Modeling and Simulation of Chemo-Elasto-Plastic Deformation in Silicon Battery Particles and Surrounding Solid-Electrolyte Interphase

Core Concepts

The core message of this article is to investigate the influence of different elastic strain definitions on the numerical simulation of the chemo-mechanical coupling between silicon battery particles and their surrounding solid-electrolyte interphase (SEI). The authors demonstrate that the choice of the elastic strain definition, particularly the logarithmic Hencky strain, is crucial for the stability and success of the numerical simulation, especially when incorporating plastic deformation in the SEI.

Abstract

This article presents a thermodynamically consistent chemo-elasto-plastic model for the coupled behavior of spherical symmetric amorphous silicon (aSi) particles and their surrounding spherical symmetric solid-electrolyte interphase (SEI) during battery cycling. The authors investigate the influence of the choice of the elastic strain definition on the numerical simulation of this coupled system.
The key highlights and insights are:

The authors start with a single particle setting and then extend the model to include the surrounding SEI. They consider two different definitions for the elastic strain tensor: the Green-St. Venant (GSV) strain and the logarithmic Hencky strain.

Using the GSV strain definition for the purely elastic SEI case leads to the numerical simulation aborting around 34% state of charge (SOC) due to a large increase in the tangential Cauchy stress at the particle-SEI interface.

In contrast, the logarithmic Hencky strain approach stabilizes the numerical simulation and allows for the successful incorporation of both rate-independent and rate-dependent plastic deformation in the SEI.

The rate-dependent plastic deformation in the SEI results in a typical stress-overrelaxation, which is also observed in experimental measurements of the electric field and can explain the voltage hysteresis of silicon anodes.

The authors demonstrate the efficiency of their adaptive numerical algorithm combined with higher-order finite elements on a uniform mesh for the coupled chemo-elasto-plastic problem.

The article provides valuable insights into the importance of the choice of the elastic strain definition for the numerical simulation of chemo-mechanically coupled battery active particles and their surrounding SEI, especially when considering plastic deformation.

Stats

The particle and SEI material parameters used in the simulations are provided in Table 2 of the referenced work [9].

Quotes

"Using the logarithmic strain approach, we can comfortably add a rate-independent and a rate-dependent plastic deformation for the SEI without increasing the system of equation for the plastic part of the deformation gradient [4, 9]."
"The rate-dependent case results is a typical stress-overrelaxation, which is also found in measurements of the electric field [6] and can confirm the hypothesis of [5]."

Key Insights Distilled From

Comparison of Different Elastic Strain Definitions for Largely Deformed SEI of Chemo-Mechanically Coupled Silicon Battery Particles

by Raph... at arxiv.org 04-03-2024

https://arxiv.org/pdf/2404.01884.pdf

Deeper Inquiries

How can the proposed chemo-elasto-plastic model be extended to account for the heterogeneous and anisotropic nature of the SEI layer

To extend the chemo-elasto-plastic model to account for the heterogeneous and anisotropic nature of the SEI layer, several modifications and additions can be made.

Heterogeneity:

Introduce spatially varying parameters in the model to capture the heterogeneity of the SEI layer. This can include variations in mechanical properties, diffusivity, and chemical reactions across different regions of the SEI.
Implement a multi-phase approach to represent different components or layers within the SEI, each with its own set of governing equations and properties.
Incorporate experimental data or characterization techniques to inform the model about the heterogeneous nature of the SEI.

Anisotropy:

Include anisotropic material properties in the model to account for the directional dependence of mechanical behavior in the SEI layer.
Utilize tensorial representations for properties like stiffness, strength, and diffusivity to capture anisotropic effects accurately.
Consider the orientation of the SEI layer concerning the electrode surface and incorporate this information into the model equations.

By incorporating these aspects, the extended model can provide a more realistic representation of the complex nature of the SEI layer in silicon-based battery anodes.

What are the implications of the observed stress-overrelaxation in the rate-dependent plastic SEI on the long-term performance and degradation of silicon-based battery anodes

The observed stress-overrelaxation in the rate-dependent plastic SEI can have significant implications for the long-term performance and degradation of silicon-based battery anodes.

Performance:

Stress-overrelaxation can lead to non-uniform mechanical responses in the SEI layer, affecting the overall structural integrity of the anode.
It may result in localized damage or failure within the SEI, impacting the efficiency of lithium-ion transport and leading to capacity fade or voltage hysteresis.

Degradation:

The cyclic stress-overrelaxation can accelerate mechanical degradation processes in the SEI, such as crack propagation or delamination, reducing the overall cycle life of the battery.
It can contribute to the formation of irreversible SEI components, increasing impedance and reducing the anode's charge/discharge efficiency over time.

Understanding and mitigating stress-overrelaxation in the SEI layer is crucial for enhancing the long-term stability and performance of silicon-based battery anodes.

Can the insights from this study be applied to other battery chemistries or electrode materials that undergo significant volume changes during cycling

The insights from this study can be applied to other battery chemistries or electrode materials that undergo significant volume changes during cycling, such as transition metal oxides or sulfides.

Model Adaptation:

The chemo-elasto-plastic model framework can be adjusted to accommodate the specific electrochemical and mechanical properties of different electrode materials.
Parameters related to volume expansion, stress generation, and SEI formation kinetics can be tailored to the characteristics of the new materials.

Performance Prediction:

By applying similar modeling approaches, researchers can predict the mechanical behavior, SEI evolution, and long-term performance of alternative battery chemistries.
The study's findings on stress development, plastic deformation, and rate-dependent effects can guide the design and optimization of electrode materials beyond silicon.

Overall, the fundamental principles and numerical techniques demonstrated in this study can serve as a foundation for investigating and improving the performance of various battery chemistries with dynamic volume changes.