Tuning the Hydrogen Bond Network Inside the Helmholtz Plane for Industrial Hydrogen Evolution DOI Creative Commons
Xinyu Chen, Bianjing Sun, Qunliang Song

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

Abstract The role of the hydrogen bond network (HBN) within Helmholtz plane (HP) in regulating evolution kinetics for catalyst development remains ambiguous owing to lack fundamental understanding. Herein, leveraging ab initio molecular dynamics simulations, it is discovered that introducing weak metal bonds Ru/RuO 2 remarkably reshapes HBN. Subsequently, nanosheets loaded with single Ga atoms (Ga SA ‐Ru/RuO ) are successfully synthesized using a one‐step annealing strategy. In situ characterizations and theoretical calculations demonstrate atomic electric field generated by Ru─Ga can further improve proportion 4‐coordinated hydrogen‐bonded water free water, thus ensuring sufficient supply reactants under high current density. Especially, ‐based anion exchange membrane electrolyzers (AEMWEs) require only 1.69 1.84 V reach an industrial density 1,000 mA cm⁻ alkaline seawater conditions, respectively, operate stably 200 h. This study offers atomic‐level perspective designing highly efficient catalysts production.

Language: Английский

Spatial/Electronic Symmetry Breaking of Metal-Support Catalysts for Efficient Water Dissociation and Alkaline Hydrogen Spillover DOI

Jianhang Nie,

Jinghui Shi,

Lei Li

et al.

Nano Energy, Journal Year: 2025, Volume and Issue: unknown, P. 110873 - 110873

Published: March 1, 2025

Language: Английский

Citations

0

Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting DOI Creative Commons
P. Sakthivel,

Dong Han,

T. Marimuthu

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: March 16, 2025

Abstract High‐entropy nanoparticles (HENPs) present a vast opportunity for the development of advanced electrocatalysts. The optimization their chemical compositions, including careful selection and combination elements, is critical to tailoring HENPs specific catalytic processes. To reduce extensive experimental effort involved in composition optimization, active learning techniques can be utilized predict suggest materials with enhanced electrocatalytic activity. In this study, sub‐2 nm high‐entropy catalysts incorporating eight transition metal elements are developed through an workflow aimed at identifying optimal compositions. Using initial data, approach successfully guided discovery new octonary HENP catalyst state‐of‐the‐art performance hydrogen evolution reaction (HER). Catalyst improved within prediction uncertainty machine model. For oxygen (OER), however, model demonstrated limited predictive accuracy, leading assessment workflow's boundaries. These findings underscore how integration curated data accelerate electrocatalyst discovery, while also highlighting areas further refinement.

Language: Английский

Citations

0

Tunable Catalytic Performance on Iridium Clusters‐Interspersed CoxSy‐CoO Nanosheet‐Built Hollows for Enhanced Water Splitting DOI Open Access

Tran Thien An Nguyen,

Dang Khoa Tran, Duy Thanh Tran

et al.

Small, Journal Year: 2025, Volume and Issue: unknown

Published: March 20, 2025

Abstract To reach sustainable and robust green hydrogen energy production, the development of effective long‐lasting electrocatalysts for oxygen evolution reactions (HER OER) during overall electrochemical water splitting is a critical requirement. In this study, novel hierarchical nanosheet‐based hollow heterostructure Co x S y ‐CoO integrated with active iridium clusters (Ir Cs ‐Co ‐CoO) prepared by straightforward chemical synthesis approach. The offers extensive tunnels, abundant mesopores, features high‐density site at interfaces, thus greatly improving catalytic performance through promotion synergistic effects. Ir catalyst demonstrates low overpotentials 97 mV HER 243 OER 10 mA cm −2 , showcasing remarkable stability efficiency. two‐electrode cell test reliable current response voltage 1.497 1.58 V temperature 75 25 °C, respectively. Furthermore, exhibits enhanced durability when compared to Pt/C (−) //RuO 2(+) . practical application, significant 0.5/1.0 A 1.8/1.97 has been achieved in an anion exchange membrane electrolyzer stack, while maintaining high efficiency (68%) exceptional (over 500 h), underscoring promising potential H 2 production.

Language: Английский

Citations

0

Alloy/Interface-Induced activation of Metal-Phosphorus bonds in Ni5Cu3/CoP for efficient water splitting DOI
Wei Luo, Ning Long, Jing Peng

et al.

Applied Surface Science, Journal Year: 2025, Volume and Issue: unknown, P. 163025 - 163025

Published: March 1, 2025

Language: Английский

Citations

0

Tuning the Hydrogen Bond Network Inside the Helmholtz Plane for Industrial Hydrogen Evolution DOI Creative Commons
Xinyu Chen, Bianjing Sun, Qunliang Song

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

Abstract The role of the hydrogen bond network (HBN) within Helmholtz plane (HP) in regulating evolution kinetics for catalyst development remains ambiguous owing to lack fundamental understanding. Herein, leveraging ab initio molecular dynamics simulations, it is discovered that introducing weak metal bonds Ru/RuO 2 remarkably reshapes HBN. Subsequently, nanosheets loaded with single Ga atoms (Ga SA ‐Ru/RuO ) are successfully synthesized using a one‐step annealing strategy. In situ characterizations and theoretical calculations demonstrate atomic electric field generated by Ru─Ga can further improve proportion 4‐coordinated hydrogen‐bonded water free water, thus ensuring sufficient supply reactants under high current density. Especially, ‐based anion exchange membrane electrolyzers (AEMWEs) require only 1.69 1.84 V reach an industrial density 1,000 mA cm⁻ alkaline seawater conditions, respectively, operate stably 200 h. This study offers atomic‐level perspective designing highly efficient catalysts production.

Language: Английский

Citations

0