Solid-liquid equilibrium solubility prediction of sulfanilamide in four binary solvent mixtures by using pure solvents solubility data from 278.15 to 318.15 K with the Abraham solvation parameter model, Yalkowsky Log-Linear and extended log-linear solubility thermodynamic models

溶解度 溶剂化 磺胺 溶剂 热力学 二进制数 溶解度参数 化学 工作(物理) 物理化学 有机化学 数学 物理 生物化学 算术
作者
Kalyani Kodide,Prashanth Asadi,Jyothi Thati
出处
期刊:Journal of Molecular Liquids [Elsevier BV]
卷期号:368: 120634-120634 被引量:11
标识
DOI:10.1016/j.molliq.2022.120634
摘要

The industrial application of sulfanilamide solubility in binary solvent mixtures is a critical factor in drug development, assessment, as well as future improvement. The current work eliminates the substantial experimental work, as well as the ability to apply improved and upgraded computed models that include solute physicochemical properties and activity coefficients. The predicted solid–liquid equilibrium data of sulfanilamide in acetone containing binary solvent mixtures at temperatures ranging from 278.15 to 318.15 K were calculated by applying the combined version of Jouyban-Acree model with Abraham solute parameter model, combined version of Jouyban-Acree model with Abraham solvation parameter model, combined version of Jouyban-Acree model with Hansen solubility parameter model, the Yalkowsky Log-Linear model, Extended log-linear model. In comparison to previously published binary solvent solubility data, this paper provides predicted binary solubility data using only mono-solvent solubility data as well as from the computed models. From the solubility trained model the %ARD can be ranked as the combined version of combined version of the Jouyban-Acree model with Abraham Solute parameter model (19.47 %) < the Jouyban-Acree model with Hansen solubility parameter model (23.76 %) < the Yalkowsky model (50.54 %) < the combined version of Jouyban-Acree model with Abraham solvation parameter model (68.83 %) < the Extended log-linear model (615.78 %). The combined version of Jouyban-Acree model with Abraham Solute parameter model giving most reliable predicted solubility results compared to other computed models. The most important outcome of this research will be immensely beneficial in calculating binary solubility data utilizing only mono-solvent solubility data as well as from computed models. The binary solubility predictions were calculated from already reported mono-solvent solubility data from experimentally determined, Hildebrand-Scatchard equation-1 and Hildebrand-Scatchard equation-2.
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