增塑剂
材料科学
玻璃化转变
流变仪
沥青质
差示扫描量热法
流变学
复合材料
沥青
己二酸
聚苯乙烯
化学工程
聚合物
热力学
物理
工程类
作者
Weiwei Tian,Yingli Gao,Yuelin Li,Juncai Zhu,Mao‐Sheng Zhan,Shuo Wang
标识
DOI:10.1016/j.conbuildmat.2023.132791
摘要
The main aim of this study is to explore how various plasticizers affect the rheological properties of asphalt and the causes of their varying effects on asphalt. Four plasticizers, namely dioctyl phthalate (DOP), dioctyl adipate (DOA), acetyl tributyl citrate (ATBC), and trioctyl trimellitate (TOTM), were used to modify the base asphalt. The rheological properties of the modified asphalts were assessed by bending beam rheometer (BBR) and dynamic shear rheometer (DSR) tests. The molecular weight distribution and glass transition temperature in the modified asphalts were determined using gel permeation chromatography (GPC) and differential scanning calorimetry (DSC) tests. Finally, molecular dynamics simulations were performed to calculate parameters such as glass transition temperature, mean square displacement, and relative concentration, which elucidate the mechanism of different plasticizers on asphalt. The results suggest that DOA-modified asphalt with 2% modifier admixture exhibits the best low-temperature performance, whereas ATBC has the least effect. The four plasticizers can decrease the size and proportion of large and medium molecular groups in asphalt, reducing the intermolecular forces that impede the asphalt flow at low temperatures. The plasticizer molecules can generate more free space for the thermal movement of asphalt molecules, decreasing the glass transition temperature of the asphalt. Additionally, plasticizer molecules with greater flexibility can insert more easily between asphalt molecules, enhancing their diffusion ability through lubrication. DOA and ATBC can improve the dispersion of both asphaltenes and resins, while DOP and TOTM primarily affect asphaltenes. The distribution of aromatics and saturates is not significantly influenced by any of the four plasticizers.
科研通智能强力驱动
Strongly Powered by AbleSci AI