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Formulation of approximate generalised experimental data based model in a liquid–liquid extraction using zinc oxide nanomaterial
- Source :
- Perspectives in Science, Vol 8, Iss C, Pp 664-666 (2016)
- Publication Year :
- 2016
- Publisher :
- Elsevier, 2016.
-
Abstract
- Summary The present phenomenon, i.e. enhancement of mass transfer coefficient in liquid–liquid extraction operation is a complex one and it cannot be reasoned out by any logic based model, so it is find out by experimental data based model. The present investigation is focused on the behaviour of nanofluid in the liquid–liquid extraction process. The chemical system of toluene–acetic acid–water was used, and nanofluids containing 0.1%, 0.2% and 0.3% (V/V) of zinc oxide nanoparticles of size 48.79 nm synthesised by chemical precipitation method. Maximum enhancements in the rate of mass transfer of were achieved using about 0.3 wt% zinc oxide based nanofluids; however, a decreasing variation was observed at higher concentrations. The effect of nonionic surfactants Rokanol K7 (500 ppm) on mass transfer of the liquid–liquid extraction process was also investigated and it was observed that the mass transfer coefficient increases rapidly with surfactants under a varying speed of agitation but deteriorates at high concentration. The formulation of approximate generalised experimental data based model has been developed followed by interpretation and the quantitative analysis of the model. For the aim of modelling, the experimental results obtained from liquid–liquid extraction were validated with mathematical modelling for calculation of reliability of model.
- Subjects :
- Mass transfer coefficient
Materials science
Extraction (chemistry)
Analytical chemistry
Nanoparticle
chemistry.chemical_element
02 engineering and technology
Zinc
Nanofluid
021001 nanoscience & nanotechnology
Reliability
Modelling
Nanomaterials
020401 chemical engineering
chemistry
Liquid–liquid extraction
Mass transfer
lcsh:Q
0204 chemical engineering
0210 nano-technology
lcsh:Science
lcsh:Science (General)
lcsh:Q1-390
Subjects
Details
- Language :
- German
- ISSN :
- 22130209
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Perspectives in Science
- Accession number :
- edsair.doi.dedup.....aec6680439ed3e5717e8a04ac44700e5