Measurement and Prediction of Biodiesel Surface Tensions
authors Freitas, SVD; Oliveira, MB; Queimada, AJ; Pratas, MJ; Lima, AS; Coutinho, JAP
nationality International
journal ENERGY & FUELS
keywords EQUATION-OF-STATE; DENSITY EXPERIMENTAL MEASUREMENTS; VAPOR-LIQUID INTERFACES; PLUS ALCOHOL SYSTEMS; FATTY-ACID METHYL; CPA EOS; GRADIENT THEORY; IONIC LIQUIDS; MULTICOMPONENT SYSTEMS; MUTUAL SOLUBILITIES
abstract Surface tension is one of the key properties that directly affects fuel atomization. A large value of this property makes the formation of small droplets difficult, hampering the correct fuel atomization on the engine combustion chamber. Despite its importance, there are very few data on the surface tension of biodiesels or fatty acid esters from which biodiesels are composed and even less are available on its temperature dependence. To overcome this limitation, this work reports experimental surface tensions for 10 biodiesel fuels in a wide temperature range and evaluates the ability of two models to predict these data: the parachor-based MacLeod-Sugden equation and the density gradient theory based on the cubic-plus-association equation of state (CPA EoS). It is shown that both models provide an acceptable description of the experimental surface tension of the biodiesel fuels studied, with an overall average relative deviation (OARD) of 7.7% for the MacLeod-Sugden equation using the Allen's parachors and 1.3% with the Knotts' parachors, while the CPA EoS combined with the gradient theory presents an OARD of 9.7%. The surface entropy and enthalpy derived from the measured surface tensions are also reported, and their values indicate the importance of the surface ordering in biodiesel fuels. Given the scarcity of data on surface tensions, these models prove to be useful for predicting surface tensions and their temperature dependence for biodiesel fuels.
publisher AMER CHEMICAL SOC
issn 0887-0624
year published 2011
volume 25
issue 10
beginning page 4811
ending page 4817
digital object identifier (doi) 10.1021/ef201217q
web of science category Energy & Fuels; Engineering, Chemical
subject category Energy & Fuels; Engineering
unique article identifier WOS:000296212900063
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journal analysis (jcr 2017):
journal impact factor 3.024
5 year journal impact factor 3.622
category normalized journal impact factor percentile 66.683
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