RT info:eu-repo/semantics/article
T1 Artificial neural network modeling and VFT correlation of experimental dynamic viscosity of the 2-(2-ethoxyethoxy)ethanol + 2-propanol binary mixtures at high pressures and temperatures
A1 Lifi, Mohamed
A1 Bazile, Jean Patrick
A1 Daridon, Jean Luc
A1 Galliero, Guillaume
A1 Aguilar Romero, Fernando
A1 Muñoz Rujas, Natalia
K1 Oxygenated additives
K1 Alkoxyethanol
K1 Alcohol
K1 Dynamic viscosity
K1 Vogel−Fulcher−Tammann (VFT) correlation
K1 Artificial Neural Network (ANN) model
K1 Química física
K1 Chemistry, Physical and theoretical
K1 Termodinámica
K1 Thermodynamics
K1 Alcoholes
K1 Alcohols
AB This work reports experimental dynamic viscosity (n) data for the binary mixtures of 2-(2-ethoxyethoxy)ethanol (Diethylene glycol monoethyl ether) and 2-propanol at high temperatures and high pressures. A falling-body viscometer was employed to carry out the measurements for seven compositions of the studied binary mixture, as well as for pure 2-propanol, over a temperature range of 293.15–353.15 K and pressures up to 70 MPa, with an experimental uncertainty of +-3%. At 0.1 MPa, the dynamic viscosity was measured using a classical Ubbelohde capillary viscometer with an uncertainty of +-1%. The high-pressure dynamic viscosity experimental data were correlated using the Vogel-Fulcher-Tammann (VFT) equation. To describe the viscosity of the binary system as a function of composition, temperature, and pressure, a combining rule based on the logarithm of viscosity was employed. Additionally, an Artificial Neural Network (ANN), a machine learning approach known for its accuracy in capturing nonlinear relationships, was applied to model the dynamic viscosity of the studied binary mixture. The dynamic viscosity behaviour of the analysed binary system was attributed to variations in free volume and the disruption or weakening of hydrogen bonds.
PB Elsevier
SN 0016-2361
YR 2025
FD 2025-12
LK https://hdl.handle.net/10259/11252
UL https://hdl.handle.net/10259/11252
LA eng
NO Open access funding provided by UNIVERSIDAD DE BURGOS.
DS Repositorio Institucional de la Universidad de Burgos
RD 21-abr-2026