化学
氢键
氯化胆碱
深共晶溶剂
乙二醇
甲醇
共晶体系
分离过程
范德瓦尔斯力
分子动力学
分子
物理化学
计算化学
有机化学
色谱法
合金
作者
Jiafu Xing,Yajuan Qu,Zihao Su,Mengjin Zhou,Chao Sun,Yinglong Wang,Peizhe Cui
标识
DOI:10.1021/acs.iecr.2c03488
摘要
Separation of methanol–isopropyl acetate (IPAC) obtained via isopropanol synthesis is essential. Deep eutectic solvents (DESs) have garnered extensive attention in the field of azeotropic separation owing to their advantages such as biodegradability, ecofriendliness, and cost-effectiveness. In this work, three choline-based DESs were prepared. Then, the experimental data of the synthesized DESs with methanol and IPAC were measured, which were linearly correlated with Hand and Othmer–Tobias equations. The GM/RT surface obtained using GUI-MATLAB software was used to determine the reliability of the fitting data based on the NRTL model. Choline chloride and ethylene glycol DES with a molar ratio of 1:2 exhibited the best methanol affinity. The effect of the solvent structure was studied using a combination of experimental and quantum chemistry and molecular dynamics (MD) calculations. Through electrostatic potential distribution, atoms-in-molecules, and independent gradient model analytical methods, the three DEEs were primarily extracted via a hydrogen bond interaction and van der Waals interaction, wherein the former played a dominant role in separation. MD simulation was used to reveal the effect of the structures of hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs) on the extraction process at the molecular level. The analysis results indicated that HBA was the main influencing factor in the separation, and the electrostatic interaction of Cl– and methanol was dominant in the separation. Additionally, HBDs were the secondary factor during the separation process. In this work, the reasons for the differences in the separation performances of different DESs were analyzed from a microscopic perspective, offering theoretical support for selecting suitable DESs for separating alcohol-containing azeotropic systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI