Abstract
Recent experimental and theoretical studies have demonstrated that two-dimensional (2D) transition metal dichalcogenide (TMDC) nanoflakes are one of the most promising candidates for non-noblemetal electrocatalysts for hydrogen evolution reaction (HER). However, it is still demanding to optimize their conductivity and enrich active sites for the high efficient electrochemical performance. Herein, we report a chemical vapor deposition (CVD) and thermal annealing two-step strategy to controllably synthesize hybrid electrocatalysts consisting of metallic NbS2 nanoflake backbones and highly catalytic active MoSx nanocrystalline shell on polished commercial glass carbon (GC). In addition, the amounts of MoSx in the hybrids can be easily adjusted, we first demonstrate that small amount of MoSx obviously promotes the HER activity of 2D NbS2 nanoflakes, which is in good consistence with the density functional theory (DFT) calculation results. Meanwhile, the optimized MoSx@NbS2/GC electrocatalyst displays a superior HER activity with an overpotential of -164 mV at -10 mA/cm2, a small Tafel slope of 43.2 mV/dec, and prominent electrochemical stability. This study provides a new path for enhancing the HER performance of 2D TMDC nanoflakes.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3444-3450 |
| Number of pages | 7 |
| Journal | Nanoscale |
| Volume | 10 |
| Issue number | 7 |
| DOIs | |
| State | Published - 2018 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: This project was supported by the National Natural Science Foundation of China (Grant No. 51602200, Grant No. 51472164), the 1000 Talents Program for Young Scientists of China, the Educational Commission of Guangdong Province (Grant No. 2016KZDXM008, Grant No. 2016KCXTD006, Grant No. 2015KGJHZ006), the Science and Technology Planning Project of Guangdong Province (Grant No. 2016B050501005), Shenzhen Peacock Plan (Grant No. KQTD2016053112042971), the Natural Science Foundation of SZU (Grant No. 000050, Grant no. 2017011), the National Center for Theoretical Sciences and the Ministry of Science and Technology of Taiwan (Grants No. MOST-105-2112-M-110-013-MY3), the China Postdoctoral Science Foundation (Grant No. 2016M592538), and KCC Center Competitive Funding (CCF) of King Abdullah University of Science and Technology (KAUST), Saudi Arabia. In addition, we also acknowledge the National Center for High Performance Computing, Hsinchu, Taiwan for providing computational resources.