Simple and accurate correlations for diffusion coefficients of solutes in liquids and supercritical fluids over wide ranges of temperature and density

[Display omitted] ► Very simple and accurate 2-parameter correlations for D12 in liquids and SCF. ► D12 depends on temperature and/or solvent density and/or solvent viscosity. ► Validation accomplished with a very large database: 539 systems/8219 data points. ► Database includes pairs of molecules v...

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Veröffentlicht in:The Journal of supercritical fluids 2013-04, Vol.76, p.94-114
Hauptverfasser: Magalhães, Ana L., Lito, Patrícia F., Da Silva, Francisco A., Silva, Carlos M.
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Sprache:eng
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Zusammenfassung:[Display omitted] ► Very simple and accurate 2-parameter correlations for D12 in liquids and SCF. ► D12 depends on temperature and/or solvent density and/or solvent viscosity. ► Validation accomplished with a very large database: 539 systems/8219 data points. ► Database includes pairs of molecules very different in size, polarity, mass & symmetry. ► Best global deviations are: 2.8% for correlation and 4.2% for prediction. The binary diffusion coefficients at infinite dilution, D12, are fundamental properties in chemical engineering simulation and design. In this work, very simple and accurate expressions involving two parameters are proposed/analyzed for their estimation. They depend only on temperature and/or solvent density and/or solvent viscosity. Their correlation and prediction abilities are tested with the largest database ever compiled, composed of 539 binary systems and 8219 data points, where polar/non-polar, symmetrical/asymmetrical, small/large, and light/heavy molecules are included without exception. It is shown that only two experimental D12 values are sufficient to get good parameters for the subsequent estimation of reliable diffusivities far away from the conditions of the experimental data utilized to fit them. Globally, Eqs. (2)–(4) and (9) are recommended for D12 calculation, due to the excellent results achieved for both correlation (average errors between 2.78% and 3.05%) and prediction (average errors between 4.21% and 4.44%). A comparison with models from the literature is also accomplished.
ISSN:0896-8446
1872-8162
DOI:10.1016/j.supflu.2013.02.002