Despite being promising substitutes for noble metal catalysts used in hydrogen evolution reaction (HER), the nonprecious metal catalysts (NPMCs) based on inexpensive and earth-abundant 3d transition metals (TMs) are still practically unfeasible due mainly to unsatisfactory activity and durability. Herein, a highly active and stable catalyst for HER has been developed on the basis of molybdenum-carbide-modified N-doped carbon vesicle encapsulating Ni nanoparticles (MoxC-Ni@NCV). This MoxC-Ni@NCV material was synthesized simply by the solid-state thermolysis of melamine-related composites of oxalate and molybdate with uniform Ni ions doping (Ni@MOM-com). Notably, the prepared MoxC-Ni@NCV was almost the most efficient NPMCs for HER in acidic electrolyte to date. Besides good long-term stability, MoxC-Ni@NCV exhibited a quiet low overpotential that was comparable to Pt/C. Thus, this work opens a new avenue toward the development of highly efficient, inexpensive HER catalysts.

Inspired by the branching corrected surface hopping (BCSH) method [J. Xu and L. Wang, J. Chem. Phys. 150, 164101 (2019)], we present two new decoherence time formulas for trajectory surface hopping. Both the proposed linear and exponential formulas characterize the decoherence time as functions of the energy difference between adiabatic states and correctly capture the decoherence effect due to wave packet reflection as predicted by BCSH. The relevant parameters are trained in a series of 200 diverse models with different initial nuclear momenta, and the exact quantum solutions are utilized as references. As demonstrated in the three standard Tully models, the two new approaches exhibit significantly higher reliability than the widely used counterpart algorithm while holding the appealing efficiency, thus promising for nonadiabatic dynamics simulations of general systems.

Personality traits have close relationships with risky behaviors in various domains, including physical education, competition, and athletic training. It is yet little known about how trait personality dimensions associate with risk events and how vital factors, such as risk perception, could affect the happening of risk events in adolescent athletes. The primary purpose of this study is to investigate the prediction of risk events by regression analysis with dimensions of personality, risk perception and sports, relations between risk events, risk perception, and the facets of the personality dimensions via data collecting from 664 adolescent athletes aged 13–18 years (male 364, female 300). Secondary intent is to assess school-specific levels of training risks among sports schools, regular schools, and sports and education integrated schools. The results show that psychology events are the strongest predicted by personality traits, risk perception, and sports, followed by injury and nutrition. Emotionality has the most significant positive correlation with risk events, while other traits have a significant negative correlation with risk events, except agreeableness. The integration schools are more conducive to the healthy development of adolescent athletes’ personalities. Moreover, the research indicates that sports training can strengthen the development directions of different personality characteristics.