Electrochemical Performance of Na3V2(PO4)2F3 Electrode Material in a Symmetric Cell

Advantages of a Solid Solution over Biphasic Intercalation for Vanadium-Based Polyanion Cathodes in Na-Ion Batteries

The efficient operation of metal-ion batteries in harsh environments, such as at temperatures below -20 °C or at high charge/discharge rates required for EV applications, calls for a careful selection of electrode materials. In this study, we report advantages associated with the solid solution (de)intercalation over the two-phase (de)intercalation pathway and identify the main sources of performance limitations originating from the two mechanisms. To isolate the (de)intercalation pathway as the main variable, we focused on two cathode materials for Na-ion batteries: a recently developed KTiOPO4-type NaVPO4F and a well-studied Na3V2(PO4)2F3. These materials have the same elemental composition, operate within the same potential range, and demonstrate very close ionic diffusivities, yet follow different (de)intercalation routes. To avoid any interpretation uncertainties, we obtained these materials in the form of particles with merely identical morphology and size. A detailed electrochemical study revealed a much lower capacity and energy density retention for phase-transforming Na3V2(PO4)2F3 compared to NaVPO4F, which exhibits a single-phase behavior over a wide range of Na concentrations. The reasons for the inferior rate capability and temperature tolerance for the phase-separating Na3V2(PO4)2F3 material should be affiliated with slow phase boundary propagation. We hope that the comprehensive information on limiting factors provided for both mechanisms is useful for the further optimization of electrode materials toward a new generation of high-power and low-temperature metal-ion batteries.

An Efficient Methodology Combining K-Means Machine Learning and Electrochemical Modelling for the Determination of Ionic Diffusivity and Kinetic Properties in Battery Electrodes

This paper presents an innovative and efficient methodology for the determination of the solid-state diffusion coefficient in electrode materials with phase transitions for which the assumption of applying the well-known formula from the work of Weppner et al. is not satisfied. This methodology includes a k-means machine learning screening of Galvanostatic Intermittent Titration Technique (GITT) steps, whose outcomes feed a physics-informed algorithm, the latter involving a pseudo-two-dimensional (P2D) electrochemical model for carrying out the numerical simulations. This methodology enables determining, for all of the 47 steps of the GITT characterization, the dependency of the Na⁺ diffusion coefficient as well as the reaction rate constant during the sodiation of an NVPF electrode to vary between 9 × 10-18 and 6.8 × 10-16 m²·s^-1 and between 2.7 × 10-14 and 1.5 × 10-12 m^2.5·mol^-0.5·s^-1, respectively. This methodology, also validated in this paper, is (a) innovative since it presents for the first time the successful application of unsupervised machine learning via k-means clustering for the categorization of GITT steps according to their characteristics in terms of voltage; (b) efficient given the considerable reduction in the number of iterations required with an average number of iterations equal to 8, and given the fact the entire experimental duration of each step should not be simulated anymore and hence can be simply restricted to the part with current and a small part of the rest period; (c) generically applicable since the methodology and its physics-informed algorithm only rely on "if" and "else" statements, i.e., no particular module/toolbox is required, which enables its replication and implementation for electrochemical models written in any programming language.

Advanced Materials for Electrochemical Energy Storage: Lithium-Ion, Lithium-Sulfur, Lithium-Air and Sodium Batteries

The intention behind this Special Issue was to assemble high-quality works focusing on the latest advances in the development of various materials for rechargeable batteries, as well as to highlight the science and technology of devices that today are one of the most important and efficient types of energy storage, namely, lithium-ion, lithium-sulfur, lithium-air and sodium-ion batteries [...].