Facile Fabrication of 1-Methylimidazole/Cu Nanozyme with Enhanced Laccase Activity for Fast Degradation and Sensitive Detection of Phenol Compounds

Facile construction of functional nanomaterials with laccase-like activity is important in sustainable chemistry since laccase is featured as an efficient and promising catalyst especially for phenolic degradation but still has the challenges of high cost, low activity, poor stability and unsatisfied recyclability. In this paper, we report a simple method to synthesize nanozymes with enhanced laccase-like activity by the self-assembly of copper ions with various imidazole derivatives. In the case of 1-methylimidazole as the ligand, the as-synthesized nanozyme (denoted as Cu-MIM) has the highest yield and best activity among the nanozymes prepared. Compared to laccase, the K_m of Cu-MIM nanozyme to phenol is much lower, and the v_max is 6.8 times higher. In addition, Cu-MIM maintains excellent stability in a variety of harsh environments, such as high pH, high temperature, high salt concentration, organic solvents and long-term storage. Based on the Cu-MIM nanozyme, we established a method for quantitatively detecting phenol concentration through a smartphone, which is believed to have important applications in environmental protection, pollutant detection and other fields.     

α-氨基膦酸酯的合成方法研究进展

从Lewis催化剂合成法、非Lewis催化剂合成法、绿色合成法3个方面综述了近年来国内外在α-氨基膦酸酯合成研究领域的最新进展.参考文献33篇.     

Flavonoids from Lycium barbarum Leaves Exhibit Anti-Aging Effects through the Redox-Modulation

Lycium barbarum leaves are a kind of vegetable, and modern nutrition studies have found that they have an anti-aging function. Our study aims to investigate the anti-aging effects of Lycium barbarum leaf flavonoid (LBLF) extracts and its underlying molecular mechanism. LBLFs were purified using D101 and polyamide resin, characterized by ultraperformance liquid chromatography coupled with mass spectrometry, and administered to hydrogen peroxide (H₂O₂)-treated human umbilical vein endothelial cells (HUVECs) and Caenorhabditis elegans. Appropriate enrichment conditions were optimized through dynamic adsorption and desorption experiments, the content of flavonoids reached 909.84 mg/g, rutin and kaempferol being the main ones. LBLFs attenuated H₂O₂-induced HUVEC apoptosis, decreased reactive oxygen species and malondialdehyde production levels, increased superoxide dismutase, glutathione peroxidase and catalase activities. Furthermore, pre-treatment with LBLF increased mRNA expression of erythropoietin (EPO) and heme oxygenase-1 (HO-1) via the mitogen-activated protein kinase (MAPK) signaling pathway in HUVECs. Compared with 100 µM rutin monomer, LBLF prolonged the lifespan of Caenorhabditis elegans, enhanced their mobility in middle life stages and upregulated expression of sod-2, gcs-1 and skn-1 genes, which indicated that the anti-aging effects of LBLF were due to its redox-modulation.     

An Improved Temporal Fusion Transformers Model for Predicting Supply Air Temperature in High-Speed Railway Carriages

A key element for reducing energy consumption and improving thermal comfort on high-speed rail is controlling air-conditioning temperature. Accurate prediction of air supply temperature is aimed at improving control effects. Existing studies of supply air temperature prediction models are interdisciplinary, involving heat transfer science and computer science, where the problem is defined as time-series prediction. However, the model is widely accepted as a complex model that is nonlinear and dynamic. That makes it difficult for existing statistical and deep learning methods, e.g., autoregressive integrated moving average model (ARIMA), convolutional neural network (CNN), and long short-term memory network (LSTM), to fully capture the interaction between these variables and provide accurate prediction results. Recent studies have shown the potential of the Transformer to increase the prediction capacity. This paper offers an improved temporal fusion transformers (TFT) prediction model for supply air temperature in high-speed train carriages to tackle these challenges, with two improvements: (i) Double-convolutional residual encoder structure based on dilated causal convolution; (ii) Spatio-temporal double-gated structure based on Gated Linear Units. Moreover, this study designs a loss function suitable for general long sequence time-series forecast tasks for temperature forecasting. Empirical simulations using a high-speed rail air-conditioning operation dataset at a specific location in China show that the temperature prediction of the two units using the improved TFT model improves the MAPE by 21.70% and 11.73%, respectively the original model. Furthermore, experiments demonstrate that the model effectively outperforms seven popular methods on time series computing tasks, and the attention of the prediction problem in the time dimension is analyzed.     

Theoretical Studies on the N-Phenylpyrrolidine Formation Mechanism Based on the Reaction of Phenylamine with 1,4-Butanediol

The reaction mechanism of phenylamine reacting with 1,4-butanediol to give N- phenylpyrrolidine was investigated with traditional transition state theory. Based on the experimental results, two reaction channels were discussed. The geometries of their reactants, products, intermediates and transition states were optimized. The possible transition State and activation energy were determined by vibrational analysis and IRC verification. And finally, the main reaction channel was given.     

A Novel （4,6）-Connected Net Based on Dysprosium Benzenedicarboxylate, [Dy（OAc）（BDC）]n

A new lanthanide coordination polymer, [Dy（OAc）（BDC）]n 1 （OAc = acetate, BDC = 1,4-benzenediacarboxylate）, has been synthesized under hydrothermal conditions. Single-crystal X-ray diffraction analysis reveals that complex 1 has infinite zigzag Dy-OAc chains, which are further connected by BDC to form a 3D metal-organic framework. According to topology analysis, this framework can be characterized as （4,6）-connected （3.4.54）（32.4.56.66） net that has never been reported before. Crystal structure for 1： space group Pbca, a = 13.314（3）, b = 8.0269（18）, c = 20.275（5）A, V= 2166.8（9）A3, C10H7O6Dy, Mr = 385.66, Z= 8, Dc = 2.364 g/cm^3, μ= 6.910 mm^-1, F（000） = 1448, the final R = 0.0181 and wR = 0.0520.     

涡轮叶片前缘阵列冲击冷却流动及传热特性数值研究

本文采用SST湍流模型模拟了类前缘通道内蒸汽射流阵列冲击冷却的流动与传热特性,分析了雷诺数(Re=10000～50000)、孔径比(d/H=0.5～0.9)和孔间距比(S/H=2～6)对流动及传热性能的影响规律,得到了相应的传热和摩擦关联式。结果表明:在不同雷诺数下,d/H从0.5到0.9变化时,通道压力损失系数降低了76%～79%,靶面平均努塞尔数降低了45%～49%;S/H从2增至6时,通道压力损失系数增加了1.64～1.92倍,靶面平均努塞尔数增加了54%～64%;增大d/H、减小S/H可有效提高类前缘通道蒸汽冲击冷却的综合热力系数。本文研究结果可为未来先进燃气轮机高温涡轮叶片蒸汽冷却结构的设计提供参考和借鉴。     

木卫停泊轨道间低耗能小推力转移轨道设计方法研究

对木卫停泊轨道间的低耗能小推力转移轨道设计方法进行了研究,提出基于“类halo轨道截面”法的低耗能转移轨道参数化方法和基于配点法的多体Lambert问题求解算法,并利用全局优化算法得出了燃耗最少的初步优化结果;利用多体同伦法和固定近心点高度的多圈转移控制律得到了各段小推力转移轨道的有效设计结果.所提方法同样适用于其他天体间的转移轨道设计,为多体环境下低耗能小推力转移轨道提出了新的设计思路和方法.     

应变率对含裂隙红砂岩裂纹扩展模式及破碎特征的影响

以含不同倾角预制裂纹的长方形板状红砂岩为研究对象,采用分离式霍普金森压杆沿试样宽度方向施加冲击荷载,使用高速摄像机记录裂纹扩展过程,获得试样的裂纹路径特征以及动态压缩强度和动态弹性模量,利用筛分统计法分析试样碎块分布特征,结合分形理论定量描述试样破碎程度及特点,探讨中应变率条件下含裂隙试样裂纹扩展模式与动态力学性质和破碎程度的相互关系。研究结果表明,应变率较高时试样会更多地出现远场裂纹和离层裂纹,并且相比相关低应变率实验结果,中应变率范围内试样破坏模式及裂纹分布情况随应变率的变化规律是不同的。随着应变率的提高,试样大体上从1条拉伸裂纹的临界破坏演变成X形剪切裂纹为主的复杂裂隙网络,并且不同角度预制裂隙对于这种裂纹扩展模式的演变有重要影响。在预制裂纹倾角一定的情况下,岩样动态压缩强度和动态弹性模量表现出明显的应变率效应,不同角度预制裂纹对于试样的应变率敏感性有显著影响。随裂纹倾角的增大,试样的动态强度、动态弹性模量和分形维数表现出的变化趋势具有一定的相似性,大体呈现先减小后增大的趋势,裂纹倾角为45°的试样的动态压缩强度、动态弹性模量和分形维数均为最小。随应变率的升高,不同预制裂纹倾角的试样碎块分布更加分散,应变率越高,预制裂纹倾角对于岩石冲击破碎程度、分形维数的影响越显著。