The Influence of Grain Structure in SEI on Lithium Diffusivity and Electrodeposition in Li-Metal Batteries
Authors: Ramasubramanian Ajaykrishna , Yurkiv Vitaliy , Ragone Marco , Foroozan Tara , Shahbazian-Yassar Reza , Mashayek Farzad 
Published: February 2020

Lithium metal batteries (LMBs) are among the most promising candidates for high energy density energy storage technologies [1]. In order to make LMBs commercially competitive with the other mature energy storage devices, several aspect hindering LMBs’ widespread application shall be resolved. In particular, the growth of Li dendrites can cause the LMBs performance decrease as well as severe safety problems associated with the short circuit. In this regard, the solid electrolyte interface (SEI), a nanoscopic layer formed between the metal electrode and the liquid electrolyte, controls the Li delivery to the surface of the negative electrode, where Li electrodeposition and dendrites formation occur. Thus, the understanding of Li diffusivity (e.g., pathways, energetics, etc.) through the SEI could enable the development of strategies towards safe, robust and long-lasting LMBs. For that reason, in this contribution, we present the results of a combined ab initio Density Functional Theory (DFT) calculations to study Li diffusion across the SEI and an extended phase-field model (PFM) for Li migration and electrodeposition, that is a step forward toward better understanding of Li dendrites formation and growth.

The present DFT calculations are performed using the VASP (Vienna Ab initio Simulation Package) code [2] with the plane wave basis sets and the projector augmented wave (PAW) [3] pseudo-potentials in the framework of Perdew-Burke-Ernzerhof sol (PBEsol) generalized gradient approximation (GGA) [4]. The migration barriers and diffusion coefficients are evaluated using the Nudged Elastic Band (NEB) method as implemented in VASP. To perform the NEB calculations, the minimum energy surfaces of each grain structure in SEI are first created, using a slab method. Then, the grain boundary (GB) structures are generated by forming stable interfaces between the minimum energy surfaces. After identifying the thermodynamically stable GBs, the lithium diffusion channels through them are identified, and the NEB calculations are performed. In the current study, we examine the migration barriers through the GBs of two major inorganic SEI grain structures such as Li2O and LiF. From the migration barriers, it could be observed that the diffusion through the GBs are almost two orders of magnitude faster than the compared diffusion coefficients through the bulk of the SEI structures. The evaluated diffusion coefficients and the free energies are then used to derive the thermodynamically consistent free energy density needed for the PFM model to simulate the filament growth and understand the distribution and evolution of stress fields during Li electrodeposition.

The PFM [5] is developed employing MOOSE framework [6]. In the present work the effect of solid electrolyte interface (SEI) on the evolution of Li electrodeposits is captured by modeling the GB structures in SEI and diffusion through these GBs. The results from PFM reveal thatthe anisotropic nature of Li presence at the metal/SEI interface leads to uneven electrodeposition at the Li metal surface. In addition, an elastic deformation energy of the Li solid phase is included in the free energy functional of the PFM, which allows for monitoring the stress field evolution and its influence on Li filaments structure evolution. The present results also show that a significant stress is observed at the root of the Li electrodeposits and the triple junction between the GBs.

This observation can guide the development of the experimental strategies for suppression of Li dendrites by lowering the stress field and also provide us more valuable information on the role of SEI as a transport medium, providing more scope for improvement on battery safety and performance.

References:

[1] M.D. Tikekar, S. Choudhury, Z. Tu, L.A. Archer, , Nat. Energy. 1 (2016) 16114.

[2] G. Kresse, J. Furthmüller, Phys. Rev. B.54 (1996) 11169–11186.

[3] P.E. Blöchl, Phys. Rev. B.50 (1994) 17953–17979.

[4] J.P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett.77 (1996) 3865–3868.

[5] V. Yurkiv, T. Foroozan, A. Ramasubramanian, R. Shahbazian-Yassar, F. Mashayek, Electrochim. Acta.265 (2018).

[6] M.R. Tonks, D. Gaston, P.C. Millett, D. Andrs, P., Comput. Mater. Sci.51 (2012) 20–29.