锂离子电池硅基阳极功能粘结剂的研究进展

IF 13.5 2区 化学 Q1 CHEMISTRY, PHYSICAL 物理化学学报 Pub Date : 2024-06-01 Epub Date: 2023-08-09 DOI:10.3866/PKU.WHXB202306006
Jingshuo Zhang , Yue Zhai , Ziyun Zhao , Jiaxing He , Wei Wei , Jing Xiao , Shichao Wu , Quan-Hong Yang
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引用次数: 0

摘要

硅(Si)阳极具有较高的理论重量容量(Li15Si4为3579 mAh·g−1),几乎是石墨阳极(372 mAh·g−1)的十倍。电化学电位低(0.4 V vs. Li+/Li),储量丰富。因此,硅成为高能锂离子电池发展的关键负极材料。纳米硅,通常与石墨复合,已经开始商业化。但商用硅/石墨复合材料的比容量一般在600 mAh·g−1以下,远低于硅的理论比容量。同时,纳米硅的高成本、高比表面积和低攻丝密度进一步限制了其体积能量密度和规模化生产。与上述材料相比,微si (1-10 μm)因其低成本而备受业界关注,因为它不需要高能球磨来减小粒径。此外,低比表面积和高丝锥密度有助于减少界面副反应和提高体积能量密度。因此,微硅在高体积能量密度存储器件中具有特殊的优势。但由于体积变化显著(300%)所产生的巨大应力,存在较为严重的颗粒粉碎、电极崩解、导电网络失效、固体电解质界面相生长失控等问题,极大地阻碍了其商业化。粘合剂对于适应Si体积的变化至关重要,以确保电极的完整性,并保持活性材料,导电添加剂和集流器之间的紧密接触,以提供稳定的导电网络。高容量、高稳定性的微硅基阳极的发展对粘结剂的设计提出了更大的挑战。在这篇综述中,我们首先阐明了粘结剂的结合机制,影响结合力的因素,以及缓解Si电极体积变化的粘结剂设计策略。主要从自愈性粘结剂、导电性粘结剂、离子导电性粘结剂以及功能粘结剂对稳定固体电解质界面(SEI)形成的促进作用等方面系统地讨论了硅基阳极功能粘结剂的策略和相应的机制。最后指出了在工业载荷作用下,复合材料在长周期稳定性、初始库仑效率(ICE)和粘结剂比方面存在的问题和挑战。我们提出了面向微硅阳极实际应用的功能粘结剂的发展方向:理想的粘结剂应该是多功能的,并且在微硅的长循环寿命中有助于稳定的电子/离子导电网络和稳定的SEI,其中功能粘结剂的聚合物分子结构可以通过人工智能和机器学习技术系统地设计。下载:下载高清图片(107KB)下载:下载全尺寸图片
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Research Progress of Functional Binders in Silicon-Based Anodes for Lithium-Ion Batteries
Silicon (Si) has a high theoretical gravimetric capacity (3579 mAh·g−1 for Li15Si4), which is almost ten times higher than that of graphite (372 mAh·g−1) anode. Besides, it has low electrochemical potentials (0.4 V vs. Li+/Li), and abundant reserves. Thus, Si becomes a key anode material for the development of high-energy lithium-ion batteries. Nano-Si, typically compounded with graphite, has opened its commercialization. But the specific capacity of commercial Si/graphite composites is generally below 600 mAh·g−1, which is far below the theoretical specific capacity of Si. In the meanwhile, the high cost, high specific surface area and low tap density of nano-Si limit its volumetric energy density and large-scale production further. Compared to the above materials, micro-Si (1–10 μm) is gaining industry attention for its low cost, as it does not require high-energy ball milling to reduce the particle size. Also, low specific surface area and high tap density conduce to reducing interfacial side reactions and increasing volumetric energy density. Therefore, micro-Si has a particular advantage over application in high volumetric energy density storage devices. However, due to the huge stress caused by significant volume change (300%), there are more severe problems such as particle pulverization, electrode disintegration, conductive network failure and uncontrolled growth of solid electrolyte interphases, which greatly hinder its commercialization. Binders are essential in adapting to Si volume changes to ensure the integrity of the electrode and keeping the tight contact among the active material, conductive additive and current collector to provide a stable conductive network. The development of high-capacity and high-stability micro-Si-based anodes poses greater challenges to the design of binders. In this review, we first clarify the binding mechanism of binders, factors that influence the bonding forces, and design strategies of binders for relieving the volume change of Si electrodes. As a major part, we systematically discuss the strategies and corresponding mechanisms of functional binders for silicon-based anodes from aspects of self-healing binders, conductive binders, ion-conductive binders, and the facilitating effect of functional binders on the stable solid electrolyte interphase (SEI) formation. Finally, the existing problems and challenges are pointed out in terms of long-cycle stability, initial Coulombic efficiency (ICE) and binder ratio under commercial loading. We put forward the promising directions for developing functional binders towards the practical use of micro-Si anode: an ideal binder should be multifunctional and helpful to robust electron/ion conductive networks and stable SEI throughout the long cycling life of micro-Si, where the polymer molecular structure of functional binders can be systematically designed by artificial intelligence and machine learning technologies.
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来源期刊
物理化学学报
物理化学学报 化学-物理化学
CiteScore
16.60
自引率
5.50%
发文量
9754
审稿时长
1.2 months
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