The Design of Transition Metal Sulfide Cathodes for High-Performance Magnesium-Ion Batteries

IF 14 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of materials research Pub Date : 2024-09-25 DOI:10.1021/accountsmr.4c0018110.1021/accountsmr.4c00181
Jianbiao Wang,  and , Zhi Wei Seh*, 
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Abstract

Despite the widespread use of lithium-ion battery (LIB) technology, conventional LIB suffer from severe limitations (e.g., low energy density, flammable electrolytes) that have prompted much research interest for alternative battery technologies. To overcome the limitations of lithium-ion batteries, magnesium-ion batteries (MIBs) have been proposed as promising alternative energy storage devices, with advantages of high volumetric energy density, high safety, low cost, and environmental benignity. However, the high charge density of Mg2+ in MIBs leads to sluggish electrochemical kinetics, owing to the strong electrostatic interactions between the host material and Mg2+. To mitigate this problem, transition metal sulfides (TMS) have been proposed as a solution and intensively researched as cathodes in MIBs, given that the soft features of sulfur can weaken undesirable electrostatic interactions (the low charge density of sulfur and high theoretical capacity). Nevertheless, TMS suffer from large volume variation, poor electronic conductivity as well as detrimental side reactions that all lead to degraded cycling performance. To this end, many solutions have been proposed to resolve these issues.

Herein, we present the latest research on the design of nanostructured TMS (e.g., NiS2, FeS2, and Co3S4/CoS2) and their electrochemical storage performances when used as cathodes in MIBs. We highlight and discuss important findings that include: (1) different synthetic methods for preparing TMS nanostructures, (2) nanostructures (hollow and hierarchical spheres) effectively alleviating the volume variation in the insertion/extraction of Mg2+, (3) sulfur anions enhancing the electrochemical properties, (4) the TMS cathode having a shuttle effect in the electrochemical process that can be retarded by well-designed crystalline structures. (5) density functional theoretical calculations and ab initio molecular dynamics being extensively used to support the experimental results to guide the design of high-performing TMS cathodes, and (6) advanced characterization technologies (e.g., cryogenic transmission electron microscopy, X-ray absorption spectroscopy) being effective tools to investigate the dynamic evolution of TMS cathodes during the discharge/charge process. Moreover, we also evaluate other conventional strategies for designing TMS cathodes. To advance the realization of MIBs as an energy system, recent studies of MIBs in pouch cells are reviewed and discussed with reference to the challenges faced in industrial-scale production. To satisfy increasing demand for cathodes with high energy densities, we demonstrate our prospect in machine learning-driven TMS-based cathode research, given that machine learning is highly suited for discovering new materials and reducing the time taken for developing a technology from the laboratory to commercialization.

Our Account will thus guide fabrication of other transition metal chalcogenide-based cathodes for high-performance multivalent-ion batteries.

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设计用于高性能镁离子电池的过渡金属硫化物阴极
尽管锂离子电池(LIB)技术已得到广泛应用,但传统锂离子电池存在严重的局限性(如能量密度低、电解质易燃),这促使人们对替代电池技术产生了浓厚的研究兴趣。为了克服锂离子电池的局限性,人们提出了镁离子电池(MIB),认为它具有体积能量密度高、安全性高、成本低和对环境无害等优点,是一种很有前途的替代储能设备。然而,MIB 中 Mg2+ 的高电荷密度导致电化学动力学缓慢,原因是主材料与 Mg2+ 之间存在强烈的静电相互作用。为了缓解这一问题,有人提出了过渡金属硫化物(TMS)作为 MIB 阴极的解决方案,并对其进行了深入研究,因为硫的软特性(硫的低电荷密度和高理论容量)可以削弱不良的静电相互作用。然而,TMS 的体积变化大、电子导电性差以及有害的副反应都会导致循环性能下降。在此,我们将介绍有关纳米结构 TMS(如 NiS2、FeS2 和 Co3S4/CoS2)设计及其用作 MIB 阴极时的电化学存储性能的最新研究。我们重点介绍并讨论了以下重要发现(1) 制备 TMS 纳米结构的不同合成方法;(2) 纳米结构(空心球和分层球)可有效缓解 Mg2+ 插入/萃取过程中的体积变化;(3) 硫阴离子可增强电化学性能;(4) TMS 阴极在电化学过程中具有穿梭效应,而精心设计的晶体结构可延缓这种效应。(5) 密度泛函理论计算和非初始分子动力学被广泛用于支持实验结果,以指导高性能 TMS 阴极的设计;以及 (6) 先进的表征技术(如低温透射电子显微镜、X 射线吸收光谱)是研究 TMS 阴极在放电/充电过程中动态演变的有效工具。此外,我们还评估了设计 TMS 阴极的其他传统策略。为了推动实现 MIB 作为一种能源系统,我们回顾了最近在袋式电池中对 MIB 的研究,并结合工业化生产中面临的挑战进行了讨论。为了满足对高能量密度阴极日益增长的需求,我们展示了基于机器学习驱动的 TMS 阴极研究的前景,因为机器学习非常适合发现新材料并缩短技术从实验室到商业化的开发时间。
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