制氢
分解水
氢
化学链燃烧
太阳能
热化学循环
钙钛矿(结构)
氢燃料
材料科学
氧化物
化学工程
催化作用
化学
工程物理
光催化
物理化学
燃烧
冶金
物理
有机化学
工程类
生物
生物化学
生态学
作者
Cijie Liu,Jiyun Park,Héctor A. De Santiago,Boyuan Xu,Wei Li,Dawei Zhang,Lingfeng Zhou,Yue Qi,Jian Luo,Xingbo Liu
出处
期刊:ACS Catalysis
[American Chemical Society]
日期:2024-09-25
卷期号:14 (19): 14974-15013
被引量:27
标识
DOI:10.1021/acscatal.4c03357
摘要
) as a clean fuel. This technology serves as a crucial feedstock for synthetic fuel production, aligning with the principles of sustainable energy. The efficiency of the conversion process relies on the meticulous tuning of the properties of active materials, mostly commonly perovskite and fluorite oxides. This Review conducts a comprehensive review encompassing experimental, computational, and thermodynamic and kinetic property studies, primarily assessing the utilization of perovskite oxides in two-step thermochemical reactions and identifying essential attributes for future research endeavors. Furthermore, this Review delves into the application of machine learning (ML) and density functional theory (DFT) for predicting and classifying the thermochemical properties of perovskite materials. Through the integration of experimental investigations, computational modeling, and ML methodologies, this Review aspires to expedite the screening and optimization of perovskite oxides, thus enhancing the efficiency of STCH processes. The overarching objective is to propel the advancement and practical integration of STCH systems, contributing significantly to the realization of a sustainable and carbon-neutral energy landscape.
科研通智能强力驱动
Strongly Powered by AbleSci AI