含硫磷的水溶性三嗪添加剂对硬质合金的摩擦学性能研究

合成一种水溶性润滑添加剂2,4-双-(二乙醇胺基)-6-(O,O'-二乙醇胺基二硫代磷酸酯)-S-基-1,3,5-均三嗪化合物(DDT),利用四球摩擦试验机考察其在水-乙二醇基础液中对YG8硬质合金钢球的润滑性能。结果表明:该化合物作为水基润滑添加剂可使水-乙二醇基础液的极压值提高了近5倍,并且可使硬质合金钢球磨斑直径和磨痕明显减小,表现出优异的抗磨减摩性能;通过SEM和EDS分析,可推测该水溶性化合物在摩擦过程中可能发生化学反应生成了磷酸钨、二硫化钨等化学膜,也可能生成一些含S、N小分子有机物组成的边界润滑膜,从而起到了良好的抗磨减摩作用。     

激波风洞瞬时动导数试验方法研究

为了克服高超声速激波风洞工作时间短,发展并建立了瞬时动导数实验技术。该技术在传统自由振动风洞试验装置基础上,使用新研制了高频动态天平,通过风洞启动时的随机扰动获取模型/天平系统的高频响应数据,最后经瞬时功率谱数据分析方法辨识出动稳定导数。不仅阐述了瞬时动导数实验原理与瞬时功率谱数据分析方法,而且介绍了高频动态天平及其实验装置结构。M=8.0、10°尖锥模型激波风洞试验结果表明,与自由振动方法相比,试验装置结构简单,易于实现,具有较高的精准度,有能力解决在高超声速激波风洞动稳定实验问题。     

永磁同步电动机转速伺服系统PI控制器的一种新设计方法

提出了PI控制器的一种新设计方法,将所有已知和未知的扰动集中为总扰动,简化系统模型,再用积分器作为扰动观测器对总扰动进行观测并补偿。新型PI控制器中的参数与系统性能之间的关系非常简单,易于整定。针对连续变化输入,新型PI控制器引入了输入微分前馈,具有更好的跟踪性能,且输入微分前馈仅是一个微分器,与电动机参数无关,进一步简化了控制器的设计。采用离散最速跟踪微分器对阶跃输入安排过渡过程,可以消除PI控制系统阶跃响应的超调,同时提高系统阶跃响应对控制器参数的不敏感性。实验结果验证了所提方法的有效性。     

新型苯并咪唑衍生物的合成及其性能

以三聚氯氰、正己胺、牛磺酸、2-氨基苯并咪唑为原料合成了一种新型苯并咪唑衍生物。通过红外光谱、核磁共振氢谱、高分辨率质谱对产物进行了结构表征,采用吊片法研究产物的表面活性,考察并比较了产物和2-氨基苯并咪唑的抑菌性能。结果表明:产物的临界胶束浓度及相应的表面张力分别为8.5×10-3 mol/L和33.1mN/m。产物对大肠杆菌和金黄色葡萄球菌的生长均具有较好的抑制作用,其中对金黄色葡萄球菌的抑制更显著;与2-氨基苯并咪唑相比,表面活性的引入使产物的抑菌性能大大提高。所合成的新型苯并咪唑衍生物兼备表面活性、抑菌的优良性能。     

两亲性海藻酸衍生物对纳米TiO2颗粒在水溶液中聚集行为的影响

利用十二烷基改性海藻酸钠(Na Alg-Dode)在Ti O2纳米颗粒表面上的吸附,得到了稳定的纳米Ti O2颗粒悬浮液。采用傅里叶变换红外光谱仪(FTIR)、动态光散射仪(DLS)及流变仪对颗粒粒径、表面电位及其悬浮体系的流变性进行了测定,研究了不同p H下Na Alg-Dode对纳米Ti O2颗粒在水溶液中聚集行为和流变性的影响。结果表明,加入Na Alg-Dode后,在p H=4~8内均有利于悬浮体系稳定,p H=6.3(等电点)处Ti O2颗粒的平均粒径由2.5μm降低至500 nm左右,颗粒表面Zeta电位由0降低至-40 m V左右。同时随着Na Alg-Dode的加入,Ti O2悬浮体系的剪切应力逐渐增大,表明颗粒间的相互作用增强。由此推知,Na Alg-Dode提高纳米Ti O2颗粒悬浮体系的稳定机制:Na Alg-Dode分子在不同p H下能够通过静电作用、氢键作用及疏水作用等吸附在Ti O2颗粒上,改变颗粒表面电性及空间位阻,从而降低颗粒的团聚。     

Synthesis and characterization of a new perylene bisimide (PBI) derivative and its application as electron acceptor for bulk heterojunction polymer solar cells

A symmetrical perylene bisimide derivative (PBI) with 2-(4-nitrophenyl)acrylonitrile groups at the 1,7 bay positions of perylene and solubilizing cyclohexyl units was synthesized and characterized. The absorption spectrum of PBI was broad with the most prominent peak at 655 nm and optical band gap of 1.72 eV. The electrochemical investigation indicates that PBI has a LUMO energy level of −3.9 eV which is similar to that of PCBM or PC₇₀BM. Bulk heterojunction solar cell fabricated using a blend of poly(3-hexylthiophene) (P3HT) and PBI (1:1 w/w) as active layer cast from THF exhibited power conversion efficiency (PCE) at 1.56%. However, the device with P3HT:PBI blend deposited from mixed solvent (DIO/THF) improved the PCE to 2.78% which further increased to 3.17% on using the thermal annealed active layer. The improvement in the PCE is attributed to the enhanced crystallinity of the blend (particularly P3HT) and increase in hole mobility leading to balanced charge transport.     

咔唑的提取与合成方法综述

本文综述咔唑的发展状况.对咔唑的产量、提取进行了简单介绍,重点介绍了咔唑的合成方法.     

基于广泛靶向代谢组学分析黑老虎种子中氨基酸和脂质组分

为探究黑老虎种子作为新兴植物油料资源的潜力,利用广泛靶向代谢组学技术检测分析其氨基酸和脂质组分。结果表明：在基于鉴定出的代谢物结构配置分类下,黑老虎种子含脂质类、氨基酸及衍生物类化合物分别为121种和89种,前者数量和相对含量(30.7%)在11类成分中最高,后者数量居其次,相对含量(17.8%)位于第三;鉴定出20种基础氨基酸和8种人体必需氨基酸,其中L-脯氨酸、L-天冬氨酸、L-丝氨酸等7种药效氨基酸和L-亮氨酸、L-苏氨酸、L-异亮氨酸、L-苯丙氨酸和L-赖氨酸5种人体必需氨基酸含量较高;黑老虎种子中富含亚油酸、γ-亚麻酸、α-亚麻酸等脂肪酸和以溶血磷脂酰胆碱18∶2和18∶2(2n异构)为主的磷脂。黑老虎种子氨基酸类和脂质类组分丰富,多种高度富集成分具有突出的营养功能、活性作用和药用功效,在优质植物油脂开发等领域具有较高的价值。     

Tribological study of triazine derivatives as additives in rapeseed oil

Three novel S‐P‐N type triazine derivatives were synthesised, and their structures were analysed through elemental analysis, and their tribological behaviours as additives in rapeseed oil were evaluated using a four‐ball tester. The extreme pressure and antiwear (AW) mechanism was investigated by X‐ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The results indicate that the additives possess excellent load‐carrying capacity and AW ability but have some friction‐reducing property only under the low load condition. Based on the results of XPS and SEM analysis, it can be seen that tribochemical reaction occurred between the synthesised compounds and metal surfaces during the sliding process, to form a complex film which has excellent load‐carrying capacity and AW ability. Copyright © 2010 John Wiley & Sons, Ltd.     

WELL TEST MODEL IDENTIFICATION BY ARTIFICIAL NEURAL NETWORKS

ABSTRACT

The aim of this research is to investigate the performance of artificial neural networks computing technology, to identify preliminary well test interpretation model based on derivative plot. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The trained network is then requested to identify the well test identification model for test data, which is not used during training sessions. For creation of training examples, an analytical response generator is implemented which is capable of producing responses of various models. Both the neural network simulator and the analytical response generator is enfolded into a single package which is capable of producing diagnosis plots, transferring data and filtering the input pattern. Unlike the ones presented in literature the package utilises a distributed modular structure, by which saturation possibility of the neural network is reduced considerably. Moreover, the distributed structure allows the training sequence to be initiated on different computers, thus reducing the training time up to sixteen folds. The package is verified with several examples either analytically generated or taken from literature.