
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Novel Approach for Liquid–Liquid Phase Equilibrium of Biodiesel (Canola and Sunflower) + Glycerol + Methanol

doi: 10.1021/ie4031902
In this study, a novel experimental approach was used to overcome the lack of phase equilibrium information to obtain data that is more applicable to industrial situations. Liquid–liquid equilibrium (LLE) data, tie-lines, and phase boundaries were carried out for two systems of canola oil methyl esters (containing 1 wt % KOH) + glycerol + methanol and sunflower oil methyl esters (containing 1 wt % KOH) + glycerol + methanol at three different temperatures (303.15, 313.15, and 323.15 K). The quality of data was also ascertained using Othmer–Tobias correlations. The experimental LLE data was also correlated by the nonrandom two-liquid (NRTL) and the Wilson–NRF Gibbs free energy models. The energy interaction parameters of both models were obtained for both systems. The results indicated that the Wilson–NRF provided an accurate correlation of LLE behavior with average absolute deviation (AAD%) inferior to 8.78% and 10.80% for canola and sunflower biodiesel systems, respectively. However, the NRTL model prese...
- Sharif University of Technology Iran (Islamic Republic of)
- Sharif University of Technology Iran (Islamic Republic of)
- Amirkabir University of Technology Iran (Islamic Republic of)
- Amirkabir University of Technology Iran (Islamic Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
