Chemomechanical modeling of lithiation-induced failure in high-volume-change electrode materials for lithium ion batteries

By Sulin Zhang. npj Computational Materials, 2017

136 citations recorded by the source corpus.

The rapidly increasing demand for efficient energy storage systems in the last two decades has stimulated enormous efforts to the development of high-capacity, high-power, durable lithium ion batteries. Inherent to the high-capacity electrode materials is material degradation and failure due to the large volumetric changes during the electrochemical cycling, causing fast capacity decay and low cycle life. This review surveys recent progress in continuum-level computational modeling of the degradation mechanisms of high-capacity anode materials for lithium-ion batteries. Using silicon (Si) as an example, we highlight the strong coupling between electrochemical kinetics and mechanical stress in the degradation process. We show that the coupling phenomena can be tailored through a set of materials design strategies, including surface coating and porosity, presenting effective methods to mitigate the degradation. Validated by the experimental data, the modeling results lay down a foundation for engineering, diagnosis, and optimization of high-performance lithium ion batteries.

Subfields: Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/2d8754a6042f34adcf1ab1804cc1125662fc7b06

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. K. Zhao
2. Feng Lin

In Mechanical Engineering

1. Fei Yin
2. Peter Cloetens
3. Rong Xu
4. Yijin Liu
5. Pengfei Liu
6. K. Zhao
7. Yang Yang
8. Feng Lin

Citations in the corpus

• Heterogeneous Damage in Li-Ion Batteries: Experimental Analysis and Theoretical Modeling (2019, background): “Several recent papers summarized the stateof-the-art of the field ( McDowell et al., 2016; Xu and Zhao, 2016a; Zhao and Cui, 2016; Zhang, 2017; Zhang et al., 2017; Wang et al., 2018; Zhao et al., 2019 ).”