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Vapor–Liquid Equilibria of Binary Systems with Long-Chain Organic Compounds (Fatty Alcohol, Fatty Ester, Acylglycerol, and n-Paraffin) at Subatmospheric Pressures
Journal of Chemical & Engineering Data ( IF 2.0 ) Pub Date : 2018-06-18 , DOI: 10.1021/acs.jced.8b00168
Daniela S. Damaceno 1 , Roberta Ceriani 1
Affiliation  

In the past years, the oil and fat industry has been growing on a large scale, mostly due to the need of biodiesel production. Considering this fact, the understanding of thermophysical properties and phase equilibrium of the compounds found in this industry became crucial, that is, acylglycerols, fatty esters, alcohols. Therefore, this work aims to obtain liquid–vapor equilibrium data of the following mixtures: hexadecanol + octadecanol (1.73 kPa), hexadecanol + methyl myristate (1.72 kPa), monononanin + tributyrin (1.69 kPa), and dinonanoin + octacosane (1.70 kPa) by the differential scanning calorimetry technique. As expected, the system with two long-chain alcohols (hexadecanol + octadecanol) showed an ideal behavior. In contrast, the other systems presented nonideal behavior. Experimental data were effectively regressed by the UNIQUAC model. The pure component consistency test and the variation of Van Ness consistency test were applied to all systems. Activity coefficients were modeled using the Linear UNIFAC, the Modified UNIFAC, and the Dortmund UNIFAC with both their original parameters (amn) and lipid-based regressed parameters, and also the NIST modified UNIFAC. Predictive capacity of all these methods were tested, and no single method showed to be the best for all systems.

中文翻译:

在大气压下与长链有机化合物(脂肪醇,脂肪酯,酰基甘油和链烷烃)的二元体系的汽液平衡

在过去的几年中,石油和脂肪工业已经大规模发展,这主要是由于生物柴油生产的需要。考虑到这一事实,对在该行业中发现的化合物,即酰基甘油,脂肪酯,醇的热物理性质和相平衡的理解变得至关重要。因此,这项工作的目的是获得以下混合物的液体-蒸汽平衡数据:十六烷醇+十八烷醇(1.73 kPa),十六烷醇+肉豆蔻酸甲酯(1.72 kPa),单壬酸+三丁酸甘油酯(1.69 kPa)和二壬酸+十八烷烷(1.70 kPa)通过差示扫描量热法。如预期的那样,具有两种长链醇(十六醇+十八醇)的体系表现出理想的行为。相反,其他系统表现出非理想的行为。实验数据通过UNIQUAC模型有效回归。纯组件一致性测试和Van Ness一致性测试的变化都应用于所有系统。使用线性UNIFAC,Modified UNIFAC和Dortmund UNIFAC分别用两个原始参数对活动系数进行建模(一个MN)和基于脂质的回归参数,并且还NIST改性UNIFAC。测试了所有这些方法的预测能力,没有一种方法显示出对所有系统都是最佳的。
更新日期:2018-06-18
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