OLI Mixed Solvent Electrolyte With Aspen Plus

8/2/2019 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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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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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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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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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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OLI added user blocks to Aspen PLUS

EFRACH

EFLASH

Available during Aspen PLUS Installation Must be enabled at run-time


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EFLASH

Organic (3)

Solid (4)

EFLASH

(Four outlet material streams)

Feeds

Heat

Heat

Vapor (1)

Aqueous (2)

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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

THINK


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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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SIMULATION

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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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SIMULATION

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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

THINK

0.09


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SIMULATION

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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

THINK

Acid base and phase equilibria:


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SIMULATION

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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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SIMULATION

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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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SIMULATION

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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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SIMULATION

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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

THINKSIMULATION


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SIMULATION

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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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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

THINKSIMULATION


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SIMULATION

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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

THINKSIMULATION


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SIMULATION

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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

THINKSIMULATION


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SIMULATION

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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

THINKSIMULATION


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SIMULATION

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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

THINKSIMULATION


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SIMULATION

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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

40


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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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SIMULATION

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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

THINKSIMULATION


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SIMULATION

50

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

THINKSIMULATION


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SIMULATION

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

Aspen OLI Chemistry Generator


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Aspen Plus 2006


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Aspen Plus OLI with EFRACH


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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

OLI Mixed Solvent Electrolyte With Aspen Plus

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Transcript of OLI Mixed Solvent Electrolyte With Aspen Plus