Machine Learning-Assisted Survey on Charge Storage of MXenes in Aqueous Electrolytes

被引:2
|
作者
Kawai, Kosuke [1 ]
Ando, Yasunobu [1 ,2 ]
Okubo, Masashi [1 ]
机构
[1] Waseda Univ, Sch Adv Sci & Engn, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, Japan
[2] Natl Inst Adv Ind Sci & Technol, Umezono 1-1-1, Tsukuba, Ibaraki 3058568, Japan
来源
SMALL METHODS | 2024年
关键词
electrochemical capacitor; MXene; nanosheet; machine learning; 2D TITANIUM CARBIDE; ENERGY-STORAGE; CATION INTERCALATION; V2C MXENE; CAPACITANCE; PSEUDOCAPACITANCE; SUPERCAPACITORS; EXFOLIATION; MECHANISM; PHASE;
D O I
10.1002/smtd.202400062
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Pseudocapacitance is capable of both high power and energy densities owing to its fast chemical adsorption with substantial charge transfer. 2D transition-metal carbides/nitrides (MXenes) are an emerging class of pseudocapacitive electrode materials. However, the factors that dominate the physical and chemical properties of MXenes are intercorrelated with each other, giving rise to challenges in the quantitative assessment of their discriminating importance. In this perspective, literature data on the specific capacitance of MXene electrodes in aqueous electrolytes is comprehensively surveyed and analyzed using machine-learning techniques. The specific capacitance of MXene electrodes shows strong dependency on their interlayer spacing, where confined H2O in the interlayer space should play a key role in the charge storage mechanism. The electrochemical behavior of MXene electrodes is overviewed based on atomistic insights obtained from data-driven approaches. Layered transition-metal carbide/nitride (MXene) that contains one H2O layer in the interlayer space exhibits the largest specific capacitance in aqueous electrolytes. image
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页数:11
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