Co/Ce-MOF-Derived Oxygen Electrode Bifunctional Catalyst for Rechargeable Zinc-Air Batteries.

Improving the practicality of rechargeable zinc-air batteries relies heavily on the development of oxygen electrode catalysts that are low-cost, durable, and highly efficient in performing dual functions. In the present study, a catalyst with atomic Ce and Co distribution on a nitrogen-doped carbon substrate was prepared by doping the rare earth elements Ce and Co into a metal-organic framework precursor. Rare earth element Ce, known for its unique structure and excellent oxygen affinity, was utilized to regulate the catalytic activity.

Machine Learning-Assisted Study of RENC-Doped Graphene as Potential Electrocatalysts for Oxygen Electrode Reactions.

In the application of renewable energy, the oxidation-reduction reaction (ORR) and oxygen evolution reaction (OER) are two crucial reactions. Single-atom catalysts (SACs) based on metal-doped graphene have been widely employed due to their high activity and high atom utilization efficiency. However, the catalytic activity is significantly influenced by different metals and local coordination, making it challenging to efficiently screen through either experimental or density functional theory (DFT) calculations.

Mechanistic study of Eu single atoms occupying four vacancy centers as potential electrocatalysts for the oxygen reduction reaction.

The oxygen reduction reaction (ORR) on the oxygen electrode plays a critical role in rechargeable metal-air batteries, and the development of electrochemical energy storage and conversion technologies for the ORR is of great significance. In this study, the catalytic performance of rare earth-doped graphene (EuNC-Gra) as an electrocatalyst for the ORR was investigated. The results showed that a majority of the catalysts exhibited good ORR catalytic activity under acidic conditions, with some approaching or even surpassing commercial Pt-based catalysts ( = 0.

Evaluating the Oxygen Electrode Reactions of La Single-Atom Catalysts with the N/C Coordination Effect.

There is a growing demand for bifunctional electrocatalysts for oxygen electrodes in rechargeable metal-air batteries. This article investigates the bifunctional activity of La single-atom catalysts with N/C coordination (LaNC@Gra) using density functional theory (DFT). The augmentation of N coordination will result in enhanced synthetic stability.

A Lightweight Hybrid Model Using Multiscale Markov Transition Field for Real-Time Quality Assessment of Photoplethysmography Signals.

Objective: The proliferation of wearable devices has escalated the standards for photoplethysmography (PPG) signal quality. This study introduces a lightweight model to address the imperative need for precise, real-time evaluation of PPG signal quality, followed by its deployment and validation utilizing our integrated upper computer and hardware system.

Methods: Multiscale Markov Transition Fields (MMTF) are employed to enrich the morphological information of the signals, serving as the input for our proposed hybrid model (HM).

Biometric recognition based on scalable end-to-end convolutional neural network using photoplethysmography: A comparative study.

Photoplethysmography (PPG), as one of the most widely used physiological signals on wearable devices, with dominance for portability and accessibility, is an ideal carrier of biometric recognition for guaranteeing the security of sensitive information. However, the existing state-of-the-art methods are restricted to practical deployment since power-constrained and compute-insufficient for wearable devices. 1D convolutional neural networks (1D-CNNs) have succeeded in numerous applications on sequential signals.