Solid–liquid equilibrium of l-arabinose in water+ethanol solvent system from 283.15 to 308.15K

Jiang, Linjie; Li, Suye; Jiang, Jinxia; Qiu, Jingxuan; Wang, Peng

doi:10.1016/j.molliq.2015.07.040

Cited by 15 publications

(3 citation statements)

References 15 publications

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“…The accuracy of the model was checked in several articles (14)(15)(16)(17)(18)(19)(20). The classical version of the model is able to predict the solubility in various solubility units and requires the experimental solubility of a solute in the mono-solvent systems.…”

Section: Introductionmentioning

confidence: 99%

Solubility Prediction of Drugs in Binary Solvent Mixtures at Various Temperatures Using a Minimum Number of Experimental Data Points

et al. 2018

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This study aimed to provide a rational experimental design to collect a minimum number of experimental data points for a drug dissolved in a given binary solvent mixture at various temperatures, and to describe a computational procedure to predict the solubility of the drugs in any solvent composition and temperature of interest. We gathered available solubility data sets from papers published from 2012 to 2016 (56 data sets, 3488 data points totally). The mean percentage deviations (MPD) used to check the accuracy of predictions was calculated by Eq. 10. Fifty-six datasets were analyzed using 8 training data points which the overall MPD was calculated to be 15.5% ± 15.1%, and for 52 datasets after excluding 5 outlier sets was 12.1% ± 8.9%. The paired t test was conducted to compare the MPD values obtained from the models trained by 7 and 8 training data points and the reduction in prediction overall MPD (from 17.7% to 15.5%) was statistically significant (p < 0.04). To further reduction in MPD values, the computations were also conducted using 9 training data points, which did not reveal any significant difference comparing to the predictions using 8 training data points (p > 0.88). This observation revealed that the model adequately trained using 8 data points and could be used as a practical strategy for predicting the solubility of drugs in binary solvent mixtures at various temperatures with acceptable prediction error and using minimum experimental efforts. These sorts of predictions are highly in demand in the pharmaceutical industry.

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Section: Introductionmentioning

confidence: 99%

Solubility Prediction of Drugs in Binary Solvent Mixtures at Various Temperatures Using a Minimum Number of Experimental Data Points

et al. 2018

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“…Arabinose is a five carbon sugar, one of the main monomers in the hemicellulose of softwoods. It can be used as a non-caloric sweetener, dietary fiber, in flavors and as an intermediate for the synthesis of different drugs, mainly related to human diabetes, bacteriological diagnostics, anti-virus, production of vitamin B2 (Aguedo et al, 2013;Jiang et al, 2015). Despite of these important uses, arabinose commercial production is still nowadays a complex and expensive process consisting of acid hydrolysis of Arabic gum or other raw materials followed by multiple procedures of purification (Cheng et al, 2011), so the development of an alternative and easier process (starting, for example, from a low-value raw material such as the hemicellulose) would be very interesting.…”

Section: Introductionmentioning

confidence: 99%

Selective arabinose extraction from Pinus sp. sawdust by two-step soft acid hydrolysis

Bravo

Garcés

Faba

et al. 2017

Industrial Crops and Products

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Acid hydrolysis of Pinus sp. sawdust is optimized in this work in order to selectively recover arabinose from the hemicellulose fraction by an environmental-friendly process (reactions at atmospheric pressure and mild conditions and using dilute HCl as catalyst). The influence of temperature, HCl concentration and reaction time was studied in the first experiments considering one step hydrolysis. One step hydrolysis was studied at different conditions, being the best results obtained at 65°C for 18 h with 3% of HCl, with more than 3.8 g/L of arabinose in the liquid phase. This value corresponds to more than 47.5% of recovery of the arabinose present in the original sawdust and a selectivity of a 52% in the liquid phase (hydrolysis of other hemicellulosic sugars). In a second approach, a two steps process was considered in order to maximize the arabinose recovery. The optimum results were obtained combining a first cycle at 65°C with a second one at 80°C. More than 54% of the initial arabinose was recovered in the liquid phase as monomers. This percentage increases to 100% if the oligomers are also considering (no arabinose detected in the solid phase after the treatment). At these conditions, more than 56% of the global hemicellulose sugars were removed from the solid phase, without having a relevant degradation of glucose (pentose selectivity in liquid phase is higher than 88%, corresponding the resto mainly to hemicellulosic glucose).

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“…On the other hand, the large set of monosaccharides investigated permits the identification of the most important features regarding their solubility in ILs. The solubility values were also compared with those reported in the literature for water [31][32][33][34][35][36][37][38][39][40] and methanol. 32,[41][42][43][44] The thermodynamic functions of solution were determined and the respective solvation mechanisms are presented and discussed.…”

Section: Introductionmentioning

confidence: 99%

Solubility and solvation of monosaccharides in ionic liquids

Teles

Dinis

Capela

et al. 2016

Phys. Chem. Chem. Phys.

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Solid–liquid equilibrium of l-arabinose in water+ethanol solvent system from 283.15 to 308.15K

Cited by 15 publications

References 15 publications

Solubility Prediction of Drugs in Binary Solvent Mixtures at Various Temperatures Using a Minimum Number of Experimental Data Points

Solubility Prediction of Drugs in Binary Solvent Mixtures at Various Temperatures Using a Minimum Number of Experimental Data Points

Selective arabinose extraction from Pinus sp. sawdust by two-step soft acid hydrolysis

Solubility and solvation of monosaccharides in ionic liquids

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