2026-05-11T13:36:16Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112522026-01-22T01:05:31Zcom_10259_9737com_10259_5086com_10259_2604col_10259_10448

Lifi, Mohamed 1f0a7148-9b14-44e2-a1ee-c6631a49ff82 600 Bazile, Jean Patrick c15628ae-8cfa-43bf-bea5-7147581ea0e3 600 Daridon, Jean Luc 44b571af-69ec-4f94-b9f4-5dfe0f5ff002 600 Galliero, Guillaume 4e76d1b3-a101-4047-b8e1-7062edf55d73 600 Aguilar Romero, Fernando 902 600 0000-0002-2982-9053 Muñoz Rujas, Natalia 383 600 0000-0003-2185-1392 2026-01-21T09:37:30Z 2026-01-21T09:37:30Z 2025-12 0016-2361 https://hdl.handle.net/10259/11252 10.1016/j.fuel.2025.137776 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. Open access funding provided by UNIVERSIDAD DE BURGOS. application/pdf eng Elsevier Fuel. 2025, V. 409, p. 137776 https://doi.org/10.1016/j.fuel.2025.137776 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Oxygenated additives Alkoxyethanol Alcohol Dynamic viscosity Vogel−Fulcher−Tammann (VFT) correlation Artificial Neural Network (ANN) model Química física Termodinámica Alcoholes Chemistry, Physical and theoretical Thermodynamics Alcohols 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 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Fuel 409 137776 THUMBNAIL Lifi-fuel_2025.pdf.jpg Lifi-fuel_2025.pdf.jpg IM Thumbnail image/jpeg 3882 https://riubu.ubu.es/bitstream/10259/11252/4/Lifi-fuel_2025.pdf.jpg 6676059ae38ec3f015f3b06e8b718a15 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 1362 https://riubu.ubu.es/bitstream/10259/11252/3/license.txt 5d013bfa6e473ff0db22cd82a4d71a70 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 908 https://riubu.ubu.es/bitstream/10259/11252/2/license_rdf 0175ea4a2d4caec4bbcc37e300941108 MD5 2 ORIGINAL Lifi-fuel_2025.pdf Lifi-fuel_2025.pdf application/pdf 2497476 https://riubu.ubu.es/bitstream/10259/11252/1/Lifi-fuel_2025.pdf dea74b5052ed7189bfb2a6d3a16ca20f MD5 1 10259/11252 oai:riubu.ubu.es:10259/11252 2026-01-22 02:05:31.924 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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