Molecular Simulations of the Microstructure Evolution of Solid Electrolyte Interphase during Cyclic Charging/Discharging

Impact of the Local Environment on Li Ion Transport in Inorganic Components of Solid Electrolyte Interphases

The spontaneously formed passivation layer, the solid electrolyte interphase (SEI) between the electrode and electrolyte, is crucial to the performance and durability of Li ion batteries. However, the Li ion transport mechanism in the major inorganic components of the SEI (Li2CO3 and LiF) is still unclear. Particularly, whether introducing an amorphous environment is beneficial for improving the Li ion diffusivity is under debate. Here, we investigate the Li ion diffusion mechanism in amorphous LiF and Li2CO3 via machine-learning-potential-assisted molecular dynamics simulations. Our results show that the Li ion diffusivity in LiF at room temperature cannot be accurately captured by the Arrhenius extrapolation from the high temperature (>600 K) diffusivities (difference of ∼2 orders of magnitude). We reveal that the spontaneous formation of Li-F regular tetrahedrons at low temperatures (<500 K) leads to an extremely low Li ion diffusivity, suggesting that designing an amorphous bulk LiF-based SEI cannot help with the Li ion transport. We further show the critical role of Li2CO3 in suppressing the Li-F regular tetrahedron formation when these two components of SEIs are mixed. Overall, our work provides atomic insights into the impact of the local environment on Li ion diffusion in the major SEI components and suggests that suppressing the formation of large-sized bulk-phase LiF might be critical to improve battery performance.

Self-Healable, Highly Stretchable, Ionic Conducting Polymers as Efficient Protecting Layers for Stable Lithium-Metal Electrodes

Although numerous studies on polymeric protective films to stabilize lithium (Li)-metal electrodes have been reported, the construction of self-healing polymers that enables the long-term operation of Li-metal batteries (LMBs) at relatively low temperatures has rarely been demonstrated. Herein, a highly stretchable, autonomous self-healable, and ionic-conducting polymer network (SHIPN) is synthesized as an efficient protective film for LMBs. The network backbone, synthesized from copolymerization of poly(ethylene glycol)-mono-methacrylate (PEGMMA) and 2-[[(butylamino)carbonyl]oxy]ethyl acrylate (BCOE), is chemically cross-linked via diisocyanate. With SHIPN-modified electrodes, enhanced electrochemical performance can be achieved in Li/Cu, Li/Li, and Li/LiFePO₄ (Li/LFP) cells. The SHIPN@Li/LFP cell delivers a capacity retention of 85.6% after 500 cycles at 5 °C, resulting from the low-temperature self-healability of SHIPN. In full cells with a high-mass-loading LFP cathode (∼17 mg cm^-2), the capacity retention is at least 300% higher than that with a bare Li electrode. Further physical characterizations of electrodes confirm the effect of SHIPN in enhancing the interfacial stability and suppressing Li dendrite growth. Our results will provide insights into rationally designing soft and hybrid materials toward stable LMBs at different temperatures.

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

Rechargeable batteries have become indispensable implements in our daily life and are considered a promising technology to construct sustainable energy systems in the future. The liquid electrolyte is one of the most important parts of a battery and is extremely critical in stabilizing the electrode-electrolyte interfaces and constructing safe and long-life-span batteries. Tremendous efforts have been devoted to developing new electrolyte solvents, salts, additives, and recipes, where molecular dynamics (MD) simulations play an increasingly important role in exploring electrolyte structures, physicochemical properties such as ionic conductivity, and interfacial reaction mechanisms. This review affords an overview of applying MD simulations in the study of liquid electrolytes for rechargeable batteries. First, the fundamentals and recent theoretical progress in three-class MD simulations are summarized, including classical, ab initio, and machine-learning MD simulations (section 2). Next, the application of MD simulations to the exploration of liquid electrolytes, including probing bulk and interfacial structures (section 3), deriving macroscopic properties such as ionic conductivity and dielectric constant of electrolytes (section 4), and revealing the electrode-electrolyte interfacial reaction mechanisms (section 5), are sequentially presented. Finally, a general conclusion and an insightful perspective on current challenges and future directions in applying MD simulations to liquid electrolytes are provided. Machine-learning technologies are highlighted to figure out these challenging issues facing MD simulations and electrolyte research and promote the rational design of advanced electrolytes for next-generation rechargeable batteries.

Frontiers in Theoretical Analysis of Solid Electrolyte Interphase Formation Mechanism

Solid electrolyte interphase (SEI) is an ion conductive yet electron-insulating layer on battery electrodes, which is formed by the reductive decomposition of electrolytes during the initial charge. The nature of the SEI significantly impacts the safety, power, and lifetime of the batteries. Hence, elucidating the formation mechanism of the SEI layer has become a top priority. Conventional theoretical calculations reveal initial elementary steps of electrolyte reductive decomposition, whereas experimental approaches mainly focus on the characterization of the formed SEI in the final form. Moreover, both theoretical and experimental methodologies could not approach intermediate or transient steps of SEI growth. A major breakthrough has recently been achieved through a novel multiscale simulation method, which has enriched the understanding of how the reduction products are aggregated near the electrode and influence the SEI morphologies. This review highlights recent theoretical achievements to reveal the growth mechanism and provides a clear guideline for designing a stable SEI layer for advanced batteries.