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Abstract Two-dimensional (2D) molybdenum disulfide (MoS 2 ) has been recognized as a potential substitution of platinum (Pt) for electrochemical hydrogen evolution reaction (HER). However, the broad adoption of MoS 2 is hindered by its limited number of active sites and low inherent electrical conductivity. In this work, we employed a one-step solvothermal synthesis technique to construct a ternary hybrid structure consisting of dual-phase MoS 2, titanium carbide (Ti 3 C 2 ) MXene, and carbon nanotubes (CNTs), and demonstrated synergistic effects for active site exposure, surface area enlargement, and electrical conductivity improvement of the catalyst. The dual-phase MoS 2 (DP-MoS 2 ) is directly formed on the MXene with CNTs acting as crosslinks between 2D islands. The existence of edge-enriched metallic phase MoS 2 , the conductive backbone of MXene along with the crosslink function of CNTs clearly improves the overall HER performance of the ternary nanocomposite. Moreover, the integration of MoS 2 with MXene not only increases the interlayer distance of the 2D layers but also partially suppresses the MXene oxidation and the 2D layer restacking, leading to good catalytic stability. As a result, an overpotential of 169 mV and a low Tafel slope of 51 mV/dec was successfully achieved. This work paves a way for 2D-based electrocatalyst engineering and sheds light on the development of the next-generation noble metal-free HER electrocatalysts. 

The development of active catalysts for hydrogen evolution reaction (HER) made from low-cost materials constitutes a crucial challenge in the utilization of hydrogen energy. Earth-abundant molybdenum disulfide (MoS 2 ) has been discovered recently with good activity and stability for HER. In this report, we employ a hydrothermal technique for MoS 2 synthesis which is a cost-effective and environmentally friendly approach and has the potential for future mass production. Machine-learning (ML) techniques are built and subsequently used within a Bayesian Optimization framework to validate the optimal parameter combinations for synthesizing high-quality MoS 2 catalyst within the limited parameter space. Compared with the heavy-labor and time-consuming trial-and-error approach, the ML techniques provide a more efficient toolkit to assist exploration of the most effective HER catalyst in hydrothermal synthesis. To investigate the structure-property relationship, scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and various electrochemical characterizations have been conducted to investigate the superiority of the ML validated optimized sample. A strong correlation between the material structure and the HER performance has been observed for the optimized MoS 2 catalyst.