Facile preparation of poly (2,6-dimethyl-1,4-phenylene oxide)-based anion exchange membranes with improved alkaline stability

Traditional quaternary ammonium (QA)-type anion exchange membranes (AEMs) usually exhibit insufficient alkaline stability, which impede their practical application in fuel cells. To address this issue, a facile method for the simple and accessible preparation of QA-type AEMs with improved alkaline stability was developed in this study. A series of novel AEMs (QPPO-xx-OH) were prepared from commercially available poly (2,6-dimethyl-1,4-phenylene oxide) (PPO) and 3-(dimethylamino)-2,2-dimethyl-1-propanol, via a three-step procedure that included bromination, quaternization, and ion exchange. Scanning electron microscopy revealed that dense, uniform membranes were formed. These QPPO-xx-OH membranes exhibited moderate hydroxide conductivities with ranges of 4–15 mS/cm at 30 °C and 12–36 mS/cm at 80 °C. When tested at similar ion exchange capacity (IEC) levels, the IEC retentions of QPPO-xx-OH membranes were 16–22% higher than that of traditional PPO membranes containing benzyltriethylammonium ions, after immersed in 2 M NaOH aqueous solution at 60 °C for 480 h, and the QPPO-47-OH membrane displayed excellent alkaline stability with the IEC retention of 92% after 480 h. In addition, the QPPO-xx-OH membranes also exhibited robust mechanical properties (tensile strength up to 37.6 MPa) and good thermal stability (onset decomposition temperature up to 150 °C). This study provides a new and scalable method for the facile preparation of AEMs with improved alkaline stability.     

柴达木盆地三湖地区生物气成藏基本要素及其配置性

柴达木盆地东部三湖地区位于青藏高原北部，地面平均海拔2 800 m，是该盆地第四纪沉积中心，也是中国最大的生物气田区。该区第四系厚达3 400 m，以固结较差的砂、泥岩为组成特征，长期低温和沉积水体的高盐度等条件为生物气的产生提供了丰富的物质基础，砂泥岩互层的高度发育为生物气的成藏提供了良好的储集和封盖条件，更新世以来一直存在的同沉积背斜为生物气提供了良好的圈闭条件，充足的地下水和地下水的定向流动将生物气的生、储和封存体系有机地联系在了一起，并构成了生物气聚—散的动态平衡。充足的气源供给、长期存在的圈闭、良好的封堵条件及其配置良好的区带是第四系生物气藏形成与分布的有利区带，例如该区北斜坡的涩北和台南地区为第四系生物气运移和聚集的最有利区带，易形成大气田，应作为下一步勘探的重点。      

Thermal Conductivities of Ⅲ-Ⅴ Antimonides

Thermal parameters of various Ⅲ-Ⅴ antimonides, especially the quaternary lattice matched to GaSh or InAs substrates as well as some strained ternaries, have been‘investigated theoretically. Results show that at most composition region many ternary and quaternary antimonides exhibit rather lower thermal conductivity compared to related binaries,and the reason has been discussed. The thermal designing rule of the lasers and other power devices using those antimonides also has been discussed.     

试论柴达木盆地第四系盖层的封盖机理

通过对柴达木盆地第四系高孔隙度、低突破压力和具有一定渗透性的特殊盖层研究后指出:这种特殊盖层封盖天然气的机理在于其中饱和高矿化度的地层水;泥岩盖层中孔隙流体压力同下伏气藏压力值很接近;区域盖层厚度巨大;盖层是源岩层;区内气候寒冷,冰冻期长,冰川广布。     

Flotation and adsorption of quaternary ammonium salts collectors on kaolinite of different particle size

The flotation behaviors of decyltrimethylammonium (103C), dodecyltrimethylammonium chloride (DTAC), tetradecyltrimethylammonium chloride (TTAC) and cetyltrimethylammonium chloride (CTAC) on kaolinite of different particle size fraction were studied. The adsorbed amount and adsorption isotherms of collectors on kaolinite were determined for painstaking investigation into the adsorption of quaternary amines at kaolinite–water interface by ultraviolet spectrophotometer methods. The flotation results show that the flotation recovery of kaolinite of different particle fraction increases with an increase in pH when 103C, DTAC, TTAC and CTAC are used as collectors. As the concentration of collectors increases, the flotation recovery increases. Particle size of kaolinite has a strong effect on flotation. The flotation recovery of fine kaolinite decreases with the carbon chain of quaternary ammonium salts collectors increasing, while coarse kaolinite is on the contrary. The adsorbed amount tests and adsorption isotherms show that adsorbed amount increases when the particle size of kaolinite increases or when the carbon chain length of quaternary ammonium salts increases. Within the range of flotation collector concentration, the longer the hydrocarbon chain, the more probable to be absolutely adsorbed by fine kaolinite particles and then the lower the collector concentration in the bulk, which leds to lower flotation recovery.     

双咪唑啉季铵盐的合成与缓蚀性能研究

利用两步法合成了双咪唑啉季铵盐化合物，通过失重法研究了该化合物在1g／L HCl 0．16g／L H2S 1g／L NaCl溶液和10％的盐酸溶液中对碳钢的缓蚀性能，讨论了用量、温度、时间对缓蚀性能的影响，并通过极化曲线和扫描电镜研究了该化合物的缓蚀机理。结果表明，该化合物在HCl-H2S-NaCl-H2O和10％的盐酸腐蚀环境中对碳钢具有良好的缓蚀作用，是一种以阳极控制为主的混合型缓蚀剂。     

含吡啶环的十聚钨酸季铵盐催化合成环己酮

以十聚钨酸季铵盐（[Bun Py]4W10O32）为催化剂、质量分数30%的H2O2为氧化剂,研究了环己醇催化氧化生成环己酮的反应,考察了反应时间、反应温度、H2O2和催化剂的物质的量等因素对此反应的影响。得出了此反应的最佳条件：反应温度为80℃,催化剂物质的量为0.06mmol,H2O2物质的量为125mmol,环己醇物质的量为50mmol,回流反应8h。在最佳反应条件下,环己醇的转化率为86.5%,环己酮的选择性可达到98.3%。反应后催化剂不溶于反应体系,简单过滤即可回收,重复使用3次后其活性基本不变。     

溶剂萃取分离铁锌

氯化物溶液中，铁（Ⅱ）、铁（Ⅲ）、锌（Ⅱ）与氯离子配位，形成不同的络合物，具有可萃性差异。对ＴＢＰ、叔胺、季铵进行分离性能比较后发现，季铵对铁（Ⅱ）、锌表现出优良的分离性能和较大的负载容量。机理研究表明，季铵萃锌是阴离子交换反应。模拟实验证实，经两级萃取能使铁（Ⅱ）、锌几乎完全分离。     

LIQUID PARTITIONING OF AMPHIPHILIC SOLUTIONS RELATED TO THE SOLVENT EXTRACTION OF BITUMEN FROM TAR SANDS

The Wood-Beaver process is a solvent extraction process which uses a fatty acid blend (light hydrocarbons, aromatics, and fatty acids) as the solvent and utilizes amphiphilic phase behavior and phase shift to recover the fatty acids from the solvated bitumen. The process consists of mixing the solvated bitumen with an alcohol-water wash which precipitates the bitumen as the bottom phase of the primary settler. The top phase of the settler contains the fatty acid/alcohol/water/light hydrocarbons components. The fatty acid and light hydrocarbons are then recovered in a secondary settler by shifting the phase equilibrium by either over-dosing with water or by driving off alcohol by the application of heat.

This paper presents experimental equilibrium phase behavior data and the correlations resulting from an analysis for the quaternary system of oleic acid, bitumen, isopropyl alcohol, and water. The data are presented in the form of psuedo ternary diagrams. The NRTL modelling equation was applied to the oleic acid/brine/isopropyl alcohol system in order to determine a set of interactive and non-randomness parameters that adequately describe the liquid-liquid phase behavior of this ternary system. The phase envelope and accompanying tie lines reproduced from the model showed acceptable agreement with the experimental data.     

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.