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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Aqueous viscosity of carbohydrates: Experimental data, activity coefficient modeling, and prediction with artificial neural network-molecular descriptors

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Author(s):
Varnier, Karine [1] ; Galvao, Alessandro C. [1] ; Arce, Pedro F. [2] ; Robazza, Weber S. [1]
Total Authors: 4
Affiliation:
[1] Santa Catarina State Univ UDESC, Lab ApTher Appl Thermo Phys, Dept Food & Chem Engn, BR-89870000 Pinhaizinho, SC - Brazil
[2] Univ Sao Paulo, Engn Sch Lorena, Dept Chem Engn, BR-12600970 Lorena, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JOURNAL OF MOLECULAR LIQUIDS; v. 322, JAN 15 2021.
Web of Science Citations: 0
Abstract

Food waste is a rich source of carbohydrates. This material can be reprocessed in order to produce purified compounds or other materials with high added value. The implementation of processes that enable this transformation depends on kinematic viscosity data and robust mathematical modeling. In order to meet part of this demand, the objective of this work was to study the kinematic viscosity of binary and ternary solutions involving sucrose, sorbitol, xylose and xylitol in the temperature range between 303.15K and 363.15 K at concentrations of 0.5 mol.kg(-1) to 3.0 mol.kg(-1). In the correlation of experimental data, the Eyring equation was associated to the Ma rgules, van bar, Wilson and NR-11. models. In the simulation, an artificial neural network associated with molecular descriptors was developed. The experimental results showed to be dependent on the number of OH groups present in the sugar. The mathematical modeling proved to be efficient in the treatment of the experimental data, with the NRTL model being the one with the best performance. Artificial neural networks were satisfactory in the simulation of the data, with the 7-7-5-1 architecture being the one with the best data prediction capacity. (C) 2020 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 15/05155-8 - Modeling of the thermophysical properties of pure fluids (ionic liquids and components present in natural products) and thermodynamic behaviour of the phase equilibrium of mixtures
Grantee:Pedro Felipe Arce Castillo
Support Opportunities: Regular Research Grants