Strain engineering in single-atom catalysts: GaPS4 for bifunctional oxygen reduction and evolution

被引:17
|
作者
Liu, Xuefei [1 ]
Liu, Tianyun [1 ]
Xiao, Wenjun [1 ]
Wang, Wentao [2 ]
Zhang, Yuefei [1 ]
Wang, Gang [1 ]
Luo, Zijiang [3 ]
Liu, Jin-Cheng [4 ,5 ]
机构
[1] Guizhou Normal Univ, Sch Phys & Elect Sci, Guiyang 550025, Peoples R China
[2] Guizhou Educ Univ, Guizhou Prov Key Lab Computat Nanomat Sci, Guiyang 550018, Peoples R China
[3] Guizhou Univ Finance & Econ, Coll Informat, Guiyang 550025, Peoples R China
[4] Tsinghua Univ, Dept Chem, Beijing 100084, Peoples R China
[5] Tsinghua Univ, Key Lab Organ Optoelect & Mol Engn, Minist Educ, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
GRAPHENE; ELECTROCATALYSTS; APPROXIMATION; ORIGIN;
D O I
10.1039/d2qi01047j
中图分类号
O61 [无机化学];
学科分类号
070301 ; 081704 ;
摘要
We report here a theoretical study on 34 transition metal doped two-dimensional GaPS4 catalysts, denoted as transition metal transition metal@V-S-GaPS4. Among them, the Pt@V-S1-GaPS4 single-atom catalyst is found to be stable with an ORR/OER overpotential of 0.59/0.41 V. Under the guidance of a volcano map, further biaxial strain engineering is adopted to tune the activity of Pt@V-S1-GaPS4 to the top of the volcano. The overpotentials of the OER/ORR are decreased to 0.37/0.33 V by applying a 3% tensile strain. Our results prove that Pt@V-S1-GaPS4 is an excellent candidate for OER/ORR bifunctional electrocatalysis. Moreover, bond angles and the highest occupied orbitals of the doped transition metal atoms can be used as descriptors to explain the underlying strain tunability mechanism. The machine learning method further predicts that the number of d electrons, the bond length and electronegativity are three main descriptors to determine the catalytic activity.
引用
收藏
页码:4272 / 4280
页数:9
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