Revealing SEI Morphology: In-Depth Analysis of a Modeling Approach

Abstract

In this article, we present a novel theory for the long term evolution of the solid electrolyte interphase (SEI) in lithium-ion batteries and propose novel validation measurements. Both SEI thickness and morphology are predicted by our model as we take into account two transport mechanisms, i.e., solvent diffusion in the SEI pores and charge transport in the solid SEI phase. We show that a porous SEI is created due to the interplay of these transport mechanisms. Different dual layer SEIs emerge from different electrolyte decomposition reactions. We reveal the behavior of such dual layer structures and discuss its dependence on system parameters. Model analysis enables us to interpret SEI thickness fluctuations and link them to the rate-limiting transport mechanism. Our results are general and independent of specific modeling choices, e.g., for charge transport and reduction reactions. In the near future, automotive and mobile applications demand power storage with large energy and power density. Currently, lithiumion batteries (LIBs) are the technology of choice for devices with these demands. They operate at high cell potentials and offer high specific capacities while providing long lifetimes. The latter is a consequence of the stable chemistry of modern LIB systems. A significant part of this stability can be attributed to the passivation ability of the solid electrolyte interphase (SEI). This thin layer forms between the negative electrode and the electrolyte. Hence contact between these phases is prevented and the continuous reduction of electrolyte molecules is suppressed. These reduction processes occur because the operating potential of the negative electrode lies well below the stability window of the electrolyte.1 They are suppressed because reduction products quickly form the SEI during the first charge of a pristine electrode. The self passivating ability is one of the most important distinctions between a well and a badly performing lithium-ion battery chemistry. It is of such importance because the reduction reactions consume lithium-ions, directly reducing battery capacity. However, a real SEI is not perfectly passivating and electrolyte reduction is never completely suppressed. Consequently, the lifetime of a battery is directly related to the long-term passivating ability of the SEI.Numerous studies on SEI have been conducted since Peled reported on this correlation in 1979.2 Most of these studies are experimental, investigating cycling stability as well as SEI impedance and composition. Theoretical studies are scarce in comparison, despite established methods such as DFT and DFT/MD derivatives. This can be partially explained with the chemical diversity of SEI, which has been investigated by Aurbach et al. for decades. Results are summarized in Refs. 3, 4 and include the study of SEI formation on graphite electrodes in organic solvent mixtures. The most significant finding of this time is that ethylene carbonate (EC) forms a stable SEI on graphite as opposed to propylene carbonate (PC). Another...

Theory of Impedance Spectroscopy for Lithium Batteries

“…Experimental and theoretical studies report that SEI is at least partially porous. 3,19,[43][44][45] Our recent findings suggest that solvent molecules are effectively immobilized within these pores. 46,47 However, this result does not apply to smaller and more mobile lithium ions.…”

Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries

“…New insights for atomistic modeling have been incorporated into continuum models as well. In contrast to the homogenous SEI morphology and single transport mechanism modeling, Single et al 210,211 used the two-layer/two-mechanism model 30,31 to describe the SEI morphology with a continuum model. Both electron conduction and solvent diffusion are modeled as ratedetermining transport mechanisms.…”

Rational Development of Neutral Aqueous Electrolytes for Zinc–Air Batteries

“…In this section, we discuss the computational details of our model, including the initial conditions and loads used for the simulations. More information on this topic, as well as ac omplete list of the physical, chemical, and numerical parameters [13,14,20,21,27,28,42,43,[46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61] implemented in the model, is presented in greater detail in the Supporting Information.…”