Batteries & Supercaps最新文献

A sulfide solid electrolyte was synthesized using a solution-phase approach via the dissolution of Li₃PS₄ in ethanol followed by heat treatment (90–300 °C). This method yielded an electrolyte with a maximum lithium-ion conductivity of 1.7×10⁻⁵ S cm⁻¹ at 200 °C (down to 25 % of the pristine Li₃PS₄); however, increasing the heating temperature resulted in a significant decrease in conductivity. Nuclear magnetic resonance spectroscopy revealed the decomposition of the PS₄³⁻ unit into P₂S_x dimers (P₂S₇⁴⁻ and P₂S₆⁴⁻) at high temperatures. X-ray absorption spectroscopy further confirmed a core-shell structure in the solution-phase-synthesized electrolyte, with an enriched shell of oxygen-substituted P(S/O)_x phases. Both the P₂S_x dimers in the core and the oxygen-rich shell may have contributed to the reduction in lithium-ion conductivity. Moreover, the oxygen-rich shell unexpectedly suppressed undesirable side reactions at the solid electrolyte/cathode interface. This study demonstrates the functionalization of solution-phase synthesis for sulfide solid electrolytes from ethanol, with a trade-off between conductivity and interface stability. Further optimizing the heat treatment process and shell engineering are promising avenues for enhancing the performance of all-solid-state batteries.

Calender process is important to improve the mechanical and electrochemical properties of cathode materials. To explore pressure effect on structure and resistance of electrode powder, the morphology and surface area of lithium cobalt oxide (LCO) powder under different pressure are investigated. Meanwhile, the real-time stress, density, and conductivity of LCO powder upon compaction are tested by a self-made detection system. Moreover, the battery performance of LCO powder after compaction is compared in coin cells. This work elucidates the relationship between compaction density, powder resistance, and electrochemical performance of cathode materials for lithium-ion batteries.

This work compares a state of the art data-driven model to predict the state of health (SoH) in lithium ion batteries with a new prediction model based on the mechanistic framework. The mechanistic approach attributes the degradation to individual components such as loss of available capacity on each electrode as well as loss of cyclable lithium. By combining the mechanistic framework with data-driven models for the component losses based on a design of experiment, we achieve a cycle aging model that can predict capacity degradation as well as degradation-induced changes to the discharge potential curve. Using this cycle aging model alongside with a semi-empirical calendar aging model, we present a holistic aging model that we validate on independent validation tests containing time-variant load profiles. While the purely data-driven model is better at predicting the SoH, the mechanistic model clearly has it advantages in a deeper understanding that can potentially enhance the current methods of tracking and updating the characteristic open-circuit voltage curve over lifetime.

The Cover Feature displays an operator using our mixed-reality holographic notebook to report the manufacturing parameters he is intending to use in a battery pilot line. Our technology paves the way to breaking the barrier between the digital and the real worlds, for maximum efficiency of the operator‘s work. More information can be found in the Concept by A. A. Franco and co-workers (DOI: 10.1002/batt.202400042).

The Front Cover shows a rendering of a multi-layer sulfide-based solid-state battery with the symbols in the top right-hand corner representing part of a possible process chain for manufacturing such a battery. A multi-level component manufacturing route as describe in the publication is shown. More information can be found in the Research Article by C. Singer, L. Wach and co-workers (DOI: 10.1002/batt.202400142)