本征型聚酰亚胺介电常数的定量构效关系模型构建与研究

范振国; 刘四委; 池振国; 张艺; 许家瑞

doi:10.11777/j.issn1000-3304.2020.20278

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本征型聚酰亚胺介电常数的定量构效关系模型构建与研究

研究论文 | 更新时间：2024-02-20

- 本征型聚酰亚胺介电常数的定量构效关系模型构建与研究
- Construction and Study of Quantitative Structure-Property Relationship Model for Intrinsic Polyimide Dielectric Constant
- 高分子学报 2021年52卷第7期页码：750-761
- 作者机构：
  
  1.中山大学聚合物复合材料及功能材料教育部重点实验室高性能树脂基复合材料广东省重点实验室广东省高性能有机聚合物光电功能薄膜工程技术研究中心化学学院广州 510275
  2.广东粤财投资控股有限公司广州 511045
- 作者简介：
  
  E-mail: ceszy@mail.sysu.edu.cn
  xjr@mail.sysu.edu.cn
- 基金信息：
  
  广东省科技计划项目(2020B010182001;2019B040401002);国家自然科学基金(基金号 ┣U20A20255);51873239┫;国家重点基础研究发展计划(973计划，项目号2014CB643605)和广东省“特支计划”科技创新领军人才项目(2016TX03C295)
- DOI：10.11777/j.issn1000-3304.2020.20278
  中图分类号：
- 纸质出版日期：2021-07-20，
  
  网络出版日期：2021-05-21，
  
  收稿日期：2020-12-16，
  
  修回日期：2020-12-25，
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范振国,刘四委,池振国等.本征型聚酰亚胺介电常数的定量构效关系模型构建与研究[J].高分子学报,2021,52(07):750-761.

Zhen-guo Fan, Si-wei Liu, Zhen-guo Chi, Yi Zhang, Jia-rui Xu. Construction and Study of Quantitative Structure-Property Relationship Model for Intrinsic Polyimide Dielectric Constant[J]. ACTA POLYMERICA SINICA, 2021,52(7):750-761.
范振国,刘四委,池振国等.本征型聚酰亚胺介电常数的定量构效关系模型构建与研究[J].高分子学报,2021,52(07):750-761. DOI： 10.11777/j.issn1000-3304.2020.20278.

Zhen-guo Fan, Si-wei Liu, Zhen-guo Chi, Yi Zhang, Jia-rui Xu. Construction and Study of Quantitative Structure-Property Relationship Model for Intrinsic Polyimide Dielectric Constant[J]. ACTA POLYMERICA SINICA, 2021,52(7):750-761. DOI： 10.11777/j.issn1000-3304.2020.20278.

摘要

综合运用量子化学方法及基团贡献法，采集了78种不同化学结构聚酰亚胺的结构参数. 采用通径分析法从16种参数中筛选出了对介电常数具有显著影响的8种结构参数，在此基础上，构建了2种针对聚酰亚胺介电常数的定量构效关系模型，平均相对误差均在10%以内. 研究认为影响聚酰亚胺薄膜介电常数的最重要因素为分子体积，从宏观角度来看即体系的自由体积尺寸. 评价了2种模型的适用性及稳定性，对比发现人工神经网络模型具备更高的精度，相对误差均在5%以内，多元线性回归模型的精度在10%以内，但具备更好的物理意义. 设计了18种低介电常数的聚酰亚胺结构单元，并预测其介电常数. 研究发现增加体系的含氟量可以降低其介电常数，最佳含氟量为0.25~0.37之间. 侧基占比

S/M

最佳比例为0.5~0.6左右，侧基占比过大将会导致介电常数上升. 基于上述研究，设计了3种超低介电常数的聚酰亚胺结构，其中最低预测介电常数为1.22.

Abstract

The structure parameters of 78 polyimides with different chemical structures were collected by using quantum chemistry method and group contribution method. Eight structural parameters with significant influence on dielectric constant were selected from 16 kinds of parameters by path analysis. On this basis

two kinds of quantitative structure-property relationship models for polyimide were constructed

and the average relative errors were within 10%. It is considered that the most important factor affecting the permittivity of polyimide film is molecular volume

which is the free volume size of the molecular from the macroscopic point of view. The applicability and stability of the two models are evaluated. It is found that artificial neural network has higher accuracy

the relative error is less than 5%

and the accuracy of multiple linear regression model is less than 10%

but it has better physical significance. Eighteen polyimide structural units with low dielectric constant were designed and their dielectric constants were predicted. It is shown that the dielectric constant can be reduced by increasing the fluorine content of the molecular

and the optimum fluorine content is between 0.25 and 0.37. The optimal ratio of side chain to main chain is about 0.5-0.6

which will lead to the increase of dielectric constant. Based on the above research

three polyimide structures with ultra-low dielectric constant were designed

and the lowest predicted dielectric constant was 1.22.

关键词

聚酰亚胺介电常数定量构效关系多元线性回归人工神经网络

Keywords

PolyimideDielectric constantQuantitative structure-property relationshipMultiple linear regressionArtificial neural network

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