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Abstract The oxidative dehydrogenation of propane, primarily sourced from shale gas, holds promise in meeting the surging global demand for propylene. However, this process necessitates high operating temperatures, which amplifies safety concerns in its application due to the use of mixed propane and oxygen. Moreover, these elevated temperatures may heighten the risk of overoxidation, leading to carbon dioxide formation. Here we introduce a microchannel reaction system designed for the oxidative dehydrogenation of propane within an aqueous environment, enabling highly selective and active propylene production at room temperature and ambient pressure with mitigated safety risks. A propylene selectivity of over 92% and production rate of 19.57 mmol mCu −2 h−1 are simultaneously achieved. This exceptional performance stems from the in situ creation of a highly active, oxygen-containing Cu catalytic surface for propane activation, and the enhanced propane transfer via an enlarged gas-liquid interfacial area and a reduced diffusion path by establishing a gas-liquid Taylor flow using a custom-made T-junction microdevice. This microchannel reaction system offers an appealing approach to accelerate gas-liquid-solid reactions limited by the solubility of gaseous reactant.

The uniformity of hot air flow inside the airflow dryer not only affects the moisture distribution at the outlet, but also affects the quality of the product. Based on the guide plate structure of the SH23A airflow tobacco dryer, a gradient curved guide plate dryer is designed, and the flow field distribution of the dryer is numerically investigated under different flow distribution conditions at the hot air inlet and flue gas inlet. The results show that the airflow uniformity is affected by the flow distribution at the inlet of the heated air and the inlet of the cigarette smoke, the structure of the guide plate, etc., the non-uniformity coefficient decreases with the increase of hot air inlet flow rate. The non-uniformity coefficient of tapered arc deflector decreases by 9–12 %.

While the electrochemical conversion of CO2 to highly reduced products is unique to copper, there are still gaps in understanding copper catalysts’ efficacy. Here, authors find that co-electrolysis of CO2 with O2 can enhance copper’s catalytic activities.

Lithium-ion batteries (LIBs) have been widely used for electric vehicles owing to their high energy density, light weight, and no memory effect. However, their health management problems remain unsolved in actual application. Therefore, this paper focuses on battery capacity as the key health indicator and proposes a data-driven method for capacity prediction. Specifically, this method mainly utilizes Convolutional Neural Network (CNN) for automatic feature extraction from raw data and combines it with the Bidirectional Long Short-Term Memory (BiLSTM) algorithm to realize the capacity prediction of LIBs. In addition, the sparrow search algorithm (SSA) is used to optimize the hyper-parameters of the neural network to further improve the prediction performance of original network structures. Ultimately, experiments with a public dataset of batteries are carried out to verify and evaluate the effectiveness of capacity prediction under two temperature conditions. The results show that the SSA-CNN-BiLSTM framework for capacity prediction of LIBs has higher accuracy compared with other original network structures during the multi-battery cycle experiments.

In this study, L-carnosine was chosen as the model compound to systematically study solution-mediated polymorphic transformation by online experiment and theoretical simulation. Form II, a new polymorph of L-carnosine, was developed using an antisolvent crystallization method. The properties of form I and form II L-carnosine were characterized by powder X-ray diffraction, polarizing microscope, thermal analysis, and Raman spectroscopy. In order to explore the relative stability, the solubility of L-carnosine form I and form II in a (water + DMAC) binary solvent mixture was determined by a dynamic method. During the solution-mediated polymorphic transformation process of L-carnosine in different solvents, Raman spectroscopy was employed to detect the solid-phase composition of suspension in situ, and the gravimetric method was used to measure the liquid concentration. In addition, the effect of the solvent on the transformation process was evaluated and analyzed. Finally, a mathematical model of dissolution–precipitation was established to simulate the kinetics of the polymorphic transformation process based on the experimental data. Taking the simulation results and the experimental data into consideration, the controlling step of solution-mediated polymorphic transformation was discussed.

Traditional regenerative braking control strategies only consider how to ensure motor to work along with the battery/motor joint high-efficiency working line, but do not consider continuously variable transmission efficiency. However, continuously variable transmission efficiency varies between 70% and 95% which cannot be neglected. Based on the analysis of relationship among the battery, motor, continuously variable transmission, and synthesis efficiency, the battery/motor/continuously variable transmission joint high efficiency is calculated and obtained, and the regenerative braking control strategy is proposed. Comparing the previous control strategy with battery/motor joint high efficiency, the motor average generating efficiency increases by 2.91%, and braking energy recovery rate increases by 4.09% under Extra Urban Driving Cycle, while the motor average generating efficiency increases by 3.84%, and braking energy recovery rate increases by 5.74% under Federal Test Procedure-72 through offline simulation. Furthermore, under the hardware-in-the-loop test, the average generating efficiency increases by 2.72%, and the braking energy recovery rate increases by 5.03% under Extra Urban Driving Cycle, while the average generating efficiency increases by 3.13%, and the braking energy recovery rate increases by 3.94% under Federal Test Procedure-72. Both simulation and hardware-in-the-loop test results show that the proposed regenerative braking control strategy can realize battery, motor, and continuously variable transmission to work with joint high efficiency which can enhance braking energy recovery rate.