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用齐格勒-纳塔催化剂制备的聚烯烃分子量和化学组成的双变量分布的同时反褶积

Simultaneous deconvolution of the bivariate distribution of molecular weight and chemical composition of polyolefins made with ziegler-natta catalysts.

作者信息

Alghyamah Abdulaziz A, Soares João B P

机构信息

Department of Chemical Engineering, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.

出版信息

Macromol Rapid Commun. 2009 Feb 18;30(4-5):384-93. doi: 10.1002/marc.200800592. Epub 2008 Dec 17.

Abstract

Polyolefins made with Ziegler-Natta catalysts have non-uniform distributions of molecular weight (MWD) and chemical composition (CCD). The MWD is usually measured by high-temperature gel permeation chromatography (GPC) and the CCD by either temperature rising elution fractionation (TREF) or crystallization analysis fractionation (CRYSTAF). A mathematical model is needed to quantify the information provided by these analytical techniques and to relate it to the presence of multiple site types on Ziegler-Natta catalysts. We developed a robust computer algorithm to deconvolute the MWD and CCD of polyolefins simultaneously using Flory's most probable distribution and the cumulative CCD component of Stockmayer's distribution, which includes the soluble fraction commonly present in linear low-density polyethylene (LLDPE) resins and have applied this procedure for the first time to several industrial LLDPE resins. The deconvolution results are reproducible and consistent with theoretical expectations.

摘要

用齐格勒-纳塔催化剂制备的聚烯烃具有分子量分布(MWD)和化学组成分布(CCD)不均匀的特点。MWD通常通过高温凝胶渗透色谱法(GPC)测量,而CCD则通过升温淋洗分级法(TREF)或结晶分析分级法(CRYSTAF)测量。需要一个数学模型来量化这些分析技术提供的信息,并将其与齐格勒-纳塔催化剂上多种活性中心类型的存在联系起来。我们开发了一种强大的计算机算法,利用弗洛里最可几分布和斯托克迈耶分布的累积CCD组分,同时对聚烯烃的MWD和CCD进行反卷积,该分布包括线性低密度聚乙烯(LLDPE)树脂中常见的可溶部分,并首次将此方法应用于几种工业LLDPE树脂。反卷积结果具有可重复性,且与理论预期一致。

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