In the present paper we have experimentally determined the density, saponification value, iodine value, acid value, peroxide value for four different edible oils: sunflower oil, corn oil, rapeseed oil and peanut oil. Density was determined in the temperature range of 20 o C -50 o C, with a 10 degree step increase. The physicochemical properties of the investigated oils were within the requirements of food domain: saponification value varied from 164.84 to 206.45 mg KOH/g, peroxide value varied from 9.99 to 24.49 mEg O 2 /kg of sample, acid value varied from 0.22 to 3.97 mg KOH/g, iodine value varied from 94.35 to 102.02 g I 2 /100 g sample, and density varied from 0.9031 to 0.9208 g/cm 3 . Based on experimental data, density were correlated with others properties of edible oils. An empirical model was proposed to correlate oil density with iodine value and temperature. The results of the proposed model were compared with a model from literature. The accuracy of the proposed model was very good, the AAD varying in the range of 0.078 % to 0.092 %. The proposed model can be recommended for density of vegetable oils evaluation based on their IV, at different temperatures in the range of 20 o C to 50 o C.
The increase of the environment pollution, together with the instable price of crude oil led in the last years to a renewed focus on biofuels. As the demand in the transport sector is continuously increasing, and taking into account the benefits of biofuels, it is expected that the market demand for biofuels to be increased in the near future. In this context, it will be interesting to investigate if new types of biofuels could be used as mixtures with other fuels for internal combustion engines. The aim of this paper is the study of density and viscosity variation with composition and temperature for ternary mixtures biodiesel + diesel fuel + bioalcohol. Experimental densities and viscosities data for ternary blends diesel fuel+biodiesel +isopropyl alcohol/1-butyl alcohol are presented, and some empirical models proposed to predict these properties for binary systems diesel fuel+biodiesel are evaluated for the proposed ternary blends.
For now, biodiesel is the commonly accepted biofuel as a substitute for diesel fuel in internal combustion engines. Diesel fuel blends with up to 20% biodiesel can be used in diesel engines without any modification. A lot of studies regarding diesel fuel+biodiesel blends properties are presented in the literature. Some of the important properties of diesel fuel+biodiesel blends can be evaluated from other blends properties. For example, density and viscosity of biodiesel blends can be predicted based on blend refractive index. More than that, refractive index can be used as a reliable physical property to predict transesterification reaction progress. As a result, the refractive index of diesel fuel+biodiesel blends is important in order to characterize these blends or to monitor the evolution of transesterification process of vegetable oils or animal fats. The refractive index of diesel fuel+biodiesel blends can be experimentally determined or evaluated based on refractive indices of diesel fuel and biodiesel. The aim of this study was to estimate the accuracy of refractive index of diesel fuel +biodiesel blends calculation, using models initially proposed to evaluate the refractive index of a binary liquid mixture. It was shown that the refractive index of diesel fuel+biodiesel blends can be accurately predicted from refractive indices of the components of the blend. Wiener, Heller and Edward equations can be recommended to predict with a great accuracy the refractive index of diesel fuel+biodiesel blends.
Abstract. The properties of gasoline change as a result of blending with a bioalcohol, affecting the behavior of the pseudo-binary system. The aim of this paper is to present experimental data of the refractive index for pseudobinary mixtures of a reformate gasoline with ethanol, isopropanol and n-butanol over the entire composition range and for temperature ranging from 293.15 K to 313.15 K. The accuracy of different equations to predict the refractive index of the mixtures was tested. The best prediction accuracy (the lower AAD) corresponded to Eykman and Lorentz-Lorenz mixing rules. A logarithmic equation proposed to correlate the refractive index with composition and temperature of gasoline+alcohol mixtures showed a good accuracy (the absolute average deviation AAD < 0.052%). The deviations in refractive index for investigated systems are negative over the entire composition range and at all investigated temperatures.
The major objective of this study is to report physico-chemical properties of sunflower oil samples collected from different stages of the technological process for sunflower oil refining for food industry. The samples of oil were crude oil, washed oil, bleached oil and deodorized oil. The physico-chemical properties of sunflower oil experimentally determined were density, saponification value (SV), iodine value (IV), and acid value (AV). It was found that the density of sunflower oil remains approximately constant over the different stages of the manufacturing flow of cooking oil, except the crude oil. The acid value significantly decreases from crude oil (2.588) to deodorized oil (0.366). The iodine value and saponification value of the different samples of the sunflower oil corresponding to different stages of oil processing varies slightly. The capacity of different models to accurately correlate and/or predict the density of vegetable oil was tested. The density of sunflower oil can be accurately estimated from its SV and IV or with an empirical equation, when density data are available.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.