Equilibrium Solubility of Sulfadiazine in (Acetonitrile + Ethanol) Mixtures: Determination, Correlation, Dissolution Thermodynamics, and Preferential Solvation

IF 2.5 4区 工程技术 Q3 CHEMISTRY, PHYSICAL
Daniel Ricardo Delgado, Claudia Patricia Ortiz, Fleming Martínez, Abolghasem Jouyban
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引用次数: 0

Abstract

The equilibrium solubility of sulfadiazine (SD, 3) in several {acetonitrile (MeCN) + ethanol (EtOH)} mixtures at nine temperatures from T/K = (278.15 K to 318.15) has been determined by following the shake flask method. SD solubility increased with temperature-arising as well as with the MeCN proportion-increasing in the mixtures. Thus, x3 increased from 7.74 × 10−5 in neat EtOH to 6.20 × 10−4 in neat MeCN at T/K = 298.15. SD solubility was adequately correlated with a second-order multivariate equation as function of both mixtures composition and temperature. Moreover, two models including the Jouyban–Acree and Jouyban–Acree–van’t Hoff models were applied to mathematical SD solubility data modeling in solvent mixtures. The accuracy of each model is investigated by the mean relative deviations (MRD%) of the back-calculated solubility. A full predictive model was provided by training the Jouyban–Acree–van’t Hoff model with only seven experimental solubility data which provided excellent predictions with the MRD% of 3.7 %. All used models show a low MRD% values (< 4.0 %) for the calculated data indicating a good correlation of SD solubility data with the given mathematical models. By means of the van’t Hoff and Gibbs equations, the apparent thermodynamic quantities relative to SD dissolution and mixing processes, namely Gibbs energies, enthalpies, and entropies, were calculated and reported. Apparent dissolution quantities of SD were positive in all cases indicating endothermic and entropy-driven behaviors. A non-linear enthalpy–entropy relationship was observed for SD in the plot of SD dissolution enthalpy vs. Gibbs energy. Observed trend exhibits negative slope in the composition from neat EtOH to the mixture of 0.05 in mass fraction of MeCN indicating entropy-driving mechanism for this SD transfer process. Moreover, variant but positive slopes were found in the composition interval of 0.05 < w1 < 1.00 indicating enthalpy-driving mechanism for these SD transfer processes. Furthermore, the preferential solvation of SD by MeCN or EtOH was analyzed by using the inverse Kirkwood–Buff integrals. Thus, SD is preferentially solvated by EtOH molecules in EtOH-rich mixtures but preferentially solvated by MeCN in MeCN-rich mixtures. In this way, this research expands the literature investigations about the solubility of SD in some non-aqueous cosolvent mixtures conformed by MeCN and other alcohols.

Abstract Image

磺胺嘧啶在(乙腈+乙醇)混合物中的平衡溶解度:测定、相关性、溶解热力学和优先溶解度
采用振荡烧瓶法测定了磺胺嘧啶(SD,3)在几种{乙腈(MeCN)+乙醇(EtOH)}混合物中的平衡溶解度,温度范围为 T/K = (278.15 K 至 318.15)。随着温度的升高以及混合物中 MeCN 比例的增加,SD 溶解度也随之增加。因此,在 T/K = 298.15 时,x3 从纯 EtOH 中的 7.74 × 10-5 增至纯 MeCN 中的 6.20 × 10-4。标清溶解度与二阶多元方程充分相关,是混合物成分和温度的函数。此外,包括 Jouyban-Acree 模型和 Jouyban-Acree-van't Hoff 模型在内的两个模型也被应用于溶剂混合物中标清溶解度数据的数学建模。通过反向计算溶解度的平均相对偏差(MRD%)来考察每个模型的准确性。通过对 Jouyban-Acree-van't Hoff 模型进行训练,仅用 7 个实验溶解度数据就建立了一个完整的预测模型,该模型的预测效果极佳,MRD% 为 3.7%。所有使用的模型都显示计算数据的 MRD% 值较低 (< 4.0 %),这表明标清溶解度数据与给定的数学模型具有良好的相关性。通过范特霍夫方程和吉布斯方程,计算并报告了与标示溶解和混合过程有关的表观热力学量,即吉布斯能、焓和熵。在所有情况下,SD 的表观溶解量均为正值,表明其具有内热和熵驱动行为。在标示溶解焓与吉布斯能的曲线图中,可以观察到标示溶解焓与吉布斯能之间的非线性焓熵关系。从纯 EtOH 到 MeCN 质量分数为 0.05 的混合物,观察到的趋势呈现负斜率,这表明 SD 转移过程的熵驱动机制。此外,在 0.05 < w1 < 1.00 的成分区间内发现了不同的正斜率,表明这些 SD 转移过程的焓驱动机制。此外,还利用反柯克伍德-巴夫积分分析了 SD 在 MeCN 或 EtOH 中的优先溶解性。因此,在富含 EtOH 的混合物中,SD 优先被 EtOH 分子溶解,而在富含 MeCN 的混合物中,SD 优先被 MeCN 溶解。因此,这项研究拓展了有关 SD 在一些由 MeCN 和其他醇类组成的非水共溶剂混合物中溶解性的文献研究。
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来源期刊
CiteScore
4.10
自引率
9.10%
发文量
179
审稿时长
5 months
期刊介绍: International Journal of Thermophysics serves as an international medium for the publication of papers in thermophysics, assisting both generators and users of thermophysical properties data. This distinguished journal publishes both experimental and theoretical papers on thermophysical properties of matter in the liquid, gaseous, and solid states (including soft matter, biofluids, and nano- and bio-materials), on instrumentation and techniques leading to their measurement, and on computer studies of model and related systems. Studies in all ranges of temperature, pressure, wavelength, and other relevant variables are included.
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