Uncertainty Quantification Analysis on Mechanical Properties of the Structured Silicon Anode via Surrogate Models

Abstract

Silicon anode is the most promising candidate for next generation lithium ion batteries. A major drawback limiting its application is the significant volume change during lithiation-delithiation process, which may cause material pulverization and capacity degradation. A novel 3D bi-continuous nanoporous structured Si anode, consisting of porous metal scaffolds and thin Si coating layers, was proven to be an effective method to tackle this issue; however, uncertainty and non-uniformity, inherited from the fabrication process, will be inevitably introduced as important considerations for the performances of the Si anode. In this paper, uncertainty quantification (UQ) analysis is performed on the structured Si anode system to evaluate the influences of various design variables on its performances and to find the design optimization strategy. The biggest hurdle in the UQ study is the computational cost; to mitigate this challenge, a Gaussian Process based surrogate model is constructed using finite element simulation results as training data. It is found that the performances of the anode are rather sensitive to the geometric parameters, i.e. scaffold non-uniformity and Si layer thickness, whereas the mechanical properties of the materials are relatively less important. Furthermore, the optimal design is proposed to minimize the stress concentration in the Si anode.