0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract The surface reconstruction of electrochemically activated catalysts is an effective way to improve performance. However, there is currently a dearth of study on the surface reconstruction of silicide catalysts for hydrogen evolution reactions (HER). Here, a new HER electrocatalyst, LaRuSi 3 , is synthesized and electrochemically triggered it to produce Ru clusters on its surface. Experimental data and theoretical simulations reveal that Ru clusters optimize the charge distribution of LaRuSi 3 , which promotes the adsorption of water by Ru sites and improves the adsorption of hydrogen by Si sites. The conductivity and electrochemical active sites of the catalysts are also enhanced. The catalyst has an overpotential of 45 mV to attain a current density of 10 mA cm −2 in alkaline media, which exceeds the majority of other Ru‐based compounds. This work contributes to the exploration of more efficient novel silicides HER electrocatalysts and broadens the application of surface reconstruction techniques.
Huanhuan Zhang, Kai Song, Zhiping Lin, Zongpeng Wang, Lili Zhang, Shijie Shen, Lin Gu, Wenwu Zhong (2024). In Situ Reconstructed Ru Clusters on LaRuSi<sub>3</sub> with Enhanced Electrocatalytic Activity for Alkaline Hydrogen Evolution. , 34(44), DOI: https://doi.org/10.1002/adfm.202405897.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2024
Authors
8
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1002/adfm.202405897
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access