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A high-throughput computing procedure for predicting vapor-liquid equilibria of binary mixtures – Using carbon dioxide and n-alkanes as examples
- Source :
- Fluid Phase Equilibria. 452:58-68
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- An automatic high-throughput computing (HTC) procedure is implemented for calculating vapor-liquid equilibrium (VLE) curves of binary systems using molecular dynamics simulation and coarse-grained force field. The HTC procedure builds simulation models, carries out the simulations, and validates the simulations automatically. The procedure is demonstrated by calculating the VLE curves for 16 binary mixtures of carbon dioxide and n-alkanes on 856 state points in the temperature range of 277.2–420.0 K and pressure range of 0.3–25.0 MPa. The averaged uncertainties in predictions are 0.119 MPa for pressure, 0.007 and 0.029 for liquid and vapor CO 2 molar fractions, and 0.005 and 0.010 for liquid and vapor densities respectively. The Validation against experiment data on 10 binary systems and 316 state points shows that the predictions are accurate with average deviation of about 5% for CO 2 mole fraction and 3.5% for saturated density at pressure range to P P c . This automatic procedure can only be used for the prediction of the vapor-liquid equilibrium. The computed data can be obtained from http://sun.sjtu.edu.cn/msd .
- Subjects :
- N alkanes
General Chemical Engineering
General Physics and Astronomy
Binary number
Thermodynamics
02 engineering and technology
Atmospheric temperature range
021001 nanoscience & nanotechnology
Mole fraction
Force field (chemistry)
chemistry.chemical_compound
Molecular dynamics
020401 chemical engineering
chemistry
Carbon dioxide
Vapor liquid
0204 chemical engineering
Physical and Theoretical Chemistry
0210 nano-technology
Subjects
Details
- ISSN :
- 03783812
- Volume :
- 452
- Database :
- OpenAIRE
- Journal :
- Fluid Phase Equilibria
- Accession number :
- edsair.doi...........5b55fab3e971785c7162966fccec1564
- Full Text :
- https://doi.org/10.1016/j.fluid.2017.08.021