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Objective: This study aimed to obtain the temperature distribution law of different points in citrus fruit over time during heat treatment. Methods: The temperature change of citrus peel during heat treatment was studied from the perspective of heat transfer. A new method was applied to calculate the temperature transfer rule in citrus peel, and a new mathematical model was established to simulate the temperature distribution of citrus peel during heat treatment. The spatial and temporal distribution of the internal temperature field of three kinds of citrus (Fengjie Navel orange, longevity blood orange and Ziyang Tangerine) was studied. Results: The study showed that the heat treatment time decreased exponentially with the increase of water temperature, the detailed exponential relationship expression of different varieties of citrus was obtained, and the function formula between the heat treatment time and water bath temperature was proposed by the data regression method. Conclusion: Heat treatment time decreases exponentially with the increase of water bath temperature. Due to an insufficient heat transfer temperature differential, too low water temperatures will significantly lengthen the time needed for heat treatment and increase energy usage.

In order to solve the problem of poor accuracy of blasting vibration prediction by the traditional Sadowski empirical formula and BP neural network, a model based on the mind evolutionary algorithm (MEA) is proposed for the first time to optimize the BP neural network. The blasting demolition of a raft slab foundation of an underground garage in Shenyang City, Liaoning Province, China, is taken as a research object, and the effects of the horizontal distance between different monitoring points, demolition area, elevation difference, the maximum amount of a single section of the charge, and the horizontal angle between the measurement point and the minimum resistance line on the peak velocity of vibration are taken into account. The empirical Sadowski formula, the MEA-BP algorithm, and the GA-BP algorithm were introduced to randomly train the 40 sets of data monitored at the site and to predict the eight sets of data outside the training, respectively. The results showed that the maximum relative errors of the results predicted by the MEA-BP model, the GA-BP model, and the empirical Sadowski formula were 14.94%, 19.36%, and 22.81%, respectively, and the average relative errors were 8.88%, 10.79%, and 16.84%, respectively. The prediction results corroborate that the MEA-BP algorithm has high adaptability in blasting vibration prediction for raft foundation demolition and provides reference for the prediction of vibration peak velocity in similar blasting projects. [ABSTRACT FROM AUTHOR]

The design of pseudocapacitive electrodes that exhibit high‐rate and high volumetric capacitances is a big challenge, since it requires subtle modulation of ion‐intercalation structures that are able to achieve high electrochemical activity, fast ion transport, and facilitated electron transfer, simultaneously. Herein, controllable and selective etching of B atoms from B‐doped Ti3AlC2 precursors is reported, which generates boron‐vacancy doped MXene (B‐V‐MXene) nanosheets with finely‐regulated, ion‐intercalation structures. Electrochemical studies and density‐functional‐theory calculations demonstrate that Ti around vacancies possess higher surface‐redox activity with protons than those on pristine MXenes for the improvement of capacitances. In addition, interlayer spacing can be optimized on B‐V‐MXenes in promoting proton intercalation. More importantly, the dopant B atoms can increase the electron density on Ti, facilitating the adsorption of the intercalated protons; and further, B 2p‐Ti 3d hybridized band sits closer to the Fermi energy than that of C 2p bands, which bridges the energy gap for electron transfer in the pseudo‐capacitive reaction. With synergy of all these effects, the novel B‐V‐MXene compact electrodes can deliver the previously unmatched high volumetric capacitances of 807 F cm−3 at 1,000 mV s−1 and 1,815 F cm−3 at 5 mV s−1, with excellent cycle stability over 10,000 cycles. [ABSTRACT FROM AUTHOR]

Photoelectrocatalysis (PEC) is regarded as a promising and sustainable process for removal of organic contaminants from wastewater. Meanwhile, enzymatic catalysis also provides an effective way to carry out polluted environment remediation under mild conditions. In this study, a biophotoelectrocatalytic (BPEC) system is designed to remove 4‐nitrophenol (4‐NP) based on a combination of PEC and enzymatic catalysis. The developed BPEC system is constructed with a Ag3PO4/BiVO4 photoanode and a horseradish peroxidase (HRP)‐loaded carbon cloth (CC) cathode. On the photoanode, the construction of a direct Z‐scheme Ag3PO4/BiVO4 heterojunction enhanced the separation efficiency of photogenerated carriers, which promoted the PEC degradation of 4‐NP under visible light irradiation. After HRP was immobilized on the cathode, the degradation efficiency of 4‐NP reached 97.1 % after 60 min PEC treatment. The result could be ascribed to the HRP‐catalyzed oxidation reaction via in situ‐generated H2O2 from the CC cathode during the PEC process. Moreover, the possible degradation pathways of 4‐NP in such a BPEC system are also discussed. [ABSTRACT FROM AUTHOR]