Benchmarking of Coatings for Cathode Active Materials in Solid-State Batteries Using Surface Analysis and Reference Electrodes.

Fast and reliable evaluation of degradation and performance of cathode active materials (CAMs) for solid-state batteries (SSBs) is crucial to help better understand these systems and enable the synthesis of well-performing CAMs. However, there is a lack of well-thought-out procedures to reliably evaluate CAMs in SSBs. Current approaches often rely on X-ray photoelectron spectroscopy (XPS) for the evaluation of degradation.

Artificial Intelligence Applied to Battery Research: Hype or Reality?

This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily understandable, review of general interest to the battery community. It addresses the concepts, approaches, tools, outcomes, and challenges of using AI/ML as an accelerator for the design and optimization of the next generation of batteries─a current hot topic.

Electrochemical assessments of droplet contents in microfluidic channels. Application to the titration of heterogeneous droplets.

Series of aqueous droplets containing redox species were generated on-demand in a microfluidic channel and detected downstream by an electrochemical cell. Depending on the cell geometry, amperometric detections were performed to simultaneously determine the velocity, volume and content of circulating droplets in oil. Volumes and velocities were estimated from specific transition times on the chronoamperometric responses, while charge were evaluated from current integration.