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In this paper, we report for the first time the successful formation of a covalent cross-linking structure between polyacrylic acid and polyamide 66 in an electrospun nanofiber membrane by the facilitated amidation reaction using N-Hydroxy-succinimide (NHS) and N-(3-Dimethylaminopropyl)-N'-ethyl-carbodiimide hydrochloride (EDC). The structure and properties of the fiber membrane are characterized using scanning electron microscopy, wide field X-ray diffraction and differential scanning calorimetry. The results show that the presence of the cross-linked structure not only affects the construction of the nanofiber network framework but also influences the pore size distribution and size of the fiber membrane surface, which in turn affects its retention of contaminants and water absorption performance. After modification, the cross-linked membranes exhibited a significant retention performance of up to 77% for methyl tert-butyl ether (MTBE) with a reduced pure water flux. Furthermore, after crosslinking, the fiber membrane has been strongly enhanced with more stable pH response behavior. [ABSTRACT FROM AUTHOR]

Island-type petrochemical parks have gradually become the 'trend' in establishing new parks because of the security advantages brought by their unique geographical locations. However, due to the frequent occurrence of natural disasters and difficulties in rescue in island-type parks, an early warning model is urgently needed to provide a basis for risk management. Previous research on early warning models of island-type parks seldom considered the particularity. In this study, the early warning indicator system is used as the input parameter to construct the early warning model of an island-type petrochemical park based on the back propagation (BP) neural network, and an actual island-type petrochemical park was used as a case to illustrate the model. Firstly, the safety influencing factors were screened by designing questionnaires and then an early warning indicator system was established. Secondly, particle swarm optimization (PSO) was introduced into the improved BP neural network to optimize the initial weights and thresholds of the neural network. A total of 30 groups of petrochemical park data were taken as samples—26 groups as training samples and 4 groups as test samples. Moreover, the safety status of the petrochemical park was set as the output parameter of the neural network. The comparative analysis shows that the optimized neural network is far superior to the unoptimized neural network in evaluation indicators. Finally, the Zhejiang Petrochemical Co., Ltd., park was used as a case to verify the accuracy of the proposed early warning model. Ultimately, the final output result was 0.8324, which indicates that the safety status of the case park was "safer". The results show that the BP neural network introduced with PSO can effectively realize early warning, which is an effective model to realize the safety early warning of island-type petrochemical parks. [ABSTRACT FROM AUTHOR]

Polyamide 66 microporous membranes were prepared by cold non-solvent-induced phase separation using polyamide 66-formic acid-propylene carbonate as a ternary membrane-forming system. The formed membranes exhibited a special bicontinuous structure consisting of interglued spherical crystals or interlocked bundles of microcrystalline aggregates. The variation of the microporous structure under the influence of preparation conditions, solvent, aging time, and polymer concentration affects the comprehensive performance of the membranes. For example, the cold-induced operation and the use of different membrane-forming solvents contributed to the crystallization of polyamide 66, resulting in an increased contact angle of polyamide 66 membranes, obtaining a high resistance to contamination of up to 73.5%. Moreover, the formed membranes still have high mechanical strength. [ABSTRACT FROM AUTHOR]