Solubility of 1,1-diamino-2,2-dinitroethylene in different pure solvents and binary mixtures (dimethyl sulfoxide + water) and (N,N-dimethylformamide + water) at different temperatures

The solubility data of L-arginine L-pyroglutamate were determined by the static gravimetric method from 283.15 to 323.15 K in nine pure solvents (water, methanol, ethanol, isopropanol, acetone, acetonitrile, dichloromethane, ethyl acetate, and n-hexane) and a water + ethanol binary solvent system. According to experimental results, solubility was positively correlated with temperature. In the selected solvent systems, three different polymorphs denoted as α-form, β-form, and γ-form were found. In addition, from the data analysis results, the polarity, hydrogen bonding, Hildebrand solubility parameters, and the molecular structure affected the dissolution equilibrium. Two thermodynamic models including the modified Apelblat model and the Yaws model were used to correlate the solubility data. Meanwhile, these models were evaluated by the Akaike information criterion method.

Section: Solubility and Model Calculationmentioning

confidence: 99%

Solubility Behavior and Polymorphism of l-Arginine l-Pyroglutamate in Nine Pure Solvents and a Binary Water + Ethanol System

Han

Liu

et al. 2021

“…The solubility data were also correlated by another semiempirical model, named the Yaws model − (eq ). It can also be employed to fit the solubility data of a solute at different temperatures in pure solvents.…”

Section: Solubility and Model Calculationmentioning

confidence: 99%

Solubility Behavior and Polymorphism of N-Acetyl-l-proline in 16 Individual Solvents from 283.15 to 323.15 K

Huang

Qiu

et al. 2021

The mole fraction solubility data of N-acetyl-l-proline in 16 neat solvents (water, methanol, ethanol, n-propanol, isopropanol, n-butanol, isobutanol, sec-butanol, n-pentanol, acetone, 2-butanone, acetonitrile, dichloromethane, methyl acetate, ethyl acetate, and 1,4-dioxane) covering a temperature range of 283.15–323.15 K were measured by the static gravimetric method. The polymorphism of N-acetyl-l-proline was investigated by the powder X-ray diffraction test and the patterns show that there are two polymorphs within the studied solid–liquid equilibrium systems. The increasing temperature shows a positive effect on N-acetyl-l-proline solubility in all of the solvents and the largest increasing rate is observed in acetonitrile with an increase of 16-fold. The solubility behavior was found to be influenced by five factors including polarity, hydrogen bonding, solvent–solvent interactions, molecular construction, and viscosity. Two thermodynamic models, i.e., the modified Apelblat model and the Yaws model, were used for the correlation of solubility data. To evaluate the fitting results, the average relative deviation (ARD) and root-mean-square deviation (RMSD), as well as the Akaike information criterion (AIC) and Akaike weights, were computed for each model.

“…The solubility data were also correlated by another semiempirical Yaws model, − which is shown as eq . The meanings of the first two parameters ( A 1 , B 1 ) on the right side of the Yaws model were the same as those of the modified Apelblat model, while the third parameter ( C 1 ) can better describe solubility curves with the special varying trend. …”

Section: Solubility and Model Calculationmentioning

confidence: 99%

Solubility Behavior and Polymorphism of N-Acetyl-dl-methionine in 16 Individual Solvents from 283.15 to 323.15 K

Huang

Qiu

et al. 2021

The mole fraction solubility data of N-acetyl-dl-methionine in 16 pure solvents at T = 283.15–323.15 K were measured using the static gravimetric method under a pressure of 98.8 kPa. The polymorphism of N-acetyl-dl-methionine was studied by X-ray powder diffraction analysis, and the results show that there may exist two polymorphs in the studied solid–liquid equilibrium systems. The solubility increased with increasing temperature, and the largest solubility value was obtained in methanol, followed by ethanol > n-propanol > isopropanol > n-butanol > sec-butanol > isobutanol > n-pentanol > acetone > 2-butanone > water > methyl acetate > ethyl acetate > dichloromethane (except for 1,4-dioxane and acetonitrile, which intersect with other solvents). The above solubility behavior is affected by the mutual constraints of polarity, hydrogen bonding, cohesive energy density, viscosity, and molecular structure. In addition, the KAT-LSER model was applied to analyze solute–solvent and solvent–solvent intermolecular interactions. To mathematically represent the measured solubility data, the modified Apelblat model and Yaws model were employed. The average relative deviation (ARD), root-mean-square deviation (RMSD), Akaike information criterion (AIC), and Akaike values of each model were calculated to evaluate the fitting outcomes.