Artigo Produção Nacional Revisado por pares

Optimization of the methylic biodiesel purification process by intermediate of liquid–liquid equilibrium data for ternary systems containing methanol+water+(soybean, corn or brown shell of coconut) biodiesel

2013; Elsevier BV; Volume: 361; Linguagem: Inglês

10.1016/j.fluid.2013.10.018

ISSN

1879-0224

Autores

Regiane Silva Pinheiro, Aline Mara Maia Bessa, Bruna Amaral de Queiroz, Aíla Maria Souza Fontenele Duarte, Hosiberto Batista de Sant’Ana, Rílvia Saraiva de Santiago-Aguiar,

Tópico(s)

Microbial Metabolic Engineering and Bioproduction

Resumo

Biodiesel is usually produced by transesterification reactions, by intermediate of a catalytic reaction in which a source of triglycerides (from vegetable, animal or residual oils) reacts with excess of alcohol producing as main product biodiesel and as side-product glycerol. After those reactions, it is usually necessary to purify the biodiesel produced by settling process. This step is followed by liquid–liquid extraction (wash up) unit operation. Systematic studies on biodiesel washing process, especially as function of composition data, are still scarce in the literature. Liquid–liquid equilibrium data provide important means to the development and design of equipment and also in the optimization of the extraction processes. This paper, as part of continuing study in our research group, reports equilibrium data for different ternary systems of methanol + water + (soybean, corn or brown shell of coconut, here named coconut) biodiesel at 293.15 and 313.15 K at atmospheric pressure. Experimental data were carried out in equilibrium cells, by using a bath, in order to control the temperature of the system. From experimental data, distribution coefficients of methanol have been determined. The quality and reliability of the tie-line were tested by Othmer-Tobias and Hand correlations. Liquid–liquid equilibrium (LLE) data were correlated with the following activity coefficient models: NRTL, UNIQUAC and UNIFAC, with a global deviation error of 1.34%, 1.34% and 4.13%, respectively.

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