OLI Mixed Solvent Electrolyte With Aspen Plus
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Transcript of OLI Mixed Solvent Electrolyte With Aspen Plus
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Opening new doors withChemistry
THINK SIMULATION!
OLIs Mixed SolventElectrolyte with Aspen
PLUS
OLI Systems, Inc.
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THINKSIMULATION
2
Agenda
OLIs basic history
OLIs history with Aspen Technologies
Advantages/disadvantages of Aspen PLUS OLI
Architecture of the Aspen PLUS OLI interfaceIntroduction to MSE
Overview of Aspen PLUS OLI (with MSE)
Demonstration
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OLIs basic history
Company founded in 1971 by Marshall RafalFirst electrolyte simulator (ECES) 1973
Developed for OLIN Chemical
First commercial sale of ECES 1975 Dupont
The Environmental Simulation Program developed in1991
Linkage to simulators in 1995Windows program (Analyzers) became commercial in
2000Mixed-Solvent Electrolytes commercially available 2005Windows based process simulator (OLI Pro) to be
available in 2007
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OLIs history with Aspen Technologies
That Other chemical company that has a D in its name. 25 years of process simulation experience with electrolyte
1995 switched to Aspen PLUS as their process simulator
Wanted OLIs electrolytes in Aspen PLUS
1996 first Aspen PLUS OLI interface created
No model manager, version 8.2
1997 Aspen PLUS OLI linked to model manager
Version 9.0
2006 Aspen PLUS OLI updated for Aspen ONE 2006
Included change in concentration basis
Included MSE
2007 Aspen PLUS OLI updated for Aspen ONE 2006.5
General release of MSE for all Aspen PLUS OLI clients
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Advantages of Aspen PLUS OLI
User Interface
Learn one flow sheeting system
Multiple Property Options in same flowsheet
Different Non-electrolyte capability Sizing
Costing
Two Software Venders
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Disadvantages of Aspen PLUS OLI
No Corrosion
No advanced OLI technology
No Ion-exchange
No Surface Complexation No Bio-kinetics
No Scaling Tendencies
Two Software Venders
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Architecture of the Aspen PLUS OLI interface
OLI ChemistryGenerator
OLIDatabases
OLI/A+XREF
OLI NumericalSolver/Engine
.BKP
.ASP/.INP
.DBS
A+Model Manager
A+Simulation Engine
Electrolyte Flash or Property
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Architecture of the Aspen PLUS OLI interface
Aspen Unit Operations available with the OLI Property Set MIXERS FSPLIT SEP SEP2 HEATER
FLASH2 FLASH3 HEATX MHEATX RADFRAC RSTOIC RYIELD RCSTR RPLUG PUMP COMPR
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Architecture of the Aspen PLUS OLI interface
Thermodynamic Properties from OLI used by AspenPLUS (OLI propset)
PHIVMX DLMX KL DGL
PHILMX SIGLMX DV PHILPC
HVMX PHIV DL DSV
HLMX PHIL SIGL KVPCGVMX HV HSMX
GLMX HL PHIL
SVMX GV VV
SLMX GL MUVMXL
VVMX SV MUVLP
VLMX SL KVMXLP
MUVMX VV KVLP
MULMX VL DHV
KVMX MUV DHL
KLMX MUL DHLPC
DVMX KV DGV
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Architecture of the Aspen PLUS OLI interface
The OLI-Aspen Plus Cross Reference File (partial listing) Full listing is available on your computer:
C:\Program Files\OLI Systems\Alliance Suites\Aspen OLI2006\Databanks\OLIAspenPlusCompXRef.lis
ESP-NAME DB 8-CHAR ASP-ALIAS ASP-NAME
================ = ====== ========= =====================================
AR P AR AR ARGON 7440-37-1 Ar
ABIETICAC P ABIETICA C20H30O2 ABIETIC-ACID 514-10-3 C20H30O2
ACENAPHTHN P ACENAPHT C12H10-D0 ACENAPHTHENE 83-32-9 C12H10
ACENITRILE P ACENTL C2H3N ACETONITRILE 75-05-8 C2H3N
ACET2 P ACET2 ........... C4H8O4
ACETACID P ACETACID C2H4O2-1 ACETIC-ACID 64-19-7 C2H4O2
ACETAL P ACETAL C6H14O2-D1 ACETAL 105-57-7 C6H14O2
ACETALDEHD P ACEALD C2H4O-1 ACETALDEHYDE 75-07-0 C2H4O
ACETAMIDEPPT P ACETAM-S 60-35-5 C2H5NO
ACETAMIDE P ACETAMD C2H5NO-D1 ACETAMIDE 60-35-5 C2H5NO
ACETANHYD P ACETAHYD C4H6O3 ACETIC-ANHYDRIDE 108-24-7 C4H6O3
ACETANILID P ACEANILD C8H9NO ACETANILIDE
ACETATEION P ACET- CH3COO- CH3COO- ........... C2H3O2-1
ACETBR P ACETBR 506-96-7 C2H3BrO
ACETCL P ACETCL C2H3CLO ACETYL-CHLORIDE 75-36-5 C2H3ClO
ACETONE P ACETONE C3H6O-1 ACETONE 67-64-1 C3H6O
ACETPHENON P ACEPHEN C8H8O METHYL-PHENYL-KETONE 98-86-2 C8H8O
ACETYLENE P ACETYLN C2H2 ACETYLENE 74-86-2 C2H2
ACRIDINE P ACRIDINE 260-94-6 C13H9N
ACROLEIN2 P ACROLIN2 C3H4O ACROLEIN 107-02-8 C3H4O
ACRYLAMIDEPPT P ACRAMI-S 79-06-1 C3H5NO
ACRYLAMIDE P ACRYAMID C3H5NO-D1 ACRYLAMIDE 79-06-1 C3H5NO
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Architecture of the Aspen PLUS OLI interface
OLI added user blocks to Aspen PLUS
EFRACH
EFLASH
Available during Aspen PLUS Installation Must be enabled at run-time
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Architecture of the Aspen PLUS OLI interface
EFLASH
Organic (3)
Solid (4)
EFLASH
(Four outlet material streams)
Feeds
Heat
Heat
Vapor (1)
Aqueous (2)
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Architecture of the Aspen PLUS OLI interface
EFRACH
DECANTER
Vapor or Liquid
Organic
Heat Heat1
2
3
N
Feeds Products
Heat Heat
Heat Heat
Bottoms
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Introduction to MSE
Why develop a new thermodynamic model? The Bromley-Zemaitis model (a/k/a Aqueous Model-AE)
had limitations Water was required as a solvent Mole fraction of all solutes was limited to approximately 0.35
Limited in temperature (Approximately 300o
C) LLE predictions exclude critical solution points (limited to
strongly dissimilar phases)
A Mixed Solvent Electrolyte model (MSE) has advantages Water is not required Mole fraction of solute can approach and be equal to 1.0 Temperature can be up to 0.9 Tc of solution Full range of LLE calculations including electrolytes in both
phases
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Introduction to MSEAdvantages and disadvantages between AE and MSE
MSE model Model advantages:
No composition limitations
Reliable predictions formulticomponent concentratedsolutions
Full range of LLE calculationsincluding electrolytes in bothphases
Methodological advantages Multi-property regressions
Consistent use ofthermochemical properties
(no shortcuts like KFITs) Rigorous quality assurance
Disadvantages:A smaller in-place databank
but it is continuouslyextended
AE Model Advantages:
Larger existing databank
The only model available forrates of corrosion
Disadvantages:
Limitations with respect tocomposition (30 m withrespect to electrolytes,x=0.3 with respect tononelectrolytes
LLE predictions excludecritical solution points
(limited to strongly dissimilarphases)
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Introduction to MSE
Overview of species coverage between AE and MSE models.
Components
Solute Mole Fraction
0
2000
4000
6000
8000
0.0 1.0
AE
MSEBuild 7.0.54
Growing with each build
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Structure of the thermodynamic model
Definition of species that may exist in the liquid,vapor, and solid phases
Excess Gibbs energy model for solution
nonidealityCalculation of standard-state properties
Helgeson-Kirkham-Flowers equation for ionic andneutral aqueous species
Standard thermochemistry for solid and gasspecies
Algorithm for solving phase and chemical
equilibria
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THINKSIMULATIONOutline of the model:
Solution nonideality
RT
G
RT
G
RT
G
RT
Gex
IIex
LCex
LRex
LR Debye-Hckel theory for long-range electrostaticinteractions
LC Local composition model (UNIQUAC) for neutralmolecule interactions
II Ionic interaction term for specific ion-ion and ion-
molecule interactions
Excess Gibbs energy
i j
xijji
i
i
exII IBxxn
RT
G
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Outline of the model:Chemical equilibrium calculations
For a chemical reaction:
At equilibrium
with
dDcCbBaA
bB
aA
dD
cC
bB
aA
dD
cC
0
xx
xxln
RT
G
i
0
ii
0vG
Standard-statechemicalpotential of i
Infinite-dilution properties
Thermochemical databases for aqueous systems
Helgeson-Kirkham-Flowers model for T and P dependence
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Outline of the model:Constraints
Activity coefficients are converted to unsymmetrical normalization towork with infinite-dilution properties
Constraining the parameters of the GE model to reproduce the Gibbs
energy of transfer
RO2Hx
i
,,S,O2H,x
i
Activity coefficient of ion iin solvents R andS in unsymmetrical, mole-fraction basedconvention
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Mixed-solvent electrolyte model:Applicability
Simultaneous representation of multiple properties
Vapor-liquid equilibria
Osmotic coefficient/water activity and activity coefficients
Solid-liquid equilibria Properties of electrolytes at infinite dilution, such as acid-
base dissociation and complexation constants
Properties that reflect ionic equilibria, e.g., solution pH andspecies distribution
Enthalpy (Hdil or Hmix) Heat capacity
Density
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Validity range
Concentrations from infinite dilution tosaturation or fused salt or pure solute limit
Temperatures up to 0.9Tc of mixtures
This translates into 300 C for H2O dominatedsystems
For concentrated inorganic systems, substantiallyhigher temperatures can be reached
Solvents: water, various organics or solventmixtures
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Representative applications of the MSEthermodynamic model
Strong acid systems Simultaneous representation of phase equilibria
and speciation
Salt systems
Prediction of properties of multicomponentsystems
Organic salt water systems
Salt effects on VLE, LLE and SLE
Acid-base equilibria
pH of mixed-solvent systems
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VLE for H2SO4 + SO3 + H2O
1.0E-08
1.0E-07
1.0E-06
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
1.0E+01
1.0E+02
1.0E+03
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
x SO3
P,atm
0C
200C
100C
50C
25C
500C 400C300C
Phaseequilibria areaccuratelyreproduced
from 0 C to500 C
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Speciation for H2SO4 + SO3 + H2O:
0
10
20
30
40
50
60
70
80
90
100
0.0 0.2 0.4 0.6 0.8 1.0
(x SO3)1/2
molepercen
t1957HR
1959YMS
1994CRP&1995CB
2000WYCHSO4
-2
H2SO40
O30
x (SO3)=0.5
HSO4-
Predictedspeciation inconcentratedsolutions agrees
withspectroscopicdata
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Partial pressures in the H2SO4 + SO3 + H2O system
Partial pressuresof H2SO4, SO3and H2O arealso correctlyreproduced
1.E-15
1.E-14
1.E-13
1.E-12
1.E-11
1.E-10
1.E-09
1.E-08
1.E-07
50 55 60 65 70 75 80
H2SO4, Wt%
H2SO4,atm
25C
30C35C
25C
30C35CPerry 30C
Partial pressures of H2SO4
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Salt systems:Na K Mg Ca Cl NO3
Step 1: Binary systems solubility of solids
The model is valid for
systems ranging fromdilute solutions to thefused salt limit
0
10
20
30
40
50
60
70
80
90
100
-20 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320
Temperature, C
NaNO3,weight%
NaNO3
H2O(s)
Cal, NaNO3
Cal, H2O(s)
0
10
20
30
40
50
60
70
80
90
100
-40 -20 0 20 40 60 80 100 120 140 160 180 200
Temperature, C
Mg(NO3)2,
weight%
H2O(s)Mg(NO3)2.9H2O
Mg(NO3)2.6H2OMg(NO3)2.2H2OMg(NO3)2Cal, H2O(s)Cal, Mg(NO3)2.9H2O
Cal, Mg(NO3)2.6H2OCal, Mg(NO3)2.2H2OCal, Mg(NO3)2
NaNO3 H2O
Mg(NO3)2 H2O
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Modeling salt systems:Na K Mg Ca Cl NO3
Step 1: Binarysystems solubilityof solids
Water activitydecreases with saltconcentration untilthe solution becomessaturated with asolid phase
00.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65
Total apparent salt, mole fraction
Wateractivity
1 - NaCl
6 - LiCl
11 - CaCl2
3 - Mg(NO3)2
12 - Ca(NO3)2Ca(NO3)2
LiCl
Mg(NO3)2
CaCl2.2H2O
NaCl
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Step 2: Ternary systems
Solubility in the systemNaNO3 KNO3 H2Oat various
temperatures
Activity of water over
saturated NaNO3KNO3 solutions at 90 C:Strong depression atthe eutectic point
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
NaNO3, mole fraction (water free)
WaterActivity
KNO3
NaNO3+KNO3
NaNO3
0
10
20
30
40
50
60
70
80
90
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
KNO3, weight %
NaNO3,
weight%
0C 10C
20C 25C
30C 40C
50C 75C
100C 125C
150C 175C
200C
NaNO3(s)
KNO3(s)
NaNO3.KNO3(s)
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Step 3: Verification of predictions for multicomponent systems
Deliquescence datasimultaneouslyreflect solidsolubilities and
water activities
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Total apparent salt, mole fraction
Wateractivity
10 - NaNO3+KNO3
4 - NaNO3+KNO3+Ca(NO3)2+Mg(NO3)2
NaNO3
NaNO3+NaNO3.KNO3NaNO3
NaNO3+Ca(NO3)2
Mixed nitrate systems at 140 C
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Electrolyte + organic systems:Examples
Effect of electrolytes on phase equilibria in nonelectrolyte watersystems
Salting out(in) effects
Liquid-liquid equilibria in aqueous systems containing water-soluble polymers and salts
Liquid immiscibility is induced by the presence of a salt
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LLE results salt effect
0.00000
0.00005
0.00010
0.00015
0.00020
0.000250.00030
0.00035
0.00040
0.00045
0 100 200 300 400
g salt/kg H2O
Solubilityofbenzene(x)
inaqueoussaltso
lutions
NaCl
25 C
(NH4)2SO4
Solubility ofbenzene inaqueous(NH4)2SO4 andNaCl solutionsat 25C
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VLE: salting-out effect
60
70
80
90
100
110
0.0 0.2 0.4 0.6 0.8 1.0
x, y (methanol)
t/C
P=1 bar
---- Salt-free
Saturated NaCl0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0.0 0.2 0.4 0.6 0.8 1.0
x-methanol
molNaCl/kgsolvent
Solubility
25C
Simultaneous representation ofthermodynamic properties:NaCl-methanol-water
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LLE in aqueous polymersalt systems
PEG (MW=1000) + NaH2PO4 + H2O at25 C
PEG (MW=4000) + (NH4)2SO4 + H2Oat 25 C
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.000 0.005 0.010 0.015 0.020 0.025
x - PEG1000
X
-NaH2PO4
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.0000 0.0005 0.0010 0.0015 0.0020 0.0025
x - PEG 4000
x-(N
H4)2SO4
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Acid base and phase equilibria:
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Acid-base and phase equilibria:Treatment of pH in mixed solvents
Classical treatment
pH scale can be defined separately for each, pure or mixed,solvent
pH scales can be converted using the Gibbs energy of transferof the proton
Such a conversion is inconvenient (availability of Gibbs energy of
transfer, extrathermodynamic assumptions) However, it opens the possibility of a uniform calculation of pH
using an activity coefficient model as long as the modelaccurately reproduces activity coefficients of individual speciesand the Gibbs energy of transfer
10ln
,
RT
GpHpH
Awt
HwA
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Treatment of pH in mixed-solvents
Uniform treatment of apparent pH
Starting point: Aqueous definition of pH
Conversion to mole fraction scale and solvated proton basis
Activity coefficients are obtained directly from the model Values can be compared with measurements using glass
electrode
Does not require the presence of water equivalentexpressions can be obtained for other solvents
0
loglogm
mapH HH
H
OHOH
OHOHOH
xM
xpH22
2
33
loglog1000
logloglog
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Speciation Effects
Acetic Acid in EtOH-H2O Acetic Acid in MeOH-H2O
Apparent (Mixed Solvent-Based) Ionization Constants
4
6
8
10
12
0.0 0.2 0.4 0.6 0.8 1.0
x-Methanol
pKa
cal
exp
4
6
8
10
12
0.0 0.2 0.4 0.6 0.8 1.0
x-Ethanol
pKa
cal
Sen et al.
Woolley
Equilibrium constantobtained from aqueoussolutions
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Parameters in the MSE Databank (1)
Binary and principal ternary systems composed of the following primary ions
and their hydrolyzed forms Cations: Na+, K+, Mg2+, Ca2+, Al3+, NH4
+
Anions: Cl-, F-, NO3
-, CO3
2-, SO4
2-, PO4
3-, OH-
Aqueous acids, associated acid oxides and acid-dominated mixtures
H2SO4 SO3
HNO3 N2O5
H3PO4 H4P2O7 H5P3O10 P2O5
H3PO2
H3PO3
HF
HCl
HBr
HI
H3BO3
CH3SO3H
NH2SO3H
HFSO3 HF H2SO4HI I2 H2SO4
HNO3 H2SO4 SO3
H3PO4 with calcium phosphates
H Na Cl NO3
H Na Cl F
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Parameters in the MSE Databank (2)
Inorganic gases in aqueous systems CO2 + NH3
H2S + NH3
SO2 + H2SO4
N2 O2
H2 Transition metal aqueous systems
Fe(III) H O SO4, NO3
Fe(II) H O SO4, Br
Sn(II, IV) H O CH3SO3
Zn(II) H SO4, NO3, Cl
Zn(II) Li - Cl
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Parameters in the MSE Databank (3)
Transition metal aqueous systems - continued
Cu(II) H SO4, NO3
Ni(II) H SO4, NO3, Cl
Mo(VI, IV) H O Cl, SO4, NO3
W(VI) H - O - Na Cl, NO3
Most elements from the periodic table in their elemental form
Base ions and hydrolyzed forms for the majority of elements from theperiodic table
Hydrogen peroxide chemistry
H2O2 H2O H - Na OH SO4 NO3
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Parameters in the MSE Databank (4)
Miscellaneous inorganic systems in water NH2OH
NH4HS + H2S + NH3
LiCl KCl
LiCl CaCl2
Na2S2O3 LiOH H3BO3 H2O
Organic acids in water, methanol and ethanol and their Na salts Formic
Acetic (also K salt)
Citric
Adipic
Nicotinic
Terephthalic
Isophthalic
Trimellitic
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Parameters in the MSE Databank (5)
Organic components and their mixtures with water Hydrocarbons
Straight chain alkanes: C1 through C30
Isomeric alkanes: isobutane, isopentane, neopentane
Alkenes: ethene, propene, 1-butene, 2-butene, 2-methylpropene
Aromatics: benzene, toluene, o-, m-, p-xylenes, ethylbenzene, cumene,naphthalene, anthracene, phenantrene
Alcohols
Methanol, ethanol, 1-propanol, 2-propanol, cyclohexanol
Glycols
Mono, di- and triethylene glycols, propylene glycol, polyethylene glycols
Phenols
Phenol, catechol
Ketones
Acetone, methylisobutyl ketone
Aldehydes
Butylaldehyde
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Parameters in the MSE Databank (6)
Organic solvents and their mixtures with water
Carbonates
Diethylcarbonate, propylene carbonate
Amines
Tri-N-octylamine, triethylamine, methyldiethanolamine Nitriles
Acetonitrile
Amides
Dimethylacetamide, dimethylformamide
Halogen derivatives
Chloroform
Aminoacids
Methionine
Heterocyclic components
N-methylpyrrolidone, 2,6-dimethylmorpholine
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SIMULATION
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Parameters in the MSE Databank (7)
Polyelectrolytes
Polyacrylic acid
Complexes with Cu, Zn, Ca
Mixed-solvent organic systems HAc tri-N-octylamine toluene H2O
HAc tri-N-octylamine methylisobutylketone H2O
HAc MeOH EtOH H2O
HAc MeOH CO2 H2O
Dimethylformamide HFo H2O
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SIMULATION
45
Parameters in the MSE Databank (8)
Mixed-solvent inorganic/organic system
Hydrocarbon water salt (Na, K, Ca, Mg, NH4, H, Cl, SO4, NO3) systems
Mono, di- and triethylene glycols - H Na Ca Cl CO3 HCO3 - CO2H2S H2O
Phenol - acetone - SO2 - HFo - HCl H2O
Benzene NaCl and (NH4)2SO4 - H2O
Cyclohexane NaCl - H2O
n-Butylaldehyde NaCl - H2O
LiPF6 diethylcarbonate propylene carbonate
Ethanol LiCl - H2O
Methanol - H2O + NaCl, HCl
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SIMULATION
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Predictive character of the model
Levels of predictivity Prediction of the properties of multicomponent
systems based on parameters determined fromsimpler (especially binary) subsystems
Extensively validated for salts and organics
Prediction of certain properties based onparameters determined from other properties
Extensively validated (e.g., speciation or caloricproperty predictions)
THINKSIMULATION
Wh t d it f th
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SIMULATION
47
What does it mean for themodel to be predictive?
Parameters were determinedusing only binary salt + H2Odata
SLE for the ternary system
was predicted without makingany ternary fits
MSE is clearly superior evenin the applicability range ofthe aqueous model
This can work only when the
ternary system does notintroduce a chemistry change(e.g., double salts)
0
5
10
15
20
25
30
35
40
45
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
NaH2PO4, weight %
KH2PO
4,weight%
0C 5C
10C 15C
20C 25C
30C 35C
40C 45C
50C 55C
60C 65C
70C 75C
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
NaH2PO4, weight %
KH2PO
4,weight%
0C 5C
10C 15C
20C 25C
30C 35C
40C 45C
50C 55C
60C 65C
70C 75C
MSE (no ternary fits)
Aqueous model(no ternary fits)
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Predictive character of the model
Levels of predictivity - continued Prediction of properties without any knowledge of
properties of binary systems Standard-state properties: Correlations to predict the
parameters of the HKF equation Ensures predictivity for dilute solutions
Properties of solids: Correlations based on family analysis Parameters for nonelectrolyte subsystems
Group contributions: UNIFAC estimation
Quantum chemistry + solvation: CosmoThermestimation
Also has limited applicability to electrolytes as longas dissociation/chemical equilibria can beindependently calculated
THINKSIMULATION
Transport properties in the OLI
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SIMULATION
49
Transport properties in the OLIsoftware
Available transport properties: Diffusivity
Viscosity
Electrical conductivity
OLI was the first to develop transport propertymodels for concentrated, multicomponentaqueous solutions
More recently, the models have been extendedto mixed-solvent systems
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Modeling diffusivity in electrolyte systems
Limiting diffusivity
Long-range electrostatic interactions
Relaxation effect:
Short-range interactions
Hard-sphere contribution:
Combination of the two effects:
i
i
k
k
1
0
i
HS
i
D
D
0
i
HS
i
i
i0
iiD
D
k
k1DD
Enskog theory:Significant forconcentrated
solutions
MSA theory:Important inrelatively dilutesolutions
0
iD
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51
Calculation of diffusivity in MSE solutions
0.0
0.5
1.0
1.5
2.0
2.5
0.0 0.2 0.4 0.6 0.8 1.0
x'methanol
Dmethanol*109,m
2/s
xLiCl=0.005
xLiCl=0.01
xLiCl=0.02
xLiCl=0
Dmethanol in methanol-water-LiClsystem at 25C at various LiClconcentrations
xNaCl=0.005
0.0
0.5
1.0
1.5
2.0
2.5
0.0 0.2 0.4 0.6 0.8 1.0
x'methanol
Dmethanol*10
9,m
2/s
xNaCl=0.01
xNaCl=0.02
salt-free
Dmethanol in methanol-water-NaCl systemat 25C at various NaCl concentrations
THINKSIMULATION
Computation of diffusion coefficients:
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SIMULATION
52
Computation of diffusion coefficients:Species in NiCl2 solutions
For complexed species,measured diffusioncoefficients areweighted averages of
diffusion coefficients ofindividual complexes:
0.0
0.5
1.0
1.5
2.0
2.5
0 1 2 3 4 5
m NiCl2
D
109 (m2s
-1) Ni species - Stokes et
al. (1979)
Ni species - Salmon et
al. (1987)
Cl species - Stokes et
al. (1979)
D iDc
c X Q X
Q X
XiT i i
i i
T
THINKSIMULATION
M d li l i l d i i
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Modeling electrical conductivity
X
X
v
v
i
eli
ii
11 0
0
Limitingconductivity
Dependence of ionelectrolyte concentration
relaxationeffect
electrophoreticcorrection
The model includes the computation of1. Limiting conductivities of ions as a function of temperature and
solvent composition
2. Dependence of electrical conductivity on electrolyte concentration(the mean spherical approximation theory)
THINKSIMULATION
Electrical conductivity model:
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Electrical conductivity model:H2O H2SO4 SO3
0.0001
0.001
0.01
0.1
1
10
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
x-SO3
s
pecificconductivity
(S.cm-1)
THINKSIMULATION
Electrolytes in mixed solvents:
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Electrolytes in mixed solvents:MgCl2 + ethanol + water
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
0.0001 0.001 0.01 0.1 1 10
mol MgCl2/kg solvent
80%
60%
40%
100% EtOH (------)
20%
0% EtOH
specificconductivity,Scm-1
THINKSIMULATION
Vi it d l
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Viscosity model
sssLR
mix
0viscosity of the
MSE solution
viscosity of thesolvent mixture
long-rangeelectrostaticcontribution
individual ioncontributions
interactionsbetween species
Dependence ofon electrolyte
concentration
In MSE solutions, -0 is found to show regularities with respect toboth electrolyte concentrations and solvent composition, and is themost convenient quantity to define the model
THINKSIMULATION
Vi i i f l i 0
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Viscosities of solvent mixtures, 0mix
0.0
0.5
1.0
1.5
2.0
0.0 0.2 0.4 0.6 0.8 1.0
x-acetone
Viscosity
(cP)
20C
25C
50C
acetone + water
Mixing rule
ijjiij k12
1 00
l
ll
iii
vx
vxY *
*
illil
lii gvxvv0410*
Modified volume fractions
i j
ijjimix YY 0
THINKSIMULATION
Eff t f l t l t t ti
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Effects of electrolyte concentration
LR From the analyticalmodel by Onsager and Fuoss
(1932)
s defined for multiplesolvents
s-s defined for solventcombinations
00
21
42
n
n
n
N
ii
iiLRscr
z
T
Ia
i
j i
jiijjs Bcx ,0
j l i kik,jlkijllj
ssIDffxx
20''
calculated using and i0 inthe mixed solvent
j = solvent; i = ion or neutral
j,l = solvent; i,k = ion or neutral
Bi,j evaluatedbased onviscosities ofelectrolyte inpure solvent
Dik,jl(I,T) adjusted based onexperimental data
THINKSIMULATION
Vi it f H O H SO SO
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Viscosity of H2O H2SO4 SO3
0.1
1
10
100
1000
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
x-SO3
,cP
THINKSIMULATION
Viscosity of salt organic - water systems:
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Viscosity of salt organic water systems:LiNO3-ethanol-H2O
Viscosities of the ternary solutionsof LiNO3-ethanol-H2O as a functionof the molarity of LiNO3 at 25C and
at various ethanol weight percent.
0
2
4
6
8
10
12
14
16
0 5 10 15
c-LiNO3, mol/L
,cP 100 w t%
70 w t%
30 w t%
EtOH=0 w t%
THINKSIMULATION
Sublimation / salt point10
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Sublimation / salt pointcalculations
Solid-gas equilibriumcomputations for pureNH4Cl and NH4HS
0.001
0.01
0.1
1
150 200 250 300 350
t/C
sublima
tionpressur
Stull-1947
OLI
0.001
0.01
0.1
1
10
-60 -30 0 30 60 90
t/C
sublimation
pressure,at
Stull-1947
P, atm (cal)
NH4Cl
NH4HS
THINKSIMULATION
HI I2 H2O
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HI - I2 - H2O
H2O/HI/I2 full range of concentration, T
The heart of the IS Process
Challenge: presence of more than one LLEregion together with regions of VLE and SLE
THINKSIMULATION
MSE Challenge
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MSE Challenge
For systems within the AQ model limits, yes
Binary systems give reasonable resultswhen water remains the dominant solvent
When the 2nd solvent, or different solventpredominates
All major components must be studied with
respect to all solvents e.g., for MEG systems, MEG Ca and MEG Na
must be regressed, along with
Will MSE work out-of-the-box?
THINKSIMULATION
Overview of Aspen PLUS OLI
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p(with MSE)
Using the Aspen PLUS OLI Chemistry Generator
THINKSIMULATION
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
THINKSIMULATION
Aspen OLI Chemistry Generator
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Aspen OLI Chemistry Generator
THINKSIMULATION
Aspen OLI Chemistry Wizard
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Aspen OLI Chemistry Wizard
THINKSIMULATION
Aspen OLI Chemistry Wizard
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Aspen OLI Chemistry Wizard
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Aspen OLI Chemistry Wizard
THINKSIMULATION
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Aspen OLI Chemistry Wizard
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Aspen OLI Chemistry Wizard
THINKSIMULATION
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p y
THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
Aspen Plus 2006
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen Plus OLI with EFRACH
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THINKSIMULATION
Aspen OLI
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More examples?Live cases?
Questions?
THINKSIMULATION
Conclusion
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Using MSE in Aspen Plus is very similar to usingany property set.
The OLI property sets can be used withstandard Aspen PLUS unit operations or with OLI
unit operations