高效能反渗透/纳滤复合分离膜材料、其制备方法及用途

本发明公开了一种高效能反渗透/纳滤复合分离膜材料及其制备方法。该膜材料由纳米多孔材料与有机聚合物膜材料组成,并且纳米多孔材料嵌入在有机聚合物膜材料中。采用将纳米多孔材料预先自组装在由聚砜等超滤支撑材料构成的支撑层上面,随后通过聚合反应,将纳米     

多壁碳纳米管/钴镍层状双金属氢氧化物纳米复合材料的制备及电化学性能研究

以硫酸钴（CoSO₄·7H₂O）为钴源、硫酸镍（NiSO₄·7H₂O）为镍源，通过水热法将多壁碳纳米管（MWCNTs）嵌入到钴镍层状双金属氢氧化物（CoNi-LDHs）中合成CoNi-LDHs/MWCNTs复合材料。通过FT-IR、FE-SEM、XRD等分析方法对复合材料的微观组织结构和表面形貌进行表征，并通过循环伏安、恒流充放电以及交流阻抗谱等测试方法对该材料的电化学性能进行研究。结果表明，当反应体系中引入MWCNTs后，CoNi-LDHs颗粒均匀地嵌入碳纳米管网络中，与碳纳米管紧密结合交错在一起，增大了材料的表面积，为氧化还原反应提供了丰富的活性位点；在电流密度为0.5 A/g下，复合材料比电容高达1 965.55 F/g,表明该复合材料具有优异的电化学性能。     

有机多孔聚合物CO2捕集及分离性能的研究进展

有机多孔聚合物（porous organic polymers,POPs）是一类由有机构建单元连接而形成的新型多孔材料。由于其优异的物理化学稳定性以及CO₂吸附能力,近年来有关POPs在CO₂捕集和分离的研究成为一大研究热点。大量具有优异孔性质（比表面积和孔容）的POPs通过不同有机合成反应被成功地开发出来应用于CO₂吸附分离过程。本文介绍了POPs材料的CO₂捕集与分离性能的研究现状,总结了提高POPs材料CO₂分离性能的合成策略,重点分析了可以通过功能化增强吸附剂与二氧化碳分子之间的相互作用,来提高材料的CO₂分离能力的方法。     

有机膦系抑制方解石阶梯面生长的分子动力学研究

有机膦系化合物是工业冷却水系统中常用阻垢剂,对有机膦酸阻垢剂的阻垢性能及机理进行研究,能为新型阻垢剂开发应用提供合理的理论依据。根据周期性键链（PBC）理论模型,运用分子动力学方法（MD）,模拟了工业冷却水循环过程中5种有机膦阻垢剂与方解石4种阶梯面的相互作用机理。结果表明,有机膦酸分子与方解石（104）4个阶梯面的结合能均为负值,相互作用为放热过程,阻垢剂分子对方解石（104）阶梯面的生长具有良好的抑制作用。通过计算结合能,得出阻垢剂分子的吸附能力由强到弱依次为HDTMP、EDTMP、ATMP、NDP、AMP;同时观察到有机膦酸分子主要吸附在晶面的活性生长点,即阶梯面的终端拐角位置与阶梯拐点位置,占据了晶面上结晶的活性位置,抑制了晶面的进一步生长。根据有机膦酸与阶梯面结合能数据,得到4种终端阶梯面的吸附能力由强到弱依次为CO₃-CO₃、CO₃-Ca、Ca-CO₃、Ca-Ca,即稳定性越强则吸附能力越弱。     

农药设计中的活性子叠加法

活性子（Activon）是指农药分子中具有生理活性所必需的分子片段，该片段中分布着与受体通过电荷控制和轨道控制进行键合的若干部位。通过合成手段将活性子连接起来，是发现新农药的有效方法之一。     

气体中微量甲醛的脱除研究进展

主要阐述了去除甲醛气体的常用材料（吸附材料、催化氧化材料、光催化降解材料和生物技术材料）的研究进展,文中指出碳基材料、分子筛、有机金属骨架常常被用作吸附挥发性有机气体,它们具备丰富的孔道结构和较大的比表面积,碳基材料和分子筛表面存在大量丰富的基团能够有效地增大甲醛的吸附容量,提高甲醛的吸附效率;有机金属骨架表面的金属与甲醛结合成键,有效提高材料的化学吸附;以金属氧化物为载体的材料常被用作催化氧化甲醛分子,将甲醛分子转化为无毒性的二氧化碳和水;半导体材料TiO₂常被用作光催化降解材料去除甲醛;除此之外还有一些利用生物技术来去除甲醛气体。本文对比了不同材料去除甲醛的优劣性,对不同的去除材料改性研究进行了归纳总结。     

基于手性单体的聚氨酯-SiO2核壳结构复合物的制备和表征

一、前言 有机／无机复合物的研究发展成为材料领域的一个主要研究方向。有机相与无机相之间的协同效应使复合材料具有不同于单一相的光、电、磁、力等性能。目前,利用有机分子所含有的功能团与纳米无机物之间的相互作用,将有机分子固定在无机基底上被广泛研究。     

β-环糊精修饰的乙烷桥键有序介孔有机硅材料的合成及应用

该文用“嫁接”的方法将β-环糊精（β-CD）修饰在乙烷桥键有序介孔有机硅材料（PMO）上,并以同样的方法合成了β-CD修饰的介孔材料SBA-15作为对比材料。通过傅里叶红外光谱（FTIR）、高分辨透射电镜（HRTEM）、X射线粉末衍射（XRD）、氮气吸附以及热分析（TGA）实验对修饰前后的PMO材料进行表征。考察了修饰前后PMO材料对于水中污染物苯胺和对苯二酚的吸附性能,由结果可知,β-CD修饰的乙烷桥键有序介孔有机硅材料（PMO-CD）对于苯胺的吸附量为1.54mg/g,相对于PMO材料而言,其吸附能力被极大的抑制,而其对于对苯二酚的吸附量为12.94mg/g,吸附性能得到了很大的提高。因此,PMO-CD在处理水中污染物领域具有潜在的应用价值。     

笼型倍半硅氧烷（POSS）的功能化改性 及应用研究进展

有机/无机杂化材料的改性及应用是目前材料科学中最富有活力的研究领域之一。其中笼型倍半硅氧烷（Polyhedral oligomeric silsesquioxane，POSS）在分子水平上实现了有机组分与无机组分的结合，结构呈硅氧骨架连接的立体笼型，具有优异的反应活性、耐热阻燃性、多孔性和纳米尺寸效应等特性，通过化学改性可将其应用在多个领域。本文主要从官能团改性、聚合改性和配位改性三个方面阐述了POSS的改性方法，综述了POSS在耐热材料、阻燃材料、增强材料和多孔材料等领域的应用研究进展，并对POSS今后的研究方向提出了展望。可从POSS的构效关系、改性方法以及安全性等方面进行更加深入和系统的研究，以促进POSS材料更广泛的应用。     

高性能丁基橡胶/有机黏土纳米复合材料的新型制备方法

采用一种新型制备方法--预膨胀有机黏土与机械共混的方法制备丁基橡胶（IIR）/有机黏土纳米复合材料。实验结果表明,当有机黏土为10 phr时,采用预膨胀有机黏土（S-OC）与机械共混的方法制备的IIR/有机黏土纳米复合材料（IIR/S-OCNs）的拉伸强度和撕裂强度,明显优于采用熔体法制备的IIR/有机黏土（OC）纳米复合材料（IIR/OCNs）的相应性能,较纯丁基橡胶分别提高了4.96倍、0.22倍;当有机黏土为5 phr时,采用预膨胀有机黏土与机械共混的方法制备的IIR/S-OC纳米复合材料的气体渗透率,分别较纯IIR、熔体法制备的IIR/OC纳米复合材料下降了21.88%和12.50%。这种新型制备方法是将溶液制备方法的优点与熔体制备方法的优点有机地统一在了一起。该材料有可能在高级无内胎轮胎气密层以及其他要求高性能弹性体材料的领域获得应用。     

Molecular Conditional Generation and Property Analysis of Non-Fullerene Acceptors with Deep Learning

The proposition of non-fullerene acceptors (NFAs) in organic solar cells has made great progress in the raise of power conversion efficiency, and it also broadens the ways for searching and designing new acceptor molecules. In this work, the design of novel NFAs with required properties is performed with the conditional generative model constructed from a convolutional neural network (CNN). The temporal CNN is firstly trained to be a good string-based molecular conditional generative model to directly generate the desired molecules. The reliability of generated molecular properties is then demonstrated by a graph-based prediction model and evaluated with quantum chemical calculations. Specifically, the global attention mechanism is incorporated in the prediction model to pool the extracted information of molecular structures and provide interpretability. By combining the generative and prediction models, thousands of NFAs with required frontier molecular orbital energies are generated. The generated new molecules essentially explore the chemical space and enrich the database of transformation rules for molecular design. The conditional generation model can also be trained to generate the molecules from molecular fragments, and the contribution of molecular fragments to the properties is subsequently predicted by the prediction model.     

Adsorption of tetrachloroethylene (PCE) in gas phase on zeolites of faujasite type: Influence of water vapour and of Si/Al ratio

This study is focused on the adsorption of a chlorinated volatile organic compound, the tetrachloroethylene (PCE), on dealuminated faujasite type zeolites with framework Si/Al ratio between 5 and 100. PCE dynamic adsorption experiments with and without water vapour (relative humidity of, respectively, 50% and 0%) were carried out in a fixed bed reactor at 50 °C. Breakthrough curves were fitted by a model using the integral of a Gauss distribution. PCE adsorption capacities depend on the adsorbent microporous volume. However, in presence of water vapour, PCE adsorption is favoured on hydrophobic zeolites but also depends on the diffusional limitations inside the porous system. In order to have a better understanding of water molecules adsorption, isotherms were measured using thermogravimetric method at 25 °C. The presence of water vapour generally decreases PCE uptake but its influence decreases as the Si/Al ratio of the adsorbent increases. Experiments with various gases hourly space velocity (GHSV) and inlet PCE concentrations were also performed. PCE complete desorption was obtained on HFAU(Si/Al = 17) at 180 °C. This easy regeneration of the sample permitted adsorption/regeneration cycles maintaining good adsorption properties.     

Effect of soil organic carbon on sorption and desorption of perchloroethylene in soils

The objective of this study was to elucidate the sorption and desorption behaviors of PCE (Perchloroethylene, C₂Cl₄) in seven soils with different organic carbon (OC) content. Sorption/desorption kinetic and serial dilution desorption experiments were conducted in batch slurries. The sorption distribution coefficient (K _d ) of PCE ranged from 0.60 to 4.66 L kg^?1. K _d tended to increase as the soil OC increased, but K _oc tended to decrease, suggesting that adsorption into the mineral surface was not negligible in soils with low OC. Desorption kinetic data were analyzed by the two-site desorption model. The sorption/desorption of PCE was not reversible over short incubation times due to the presence of a non-desorbable site. The desorbable site fractions of PCE increased and non-desorbable site fractions decreased as the soil OC increased. It is suggested that partition of PCE into soil organic carbon is more reversible than adsorption on soil minerals.     

A deep graph convolutional network model of NOx emission prediction for coal-fired boiler

To deal with environmental problems caused by NOx production in thermal plants, it is imperative to establish a reliable model to predict NOx concentration in the combustion process. NOx formation in a coal-fired boiler is complex, and many variables affect NOx emissions. The effective information fusion of these variables can improve the accuracy of NOx concentration prediction. However, the existing NOx prediction algorithms based on thermal parameters rarely consider the mechanical knowledge of the boiler operation, and it is not easy to incorporate the topological information of production into modelling. Therefore, a graph convolutional network is proposed for NOx emission prediction. First, the key variables affecting NOx generation are selected according to the knowledge and the random forest-based variable importance. Then, the model structure is designed by exploring the topological information among thermal variables to capture the complex spatial dependence. The model inputs are constructed by coding different operation variables, and the adjacency matrix is generated according to the correlation information between variables, which can fuse data information and reduce redundancy. On this basis, the prediction model of NOx concentration is established. Historical data from a 660 MW coal-fired boiler are used in the experiment. The prediction results show that the proposed model can effectively fuse the information of characteristic variables and fully exploit the non-linear mapping relationship between process variables and NOx emission. When compared with three typical models in NOx modelling, the proposed model has better performance with a determination coefficient of 0.906.     

超高强混凝土中各组分与聚羧酸系超塑化剂之间的相互作用(英文)

超高强混凝土(ultra-high strength concrete,UHSC)的水灰比小于0.25,含有大量的硅灰等微细组分,这有利于颗粒的最优紧密堆积。硅灰的表面化学效应以及较大的表面积使其成为UHSC中最难被分散的组分。由甲基丙烯酸、甲基丙烯酸酯及甲代烯丙基磺酸合成的聚羧酸系超塑化剂能使水泥颗粒被有效润湿,然而烯丙醚-马来酸酐合成的聚羧酸系超塑化剂可以很好地分散硅灰。这2种不同的聚羧酸系超塑化剂的复合可以使其拥有不同的分子结构,从而赋予超高强混凝土很好的流动性。当只加入1种聚羧酸系超塑化剂时其掺量为1%(质量分数,下同),而当加入这种复合聚羧酸系超塑化剂时掺量为0.5%就足够了。这2种类型的聚羧酸系超塑化剂的协同效应是由于它们的选择性吸附:甲基丙烯酸盐基的聚羧酸系超塑化剂主要吸附在水泥颗粒表面,而烯丙醚基聚羧酸系超塑化剂主要吸附在硅灰颗粒表面。实验表明:小分子量的有机酸阴离子(如:柠檬酸盐、葡萄糖酸盐及酒石酸盐中的阴离子)与聚羧酸系超塑化剂之间具有潜在的协同作用。只需加入0.1%的这些阴离子即可显著提高烯丙醚基聚羧酸系超塑化剂的作用效果。这些阴离子可以起到一种辅助作用,它们同时吸附在水泥颗粒表面以及硅灰颗粒表面。水泥颗粒的表面首先由这些阴离子所占据,而硅灰颗粒表面吸附了烯丙醚基聚羧酸系超塑化剂和这些阴离子。这些阴离子起到了一种很强的静电分散效应,使烯丙醚基聚羧酸系超塑化剂的空间位阻效应得到加强。虽然聚羧酸系超塑化剂阴离子具有缓凝作用,但是使用这种复合聚羧酸系仍能制备出高早强混凝土。     

A Novel Method for Preparing Vertically Aligned CdS Nanorod Arrays and Its Application in Photovoltaic Cells with P3HT Fibers

Vertically aligned cadmium sulfide (CdS) nanorod arrays were prepared through a novel thermal annealing route. By embedding the as-prepared CdS nanorod arrays into the poly(3-hexylthiophene) (P3HT) nanofiber (NF) matrix, the photovoltaic devices were fabricated with the structure of ITO/PEDOT:PSS/CdS arrays/P3HT NF/Au. The device performance was highly dependent on the P3HT NF layer thickness in this structure, and a power conversion efficiency (PCE) of 0.23 % was obtained for optimal P3HT NF layer thickness of 150 nm. In addition, much higher PCE of 0.84 % was achieved after post-annealing. The significantly improved photovoltaic performance may be caused by the increased interfacial areas between P3HT NFs and CdS nanorods for efficient charge separation, as well as the decreased inter-nanocrystal distance caused by insulating organic ligands after the annealing treatment. The results demonstrate a promising inorganic–organic hybrid photovoltaic structure with vertically aligned CdS nanorods arrays.     

Effect of perchloroethylene (PCE) and hydraulic shock loads on a membrane‐aerated biofilm reactor (MABR) biodegrading PCE

BACKGROUND: A membrane‐aerated biofilm reactor (MABR) has previously been used to provide both anaerobic and aerobic conditions for mineralisation of perchloroethylene (PCE). However, very little is known about the stability of this reactor under hydraulic and PCE shock loads. An MABR was therefore subjected to sudden hydraulic and PCE shock loads in order to investigate its stability under such conditions. RESULTS: After each shock, the reactor responded with an increase of chemical oxygen demand (COD) and volatile fatty acids (VFA)s, a breakthrough of PCE and its biodegradation intermediates in the effluent, and a decrease in methane production. Although some PCE biodegradation intermediates were found in the effluent during each shock loading, the MABR performance recovered without the accumulation of any particular PCE biodegradation intermediates during PCE shock loads. During the hydraulic shock loads, the MABR was unstable at hydraulic retention times (HRTs) of 6 h with PCE and its biodegradation intermediates detected in the effluent. However, these intermediates were degraded when the HRT was reset to 48 h. CONCLUSIONS: This study suggests that MABRs can withstand fluctuations in influent strength and flows which occur in wastewater treatment works. Copyright © 2009 Society of Chemical Industry     

Modified molecular matrix model for predicting molecular composition of naphtha

To improve the naphtha composition prediction model based on molecular type homologous series matrix (MTHS), this paper puts forward a novelmolecular matrix to characterize the naphtha composition and the normal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novelmolecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.     

Flash point prediction of organic compounds using a group contribution and support vector machine

The flash point is one of the most important properties of flammable liquids. This study proposes a support vector regression (SVR) model to predict the flash points of 792 organic compounds from the DIPPR 801 database. The input variables of the model consist of 65 different functional groups, logarithm of molecular weight and their boiling points in this study. Cross-validation and particle swarm optimization were adopted to find three optimal parameters for the SVR model. Since the prediction largely relies on the selection of training data, 100 training data sets were randomly generated and tested. Moreover, all of the organic compounds used in this model were divided into three major classes, which are non-ring, aliphatic ring, and aromatic ring, and a prediction model was built accordingly for each class. The prediction results from the three-class model were much improved than those obtained from the previous works, with the average absolute error being 5.11–7.15 K for the whole data set. The errors in calculation were comparable with the ones from experimental measurements. Therefore, the proposed model can be implemented to determine the initial flash point for any new organic compounds.