NSF-DFG MISSION: Surface analysis & Correlative imaging using Operando Secondary Ion Mass Spectrometry - SCOPE-SIMS

• Applicant: Professor Dr. Marcus Rohnke
• Subject Area: Physical Chemistry of Solids and Surfaces, Material Characterisation
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 542354924

Electrochemical devices, including batteries, fuel cells, and solar cells, are critical for global energy needs. To optimize their performance, a comprehensive understanding of their chemical processes, both desired and undesired, is essential. While conventional electrochemical measurements offer valuable insights, they can't capture real-time chemical processes occurring at interfaces within i.e. batteries. Post-mortem analyses are limited in terms of repetition and potential sample alterations. In recent years, operando methods have been developed to address these limitations. Among these, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) stands out as a highly sensitive surface analysis technique, enabling a deeper understanding of electrode degradation processes for advancing the next-generation of battery materials. This proposal aims to advance the application of ToF-SIMS for in situ and operando studies of all-solid-state batteries (ASSBs), a promising next-generation energy storage technology known for its high energy density and enhanced safety. The research focuses on two model systems: a cathode composed of NCM (Lithium-Nickel-Cobalt-Manganese) and a silicon (Si) anode, both combined with sulfide-based solid electrolytes. The performance of ASSBs is significantly influenced by the properties of the solid-state electrolyte, including ionic conductivity, mechanical stability, and interfacial compatibility. Our findings will involve three specific tasks: i) operando ToF-SIMS method development, via the design of an integrated electrochemical cell; ii) benchmarking operando results with post-mortem electrochemical testing and molecular-level simulations; and iii) application of machine learning algorithms to correlate system properties from SIMS spectra to observed electrochemical performance. The goal is to use operando SIMS, combined with computational models and machine learning, to optimize each component, including the anode, cathode, and electrolyte, by elucidating the interfacial chemical reactivity governing electrochemical performance. By advancing the understanding of ASSB interfacial characteristics and degradation processes, this research directly contributes to the development of new energy technologies. Furthermore, the project's focus on operando analysis using cutting-edge techniques like ToF-SIMS has broader implications for materials science and surface analysis methods. The development of advanced data analysis tools has the potential to benefit various fields by enabling the extraction of physical insights from complex datasets. Additionally, the collaborative effort between Rice University and Giessen University allows for the exchange of knowledge and expertise, promoting international collaboration in research and education.

• DFG Programme: Research Grants
• International Connection: USA
• Cooperation Partners: Professorin Sinbani Lisa Biswal, Ph.D.; Professor Dr. Thomas P. Senftle