Revisiting Tracer Liu-Silva-Macedo model for binary diffusion coefficient using the largest database of liquid and supercritical systems

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abstract

This work compiles the largest database of tracer diffusion coefficients (D-12) containing 6180 experimental points from 331 non-polar and weakly polar liquid and supercritical systems. Then, the Tracer Liu - Silva - Macedo (TLSM) model and its 1-parameter correlations (TLSMd and TLSMen) are evaluated using this database, taking into account the importance of phenomenological and reliable equations for D-12 estimation. The TLSM model achieves good results with absolute average relative deviations (AARD) of 16.84 % while TLSMd and TLSMen show better performance with AARD of 4.53 % and 4.55 %, respectively. All properties and parameters needed for D-12 estimation are compiled in Appendix. For comparison, the models of Wilke-Chang and Reddy-Doraiswamy, and the correlations of Magalhaes et al. (LJ-1) and Dymond-Hildebrand-Batschinsky (DHB) are also assessed. (C) 2020 Elsevier B.V. All rights reserved.

subject category

Chemistry, Physical; Engineering, Chemical

authors

Zezere, B; Portugal, I; Gomes, JRB; Silva, CM

our authors

foto Bruno Miguel Martins Zêzere

Bruno Miguel Martins Zêzere

PhD Student
foto Carlos Manuel Silva

Carlos Manuel Silva

Associate Professor
foto Inês Portugal

Inês Portugal

Assistant Professor
foto José R. B. Gomes

José R. B. Gomes

Principal Researcher

Groups

G4 - Renewable Materials and Circular Economy
G6 - Virtual Materials and Artificial Intelligence

Projects

CICECO - Aveiro Institute of Materials (UIDB/50011/2020)

CICECO - Aveiro Institute of Materials (UIDP/50011/2020)

acknowledgements

This work was developed within the scope of the project CICECO-Aveiro Institute of Materials, UIDB/50011/2020 & UIDP/50011/2020, financed by national funds through the Portuguese Foundation for Science and Technology/MCTES. Bruno Zezere thanks FCT for the PhD grant SFRH/BD/137751/2018.

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Publication Details

type
Journal Article
year
2021
journal
JOURNAL OF SUPERCRITICAL FLUIDS
volume
168
article number
105073
publisher
ELSEVIER
issn
0896-8446
isbn
1872-8162
digital object identifier
10.1016/j.supflu.2020.105073
web of science article identifier
WOS:000618742600011

Journal Metrics (JCR 2019)

Journal Impact Factor
3.744
Journal Impact Factor (5 yrs)
3.536
category normalized journal percentile
67.828

Citations

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