基于图像化特征的聚烯烃弹性体链结构表征：从一维参数到二维分布

杜斌; 高源; 康静怡; 陈商涛; 祝文亲; 张凤波; 许蔷

doi:10.11777/j.issn1000-3304.2026.26211

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基于图像化特征的聚烯烃弹性体链结构表征：从一维参数到二维分布

研究论文 | 更新时间：2026-11-03

- 基于图像化特征的聚烯烃弹性体链结构表征：从一维参数到二维分布
- Image-based Characterization of the Chain Structure of Polyolefin Elastomers: From One-dimensional Parameters to Two-dimensional Distribution
- 高分子学报 2026年页码：1-12
- 作者机构：
  
  1.中国石油天然气股份有限公司石油化工研究院北京 102206
  2.中国石油合成树脂及新材料重点实验室北京 102206
- 作者简介：
  
  E-mail: xuqiang010@petrochina.com.cn
- 基金信息：
- DOI：10.11777/j.issn1000-3304.2026.26211
  中图分类号：
- 收稿：2026-06-12，
  
  录用：2026-07-30，
  
  网络首发：2026-11-03，
- 稿件说明：
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杜斌, 高源, 康静怡, 陈商涛, 祝文亲, 张凤波, 许蔷. 基于图像化特征的聚烯烃弹性体链结构表征：从一维参数到二维分布. 高分子学报, doi: 10.11777/j.issn1000-3304.2026.26211.

Du, B.; Gao, Y.; Kang, J. Y.; Chen, S. T.; Zhu, W. Q.; Zhang, F. B.; Xu, Q. Image-based characterization of the chain structure of polyolefin elastomers: from one-dimensional parameters to two-dimensional distribution. Acta Polymerica Sinica (in Chinese), doi: 10.11777/j.issn1000-3304.2026.26211.
杜斌, 高源, 康静怡, 陈商涛, 祝文亲, 张凤波, 许蔷. 基于图像化特征的聚烯烃弹性体链结构表征：从一维参数到二维分布. 高分子学报, doi: 10.11777/j.issn1000-3304.2026.26211. DOI： CSTR： 32057.14.GFZXB.2026.7709.

Du, B.; Gao, Y.; Kang, J. Y.; Chen, S. T.; Zhu, W. Q.; Zhang, F. B.; Xu, Q. Image-based characterization of the chain structure of polyolefin elastomers: from one-dimensional parameters to two-dimensional distribution. Acta Polymerica Sinica (in Chinese), doi: 10.11777/j.issn1000-3304.2026.26211. DOI： CSTR： 32057.14.GFZXB.2026.7709.

摘要

聚烯烃弹性体(POE)的链结构非均匀性通常需要从分子量和支化结构2个方面共同描述，但这两者之间的关联关系难以通过常规的一维表征方法获得. 交叉分级色谱可获得分子量与支化的二维联合分布，然而所得二维谱图通常只能定性观察，缺乏将其转化为定量信息的处理方法. 研究以乙烯/1-辛烯和乙烯/1-丁烯共聚弹性体为对象，提出基于图像化特征提取的二维链结构分析方法，将温度梯度相互作用(TGIC-GPC)色谱图作为概率密度图像，从低阶矩、形状、拓扑、散度和分位数5个维度提取可定量的图像特征，将原本只能定性观察的二维分布转化为一组可计算的结构特征. 该方法可定量获取温度与分子量的关联程度等信息，并能在不依赖性能数据的情况下区分2类共聚单体样品. 结果表明，图像化特征为POE二维链结构的定量描述提供了一条有效途径.

Abstract

The chain structure heterogeneity of polyolefin elastomer (POE) requires characterization in terms of both molecular weight and branching structure

yet the relationship between these two parameters proves challenging to establish using conventional one-dimensional characterization techniques. While cross-fractionation chromatography can provide the two-dimensional joint distribution of molecular weight and branching

the resulting chromatograms are typically interpreted only qualitatively

lacking established methodology for quantitative information conversion. This study focused on ethylene/1-octene and ethylene/1-butene copolymer elastomers. First

the overall differences in chain structure were characterized using mean parameters and one-dimensional dispersion parameters. Subsequently

an image-based feature extraction approach was applied to analyze the two-dimensional joint distribution

with the TGIC-GPC chromatography treated as a probability density image. Quantifiable image features were extracted across five dimensions: low-order moments

shape descriptors

topological characteristics

divergence

and quantiles. This approach converted a distribution that could previously only be observed qualitatively into a set of computable structural features. The study examined whether the method can extract coupled information inaccessible to one-dimensional characterization and evaluates its discrimination capability for different comonomer systems. The proposed method can quantitatively capture information such as the correlation between elution temperature and molecular weight

and can distinguish between the two comonomer families without relying on property-based data. The results indicate that image-based feature extraction provides an effective route for the quantitative description of the two-dimensional chain structure of POE.

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