2026-05-30T23:21:00Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112582026-02-17T10:55:00Zcom_10259_9737com_10259_5086com_10259_2604col_10259_10448

00925njm 22002777a 4500 dc Yatim, Fatima Ezzahra author Samadi, Khaoula author Abala, Ilham author Lifi, Mohamed author Muñoz Rujas, Natalia author Aguilar Romero, Fernando author Alaoui, Fatima E. M. author 2025-09 Bioenergy and biofuels are at a critical stage of development. Their role in decarbonising the transport sector, particularly in reducing emissions from shipping and aviation, is widely recognized. Waste Cooking Oil Biodiesel (WCOB) is a promising biofuel, due to its economic viability and sustainability. Additionally, oxygenated additives, such as Dibutyl Ether (DBE), enhance the properties of biofuel blends by improving combustion efficiency and reducing emissions. In this study, the density of WCOB and DBE, was systematically investigated under controlled temperature and pressure conditions. Four mixtures with mass fractions of 0.3500, 0.4998, 0.6750, and 0.8492 were prepared. Density measurements were performed over a temperature range of 298.15 K–393.15 K and a pressure range of 1–140 MPa. The Tait equation was used to correlate the experimental density data, which were subsequently used to determine the derived thermodynamic properties of isobaric expansion and isothermal compressibility. The blend density was also predicted using the PC-SAFT equation of state and artificial neural networks (ANN). Models accuracy was evaluated and discussed using a statistical metrics. The ANN model provided the best accuracy for the complete dataset, with AAD = 0.1246 %, MD = 2.3046 % and RMSE = 1.84.10−3, demonstrating its effectiveness in predicting blend densities. 0960-1481 https://hdl.handle.net/10259/11258 10.1016/j.renene.2025.124469 Biofuel blends Waste cooking oil Dibutyl ether Density PC-Saft model Artificial neural network Biofuels as a sustainable energy solution: Density measurement and modeling of waste cooking oil and DBE blend