共晶体系
化学
氯化胆碱
三元运算
深共晶溶剂
热容
热力学
群贡献法
工作(物理)
甜菜碱
绝对偏差
有机化学
统计
相平衡
程序设计语言
物理
相(物质)
合金
计算机科学
数学
作者
Thomas Di Pietro,Laëtitia Cesari,Fabrice Mutelet
标识
DOI:10.1016/j.fluid.2023.113854
摘要
The most recent database regrouping two key properties for the use of deep eutectic solvents in chemical processes, namely the density and the heat capacity, was used to develop simple group contribution models for predicting these properties. The databank contains a total of 3266 data points for 231 systems and 573 data points for 27 systems for density and heat capacity, respectively. These models only require the temperature and the number of each group in the molecules with no limitation on the number of molecules composing the studied deep eutectic solvent. The resulting average deviations are of 1.95% for density with 42.8% of the data having an average deviation under 1%, and 3.09% for heat capacity, with 55.5% of the data with a deviation under 1%. Both binary and ternary deep eutectic solvents have been investigated, with the deviation for ternary systems being of 1.05% in the case of the density model. Several families of DESs have been examined, with the best results obtained for DESs based on choline chloride, betaine and the benzyltrialkylammonium cation. These models are compared to more complex group contribution models from the literature. The models from this work are easy to implement and to modify when new data are available and are a step in the direction of the general prediction of properties of deep eutectic solvents.
科研通智能强力驱动
Strongly Powered by AbleSci AI