Abstract

A broad variety of materials are currently the subject of research for energy applications. For example, in new battery technologies, a very topical issue and a key societal challenge [1]. Many different electrolytes have been proposed for use in next-generation solid state batteries, with the potential to provide greener, more efficient energy storage. A key stumbling block in proposed electrolytes is often low conductivity. Therefore, when considering a new material, the first step is to understand ion transport. The Arrhenius law is ubiquitous in the physical sciences. It describes how an observable property scales with temperature, T, as exp(±A/T) for a constant A, interpreted as an activation energy. Often transport coefficients are well-described by an Arrhenius fit. However, there are many exceptions, making it difficult to extract an activation energy from macroscopic transport properties. One reason for non-Arrhenius behaviour is correlated motion [2]. For example, the diffusion of individual ions depends upon the diffusion of neighbouring ions. Ions may also become trapped due to local structure and undergo movement but in a back-and-forth motion that does not contribute to overall transport. Using methods developed for supercooled liquids [3], we identify ion ‘jumps’, particularly those that are productive for transport, and correlated motion. The method enables us to extract the true underlying activation energy from diffusion data and recover the Arrhenius law. The methods can be demonstrated for low-dimensional-networked Li-rich anti-perovskites, potential solid electrolytes [4]. References [1] Faraday Insights – Solid-State Batteries: The Technology of the 2030s but the Research Challenge of the 2020s, Issue 5: February 2020 [2] NM Vargas-Barbosa and B Roling, ChemElectroChem 7:367–385 (2020) [3] VK de Souza and DJ Wales, J. Chem. Phys., 129:164507 (2008) [4] AC Coutinho Dutra et al, Energy Adv. 2:653–666 (2023)