Health diagnosis and recuperation of aged Li-ion batteries with data analytics and equivalent circuit modeling.

Battery health assessment and recuperation play crucial roles in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms, it is challenging to estimate battery health and devise an effective strategy for cell rejuvenation. This paper presents aging and reconditioning experiments of 62 commercial lithium iron phosphate cells, which allow us to use machine learning models to predict cycle life and identify important indicators of recoverable capacity.

Closed-Loop Multi-Objective Optimization for Cu-Sb-S Photo-Electrocatalytic Materials' Discovery.

Copper antimony sulfides are regarded as promising catalysts for photo-electrochemical water splitting because of their earth abundance and broad light absorption. The unique photoactivity of copper antimony sulfides is dependent on their various crystalline structures and atomic compositions. Here, a closed-loop workflow is built, which explores Cu-Sb-S compositional space to optimize its photo-electrocatalytic hydrogen evolution from water, by integrating a high-throughput robotic platform, characterization techniques, and machine learning (ML) optimization workflow.

Machine learning-assisted optimization of multi-metal hydroxide electrocatalysts for overall water splitting.

Green hydrogen produced electrochemical water splitting is a suitable candidate to replace emission-intensive fuels. However, the successful widespread adoption of green hydrogen is contingent on the development of low-cost, earth-abundant catalysts. Herein, machine learning models built on experimental data were used to optimize the precursor ratios of hydroxide-based electrocatalysts, with the objective of improving the product's electrocatalytic performance for overall water splitting.

Noble metal alloy thin films by atomic layer deposition and rapid Joule heating.

Metal alloys are usually fabricated by melting constituent metals together or sintering metal alloy particles made by high energy ball milling (mechanical alloying). All these methods only allow for bulk alloys to be formed. This manuscript details a new method of fabricating Rhodium-Iridium (Rh-Ir) metal alloy films using atomic layer deposition (ALD) and rapid Joule heating induced alloying that gives functional thin film alloys, enabling conformal thin films with high aspect ratios on 3D nanostructured substrate.