{"title":"在 283.15 至 323.15 K 温度范围内,α-氨基异丁酸在 13 种溶剂中的溶解度特性","authors":"Mingyu Jing, Yongjie Wang, Dandan Liu, Shujing Zhang, Jiaxin Wang, Peng Wang* and Bingbing Li*, ","doi":"10.1021/acs.jced.4c00023","DOIUrl":null,"url":null,"abstract":"<p >In this study, the solid–liquid equilibrium solubility and solvent effects of α-aminoisobutyric acid in 13 monosolvent systems (water, methanol, ethanol, <i>n</i>-propanol, isopropanol, <i>n</i>-butanol, isobutanol, <i>N</i>,<i>N</i>-dimethylformamide, acetonitrile, acetone, ethyl acetate, 2-butanone, and methyl acetate) were reported at the pressure of 101.2 kPa (at <i>T</i> = 283.15–323.15 K). Among the 13 monosolvents, the solubility increased with the increase of absolute temperature, the order is water > <i>N</i>,<i>N</i>-dimethylformamide > methanol > ethyl acetate >2-butanone > ethanol > <i>n</i>-propanol > <i>n</i>-butanol ≈ <i>n</i>-pentanol > isopropanol > acetone > methyl acetate ≈ acetonitrile. The modified Apelblat model, Yaws model, Margules model, and nonrandom two-liquid (NRTL) model were employed to correlate the experimental solubility, and the OriginPro 2019b software was used for analysis and fitting, and the fitting results of the four models were all satisfactory. In addition, through a comparison of the average ARD and root-mean-square deviation (RMSD) values of the four models, the Yaws model achieved the best correlation result. Hirshfeld surface analysis (HS) and molecular electrostatic potential surface (MEPS) performed by the CrystalExplorer software and Gauss 5.0 program were used to determine the internal interactions within α-aminoisobutyric acid solutions. In addition, Hansen solubility parameters (HSPs) were utilized to analyze the solubility behavior. Furthermore, mixing thermodynamic characteristics of α-aminoisobutyric acid in selected solvents were calculated by the NRTL model, which revealed that the mixing process was spontaneous and entropy-driven. These experimental results could be utilized for the purification, crystallization, and industrial applications of α-aminoisobutyric acid, as well as similar substances.</p>","PeriodicalId":42,"journal":{"name":"Journal of Chemical & Engineering Data","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Solubility Behavior of α-Aminoisobutyric Acid in 13 Individual Solvents at Temperatures Ranging from 283.15 to 323.15 K\",\"authors\":\"Mingyu Jing, Yongjie Wang, Dandan Liu, Shujing Zhang, Jiaxin Wang, Peng Wang* and Bingbing Li*, \",\"doi\":\"10.1021/acs.jced.4c00023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >In this study, the solid–liquid equilibrium solubility and solvent effects of α-aminoisobutyric acid in 13 monosolvent systems (water, methanol, ethanol, <i>n</i>-propanol, isopropanol, <i>n</i>-butanol, isobutanol, <i>N</i>,<i>N</i>-dimethylformamide, acetonitrile, acetone, ethyl acetate, 2-butanone, and methyl acetate) were reported at the pressure of 101.2 kPa (at <i>T</i> = 283.15–323.15 K). Among the 13 monosolvents, the solubility increased with the increase of absolute temperature, the order is water > <i>N</i>,<i>N</i>-dimethylformamide > methanol > ethyl acetate >2-butanone > ethanol > <i>n</i>-propanol > <i>n</i>-butanol ≈ <i>n</i>-pentanol > isopropanol > acetone > methyl acetate ≈ acetonitrile. The modified Apelblat model, Yaws model, Margules model, and nonrandom two-liquid (NRTL) model were employed to correlate the experimental solubility, and the OriginPro 2019b software was used for analysis and fitting, and the fitting results of the four models were all satisfactory. In addition, through a comparison of the average ARD and root-mean-square deviation (RMSD) values of the four models, the Yaws model achieved the best correlation result. Hirshfeld surface analysis (HS) and molecular electrostatic potential surface (MEPS) performed by the CrystalExplorer software and Gauss 5.0 program were used to determine the internal interactions within α-aminoisobutyric acid solutions. In addition, Hansen solubility parameters (HSPs) were utilized to analyze the solubility behavior. Furthermore, mixing thermodynamic characteristics of α-aminoisobutyric acid in selected solvents were calculated by the NRTL model, which revealed that the mixing process was spontaneous and entropy-driven. These experimental results could be utilized for the purification, crystallization, and industrial applications of α-aminoisobutyric acid, as well as similar substances.</p>\",\"PeriodicalId\":42,\"journal\":{\"name\":\"Journal of Chemical & Engineering Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chemical & Engineering Data\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.jced.4c00023\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical & Engineering Data","FirstCategoryId":"1","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jced.4c00023","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Solubility Behavior of α-Aminoisobutyric Acid in 13 Individual Solvents at Temperatures Ranging from 283.15 to 323.15 K
In this study, the solid–liquid equilibrium solubility and solvent effects of α-aminoisobutyric acid in 13 monosolvent systems (water, methanol, ethanol, n-propanol, isopropanol, n-butanol, isobutanol, N,N-dimethylformamide, acetonitrile, acetone, ethyl acetate, 2-butanone, and methyl acetate) were reported at the pressure of 101.2 kPa (at T = 283.15–323.15 K). Among the 13 monosolvents, the solubility increased with the increase of absolute temperature, the order is water > N,N-dimethylformamide > methanol > ethyl acetate >2-butanone > ethanol > n-propanol > n-butanol ≈ n-pentanol > isopropanol > acetone > methyl acetate ≈ acetonitrile. The modified Apelblat model, Yaws model, Margules model, and nonrandom two-liquid (NRTL) model were employed to correlate the experimental solubility, and the OriginPro 2019b software was used for analysis and fitting, and the fitting results of the four models were all satisfactory. In addition, through a comparison of the average ARD and root-mean-square deviation (RMSD) values of the four models, the Yaws model achieved the best correlation result. Hirshfeld surface analysis (HS) and molecular electrostatic potential surface (MEPS) performed by the CrystalExplorer software and Gauss 5.0 program were used to determine the internal interactions within α-aminoisobutyric acid solutions. In addition, Hansen solubility parameters (HSPs) were utilized to analyze the solubility behavior. Furthermore, mixing thermodynamic characteristics of α-aminoisobutyric acid in selected solvents were calculated by the NRTL model, which revealed that the mixing process was spontaneous and entropy-driven. These experimental results could be utilized for the purification, crystallization, and industrial applications of α-aminoisobutyric acid, as well as similar substances.
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.