Computational screening of O‐functional MXenes for electrocatalytic ammonia synthesis

作     者：Yijing Gao Shijie Zhang Xiang Sun Wei Zhao Han Zhuo Guilin Zhuang Shibin Wang Zihao Yao Shengwei Deng Xing Zhong Zhongzhe Wei Jian‐guo Wang 高怡静;张世杰;孙翔;赵伟;卓涵;庄桂林;王式彬;姚子豪;邓声威;钟兴;魏中哲;王建国

作者机构：Zhejiang Engineering Laboratory for Green Syntheses and Applications of Fluorine‐Containing Specialty ChemicalsInstitute of Advanced Fluorine‐Containing MaterialsZhejiang Normal UniversityJinhua 321004ZhejiangChina Institute of Industrial CatalysisCollege of Chemical EngineeringState Key Laboratory Breeding Base of Green‐Chemical Synthesis TechnologyZhejiang University of TechnologyHangzhou 310032ZhejiangChina Key Laboratory of the Ministry of Education for Advanced Catalysis MaterialsInstitute of Physical ChemistryZhejiang Normal UniversityJinhua 321004ZhejiangChina 

基　　金：国家自然科学基金(21878272,21625604) 山东省自然科学基金(ZR2020ZD35) 

出 版 物：《Chinese Journal of Catalysis》 (催化学报（英文）)

年 卷 期：2022年第43卷第7期

页      码：1860-1869页

摘      要：The nitrogen reduction reaction(NRR)using new and efficient electrocatalysts is a promising al‐ternative to the traditional Haber‐Bosch ***,it remains a challenge to design efficient catalysts with improved catalytic ***,various O‐functional MXenes were investigated as NRR catalysts by a combination of density functional theory calculations and least absolute shrinkage and selection operator(LASSO)***_(3)C_(2)O_(X) has been regarded as a promising catalyst for the NRR because of its stability,activity,and *** poten‐tial‐determining step is*NH_(2) hydrogenation to*NH3 with a limiting potential of-0.45 ***‐more,via LASSO regression,the descriptors and equations fitting the relationship between the properties of O‐functional MXenes and NRR activity have been *** work not only pro‐vides a rational design strategy for catalysts but also provides machine learning data for further investigation.

主 题 词：Electrocatalytic ammonia synthesis O‐functional MXenes Density functional theory Least absolute shrinkage and selection operator regression Gibbs free energy 

学科分类：081702[081702] 081705[081705] 08[工学] 0817[工学-轻工类] 080502[080502] 0805[工学-能源动力学] 

核心收录：

D　O　I：10.1016/S1872-2067(21)64011-1

馆 藏 号：203111766...