A novel bio‐based phthalonitrile resin derived from catechin: synthesis and comparison of curing behavior with petroleum‐based counterpart

The development of bio‐based thermosetting resins with good thermal stability can potentially afford sustainable polymers as replacements for petroleum‐based polymers. We report a practical route to a novel catechin‐based phthalonitrile resin precursor (CA‐Ph), which contains free phenolic hydroxyl groups that result in ‘self‐curing’ at elevated temperatures to afford a thermostable polymer. Comparison of the performance of this CA‐Ph resin with that of a conventional petroleum‐based bisphenol A phthalonitrile resin (BPA‐Ph; containing 5 wt% of the curing agent 4,4′‐diaminodiphenylsulfone) revealed that CA‐Ph exhibits a lower melting point and curing temperature. Cured CA‐Ph resin retains 95% of its weight at 520 °C under a nitrogen atmosphere, which compares favorably with results obtained for BPA‐Ph resin that retains 95% of its weight at a lower temperature of 484 °C. Kinetic results indicated that the curing reactions of both CA‐Ph and BPA‐Ph systems follow an autocatalytic mechanism. These results suggest that catechin is a useful bio‐based feedstock for the preparation of self‐curing and thermally stable phthalonitrile resins for advanced technological applications. © 2017 Society of Chemical Industry     

生物质源多孔碳制备及其对废水中药物吸附研究进展

城市现代化与工业化的快速发展给环境造成的污染日趋严重，尤其以水体污染最为明显。近年来，工业废水中药物的含量逐年上升，污染程度已经不容忽视。因此，开发新型多孔材料用于废水中药物分子的吸附分离，已经成为了当前的研究热点。综述了近年来生物质源多孔碳（生物炭）在废水中污染物吸附分离方面的研究，首先简单介绍了废水中污染物的治理方法，在此基础上重点探讨了生物炭的制备与修饰，并结合碳材料表面化学性质与孔道结构，总结并展望了生物炭对药物的吸附性能。     

基于SVM的煤与瓦斯突出预测模型及应用

为有效预测矿井内煤与瓦斯突出的危险程度,对其影响因素做了分析与探讨,分别构建了基于粒子群优化算法以及遗传算法支持向量机的煤与瓦斯突出预测模型,并且通过实例对两种模型预测的准确性进行了验证。分别利用单项以及综合指标、BP神经网络以及PSO-SVM模型、GA-SVM模型,对寺河煤矿二号井的突出区域进行预测比较。结果表明,PSO-SVM的预测模型不仅可以在小样本数据中预测出煤与瓦斯突出程度的大小,而且综合预测结果更加精确,其在解决矿井内煤与瓦斯突出的小样本数据中显示出更加强大、通用的性能。     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Detecting Cysteine in Bioimaging with a Near-Infrared Probe Based on a Novel Fluorescence Quenching Mechanism

Near-infrared (NIR) fluorescent probes are very significant for detecting cysteine in biological systems. Herein, we report a highly selective and sensitive NIR turn-on fluorescent probe (BDP-NIR) based on BODIPY with large Stokes shift (105 nm) for detecting Cys. We clarified the sensing mechanism based on the different thiol-induced S_NAr substitution/rearrangement reaction of the probe with cysteine and homocysteine/glutathione, which leads to the corresponding amino- and thiol-BODIPY dyes with distinct photophysical properties. Moreover, a novel mechanism of fluorescence quenching was demonstrated by density functional theory calculation. The reason for the fluorescence quenching of the probe might be intersystem crossing (from singlet to triplet excited state). Moreover, BDP-NIR had a high linear dynamic range of 0–500 μM, which was promising for detecting cysteine quantificationally. Significantly, BDP-NIR was capable of sensing endogenous cysteine in living cells and in vivo.     

咖啡渣活性炭的制备、表征及其对Cr(Ⅵ)的吸附机制研究

以碘吸附值为评价指标，活化时间、活化温度和浸渍比为影响因素，采用响应面法试验设计对磷酸活化法制备咖啡渣活性炭的工艺条件进行优化，并通过静态吸附试验研究了不同吸附时间、溶液pH值和吸附温度条件下，活性炭对水溶液中Cr（Ⅵ）吸附性能的影响，最后利用Langmuir、Freundlich吸附等温方程、准一级动力学方程、准二级动力学方程和颗粒内部扩散方程进行拟合。试验结果表明，制备咖啡渣活性炭的最佳工艺条件为活化时间1 h、活化温度498℃、浸渍比1.72；在此条件下活性炭得率为30.4%，碘吸附值为（799±16）mg/g，比表面积为1 006 m²/g，孔容为0.779 cm³/g、微孔孔容为0.051 cm³/g、平均孔径为3.088 nm。较低pH值和较高温度能够促进活性炭对Cr（Ⅵ）的吸附；Langmuir等温方程能够更好地描述活性炭对Cr（Ⅵ）的吸附效果；活性炭对Cr（Ⅵ）的吸附分3个阶段：快速吸附阶段、慢速吸附阶段和吸附平衡阶段，10 min内可完成吸附总量的79%，360 min内达到吸附平衡，该吸附过程符合准二级吸附动力学方程。分析表明咖啡渣活性炭对Cr（Ⅵ）的吸附主要为单分子层的化学吸附。