PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 16, 2021Small163 citations

Ni/Mo Bimetallic‐Oxide‐Derived Heterointerface‐Rich Sulfide Nanosheets with Co‐Doping for Efficient Alkaline Hydrogen Evolution by Boosting Volmer Reaction

View Full Paper
LZLiyang ZhangYZYujie ZhengJWJiacheng Wang

Key Points

Key points are not available for this paper at this time.

Abstract

Abstract Molybdenum disulfide (MoS 2 ) is a promising alternative to Pt‐based catalysts for electrocatalytic hydrogen evolution reaction (HER) in an acidic environment. However, alkaline HER activity for molybdenum disulfide is limited by its slow water dissociation kinetics. Interface engineering is an effective strategy for the design of alkaline HER catalysts. However, the restricted heterointerfaces of current catalysts have significantly limited their alkaline HER performance. Herein, a novel assembly of cobalt‐doped interface‐ and defect‐rich MoS 2 /Ni 3 S 2 hetero‐nanosheet anchoring on hierarchical carbon framework for alkaline HER is reported by directly vulcanizing NiMoO 4 nanosheets. In the heterostructure nanosheet, Ni 3 S 2 acts as a water dissociation promoter and MoS 2 acts as a hydrogen acceptor. Density functional theory calculations find that redistribution of charges at the heterointerface can reduce hydrogen adsorption Gibbs free energy (∆ G H* ) and water decomposition energy barrier. The resulting hierarchical electrode with the synergistic effect of both hybrid components shows a low overpotential of 89 mV at −10 mA cm −2 in 1 m KOH, a Tafel slope as low as 62 mV dec −1 , and can run at −100 mA cm −2 for at least 50 h without obvious voltage change. This study provides a potentially feasible strategy for the design of heterostructure‐based electrocatalysts with abundant active interfaces.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Zhang et al. (2021) studied this question.

synapsesocial.com/papers/6a2a7ede68d30cd8c0e9a267https://doi.org/10.1002/smll.202006730
Ask AI
Helpful
Bookmark
Share
View Full Paper