The oxygen evolution reaction (OER) serves as the core step in water?splitting for hydrogen production,and its catalytic efficiency directly affects the economic conversion efficiency of hydrogen energy. In this work, a magnetic field?assisted one?step reduction method was used to successfully prepare amorphous metal boride nanobead catalysts. The phase composition and electrochemical properties of the catalysts were characterized, and the catalysts were applied to promote the OER catalytic reaction. The results show that among the various prepared metal borides, the cobalt?iron boride (CoFeB) directional nanobeads exhibited superior catalytic performance and remarkable stability, requiring an overpotential of only 330 mV at a current density of 10 mA/cm² with a Tafel slope of 82 mV/dec. The excellent electrocatalytic performance of the catalyst mainly stems from the synergistic effect of Co and Fe, which optimizes the electronic structure of active sites and significantly enhances catalytic efficiency. Furthermore, the effects of magnetic field strength and surfactant mass on the morphology and electrochemical behavior of CoFeB samples were systematically investigated, uncovering the strong correlation between catalytic activity, directional nanoparticle assembly, and structural features. The strategy proposed in this study is simple and scalable, providing a new approach for the design and development of high?efficiency and low?cost metal boride catalysts.

Deep and ultra-deep carbonate oil and gas reservoirs, with their vast reserves and immense potential, have emerged as critical strategic assets in global energy supply. However, the complex challenges posed by high-temperature, high-pressure environments, intricate pore-throat structures, and the coexistence of macro-pores, dissolution cavities, and fractures make traditional exploration and production technologies insufficient to manage such complexity. As exploration and development progress, precise reservoir characterization and seepage behavior research face significant hurdles, including advanced modeling, complex seepage experiments, and accurate description of reservoir properties. Therefore, this review offers an in-depth analysis of the latest developments and key challenges in the characterization and seepage behavior of deep and ultra-deep carbonate reservoirs. It provides a comprehensive summary of cutting?edge methods for detailed microstructural reservoir characterization and multi?attribute seismic interpretation techniques enhanced by artificial intelligence. The paper also explores the application and success of multi?scale characterization approaches in complex reservoirs,while outlining the primary technical strategies and emerging trends in reservoir identification and description. Additionally,the article emphasizes recent advancements in understanding seepage characteristics under high-temperature and high?pressure conditions in deep carbonate reservoirs, focusing on multi-scale seepage theory and gas-water two?phase flow mechanisms. By examining experimental data and theoretical models from both domestic and international research, the review highlights current challenges and future directions in seepage studies, providing valuable insights for the development and efficient exploitation of deep and ultra?deep oil and gas reservoirs.