Unravel SEI Formation on Li Metal Interfaces By Mechanistic Multi-Scale Modelling

Abstract

Nowadays, lithium metal anodes are often referred to as the ‘holy grail’ of next-generation battery technology. Compared to graphite anodes used in state-of-the-art lithium-ion batteries they promise several times higher energy densities [1]. However, Li metal shows a high reactivity with liquid electrolytes and uncontrolled dendrite growth which hinders a safe and efficient cyclability and therefore the commercial application in rechargeable batteries. Thus, stabilization of the solid-electrolyte interphase (SEI) between liquid electrolyte and the lithium surface is the key challenge to be solved before bringing this promising battery technology to market. In order to suppress unwanted effects such as dendrite formation, persistent loss of active material and high kinetic losses, this layer of electrolyte decomposition products needs to be electrically insulating and should prevent direct contact of metal with electrolyte while ensuring a good ionic conductivity and mechanical stability.Such a beneficial SEI design requires detailed understanding of the fundamental formation mechanism and the resulting chemical SEI composition and structure depending on electrolyte composition. In literature, a large range of experimental methods are applied to characterize the SEI under various conditions [2]. These approaches are mainly descriptive and struggle to identify and understand the underlying mechanisms. Theoretical approaches like density functional theory (DFT), ab-initio molecular dynamics (MD) or classical MD are well suited to determine reaction mechanisms and to model the very beginning of SEI formation in the ns-range. However, they are too computationally expensive to model technical relevant length- and time scales [3].Therefore, this work focuses on overcoming these restrictions by developing an efficient multiscale-model with input from ab-initio calculations. The acceleration originates from focusing on rare events such as reaction or diffusion processes in a 3-dimensional kinetic Monte Carlo instead of considering the vibrational motions of single atoms like in molecular dynamics. Thereby, every process is represented by a probability derived from ab-initio calculations to ensure physical correctness. An additional coupling with efficient ordinary differential equations as shown in [4] ensures electroneutrality in the simulation box.Implementation of the degradation reactions for a 1.2M LiPF6/EC electrolyte obtained from molecular simulations (see Figure 1, appendix), allows to unravel the initial SEI formation, the emerging structure and its composition within the first µs. The simulation suggests an almost instantaneous formation of SEI species on the pristine Li metal within the first nanoseconds after immersion. Due to this early passivation layer the formation process slows down continuously until electron tunneling is blocked by SEI species and a first passivation of the lithium surface is reached. Interestingly, the formed passivation layer mainly consists of inorganic species such as LiF close ...

Accessing the Primary Solid–Electrolyte Interphase on Lithium Metal: A Method for Low‐Concentration Compound Analysis

“…The results of the solid phase were in accordance with previous studies, [52–54] where the general SEI of a simple lithium‐metal‐based battery containing a carbonate‐based electrolyte with LiPF 6 as conducting salt and without any electrolyte additives, was expected to include significant amounts of organic decomposition products, probably containing higher oligo‐ or even polycarbonates or ‐ethers together with lithium carbonate as an inorganic decomposition product. According to prior reports, and especially those on simulations of primary SEI formation, the share of lithium fluoride was expected to be higher, owing to the favorable decomposition of the conducting salt in contact with lithium metal [49] . However, the results of this study show relatively low amounts of lithium fluoride and, together with the analysis of the liquid electrolyte phase, it can be stated that the reactivity of LiPF 6 during primary SEI formation is low, maybe even negligible.…”

“…According to prior reports, and especially those on simulations of primary SEI formation, the share of lithium fluoride was expected to be higher, owing to the favorable decomposition of the conducting salt in contact with lithium metal. [49] However, the results of this study show relatively low amounts of lithium fluoride and, together with the analysis of the liquid electrolyte phase, it can be stated that the reactivity of LiPF 6 during primary SEI formation is low, maybe even negligible.…”

“…In addition, its presence without hints on its degradation products indicates a non‐acidic environment in which LiPF 6 is stable. These results can be helpful for any kind of simulation study on interphase formation in lithium‐based batteries, as it simplifies the reaction mechanism network due to the missing involvement of the conducting salt [49] …”

“…These results can be helpful for any kind of simulation study on interphase formation in lithium-based batteries, as it simplifies the reaction mechanism network due to the missing involvement of the conducting salt. [49] In summary, the results for the analysis of the liquid electrolyte phase reveal a wide variety of compounds that so far only have been observed in the context of LIBs but have never been observable in a study concerning the primary SEI formation on lithium metal (i. e., in LMBs). Therefore, the accumulation method reveals to be a valid method to study the starting point of any kind of liquid electrolyte that is supposed to be in contact with lithium metal in a battery cell.…”

Impact of electrolyte impurities and SEI composition on battery safety

“…Furthermore, approaches using kMC methods in combination with computational chemistry support long-time existing hypotheses about the composition and morphology of the SEI. 17–19 These studies illustrate how simulations can be used as powerful tools to unravel, supplement or support existing theories on SEI growth and functionality.…”