Solid state batteries (SSBs) based on alkali-metal (Li, Na, Mg, etc) chemistry have attracted much attention from both academia and industry in the last decade. They are considered as promising alternatives for conventional Li-ion batteries for a number of important applications (e.g. electrified transportation and grid storage), owing to the enhanced safety properties and potentially much higher energy density. For instance, SSBs with Li metal anodes have the potential for specific energy >500 Wh/kg, energy density >1500 Wh/L, and potential lower cost of <$100/kWh; SSBs with Na metal anode have the potential for specific capacity> 1100 mAh/g, energy density ~ 400-500 Wh/kg, and power density >5 kW/kg and potential lower cost due to abundant raw material reserves on earth. After a decade of extensive research efforts, many novel high-performance solid electrolyte materials have been discovered and reported. So far, there are significant challenges in structure/interface design, characterization, and manufacturing of SSBs. The anodes and cathodes in solid-state could impart significant stresses at interfaces; and the interplay between stresses, electrochemistry, interfacial and layer structures could lead to morphological evolution of the layers to form interphases and chemo-mechanical degradation during cycling. In addition, fast charging such as in automotive applications could drive the SSBs towards early performance degradation with reduced reliability and safety margins. Moreover, manufacturing challenges also impede the practical applications of SSBs towards to technology commercialization.
This symposium aims to provide an interdisciplinary forum for colleagues from both academia and industry, to address the fundamental and technological aspects and the challenges involved in the development of SSB devices and characterizations. Key focus areas of the symposium include: development of new solid electrode materials, new device fabrication methodologies, fast charging of SSBs, in-operando and in-situ characterization of interfaces and layer morphologies, application of artificial intelligence and machine learning concepts for battery diagnostics and estimating the state of charge (SOC) and the state of health (SOH), and multiscale electrochemical modeling to analyze the performance and safety aspects of SSBs, manufacture methods and life cycle analysis, etc.
Hui (Hailey) Wang
University of Louisville
Pacific Northwest National Laboratory
Energy Processes and Materials Division
University of California Riverside
Department of Mechanical Engineering
Hongli (Julie) Zhu
Mechanical and Industrial Engineering