Operando Monitoring of Internal Li-Driven Stress in Solid-State and Liquid Battery Electrodes Enabled by Optical Sensing

Batteries are nowadays the most efficient mean of energy storage and play a key role in the energy transition from fossil fuels to renewable energies. Particularly Li-ion batteries are the leading technology in a wide range of strategic industries, going from portable electronics to electric vehicles. However, after decades of improvement in terms of power density and lifetime, a ceiling in its development is foreseen in the near future. In this context, solid-state batteries (SSBs) are enjoying a growing interest as the next-generation of batteries owing to their theoretically enhanced safety and energy density. However, the excitement around SSBs is partially tarnished by a number of unresolved issues that still prevent their commercialization. One of them regards their higher propensity to mechanical degradation compared to their Li-ion counterparts due to the stiff nature of solid electrolytes. Hence, the internal stress monitoring within the device becomes crucial. So far, this has been done from outside of the battery, via external force sensors recording the stress evolution at cell level and thus providing an incomplete picture of stresses at component level. Inspired by the use of integrated optical fibers with Fiber Bragg Grating (FBG) sensors into large composite structures (such as bridges, railways and aircrafts) for health structural monitoring, we here extend this approach from civil engineering to the battery field. In this work, we demonstrate for the first time a strategy based on optical sensing to monitor local Li-driven anisotropic stresses in solid-state and liquid batteries directly from the inside and at electrode level. For proof-of-concept purpose, we studied Li-driven stress evolution in liquid cells with Li-alloying electrodes (InLi_x and Si) and in all-solid state Li-ion batteries for InLi_x electrodes as well. Additionally, for the ASSB system we could also track its response as a function of the external cycling pressure applied for battery operation. In both cases we followed the optical signal which was further translated into stress and correlated with the electrochemistry. These findings are timely, as they open a new playground for developing internal diagnostic techniques devoted to explain, predict and prevent mechanical failure of liquid and solid-state batteries. In the longer run, this work will also bring guidance for improved electrode and cell design as well as for ensuring battery operation within optimal conditions, thus enhancing its performance and lifetime. Lastly, this work also aims to encourage interdisciplinary work in order to expand the search for solutions for battery systems beyond the battery and material communities.