Experimental Measurement and Modeling of Liquid–Liquid Equilibria for the Ternary System Water + Propan-1-ol + Ethyl Acetate

IF 2.4 3区 工程技术 Q3 CHEMISTRY, MULTIDISCIPLINARY
Journal of Chemical & Engineering Data Pub Date : 2026-10-08 Epub Date: 2026-09-09 DOI:10.1021/acs.jced.6c00298
John O. Bamikole, Caitlin Stapelberg, Caleb Narasigadu
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引用次数: 0

Abstract

The world’s growing energy needs and the depletion of fossil fuels have driven demand for renewable alternatives, such as biofuels. Propan-1-ol is a valuable biofuel component; however, the presence of water during its production remains a significant challenge. A viable solution is liquid–liquid extraction to selectively recover propan-1-ol from a water mixture. Ethyl acetate is considered a promising solvent due to its chemical stability, eco-friendly nature, moderate water immiscibility, and favorable density difference for phase separation in a water-propan-1-ol mixture. In this study, ternary LLE measurements for water (1), propan-1-ol (2), and ethyl acetate (3) were conducted at 298.15, 313.15, and 328.15 K to evaluate ethyl acetate as a solvent for extracting propan-1-ol. The selectivity and capacity of the solvent were calculated. The experimental data were modeled using the NRTL and UNIQUAC activity models, both of which adequately describe the phase behavior, with NRTL slightly better than UNIQUAC. The group method of data handling (GMDH) neural network was also employed to complement the thermodynamic model, accurately predicting phase composition. The findings of this study show that ethyl acetate has excellent potential for selectively extracting propan-1-ol from water, with the extraction efficiency increasing with temperature.

水+丙-1-醇+乙酸乙酯三元体系液-液平衡的实验测量与模拟
世界不断增长的能源需求和化石燃料的枯竭推动了对生物燃料等可再生能源替代品的需求。丙烷-1-醇是一种有价值的生物燃料成分;然而,在其生产过程中,水的存在仍然是一个重大挑战。可行的解决方案是液-液萃取,以选择性地从水混合物中回收丙烷-1-醇。乙酸乙酯因其化学稳定性、环保性、适度的水不混溶性以及在水-丙烷-1-醇混合物中有利于相分离的密度差而被认为是一种很有前途的溶剂。本研究分别在298.15、313.15和328.15 K下对水(1)、丙烯-1-醇(2)和乙酸乙酯(3)进行了ternaryLLE测定,以评价乙酸乙酯作为提取丙烯-1-醇的溶剂。计算了溶剂的选择性和容量。实验数据采用NRTL和UNIQUAC活度模型进行建模,两者均能较好地描述相行为,其中NRTL略优于UNIQUAC。采用数据处理(GMDH)神经网络的分组方法对热力学模型进行了补充,准确地预测了相组成。研究结果表明,乙酸乙酯具有很好的从水中选择性提取丙烯-1-醇的潜力,提取效率随温度的升高而提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Chemical & Engineering Data
Journal of Chemical & Engineering Data 工程技术-工程:化工
CiteScore
5.20
自引率
19.20%
发文量
324
审稿时长
2.2 months
期刊介绍: The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.
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