Revisiting Ultrafast Dynamics in Carbonate-Based Electrolytes for Li-Ion Batteries: Clarifying 2D-IR Cross-Peak Interpretation

J Phys Chem B. 2023 Nov 9;127(44):9566-9574. doi: 10.1021/acs.jpcb.3c05480. Epub 2023 Oct 31.

Abstract

Understanding chemical exchange in carbonate-based electrolytes employed in Li-ion batteries (LIBs) is crucial for elucidating ion transport mechanisms. Ultrafast two-dimensional (2D) IR spectroscopy has been widely used to investigate the solvation structure and dynamics of Li-ions in organic carbonate-based electrolytes. However, the interpretation of cross-peaks observed in picosecond carbonyl stretch 2D-IR spectra has remained contentious. These cross-peaks could arise from various phenomena, including vibrational couplings between neighboring carbonyl groups in the first solvation shell around Li-ions, vibrational excitation transfers between carbonyl groups in distinct solvation environments, and local heating effects. Therefore, it is imperative to resolve the interpretation of 2D-IR cross-peaks to avoid misinterpretations regarding ultrafast dynamics found in LIB carbonate-based electrolytes. In this study, we have taken a comprehensive investigation of carbonate-based electrolytes utilizing 2D-IR spectroscopy and molecular dynamics (MD) simulations. Through meticulous analyses and interpretations, we have identified that the cross-peaks observed in the picosecond 2D-IR spectra of LIB electrolytes predominantly arise from intermolecular vibrational excitation transfer processes between the carbonyl groups of Li-bound and free carbonate molecules. We further discuss the limitations of employing a picosecond 2D-IR spectroscopic technique to study chemical exchange and intermolecular vibrational excitation transfer processes, particularly when the effects of the molecular photothermal process cannot be ignored. Our findings shed light on the dynamics of LIB electrolytes and resolve the controversy related to 2D-IR cross-peaks. By discerning the origin of these features, we could provide valuable insights for the design and optimization of next-generation Li-ion batteries.