Modeling solid-electrolyte interfacial phenomena in silicon anodes

https://doi.org/10.1016/j.coche.2016.08.017Get rights and content

Highlights

  • Review of solvent decomposition at the lithiated Si surface from first-principles.

  • Review of ab-initio calculations for electrolyte decomposition at the Si surface.

  • Review of current understanding from first-principles of SEI formation and growth.

Silicon shows promising characteristics to replace graphite as the anode material in Li-ion batteries (LIBs). However addressing the volume changes in silicon during lithiation and the formation of the solid-electrolyte interphase (SEI) at the silicon-based anodes are essential to make this a practical technology. The electrolyte decomposition can lead to a continuous growth of the SEI layer; which in turn serves a double purpose: passivation of the anode surface and barrier for the Li+ diffusion. Despite the great importance of the SEI in Si-based anodes on the cycling performance of the LIBs, a deeper understanding of the SEI evolution, composition, and morphology is still lacking. In this article, we briefly review the recent findings in the field of computational materials science regarding the initial stages and growth of the SEI layer on silicon anodes.

Introduction

Energy storage devices such as batteries are necessary for the advancement of Plugless electric vehicles (EVs), low-power battery-on-a-chip, electricity storage in distribution networks, portable electronics and so forth. Due to the market penetration of rechargeable batteries in the automotive industry, the United States Advanced Battery Council (USABC) has established long-term goals that demand batteries to provide EVs with driving ranges greater than 200 miles and a battery life greater than 100,000 miles (2016, www.uscar.org). Lithium-ion batteries (LIBs) are suitable candidates to drive the technology to harvest a higher energy density to power portable devices and EVs. A typical electrochemical cell for this system includes graphite-lithium cobalt oxide (LiCoO2) with lithium hexafluorophosphate (LiPF6) and organic solvents as the electrolyte mixture [1, 2]. Graphite has replaced lithium metal as the anode electrode material due to the uncontrollable dendritic Li growth and limited Coulombic efficiency (C.E.) during Li deposition/stripping in Li metal anode-based batteries [3, 4, 5, 6, 7, 8, 9]. In the graphite anode-based batteries, graphite has a Li charge storage capacity of 372 mAh/g (with a theoretical capacity of up to one Li+ for every six carbon atoms, LiC6) [10]. Hence, the combination of these standard materials results in a relatively low voltage (i.e. 3.4 eV) which is deemed insufficient for EV's battery packs. It is widely known that modern cathode materials such as LiCoO2, lithium manganese oxide (LiMn2O4), and lithium iron phosphate (LiFePO4) are limited to intercalation/insertion compounds [11]. Thus, any considerable improvement in the electrode must be made of the anode material. Finding a suitable anode material is an effective way to solve the problem related to Li dendrite growth and to improve Li resource utilization [5, 12, 13, 14, 15]. Specifically, LIBs consisting of a transition metal oxide cathode and a silicon anode are a promising solution due to their potentially high energy and power density [16, 17].

Silicon (Si) as an anode material offers a tenfold increase in capacity per unit weight (4200 mAh/g, lithiated to Li4.4Si) when compared to the widely-used graphite anode [18, 19, 20, 21, 22]. Furthermore, the lithiation voltage plateau (0.2–0.3 V versus Li/Li+) for Si could prevent lithium plating, dendrite formation, and growth [19, 23]. Despite these improvements over graphite, it is still a significant challenge to implement Si as an anode in LIBs due to the volume change that takes place during cycling (up to four times its volume when charged with lithium ions) which leads to low C.E. and poor capacity retention [24, 25, 26, 27]. On the other hand, the reaction mechanisms that result in the decomposition of the electrolyte and simultaneous solid-electrolyte interphase (SEI) formation remain elusive. This article briefly summarizes the computational research activities in the field of LIBs with Si as an anode material and reports recent works and improvements on this subject. We emphasize the study of LIBs with Si anodes on the formation (i.e. understanding of the processes that lead to electrolyte decomposition at the Si surface) and growth of the SEI layer.

Section snippets

Solvent decomposition at the lithiated Si surface

Martinez de la Hoz, Balbuena, and co-workers [28•, 29•, 30•] studied the interaction of electrolyte molecules with lithiated Si anodes, using ab-initio molecular dynamics (AIMD) simulations. First, reduction mechanisms of the ethylene carbonate (EC) solvent molecule and those of the additives fluoroethylene carbonate (FEC) and vinylene carbonate (VC) were determined as a function of the lithiation degree of the Si anode. It is important to note that as the Li/LixSiy cell is cycled

Summary and concluding remarks

Overall, the results we have discussed in this article have important implications for the initial and growth stages of SEI layer formation on Si anodes. Since EC reduces to different adsorbed species and charged fragments at different lithiation stages, the composition of the SEI layer is expected to vary during the first cycling processes. Furthermore, the composition of the SEI layer varies depending on the anode material and decomposed solvent further away from the surface can lead to

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgements

This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, Subcontract No. 7060634 under the Advanced Batteries Materials Research (BMR) Program, and by the Qatar National Research Fund (QNRF) through the National Priorities Research Program (NPRP 7-162-2-077). PPM and ZL acknowledge financial support from NSF Grant No. 1438431. Computational resources from

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