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釜内增韧PP橡胶组分序列结构13C-NMR谱数据的统计理论处理
引用本文:姚薇,黄佃平,赵永仙,邵华峰,黄宝琛.釜内增韧PP橡胶组分序列结构13C-NMR谱数据的统计理论处理[J].高分子材料科学与工程,2008,24(3):19-23.
作者姓名:姚薇  黄佃平  赵永仙  邵华峰  黄宝琛
作者单位:青岛科技大学橡胶材料与工程教育部重点实验室,山东,青岛,266042
基金项目:国家“863”项目(2006AA03Z546)
摘    要:首先用Bernoullian模型和Markov模型统计公式对10组釜内增韧PP橡胶组分(乙丙共聚物)13C-NMR谱数据进行分析比较,由其所得方差值可知,所有样品中的橡胶组分数据均不符合Bernoullian模型,而符合一级Markov模型;然后用Markov模型的统计公式计算,画出共聚物乙烯、丙烯的数量和质量分布曲线,由此可直观地比较各样品的组成分布;同时定量给出了共聚物数均和重均链段长度、链段分布指数及长链段的含量。

关 键 词:PP-R  13C-NMR  Bernoullian模型  Markov模型
文章编号:1000-7555(2008)03-0019-05
修稿时间:2006年10月6日

The Disposal with the Statistical Theory on 13C-NMR Data of the Sequence Structure of Rubber Components Used to Strengthen the Toughness of PP in a Kettle
YAO Wei,HUANG Dian-ping,ZHAO Yong-xian,SHAO Hua-feng,HUANG Bao-chen.The Disposal with the Statistical Theory on 13C-NMR Data of the Sequence Structure of Rubber Components Used to Strengthen the Toughness of PP in a Kettle[J].Polymer Materials Science & Engineering,2008,24(3):19-23.
Authors:YAO Wei  HUANG Dian-ping  ZHAO Yong-xian  SHAO Hua-feng  HUANG Bao-chen
Affiliation:(Key Laboratory of Rubber-Plastics of Ministry of Education,Qingdao University of Science and Technology,Qingdao 266042,China)
Abstract:Ten groups of data of 13C-NMR on rubber components(polyethylene and polypropylene) used to strengthen the toughness of PP in a kettle were analyzed and compared in use of the statistical formula under Bernoullian model and Markov model firstly.The result of calculating variance indicates that all the data disagree with the Bernoullian model but accord with the first stair Markov model.Then,after the calculation with the Markov model,the distribution curves on quantity and weight of the ethylene component and the propylene component in a copolymer were drawn,with which the composition and the distribution of the sample can be compared directly;meanwhile the length,the distribution index,and the content of the chain segment were characterized quantitatively by both number average method and weight average method in the copolymer.
Keywords:PP-R  13C-NMR  Bernoullian model  Markov model
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