AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (5.3 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Continuous modulation of oxygen vacancies in MoO3−x quantum dots enables to tunable nitrogen reduction reactivity

Zhihao Lu1Yingying Wei2Teng Wang1Renquan Hu1Ning Xu1Fangjun Cao3 ( )Jianping Lai2Yong Yang1( )
State Key Laboratory of Solidification Processing, Center of Advanced Lubrication and Seal Materials, Northwestern Polytechnical University, Xi’an 710072, China
State Key Laboratory Base of Eco-Chemical Engineering, Ministry of Education, International Science and Technology Cooperation Base of Eco-Chemical Engineering and Green Manufacturing, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Key Laboratory for Animal Conservation, Shaanxi Institute of Zoology, Xi’an 710072, China
Show Author Information

Abstract

The electrochemical nitrogen reduction reaction (eNRR) is a sustainable pathway for ammonia production, yet its practical implementation is hindered by the inherent thermodynamic stability of nitrogen and the competitive hydrogen evolution reaction (HER). Therefore, designing efficient electrocatalysts with superior eNRR activity and selectivity remains challenging. In this work, ultrasmall molybdenum oxide quantum dots (MoO3−x QDs) rich in oxygen vacancies (OVs) were synthesized through an ultrafast wet-chemical approach. Owing to the exceptionally high surface-to-volume ratio, the 3 nm quantum-confined architecture of the MoO3−x QDs has a high density of accessible active sites, facilitating charge transfer kinetics at the nanoscale. The number of OVs within MoO3−x QDs can be precisely tailored by adjusting the amount of ligand introduced and effectively modifying the electronic structure of neighboring Mo sites in favor of the adsorption and hydrogenation of nitrogen, enhancing eNRR selectivity. Owing to the synergistic effects of quantum confinement and vacany engineering, the optimized MoO3−x QD catalysts exhibit outstanding eNRR performance, achieving a good NH3 yield rate of 38.55 μg·h−1·mg−1 with a Faradaic efficiency of 8.2% at −0.15 V (vs. RHE), which surpasses that of most reported Mo-based eNRR catalysts under comparable conditions. Furthermore, in situ Fourier transform infrared (FTIR) characterization revealed that the eNRR reaction pathway of MoO3−x QDs follows an associative distal mechanism. This work establishes a dual-modulation strategy that integrates quantum size effects with vacancy engineering, providing a promising avenue for designing transition metal oxide catalysts with enhanced activity and selectivity in multielectron transfer reactions.

Graphical Abstract

Sulfur-doped molybdenum oxide quantum dots with gradient oxygen vacancies were synthesized via an ultrafast wet-chemical strategy for enhanced electrocatalytic nitrogen reduction reaction performance.

Electronic Supplementary Material

Download File(s)
8514_ESM.pdf (2.6 MB)

References

【1】
【1】
 
 
Nano Research
Article number: 94908514

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Lu Z, Wei Y, Wang T, et al. Continuous modulation of oxygen vacancies in MoO3−x quantum dots enables to tunable nitrogen reduction reactivity. Nano Research, 2026, 19(3): 94908514. https://doi.org/10.26599/NR.2026.94908514

935

Views

144

Downloads

0

Crossref

0

Web of Science

0

Scopus

0

CSCD

Received: 04 January 2026
Revised: 30 January 2026
Accepted: 30 January 2026
Published: 13 March 2026
© The Author(s) 2026. Published by Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).