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The enhancement of catalytic activity can be achieved by removing non-active components from the surface of catalyst materials, thereby increasing the accessibility of active sites. In this study, an electrically driven method is described for the removal of non-active phosphorus (P) to optimize the surface composition of iron-nickel phosphide (denoted as P-O-NFF), resulting in the exposure of more active Fe-Ni sites for oxygen evolution reaction (OER). The optimized P-O-NFF electrode exhibits exceptional OER catalytic activity, with an overpotential of 217 mV at 10 mA cm. Furthermore, it demonstrates significant stability, maintaining a 100 % voltage retention rate after 300 h at a high current density of 200 mA cm. The superior performance can be attributed to the disruption of the original crystalline lattice during the electrically driven P dissolution, which leads to the formation of amorphous Fe-Ni hydroxide/oxyhydroxide that enhances active sites exposure. This work offers a simple and effective method for controlling the surface component of catalysts to enhance their catalytic performance, which has the potential to advance industrial water electrolysis technology.
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http://dx.doi.org/10.1016/j.jcis.2024.12.031 | DOI Listing |
ACS Sens
September 2025
Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia with multiple clinical manifestations and complications, such as cardiovascular disease, kidney dysfunction, retinal impairment, and peripheral neuropathy. Continuous and minimally invasive glucose monitoring is essential for effective DM management. Microneedles (MNs)-based sensing platforms offer a promising solution; however, conventional polymeric MNs suffer from limited electrochemical sensitivity due to their insufficient electroactive surface area and inefficient loading of catalytic and enzymatic components.
View Article and Find Full Text PDFAdv Mater
September 2025
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China.
Van der Waals (vdW) layered materials have gained significant attention owing to their distinctive structure and unique properties. The weak interlayer bonding in vdW layered materials enables guest atom intercalation, allowing precise tuning of their physical and chemical properties. In this work, a ternary compound, NiInSe (x = 0-0.
View Article and Find Full Text PDFSmall
September 2025
State Key Laboratory of Functional Materials and Devices for Special Environments Conditions, Xinjiang Key Laboratory of Electronic Information Materials and Devices, Xinjiang Technical Institute of Physics and Chemistry of CAS, Urumqi, 830011, P. R. China.
Owing to its wide bandgap, LaAlO has garnered extensive attention in the field of high-temperature negative temperature coefficient (NTC) thermistors. However, its poor thermal stability and excessively high B value limit the working temperature range. In this work, introducing O 2p and Ni 3d hybrid energy levels into the bandgap is proposed via Ni doping and inducing stacking faults in the crystal structure to narrow the bandgap and enhance aging performance.
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September 2025
Smart Material Research Laboratory, Department of Physics, Indian Institute of Technology Roorkee, Roorkee, 247667, India.
Achieving superior energy storage performance in dielectric materials under low electric fields remains a challenge. Most recent advancements require high fields that limit device applicability. Developing dielectric capacitors with high recoverable energy density (W), efficiency (η), and energy-storage coefficient (W/E) at low/moderate fields is critical for safer, compact, and durable electronics.
View Article and Find Full Text PDFHum Brain Mapp
September 2025
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.
Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.
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