Litcius/Paper detail

Boosting Highly Active Exposed Mo Atoms by Fine-Tuning S-Vacancies of MoS<sub>2</sub>-Based Materials for Efficient Hydrogen Evolution

Tian Lian, Xiaoyun Li, Yilong Wang, Shao-Ju Zhu, Xiaoyu Yang, Zhan Liu, Cuifang Ye, Jinping Liu, Yu Li, Bao‐Lian Su, Lihua Chen

2022ACS Applied Materials & Interfaces35 citationsDOI

Abstract

Guided by the theoretical calculation, achieving an efficient hydrogen evolution reaction (HER) by S-vacancy engineering toward MoS2-based materials is quite challenging due to the contradictory relationship between the adsorption free energy of hydrogen atoms (ΔGH) of the exposed Mo atoms (EMAs) and the number of EMAs per unit area (NEMAs). Herein, we demonstrate a novel one-pot incorporating-assisted compositing strategy to realize fine-tuning the concentration of S-vacancies (CS-vacancies) of MoS2-based materials to boost highly active EMAs for efficient HER. In our strategy, S-vacancies are modulated into basal planes of MoS2 via decreasing the formation energy of S-vacancies by oxygen incorporation; moreover, CS-vacancies of the basal planes is precisely regulated by simply controlling the molar amount of the Co precursor based on the electron injection effect. At low or excessively high CS-vacancies, the as-synthesized electrocatalysts lack “highly active EMAs” in quantity or nature. The balance between the intrinsic activity of EMAs and NEMAs is realized for boosting EMAs with high catalytic performance. The optimal electrocatalysts exhibit excellent activity and stability at fine-tuning CS-vacancies to 9.61%. Our results will pave a novel strategy for unlocking the potential of an inert basal plane in MoS2 for high-performance HER.

Topics & Concepts

Materials scienceBoosting (machine learning)HydrogenNanotechnologyEngineering physicsOptoelectronicsChemical physicsComputer sciencePhysicsChemistryEngineeringMachine learningOrganic chemistryElectrocatalysts for Energy ConversionMXene and MAX Phase Materials2D Materials and Applications