Swiss Ai Research Overview Platform
All-solid-state batteries (ASSBs) are receiving considerable attention from the battery community mainly due to their capability of drastically enhancing the safety and increasing the energy density by enabling the use of metallic anodes compared to the existing lithium-ion batteries (LIBs). Despite these conspicuous advantages, ASSBs are still at research stage, leaving a substantial gap before practical adoption. Main challenge with ASSBs lies in their inferior rate performance and long-term cyclability, both primarily originating from the destabilization of electrode-electrolyte interface and the creation and propagation of mechanical stress. Energy density should also be carefully evaluated, and a well-known approach to compensate for it, is to use lithium (Li) metal anodes. Whereas individual state-of-the-art solid electrolytes offer high ionic conductivities enough for cell operation, once assembled, the cell performance is mostly not as good as expected, indicating the importance and challenge of particle-to-particle interface. Once electrolyte and active material particles are in contact, (electro-) chemical reactions take place leading to a space-charge effect build a lithium ion depleted layer, imposing a barrier for Li ion transport. The complexity of the problem necessitates an interdisciplinary research approach to tackle inferior cell performance of ASSBs and establish a fundamental understanding on the interface and morphology problems. In this direction, here, we propose a systematic strategy targeting the interface engineering of sulfide-based solid electrolytes (SEs), high voltage Ni-rich layered cathode active materials (CAMs) and Li-metal anodes. The choice of sulfide SEs arise from the consensus that sulfide SEs are suitable and a unique material for good interface contact due to their ductile mechanical properties and ability to be cold pressed. Our synergistic effort involves in-depth understanding of interfacial reactions guided by advanced diagnostics and machine-learning driven atomic scale modeling to achieve both thermodynamic and chemical stability through (1) Coskun group@UniFr, AC: the design and synthesis of elastic polymeric binders and surface stabilization of sulfide electrolytes and membrane coating on the Li-metal surface. (2) El Kazzi group@PSI, MEK: Surface and bulk operando analysis and characterization of electrochemical cells and the identification of interfacial reaction byproducts and intermediates (3) Ceriotti group@EPFL, MC: Structure, stability and reactivity of SE from machine-learning accelerated molecular simulations and (4) Choi group@SNU, JWC: the advanced electrochemical characterization of battery electrodes, optimization of cell conditions and testing battery electrodes at industrially relevant cell conditions. Accordingly, the specific five work packages (WPs) for the project involve (1) the development of solution-processed electrode coating using elastic binders and stabilization of SEs (AC) guided by machine learning (MC), (2) optimization of Ni-rich layered cathode active materials (JWC & MEK), (3) protection and interface optimization of Li-free anodes (AC, JWC), (4) characterization of electrodes using operando analytic tools (MEK, MC) and finally (5) demonstration of 2 Ah prototype cell (JWC, AC, MEK). Critically, the development of individual electrode components, machine learning and operando analyses will be intimately linked to identify interfacial issues and the solutions. In particular, the design for polymeric binders and electrolyte themselves as well as their interaction with active electrode materials will enable breakthroughs for the development of high performance ASSBs comparable to that of current LIBs.