Rezaie Ali, Ghasemi Hassan, Eslami Fatemeh
Department of Chemical Engineering, Tarbiat Modares University, Jalal Al Ahmad HWY, P.O. Box: 14115-111, Tehran, Iran.
Sci Rep. 2023 Sep 1;13(1):14362. doi: 10.1038/s41598-023-40761-x.
Electrolytes have a wide range of technological applications. Despite the recent improvements in characterizing and predicting the phase behavior of microemulsion systems by hydrophilic-lipophilic deviation (HLD) and net-average curvature (NAC) frameworks, they are ineffective in the presence of different salts. This work seeks to bridge this gap by investigating the influence of salt nature on the microemulsion phase formulation. First, a one-dimensional salinity scan on different microemulsion systems consisting of sodium dodecyl benzene sulfonate as a surfactant, hexane as an oil and, several brines was carried out, and the effect of each salt on the phase behavior were precisely evaluated. The results for optimum salinity and solubilization parameter of different salts were consistent with the Hofmeister series. In addition, multiple linear regression model is presented to accurately predicting the optimum salinity of different salts using this research data and all the available experimental data. The results revealed that the values estimated by this model is in significant consistency with the experimental data by correlation coefficient of 0.92. Finally, the effect of salt type on the NAC parameters (length parameter, and characteristic length[Formula: see text] were evaluated to improve the predicting ability of this equation of state in the presence of various salts. We found that salt nature has a significant impact on both these parameters. It was found that the length parameter is linearly dependent on the optimum ionic strength of salts while the salting-out capacity of each salt was predominant factor affecting the characteristic length.
电解质具有广泛的技术应用。尽管最近通过亲水亲油偏差(HLD)和净平均曲率(NAC)框架在表征和预测微乳液体系的相行为方面取得了进展,但在存在不同盐的情况下它们并不有效。这项工作旨在通过研究盐的性质对微乳液相组成的影响来弥合这一差距。首先,对由十二烷基苯磺酸钠作为表面活性剂、己烷作为油以及几种盐水组成的不同微乳液体系进行了一维盐度扫描,并精确评估了每种盐对相行为的影响。不同盐的最佳盐度和溶解参数结果与霍夫迈斯特序列一致。此外,提出了多元线性回归模型,以使用本研究数据和所有可用的实验数据准确预测不同盐的最佳盐度。结果表明,该模型估计的值与实验数据具有显著一致性,相关系数为0.92。最后,评估了盐类型对NAC参数(长度参数和特征长度[公式:见正文])的影响,以提高该状态方程在存在各种盐时的预测能力。我们发现盐的性质对这两个参数都有显著影响。发现长度参数与盐的最佳离子强度呈线性相关,而每种盐的盐析能力是影响特征长度的主要因素。