14 July 2020, Publish date 31 July 2020,
    Abstract
  • Over the past decade, the first-principles-aided thermodynamic models have become standard theoretical tools in research on structural stability and evolution of transition-metal heterogeneous catalysts under reaction environment. Advances in first-principles-aided thermodynamic models mean it is now possible to enable the operando computational modeling, which provides a deep insight into mechanism behind structural stability and evolution, and paves the way for high-through screening for promising transition-metal heterogeneous catalysts. Here, we briefly review the framework and foundation of first-principles-aided thermodynamic models and highlight its contribution to stability analysis on catalysts and identification of reaction-induced structural evolution of catalyst under reaction environment. The present review is helpful for understanding the ongoing developments of first-principles-aided thermodynamic models, which can be employed to screen high-stability catalysts and predict their structural reconstruction in future rational catalyst design.

     

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