Prsentation PowerPoint

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18th European Symposium on Computer Aided Process
Engineering
Modeling the Phase Equilibria of Nitriles by the
soft-SAFT equation of State.
A. Belkadi, M-K. Hadj-Kali, F. Llovell ,
V. Gerbaud, X. Joulia, L. F. Vega LGC
(Toulouse, France) ICMAB (Barcelona, Spain)
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Introduction
Process simulation
Thermodynamic modeling
Phase equilibrium
Cubic EoS
Molecular based EoS
SRK / PR /
Tc / Pc / ?
SAFT / CPA /
s / e / Q
Pure compounds data base
Thermodynamicproperties
Thermodynamic models
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Why using a molecular based EoS (SAFT) ?

• Direct access to fluid intrinsic properties
• Strong physical meaning of the molecular
  parameters.
• Accurate prediction of VLE of heavier molecules
  by extrapolation of molecular parameters fitted
  on small molecules.
• Handling of complex fluids (ionic liquids VLLE,
  electrolytes, quadrupolar solvents, hydrogen
  bonding mixtures)

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Outline

• Introduction
• Statistical Associating Fluid Theory
• Nitriles Family Previous works and present work
  
• Methodology
• Isomers distinction (iso- and nbutyronitrile)
• Binary VLE calculations (ACN-CO2)
• Conclusions and perspectives

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Statistical Associating Fluid Theory (1/3)
(Chapman et al.1989)
Sum of molecular interactions

• Segments interactions (reference fluid)

• Chain formation

• Association

• Polarity

Free Helmholtz energy (A)
Aseg
Aid
Achain
Aassoc
Apol
A
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Statistical Associating Fluid Theory (2/3)
Terms of the soft-SAFT equation
Pv
Zmultipole
Z
1
Zassoc
Zseg
Zchain
RT
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Statistical Associating Fluid Theory (3/3)

• Parameters of the soft-SAFT equation

s
Chain molecules
e/kB
m
eHB/kB
Associative molecules
?HB
Polar molecules
µ,Q
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Previous works the proposed model
Nitriles model with soft-SAFT EoS

• Literature models (Spuhl al. 2004) with PC-SAFT
  EoS

Chain formation
Association
Polar
AAD(?liq)
Model 1
12.08
?
?
?
Model 2
3.11
?
?
?
?
?
?
0.89
Model 3

• Experimental NMR data (Jackowski et al, 1995)
  association due to the strong interaction between
  CN groups

s,e
Proposed model in this work
Lennard-Jones spheres
Chain formation
Association
Polar
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Methodology (3 steps)

• Optimize molecular parameters of light nitriles

Vapor liquid equilibrium

• Linear correlation of SAFT molecular parameters
  as a function of molecular weight MW within the
  homologous serie
• Transferability by extrapolation to heavier
  nitriles valeronitrile and hexanontirile

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Step1 ? parameter fitting on Light nitriles
CH3CN
C2H5CN
C3H7CN
DIPPR data base
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Step 2 ? Linear correlations
molecular parameters function (Mw)
Step 3 ? Transferability
C4H9CN
C5H11CN
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Results
Solid lines soft-SAFT predictionsSymbols DIPPR
data base
Pure compounds VLE
AAD(?liq) 0.7
AAD(Psat) 2
Light nitriles (aceto, propio and butyro)
Heavy nitriles (valeor and hexano)
Temperature dependence of the mole fraction of
monomers
Figure 2 Molar fraction of acetonitrile monomers
predicted by soft-SAFT approach
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Isomer distinction
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Binary mixture calculations (ACN CO2)
(without any binary parameters)
Exp Data R. Wiebe, V. L. Gaddy, J. Am. Chem.Soc.
62 (1940) 815-817.
(?) 298K (?) 308K (?) 343K () 373K
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Conclusions

• A valid approach to model heavy molecules,
• Mimicking the strong polar behavior of nitriles
  by a single association,
• Possibility to distinguish isomers,

Perspectives

• Improve SAFT predictions capacity in mixtures
• by fitting the binary interaction parameters
• Improve pure nitriles modeling by taking into
  account the dipolar contribution
• Test cross-association schemes (water-acetonitrile
  )