假电容器
超级电容器
纳米技术
材料科学
纳米孔
表征(材料科学)
计算机科学
电极
电容
化学
物理化学
作者
Sheng Bi,Lisanne Knijff,Xiliang Lian,Alicia van Hees,Chao Zhang,Mathieu Salanne
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-07-25
卷期号:18 (31): 19931-19949
被引量:1
标识
DOI:10.1021/acsnano.4c01787
摘要
Capacitive storage devices allow for fast charge and discharge cycles, making them the perfect complements to batteries for high power applications. Many materials display interesting capacitive properties when they are put in contact with ionic solutions despite their very different structures and (surface) reactivity. Among them, nanocarbons are the most important for practical applications, but many nanomaterials have recently emerged, such as conductive metal-organic frameworks, 2D materials, and a wide variety of metal oxides. These heterogeneous and complex electrode materials are difficult to model with conventional approaches. However, the development of computational methods, the incorporation of machine learning techniques, and the increasing power in high performance computing now allow us to tackle these types of systems. In this Review, we summarize the current efforts in this direction. We show that depending on the nature of the materials and of the charging mechanisms, different methods, or combinations of them, can provide desirable atomic-scale insight on the interactions at play. We mainly focus on two important aspects: (i) the study of ion adsorption in complex nanoporous materials, which require the extension of constant potential molecular dynamics to multicomponent systems, and (ii) the characterization of Faradaic processes in pseudocapacitors, that involves the use of electronic structure-based methods. We also discuss how recently developed simulation methods will allow bridges to be made between double-layer capacitors and pseudocapacitors for future high power electricity storage devices.
科研通智能强力驱动
Strongly Powered by AbleSci AI