Transition metal oxides show great promise as Earth-abundant catalysts for the oxygen evolution reaction in electrochemical water splitting. However, progress in the development of highly active oxide nanostructures is hampered by a lack of knowledge of the location and nature of the active sites. Here we show, through atom-resolved scanning tunnelling microscopy, X-ray spectroscopy and computational modelling, how hydroxyls form from water dissociation at under coordinated cobalt edge sites of cobalt oxide nanoislands. Surprisingly, we find that an additional water molecule acts to promote all the elementary steps of the dissociation process and subsequent hydrogen migration, revealing the important assisting role of a water molecule in its own dissociation process on a metal oxide. Inspired by the experimental findings, we theoretically model the oxygen evolution reaction activity of cobalt oxide nanoislands and show that the nanoparticle metal edges also display favourable adsorption energetics for water oxidation under electrochemical conditions.
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http://dx.doi.org/10.1038/ncomms14169 | DOI Listing |
Sci Rep
January 2025
Faculty of Biotechnology, October University for Modern Sciences and Arts (MSA), 6th of October City, Egypt.
Nanotherapy has emerged as a promising strategy for the targeted and efficient treatment of melanoma, the most aggressive and lethal form of skin cancer, with minimized systemic toxicity. However, the therapeutic efficacy of cobalt oxide nanoparticles (CoONPs) in melanoma treatment remains unexplored. This study aimed to assess the therapeutic potential of CoONPs in melanoma treatment by evaluating their impact on cell viability, genomic DNA and mitochondrial integrity, reactive oxygen species (ROS) generation and apoptosis induction in melanoma A-375 cells.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Department of Battery and Chemical Engineering, Hanyang University, Ansan, Gyeonggi-do 15588, Republic of Korea.
Designing and constructing hierarchically structured materials with heterogeneous compositions is the key to developing an effective catalyst for overall water-splitting applications. Herein, we report the fabrication of hollow-structured selenium-doped nickel-cobalt hybrids on carbon paper as a self-supported electrode (denoted as Se-Ni|Co/CP, where Ni|Co hybrids consist of nickel-cobalt alloy-incorporated nickel-cobalt oxide). The procedure involves direct growth of zeolitic imidazolate framework-67 (ZIF-67) on bimetal-based nickel-cobalt hydroxide (NiCoOH) electrodeposited on CP, followed by selenous etching and pyrolysis to obtain the final Se-Ni|Co/CP electrocatalytic system.
View Article and Find Full Text PDFSmall Methods
January 2025
Department of Physics, Tamkang University, Tamsui, 25137, Taiwan.
This investigation explores the potential of co-incorporating nickel (Ni) and cobalt (Co) into copper oxide (CuO) nanostructures for bifunctional electrochemical charge storage and oxygen evolution reactions (OER). A facile wet chemical synthesis method is employed to co-incorporate Ni and Co into CuO, yielding diverse nanostructured morphologies, including rods, spheres, and flake. The X-ray diffraction (XRD) and Raman analyses confirmed the formation of NiCo-CuO nanostructure, with minor phases of nickel oxide (NiO) and cobalt tetraoxide (CoO).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biology, Rasht Branch, Islamic Azad University, Rasht, Iran.
The current chemotherapy treatments for liver cancer have shown limited effectiveness. Therefore, there is an urgent need to develop new drugs to combat this disease more effectively. This study reports synthesis of cobalt oxide nanoparticles coated with glucose, and conjugated with Ellagic acid.
View Article and Find Full Text PDFMicrosc Microanal
January 2025
Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin 14195, Germany.
In catalysis research, the amount of microscopy data acquired when imaging dynamic processes is often too much for nonautomated quantitative analysis. Developing machine learned segmentation models is challenged by the requirement of high-quality annotated training data. We thus substitute expert-annotated data with a physics-based sequential synthetic data model.
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