硼酸锌的性质、制备及阻燃应用

硼酸锌是最早的无机阻燃剂之一,具有热稳定性好、毒性低和消烟等良好的特点。综述了硼酸锌的主要性质、制备工艺和阻燃机理,同时也对硼酸锌与其他无机阻燃剂的复配效应和硼酸锌在各个领域中的应用进行了阐述。重点介绍了3大类制备硼酸锌的方法：传统的制备工艺由于原料价格较高或后处理工序复杂而存在弊端;超细硼酸锌的制备对硼酸锌的粒径要求比较高,但是由于其性能比较好,是目前研究的主要对象;固相法制备硼酸锌的研究,国外比国内进行得早,也较成熟一点,并指出通过高温烧结得到的硼酸锌是一种含有几种不同结构硼酸锌的混合物。最后指出了制备晶须状硼酸锌的意义。     

硼酸锌的合成及在阻燃聚烯烃中的应用

介绍了硼酸锌的理化性质、毒性、生产工艺和产品标准。总结了硼酸锌对聚烯烃的阻燃机理和特点。综述了近十年来硼酸锌在聚烯烃阻燃方面的研究成果。     

硼酸锌在阻燃橡胶及制品中应用的研究进展

介绍了硼酸锌的物化性质、毒性、生产方法和产品标准。概述了硼酸锌的阻燃机理和特性。综述了近十年来硼酸锌用于阻燃橡胶及其制品方面的研究成果。     

超细硼酸锌阻燃剂的制备及其性能研究

以硼砂和氯化锌为原料,研究了原料浓度、搅拌速度、乳化剂种类和用量等因素对硼酸锌粒径和粒径分布的影响。通过优化实验,制备了超细硼酸锌,数均平均粒径73nm,比表面积31.5m2/g,90%的粒子在纳米尺度范围。XRD衍射图与采用化学分析测定结果证明产物为低水硼酸锌(2ZnO.3B2O3.3.5H2O),电镜分析表明其晶体形貌为不规则的球形。将超细硼酸锌应用于聚氯乙烯,当硼酸锌用量为树脂质量的10%~30%,成炭率比未阻燃的聚氯乙烯大幅增加。表明超细硼酸锌在提高聚氯乙烯阻燃性的同时有很好的抑烟效果。     

硼酸锌阻燃苯乙烯系树脂的研究进展

介绍了硼酸锌的物化性质、毒性、生产工艺和产品标准。阐述了硼酸锌对苯乙烯系树脂的阻燃机制和特点。综述了近十年来硼酸锌在苯乙烯系树脂阻燃方面的研究进展。     

硼酸锌的应用研究进展

介绍了硼酸锌的阻燃机理以及硼酸锌及其复合体系的应用研究进展,指出了其今后的发展方向。     

硼酸锌在LDPE阻燃中的协效作用

阻燃协效剂硼酸锌加入无卤及有卤阻燃聚乙烯中,对其性能进行了测试,包括力学性能、阻燃性能。结果表明:硼酸锌对无卤及有卤体系都具有良好的协同效应,加入硼酸锌的体系是高效阻燃体系。     

硼酸锌对聚丙烯/EPFR/4A分子筛膨胀阻燃体系的协同作用

研究了硼酸锌(ZB)对PP/EPFR/4A分子筛膨胀阻燃体系的协同阻燃作用。UL-94垂直燃烧和极限氧指数实验结果表明:加入2%的硼酸锌能够有效提高聚丙烯的阻燃性,无卤阻燃PP的极限氧指数从不添加硼酸锌时的27%增加到31.5%。锥形量热器测试表明:加入2%的硼酸锌后材料的热释放速率(HRR)下降了37.5%,且第二个放热峰消失。扫描电镜实验结果表明:适量硼酸锌能够促进体系在高温下形成致密的炭层,阻止炭层下聚合物的燃烧。动态红外结果表明:硼酸锌能够提高聚丙烯/EPFR/4A分子筛复合材料体系的热稳定性。     

硼酸锌阻燃聚氯乙烯研究进展

介绍了硼酸锌的物化性质、毒性、生产过程和产品标准等。总结了硼酸锌对聚氯乙烯(PVC)的阻燃机理和特点。综述了近10年来硼酸锌在PVC阻燃方面的研究成果。     

ZB—硼酸锌的制备和应用

七十年代美国硼砂和化学公司首先开发成功Z_B—硼酸锌。2ZnO·3B_2O_3·3.5H_2O,商品名为:Firebrake Z_B,克服了其它各种硼酸锌的不足,因而扩大了在塑料中的应用。尤其是在难燃运输带中,无焰燃烧的效果是非常理想的。Zn—硼酸锌为白色结晶粉末,比重2.67,熔点980℃,失结晶水温度>300℃。ZB—硼酸锌可广泛用于各种塑     

玻璃纤维/纳米复合材料桩钉的生物性能研究

采用玻璃纤维、纳米粘土制备复合材料桩钉,测试其力学性能,并通过细胞毒性试验、溶血性试验研究桩钉的生物性能,为临床应用提供技术保证.     

芳纶表面改性研究进展

简单回顾了芳纶的发展历史,阐述了表面涂层法、化学改性、物理改性等几种芳纶表面改性方法的研究现状,同时介绍了3种常用来表征纤维复合材料界面结合强度的方法,最后指出芳纶表面改性技术的发展方向。     

Neural and Hormonal Basis of Opposite-Sex Preference by Chemosensory Signals

In mammalian reproduction, sexually active males seek female conspecifics, while estrous females try to approach males. This sex-specific response tendency is called sexual preference. In small rodents, sexual preference cues are mainly chemosensory signals, including pheromones. In this article, we review the physiological mechanisms involved in sexual preference for opposite-sex chemosensory signals in well-studied laboratory rodents, mice, rats, and hamsters of both sexes, especially an overview of peripheral sensory receptors, and hormonal and central regulation. In the hormonal regulation section, we discuss potential rodent brain bisexuality, as it includes neural substrates controlling both masculine and feminine sexual preferences, i.e., masculine preference for female odors and the opposite. In the central regulation section, we show the substantial circuit regulating sexual preference and also the influence of sexual experience that innate attractants activate in the brain reward system to establish the learned attractant. Finally, we review the regulation of sexual preference by neuropeptides, oxytocin, vasopressin, and kisspeptin. Through this review, we clarified the contradictions and deficiencies in our current knowledge on the neuroendocrine regulation of sexual preference and sought to present problems requiring further study.     

“过程工程学”的由来及对“不可逆循环过程”的研究

1996年我们发现，如果能实现酸?碱?盐闭路化学循环，则化工清洁生产就能达到零排放。从此开始了盐水解法酸碱联产新化工单元的研究。2012年提出了“动态多相动力学封闭系统”理论，发现这是非平衡热力学中的第三类“熵致有序”结构。将这一理论推广至太阳系，发现了“熵循环流”与“宇宙永动机”，还给出了时间新定义。     

Student perceptions and instructor experiences in implementing an online homework system in a large second-year engineering course

In a large course, grading assignments is a time-consuming process requiring considerable resources. Online homework software systems are therefore increasingly being utilized. In this article, we will detail our experiences implementing online homework assignments in our course CH E 243: Engineering Thermodynamics; a large, multi-section course with more than 600 students/year in 4 sections. In Year 1 we employed commercial software, and in Year 2 we developed our own online assignments. In both years, assignments had both online and written components. After each year we conducted a survey of the students to gage their perception regarding the implementation and benefits of the online and written assignments, and the contribution of these tools to the students’ ability to master the material. We found that most students were satisfied with the online system, and recommended using it again the following year. Students generally perceived written assignments to be more helpful in achieving mastery of the course material than the online ones. Students perceived our in-house developed system much more positively than the commercial software (as did we). Overall, we perceived that the class performance was better when our own online assignments were used, and the number of students who failed the course was reduced.     

Chaos in the Fractional Order Logistic Delay System

In this paper, we study the chaoticbehaviors in a fractional order logistic delay system. Wefind that chaos exists in the fractional order logisticdelay system with an order being less than 1. In addition,we numerically simulate the continuances of the chaoticbehaviors in the logistic delay system with orders from0.1 to 0.9. The lowest order we find to have chaos in thissystem is 0.1. Then we further investigate two methodsin controlling the fractional order chaotic logistic delaysystem based on feedback. Finally, we investigate a lagsynchronization scheme in this system. Numericalsimulations show the effectiveness and feasibility of ourapproach.     

Required levels of catalysis for emergence of autocatalytic sets in models of chemical reaction systems

The formation of a self-sustaining autocatalytic chemical network is a necessary but not sufficient condition for the origin of life. The question of whether such a network could form "by chance" within a sufficiently complex suite of molecules and reactions is one that we have investigated for a simple chemical reaction model based on polymer ligation and cleavage. In this paper, we extend this work in several further directions. In particular, we investigate in more detail the levels of catalysis required for a self-sustaining autocatalytic network to form. We study the size of chemical networks within which we might expect to find such an autocatalytic subset, and we extend the theoretical and computational analyses to models in which catalysis requires template matching.     

几种典型粘土矿物的X射线定性分析

针对在X射线的衍射测试中,有时会出现不同粘土矿物的重迭峰现象,不易正确定性判断矿物类型的问题,本文采用不同的样品处理方法,使高岭石、蒙脱石、绿泥石显示出各自特有的衍射特征,并以此将它们正确区分开。     

Predicting the diameters of droplets produced in turbulent liquid–liquid dispersion

The droplet size distribution in liquid–liquid dispersions is a complex convolution of impeller speed, impeller type, fluid properties, and flow conditions. In this work, we present three a priori modeling approaches for predicting the droplet diameter distributions as a function of system operating conditions. In the first approach, called the two-fluid approach, we use high-resolution solutions to the Navier–Stokes equations to directly model the flow of each phase and the corresponding droplet breakup/coalescence events. In the second approach, based on an Eulerian–Lagrangian model, we describe the dispersed fluid as individual spheres undergoing ongoing breakup and coalescence events per user-defined interaction kernels. In the third approach, called the Eulerian–Parcel model, we model a sub-set of the droplets in the Eulerian–Lagrangian model to estimate the overall behavior of the entire droplet population. We discuss output from each model within the context of predictions from first principles turbulence theory and measured data.     

IMPROVED BOOTSTRAP PREDICTION INTERVALS FOR AUTOREGRESSIONS

Abstract. We consider bootstrap construction and calibration of prediction intervals for nonGaussian autoregressions. In particular, we address the question of prediction conditioned on the last p observations of the process, for which we offer an exact simulation technique and an approximate bootstrap approach. In simulations for a variety of first-order autoregressions, we compare various nonparametric prediction intervals and find that calibration gives reasonably narrow prediction intervals with the lowest coverage probability mean squared error among the methods used.