JOURNAL ARTICLE

Multicomponent and Hierarchical Ni(OH)2/NiFe2O4/Ni3S2 Nanosheets on Nickel Foam for Seawater Electrolysis.

  • Published In: ChemNanoMat, 2025, v. 11, n. 6. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Zhao, Menghan; Sun, Heng; Li, Meiyue; Gong, Yanshang; Lu, Zhou; Yuan, Ding; Zhang, Lixue; Sun, Jiankun 3 of 3

Abstract

Developing highly efficient, durable, and easily available noble‐metal electrocatalysts is crucial for large‐scale seawater electrolysis but remains a challenge. Here, we report a high‐performance oxygen evolution reaction (OER) catalyst, Ni(OH)2/NiFe2O4/Ni3S2@NF, synthesized through a simple one‐step hydrothermal method, showcasing a low overpotential of 413 mV at a large current density of 1000 mA cm−2, coupled with excellent stability at an industrial current density of 500 mA cm−2 for over 100 h in alkaline natural seawater solution. Such excellent OER performance is attributed to the abundant component and hierarchical architecture of Ni(OH)2/NiFe2O4/Ni3S2@NF catalyst, featuring 3D porous structure of interconnected nanosheets array, which endows more active sites and promotes efficient mass transport, further significantly enhancing catalytic activity and reaction kinetics. The anion exchange membrane water electrolyzer (AEMWE), featuring a Ni(OH)2/NiFe2O4/Ni3S2@NF anode and a MoNi@NF cathode, exhibits exceptional activity and stability in alkaline seawater, achieving an industrial current density of 1000 mA cm−2 at a low cell voltage of 2.35 V. This work offers valuable insights for the development of cost‐effective and robust OER electrocatalysts suitable for stable operation in harsh seawater electrolysis systems. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:ChemNanoMat. 2025/06, Vol. 11, Issue 6, p1
  • Document Type:Article
  • Subject Area:Geology
  • Publication Date:2025
  • ISSN:2199692X
  • DOI:10.1002/cnma.202500137
  • Accession Number:185861893
  • Copyright Statement:Copyright of ChemNanoMat is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.