To DISP or Not? The Far-Reaching Reaction Mechanisms Underpinning Lithium-Air Batteries.

The short history of research on Li-O batteries has seen a remarkable number of mechanistic U-turns over the years. From the initial use of carbonate electrolytes, that were then found to be entirely unsuitable, to the belief that (su)peroxide was solely responsible for degradation, before the more reactive singlet oxygen was found to form, to the hypothesis that capacity depends on a competing surface/solution mechanism before a practically exclusive solution mechanism was identified. Herein, we argue for an ever-fresh look at the reported data without bias towards supposedly established explanations.

Singlet oxygen formation in non-aqueous oxygen redox chemistry: direct spectroscopic evidence for formation pathways and reliability of chemical probes.

Singlet oxygen (O) formation is now recognised as a key aspect of non-aqueous oxygen redox chemistry. For identifying O, chemical trapping 9,10-dimethylanthracene (DMA) to form the endoperoxide (DMA-O) has become the main method due to its sensitivity, selectivity, and ease of use. While DMA has been shown to be selective for O, rather than forming DMA-O with a wide variety of potentially reactive O-containing species, false positives might hypothetically be obtained in the presence of previously overlooked species.

On the nanoscale structural evolution of solid discharge products in lithium-sulfur batteries using operando scattering.

The inadequate understanding of the mechanisms that reversibly convert molecular sulfur (S) into lithium sulfide (LiS) via soluble polysulfides (PSs) formation impedes the development of high-performance lithium-sulfur (Li-S) batteries with non-aqueous electrolyte solutions. Here, we use operando small and wide angle X-ray scattering and operando small angle neutron scattering (SANS) measurements to track the nucleation, growth and dissolution of solid deposits from atomic to sub-micron scales during real-time Li-S cell operation. In particular, stochastic modelling based on the SANS data allows quantifying the nanoscale phase evolution during battery cycling.