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Chemical composition distribution of binary and multicomponent copolymers.

机译:二元和多组分共聚物的化学组成分布。

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Chemical composition distribution (CCD) of copolymers describes the distribution of average comonomer content among copolymer chains. This information is very important as CCD can significantly influence physical properties of copolymers. The main goal of this study is to further our understanding of the CCD of copolymers.; The present understanding of CCD of multicomponent copolymers is very limited and there are no analytical equations capable of describing this distribution. In the present study, analytical expressions for describing the CCDs of random multicomponent copolymers are developed using a statistical approach. The results from this theoretical expression are validated with the results from Stockmayer's distribution and Monte Carlo simulations for limiting cases.; In the case of semi-crystalline binary copolymers, temperature rising elution fractionation (Tref) and crystallization analysis fractionation (Crystat) can be used for the estimation of CCD. The effects of chain microstructure and operating conditions on these techniques are investigated using a series of ethylene/alpha-olefin copolymers with well-defined microstructures. Both molecular weight and comonomer content are shown to significantly affect the shape of Crystaf profiles. Fortunately, comonomer content is the main determining factor for Crystaf peak temperature, permitting the use reliable calibration curves for this technique. A Crystaf model based on the average ethylene sequence distribution in the chains is proposed and the results from this model show very good agreement with the present and previously reported experimental data.; The typical operating conditions used in Tref and Crystaf analyses are found to lead to fractionation conditions that are far from the thermodynamic equilibrium. Consequently, crystallization kinetics can strongly influence the CCD estimated with Tref and Crystaf. Sample cocrystallization during analysis is also considered as it may interfere with the fractionation processes of both techniques. The similarity of chain crystallizabilities and fast cooling rates are found to promote cocrystallization. Cocrystallization under a certain conditions can be so strong that it can seriously affect the interpretation of the CCD measured with Crystaf and Tref.
机译:共聚物的化学组成分布(CCD)描述了共聚物链中平均共聚单体含量的分布。该信息非常重要,因为CCD可以显着影响共聚物的物理性能。这项研究的主要目的是加深我们对共聚物CCD的理解。当前对多组分共聚物的CCD的理解是非常有限的,并且没有能够描述该分布的分析方程式。在本研究中,使用统计方法开发了用于描述无规多组分共聚物CCD的分析表达式。该理论表达式的结果已得到Stockmayer分布和蒙特卡罗模拟在有限情况下的结果的验证。在半结晶二元共聚物的情况下,可以使用升温洗脱分馏(Tref)和结晶分析分馏(Crystat)来估算CCD。使用一系列定义明确的微结构的乙烯/α-烯烃共聚物,研究了链微结构和操作条件对这些技术的影响。分子量和共聚单体含量均显示出显着影响Crystaf曲线的形状。幸运的是,共聚单体含量是决定Crystaf峰温度的主要因素,因此可以为该技术使用可靠的校准曲线。提出了基于链中平均乙烯序列分布的Crystaf模型,并且该模型的结果表明与当前和先前报道的实验数据非常吻合。发现在Tref和Crystaf分析中使用的典型操作条件导致分馏条件远离热力学平衡。因此,结晶动力学会强烈影响用Tref和Crystaf估算的CCD。还考虑了分析过程中的样品共结晶,因为它可能会干扰两种技术的分馏过程。发现链结晶性和快速冷却速率的相似性促进了共结晶。在某些条件下,共结晶可能非常强,以至于严重影响使用Crystaf和Tref测得的CCD的解释。

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