Phase Equilibrium Involving Xylitol, Water, and Ethylene Glycol or 1,2-Propylene Glycol: Experimental Data, Activity Coefficient Modeling, and Prediction with Artificial Neural Network-Molecular Descriptors

Abstract

The xylitol molecule is an important building block that can be used in the production of such interesting chemicals as ethylene glycol and 1,2-propylene glycol. The development of productive processes that enable this transformation depends on various experimental and theoretical information. In order to supply part of this demand, this work sought to study the solubility of xylitol in binary liquid solutions formed by water, ethylene glycol, and 1,2-propylene glycol in the temperature range between 293.15 and 323.15 K, covering the entire molar composition range of the solution. The Jouyban–Acree, NRTL, and UNIQUAC models were used in the correlation of experimental data, and the mUNIFAC model was applied in the prediction of experimental data. In addition, an artificial neural network associated with molecular descriptors was developed to simulate the data. Xylitol showed solubility in the pure components with decreasing values in the following order: water, ethylene glycol, and 1,2-propylene glycol. The solubility in binary solutions had intermediate values according to the intermediate concentration values. The models used proved capable of correlating or predicting the experimental data. The artificial neural networks had a satisfactory performance in the data simulation, and the best observed architecture used four layers of the type 7-3-3-1.

Phase Equilibrium Involving Xylose, Water, and Ethylene Glycol or 1,2-Propylene Glycol at Different Temperatures

“…The propagation method was employed to estimate the experimental uncertainty of the solubility data expressed as mass fraction. Further information about the experimental technique applied to determine the liquid composition in equilibrium with the solid phase can be found in a work previously published …”

“…Further information about the experimental technique applied to determine the liquid composition in equilibrium with the solid phase can be found in a work previously published. 30…”

Experimental Study and Modeling of the Liquid–Liquid and Solid–Liquid–Liquid Equilibrium of Aqueous Solutions Involving 1-Butanol and Xylitol at Different Temperatures

“…The conversion of biomass into a variety of fuels and chemicals has gained much attention in the last decades due to demands associated with the exploitation of a nonrenewable source of carbon. 1 In this context, different groups of molecules have been investigated as potential building blocks 2 or substitutes for ongoing processes.…”

Effect of Storage Time on the Physical, Chemical, and Rheological Properties of Blueberry Jam: Experimental Measurements and Artificial Neural Network Simulation

“…The combination of artificial neural networks (ANN) and molecular descriptors (MD) is a technique recently used for the prediction of physical, chemical, and thermodynamic properties of pure fluids and solutions or mixtures. The authors have already used this technique in several research studies [32,33]. SMILES (Simplified Molecular Input The field of molecular descriptors is based on the mass of different theories such as algebra, graph theory, information theory, computational chemistry, theories of organic reactivity and physical chemistry.…”

“…The combination of artificial neural networks (ANN) and molecular descriptors (MD) is a technique recently used for the prediction of physical, chemical, and thermodynamic properties of pure fluids and solutions or mixtures. The authors have already used this technique in several research studies [32,33]. SMILES (Simplified Molecular Input Line Entry System) is a specific, easy, and flexible chemical notation to represent a chemical structure in a way that can be interpreted by the Dragon [34,35].…”