化学工程2025，Vol.53Issue(5)：6-10,5.DOI:10.3969/j.issn.1005-9954.2025.05.002
基于机器学习的沥青电子结构计算及微观结构表征
Asphalt electronic structure calculation and microstructure characterization based on machine learning
摘要
Abstract
The study of the electronic structure of asphalt is the basis of the analysis of the microstructure of asphalt and the nature of the interaction between asphalt molecules.In order to study the relationship between electronic structure and microstructure of asphalt,DFT(density functional theory)was used to analyze the electronic structure and extract characteristic information.At the same time,the microstructural parameters of asphalt molecules were examined.BP neural networks and grey relational analysis were combined to analyze and predict the relationship between asphalt microstructure and electronic structure.The distribution of internal electrons was predicted to characterize molecular structure properties.The results show that the microstructure parameters of asphalt have good correlation with the electrostatic potential parameters of molecular surface,which can be used as the characterization index of asphalt electronic structure.关键词
道路工程/沥青微观结构/分子模拟/机器学习/电子结构Key words
road engineering/asphalt microstructure/molecular simulation/machine learning/electronic structure分类
交通工程引用本文复制引用
王仰辉,丁勇杰,奚源,王娇娇,梅子俊,张华..基于机器学习的沥青电子结构计算及微观结构表征[J].化学工程,2025,53(5):6-10,5.基金项目
国家自然科学基金资助项目(52008069) （52008069）
北京市博士后科学基金资助项目(2022-zz-054) （2022-zz-054）
