Understanding chemical degradation requires a detailed understanding of how complex, multi-physicochemical mechanisms that take place at several different time and length scales are interrelated. As a result, no comprehensive, physics-based computational modeling framework exists for chemical degradation. Yet understanding chemical degradation is crucial for the performance of a variety of structural and functional materials for energy storage, production, and utilization.
Our study addressed one specific gap: how to integrate interdependent mechanical stress, chemical diffusion, and electrical potential to study degradation mechanisms. We focused on chemical degradation at interfaces in solid-state batteries and successfully demonstrated two objectives. First, we demonstrated how to integrate chemical diffusion and mechanical stress, both by considering stress-dependent diffusion kinetics and diffusion-dependent stresses, on battery materials by combining atomistic and mesoscale approaches. Our work focused on the following battery materials: LiCoO2, Li7La3Zr2O12, and LiFePO4. Second, we demonstrated a scheme for integrating stress-dependent diffusion kinetics with electrical potential to produce a comprehensive and general electrochemomechanical model. This model was tested by predicting concentration profiles under different simulated operating conditions. Our research creates a key first step towards enabling a predictive, physics-based model of chemical degradation.
Our project supported Lawrence Livermore National Laboratory mission focus areas in energy security and scientific discovery and leveraged Livermore's core competencies in high-performance computing, energy and climate, and advanced materials. By demonstrating the feasibility of our three multiscale integration schemes for studying disordered materials and interfaces, the project also built an underlying foundation for capabilities that can be applied broadly across many Laboratory mission spaces.
Heo, T., et al. 2017. Mesoscale Modeling Study of Microstructural Impacts on the Effective Ionic Diffusivity of Solid Electrolytes for Li Batteries." Materials Research Society Fall Meeting, Boston, MA. LLNL-ABS-733792.
Shea, P., et al. 2018. Bay Area Battery Summit, Berkeley, CA. LLNL-POST-759545.
Wang, B., et al. 2018. "Multiscale Modeling of Interfaces in All-Solid-State Li-ion Batteries." 2018 Bay Area Battery Summit: Building Better Batteries, Berkeley, CA, October 2018. LLNL-POST-759543.
Wood, B., et al. 2018. "Understanding and Optimizing Ionic Conductivity in All-Solid-State Batteries Through Multiscale Simulations." Oak Ridge National Laboratory seminar. LLNL-PRES-759804.
Zhan, C., et al. 2018. "Origins and Implications of Interfacial Capacitance Enhancements in C60-Modified Graphene Supercapacitors." ACS Applied Materials & Interfaces 2018, 10, 43, 36860-36865. doi.org/10.1021/acsami.8b10349. LLNL-JRNL-754189.
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