Photothermal oxidative dehydrogenation of propane to propylene over Cu/BN catalysts.

Oxidative dehydrogenation of propane (ODHP) is a reaction with significant practical significance. As for the industrial application of ODHP, it is challenging to achieve high activity and high propylene selectivity simultaneously. In this study, to overcome this obstacle, we designed a series of Cu/BN catalysts with unique morphologies for establishing a photothermal ODHP system with high efficiency and selectivity. Characterization and evaluation results revealed that Cu/BN-NS and Cu/BN-NF with enlarged specific surface areas exhibited higher catalytic activities. The localized surface plasmon resonance (LSPR) effect of Cu nanoparticles further enhanced the photothermal catalytic performances of Cu/BN catalysts under visible light irradiation. To the best of our knowledge, it is the first time to establish a BN-based photothermal ODHP catalytic system. This study is expected to pave pathways to realize high activity and propylene selectivity for the practical application of ODHP.

Catalyst development for O2-assisted oxidative dehydrogenation of propane to propylene.

O2-Assisted oxidative dehydrogenation of propane (O2-ODHP) could convert abundant shale gas into propylene as an important chemical raw material, meaning O2-ODHP has practical significance. Thermodynamically, high temperature is beneficial for O2-ODHP; however, high reaction temperature always causes the overoxidation of propylene, leading to a decline in its selectivity. In this regard, it is crucial to achieve low temperatures while maintaining high efficiency and selectivity during O2-ODHP. The use of catalytic technology provides more opportunities for achieving high-efficiency O2-ODHP under mild conditions. Up to now, many kinds of catalytic systems have been elaborately designed, including transition metal oxide catalysts (such as vanadium-based catalysts, molybdenum-based catalysts, etc.), transition metal-based catalysts (such as Pt nanoclusters), rare earth metal oxide catalysts (especially CeO2 related catalysts), and non-metallic catalysts (BN, other B-containing catalysts, and C-based catalysts). In this review, we have summarized the development progress of mainstream catalysts in O2-ODHP, aiming at providing a clear picture to the catalysis community and advancing this research field further.

Real-Time Human Recognition at Night via Integrated Face and Gait Recognition Technologies.

Human recognition technology is a task that determines the people existing in images with the purpose of identifying them. However, automatic human recognition at night is still a challenge because of its need to align requirements with a high accuracy rate and speed. This article aims to design a novel approach that applies integrated face and gait analyses to enhance the performance of real-time human recognition in TIR images at night under various walking conditions. Therefore, a new network is proposed to improve the YOLOv3 model by fusing face and gait classifiers to identify individuals automatically. This network optimizes the TIR images, provides more accurate features (face, gait, and body segment) of the person, and possesses it through the PDM-Net to detect the person class; then, PRM-Net classifies the images for human recognition. The proposed methodology uses accurate features to form the face and gait signatures by applying the YOLO-face algorithm and YOLO algorithm. This approach was pre-trained on three night (DHU Night, FLIR, and KAIST) databases to simulate realistic conditions during the surveillance-protecting areas. The experimental results determined that the proposed method is superior to other results-related methods in the same night databases in accuracy and detection time.