Bi Sheng, Knijff Lisanne, Lian Xiliang, van Hees Alicia, Zhang Chao, Salanne Mathieu
Physicochimie des Électrolytes et Nanosystèmes Interfaciaux, Sorbonne Université, CNRS, F-75005 Paris, France.
Réseau sur le Stockage Electrochimique de l'Energie (RS2E), FR CNRS 3459, 80039 Amiens Cedex, France.
ACS Nano. 2024 Jul 25;18(31):19931-49. doi: 10.1021/acsnano.4c01787.
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.
电容式存储设备能够实现快速充放电循环,使其成为高功率应用中电池的理想补充。许多材料尽管结构和(表面)反应性差异很大,但当它们与离子溶液接触时会表现出有趣的电容特性。其中,纳米碳对于实际应用最为重要,但最近也出现了许多其他纳米材料,如导电金属有机框架、二维材料以及各种各样的金属氧化物。这些异质且复杂的电极材料难以用传统方法进行建模。然而,计算方法的发展、机器学习技术的融入以及高性能计算能力的不断提升,现在使我们能够处理这类系统。在本综述中,我们总结了这一方向上目前的研究成果。我们表明,根据材料的性质和充电机制,不同的方法或它们的组合,可以提供关于所涉及相互作用的理想原子尺度见解。我们主要关注两个重要方面:(i)复杂纳米多孔材料中离子吸附的研究,这需要将恒电位分子动力学扩展到多组分系统;(ii)赝电容器中法拉第过程的表征,这涉及使用基于电子结构的方法。我们还讨论了最近开发的模拟方法将如何为未来的高功率储能设备在双层电容器和赝电容器之间架起桥梁。