OLI's Mixed Solvent Electrolyte with Aspen PLUS
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OLI Systems, Inc. OLI’s Mixed Solvent Electrolyte with Aspen PLUS THINK SIMULATION! Opening new doors with Chemistry Agenda THINK SIMULATION OLI’s basic history OLI’s history with Aspen Technologies Advantages/disadvantages of Aspen PLUS OLI Architecture of the Aspen PLUS OLI interface Introduction to MSE Overview of Aspen PLUS OLI (with MSE) Demonstration 2 OLI’s basic history THINK SIMULATION Company founded in 1971 by Marshall Rafal First electrolyte simulator (ECES) 1973 ■ Developed for OLIN Chemical First commercial sale of ECES 1975 ■ Dupont The Environmental Simulation Program developed in 1991 Linkage to simulators in 1995 Windows program (Analyzers) became commercial in 2000 Mixed-Solvent Electrolytes commercially available 2005 Windows based process simulator (OLI Pro) to be available in 2007 3 OLI’s history with Aspen Technologies THINK SIMULATION 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 OLI’s 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 4 Advantages of Aspen PLUS OLI THINK SIMULATION User Interface Learn one flow sheeting system Multiple Property Options in same flowsheet Different Non-electrolyte capability Sizing Costing Two Software Venders 5 Disadvantages of Aspen PLUS OLI THINK SIMULATION No Corrosion No advanced OLI technology ■ No Ion-exchange ■ No Surface Complexation ■ No Bio-kinetics No Scaling Tendencies Two Software Venders 6 Architecture of the Aspen PLUS OLI interface OLI Chemistry Generator OLI Databases .BKP THINK SIMULATION A+ Model Manager .ASP/.INP .DBS OLI/A+ XREF OLI Numerical Solver/Engine A+ Simulation Engine Electrolyte Flash or Property 7 Architecture of the Aspen PLUS OLI interface THINK SIMULATION 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 8 Architecture of the Aspen PLUS OLI interface THINK SIMULATION Thermodynamic Properties from OLI used by Aspen PLUS (OLI propset) PHIVMX PHILMX HVMX HLMX GVMX GLMX SVMX SLMX VVMX VLMX MUVMX MULMX KVMX KLMX DVMX DLMX SIGLMX PHIV PHIL HV HL GV GL SV SL VV VL MUV MUL KV KL DV DL SIGL HSMX PHIL VV MUVMXL MUVLP KVMXLP KVLP DHV DHL DHLPC DGV DGL PHILPC DSV KVPC 9 Architecture of the Aspen PLUS OLI interface THINK SIMULATION The OLI-Aspen Plus Cross Reference File (partial listing) ■ Full listing is available on your computer: ◊ C:\Program Files\OLI Systems\Alliance Suites\Aspen OLI 2006\Databanks\OLIAspenPlusCompXRef.lis ESP-NAME DB ================ = AR P ABIETICAC P ACENAPHTHN P ACENITRILE P ACET2 P ACETACID P ACETAL P ACETALDEHD P ACETAMIDEPPT P ACETAMIDE P ACETANHYD P ACETANILID P ACETATEION P ACETBR P ACETCL P ACETONE P ACETPHENON P ACETYLENE P ACRIDINE P ACROLEIN2 P ACRYLAMIDEPPT P ACRYLAMIDE P 8-CHAR ====== AR ABIETICA ACENAPHT ACENTL ACET2 ACETACID ACETAL ACEALD ACETAM-S ACETAMD ACETAHYD ACEANILD ACETACETBR ACETCL ACETONE ACEPHEN ACETYLN ACRIDINE ACROLIN2 ACRAMI-S ACRYAMID ASP-ALIAS ========= AR C20H30O2 C12H10-D0 C2H3N ASP-NAME ===================================== ARGON ABIETIC-ACID ACENAPHTHENE ACETONITRILE C2H4O2-1 C6H14O2-D1 C2H4O-1 ACETIC-ACID ACETAL ACETALDEHYDE C2H5NO-D1 C4H6O3 C8H9NO CH3COO- ACETAMIDE ACETIC-ANHYDRIDE ACETANILIDE CH3COO- C2H3CLO C3H6O-1 C8H8O C2H2 ACETYL-CHLORIDE ACETONE METHYL-PHENYL-KETONE ACETYLENE C3H4O ACROLEIN C3H5NO-D1 ACRYLAMIDE 7440-37-1 514-10-3 83-32-9 75-05-8 ........... 64-19-7 105-57-7 75-07-0 60-35-5 60-35-5 108-24-7 Ar C20H30O2 C12H10 C2H3N C4H8O4 C2H4O2 C6H14O2 C2H4O C2H5NO C2H5NO C4H6O3 ........... 506-96-7 75-36-5 67-64-1 98-86-2 74-86-2 260-94-6 107-02-8 79-06-1 79-06-1 C2H3O2-1 C2H3BrO C2H3ClO C3H6O C8H8O C2H2 C13H9N C3H4O C3H5NO C3H5NO 10 Architecture of the Aspen PLUS OLI interface THINK SIMULATION OLI added user blocks to Aspen PLUS ■ EFRACH ■ EFLASH Available during Aspen PLUS Installation ■ Must be enabled at run-time 11 THINK SIMULATION Architecture of the Aspen PLUS OLI interface EFLASH Vapor (1) Aqueous (2) Organic (3) Solid (4) Feeds EFLASH (Four outlet material streams) Heat Heat 12 Architecture of the Aspen PLUS OLI interface THINK SIMULATION Vapor or Liquid EFRACH Heat 1 Heat DECANTER Feeds 2 Organic Products 3 Heat Heat Heat N Heat 13 Bottoms Introduction to MSE THINK SIMULATION 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 300 oC) ◊ 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 14 THINK SIMULATION Introduction to MSE Advantages and disadvantages between AE and MSE AE Model ■ Advantages: ◊ Larger existing databank ◊ The only model available for rates of corrosion ■ Disadvantages: ◊ Limitations with respect to composition (30 m with respect to electrolytes, x=0.3 with respect to nonelectrolytes ◊ LLE predictions exclude critical solution points (limited to strongly dissimilar phases) MSE model ■ Model advantages: ◊ No composition limitations ◊ Reliable predictions for multicomponent concentrated solutions ◊ Full range of LLE calculations including electrolytes in both phases ■ Methodological advantages ◊ Multi-property regressions ◊ Consistent use of thermochemical properties (no shortcuts like KFITs) ◊ Rigorous quality assurance ■ Disadvantages: ◊ A smaller in-place databank but it is continuously extended 15 Introduction to MSE THINK SIMULATION Overview of species coverage between AE and MSE models. 8000 6000 Components Growing with each build 4000 AE 2000 Build 7.0.54 MSE 0 0.0 1.0 Solute Mole Fraction 16 THINK SIMULATION Structure of the thermodynamic model Definition of species that may exist in the liquid, vapor, and solid phases Excess Gibbs energy model for solution nonideality Calculation of standard-state properties ■ Helgeson-Kirkham-Flowers equation for ionic and neutral aqueous species ■ Standard thermochemistry for solid and gas species Algorithm for solving phase and chemical equilibria 17 Outline of the model: Solution nonideality Excess Gibbs energy LR LC II THINK SIMULATION ex ex GLC G ex GLR GIIex RT RT RT RT Debye-Hückel theory for long-range electrostatic interactions Local composition model (UNIQUAC) for neutral molecule interactions Ionic interaction term for specific ion-ion and ionmolecule interactions G IIex ni xi x j Bij I x RT i i j THINK SIMULATION Outline of the model: Chemical equilibrium calculations For a chemical reaction: aA bB cC dD Standard-state chemical potential of i At equilibrium d xCc x D Cc Dd ln a a b b RT x x A B A B G 0 with G 0 v i i0 i Infinite-dilution properties ■ Thermochemical databases for aqueous systems ■ Helgeson-Kirkham-Flowers model for T and P dependence 19 Outline of the model: Constraints THINK SIMULATION Activity coefficients are converted to unsymmetrical normalization to work with infinite-dilution properties Constraining the parameters of the GE model to reproduce the Gibbs energy of transfer ix , H 2 O , R ix , H 2 O , S Activity coefficient of ion i in solvents R and S in unsymmetrical, mole-fraction based convention 20 Mixed-solvent electrolyte model: Applicability THINK SIMULATION 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 acidbase dissociation and complexation constants Properties that reflect ionic equilibria, e.g., solution pH and species distribution Enthalpy (Hdil or Hmix) Heat capacity Density 21 Validity range THINK SIMULATION Concentrations from infinite dilution to saturation or fused salt or pure solute limit Temperatures up to 0.9Tc of mixtures ■ This translates into 300 C for H2O – dominated systems ■ For concentrated inorganic systems, substantially higher temperatures can be reached Solvents: water, various organics or solvent mixtures 22 Representative applications of the MSE thermodynamic model THINK SIMULATION Strong acid systems ■ Simultaneous representation of phase equilibria and speciation Salt systems ■ Prediction of properties of multicomponent systems Organic – salt – water systems ■ Salt effects on VLE, LLE and SLE Acid-base equilibria ■ pH of mixed-solvent systems 23 THINK SIMULATION VLE for H2SO4 + SO3 + H2O 1.0E+03 500ºC 1.0E+02 400ºC Phase equilibria are 100ºC accurately 50ºC reproduced 25ºC 0ºC from 0 C to 500 C 300ºC 200ºC 1.0E+01 1.0E+00 P, atm 1.0E-01 1.0E-02 1.0E-03 1.0E-04 1.0E-05 1.0E-06 1.0E-07 1.0E-08 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 x SO3 24 THINK SIMULATION Speciation for H2SO4 + SO3 + H2O: 100 90 80 HSO4- mole percent 70 SO30 60 1957HR H2SO40 50 1959YMS 1994CRP&1995CB 40 SO4-2 Predicted speciation in concentrated solutions agrees with spectroscopic data 2000WYCH 30 20 10 0 0.0 0.2 0.4 0.6 (x SO3) 1/2 0.8 1.0 x (SO3 )=0.5 25 Partial pressures in the H2SO4 + SO3 + H2O system Partial pressures of H2SO4, SO3 and H2O are also correctly reproduced 1.E-07 25C 30C 35C 25C 30C 35C Perry 30C 1.E-08 H2SO4, atm 1.E-09 1.E-10 THINK SIMULATION 1.E-11 1.E-12 1.E-13 Partial pressures of H2SO4 1.E-14 1.E-15 50 55 60 65 70 75 80 H2SO4, Wt% 26 100 NaNO3 – H2O 90 80 NaNO3 , weight % THINK SIMULATION 70 60 50 40 NaNO3 30 H2O(s) 20 Cal, NaNO3 10 Cal, H2O(s) 0 -20 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 Temperature, C 100 Mg(NO3)2 – H2O 90 Mg(NO 3 )2 , weight % 80 Step 1: Binary systems – solubility of solids The model is valid for systems ranging from dilute solutions to the fused salt limit 70 H2O(s) Mg(NO3)2.9H2O Mg(NO3)2.6H2O Mg(NO3)2.2H2O Mg(NO3)2 Cal, H2O(s) Cal, Mg(NO3)2.9H2O Cal, Mg(NO3)2.6H2O Cal, Mg(NO3)2.2H2O Cal, Mg(NO3)2 60 50 40 30 20 10 Salt systems: Na – K – Mg – Ca – Cl – NO3 0 -40 -20 0 20 40 60 80 100 Temperature, C 120 140 160 180 200 27 THINK SIMULATION Modeling salt systems: Na – K – Mg – Ca – Cl – NO3 Step 1: Binary systems – solubility of solids Water activity decreases with salt concentration until the solution becomes saturated with a solid phase 1 0.9 Water activity 0.8 NaCl 0.7 1 - NaCl 0.6 6 - LiCl 0.5 11 - CaCl2 0.4 3 - Mg(NO3)2 12 - Ca(NO3)2 0.3 Ca(NO3 )2 0.2 LiCl CaCl2 .2H2 O 0.1 Mg(NO3 )2 0 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 28 THINK SIMULATION 90 80 NaNO3(s) NaNO3 , weight % 70 60 50 40 NaNO3.KNO3(s) 0C 20C 30C 50C 100C 150C 200C 10C 25C 40C 75C 125C 175C Step 2: Ternary systems 30 20 10 KNO3(s) 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 KNO3 , weight % Solubility in the system NaNO3 – KNO3 – H2O at various temperatures 0.75 0.7 Water Activity 0.65 Activity of water over saturated NaNO3 – KNO3 solutions at 90 C: Strong depression at the eutectic point KNO3 0.6 0.55 NaNO3 0.5 0.45 0.4 NaNO3 +KNO3 0.35 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 NaNO3 , mole fraction (water free) 0.8 0.9 1 29 THINK SIMULATION Step 3: Verification of predictions for multicomponent systems Deliquescence data simultaneously reflect solid solubilities and water activities 1 0.9 10 - NaNO3+KNO3 0.8 4 - NaNO3+KNO3+Ca(NO3)2+Mg(NO3)2 Water activity 0.7 0.6 0.5 NaNO3 0.4 NaNO3 0.3 NaNO3 +NaNO3 .KNO3 0.2 NaNO3 +Ca(NO3 )2 0.1 0 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 Mixed nitrate systems at 140 C 30 Electrolyte + organic systems: Examples THINK SIMULATION Effect of electrolytes on phase equilibria in nonelectrolyte – water systems ■ Salting out(in) effects Liquid-liquid equilibria in aqueous systems containing watersoluble polymers and salts ■ Liquid immiscibility is induced by the presence of a salt 31 LLE results – salt effect THINK SIMULATION 0.00045 Solubility of benzene (x) in aqueous salt solutions 0.00040 Solubility of benzene in aqueous (NH4)2SO4 and NaCl solutions at 25ºC 25 C 0.00035 0.00030 0.00025 0.00020 0.00015 (NH4)2SO4 0.00010 0.00005 NaCl 0.00000 0 100 200 300 400 g salt/kg H2O 32 THINK SIMULATION Simultaneous representation of thermodynamic properties: NaCl-methanol-water 110 7.0 P=1 bar 6.0 mol NaCl/kg solvent 100 t/C 90 80 70 ---- Salt-free —— Saturated NaCl 25°C 5.0 4.0 3.0 2.0 1.0 0.0 60 0.0 0.2 0.4 0.6 0.8 1.0 x, y (methanol) VLE: salting-out effect 0.0 0.2 0.4 0.6 0.8 1.0 x-methanol Solubility 33 0.09 LLE in aqueous polymer – salt systems 0.08 X - NaH 2PO4 0.07 0.06 THINK SIMULATION 0.05 0.04 0.03 0.02 0.01 0.00 0.000 0.005 0.010 0.015 0.020 0.025 PEG (MW=1000) + NaH2PO4 + H2O at 25 C x - PEG1000 0.030 x - (NH4)2SO4 0.025 0.020 PEG (MW=4000) + (NH4)2SO4 + H2O at 25 C 0.015 0.010 0.005 0.000 0.0000 0.0005 0.0010 0.0015 0.0020 0.0025 x - PEG 4000 34 Acid-base and phase equilibria: Treatment of pH in mixed solvents THINK SIMULATION Classical treatment ■ pH scale can be defined separately for each, pure or mixed, solvent ■ pH scales can be converted using the Gibbs energy of transfer of the proton G Ht ,w A pH A pH w RT ln 10 ■ 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 model accurately reproduces activity coefficients of individual species and the Gibbs energy of transfer 35 THINK SIMULATION Treatment of pH in mixed-solvents Uniform treatment of apparent pH ■ Starting point: Aqueous definition of pH pH log a H mH H log 0 m ■ Conversion to mole fraction scale and solvated proton basis pH log x H O log H O 3 3 1000 log MH O 2 log x H O log H O 2 2 ■ Activity coefficients are obtained directly from the model ■ Values can be compared with measurements using glass electrode ■ Does not require the presence of water – equivalent expressions can be obtained for other solvents 36 THINK SIMULATION Speciation Effects Apparent (Mixed Solvent-Based) Ionization Constants Acetic Acid in EtOH-H2O Acetic Acid in MeOH-H2O 12 12 cal cal Sen et al. 10 10 exp pKa pKa Woolley 8 6 8 6 4 4 0.0 0.2 0.4 0.6 0.8 x-Ethanol 1.0 0.0 0.2 0.4 0.6 0.8 1.0 x-Methanol Equilibrium constant obtained from aqueous solutions 37 THINK SIMULATION 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-, CO32-, SO42-, PO43-, 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 – H2SO4 •HI – I2 – H2SO4 •HNO3 – H2SO4 – SO3 •H3PO4 with calcium phosphates •H – Na – Cl – NO3 •H – Na – Cl – F 38 Parameters in the MSE Databank (2) THINK SIMULATION 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 39 Parameters in the MSE Databank (3) THINK SIMULATION 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 the periodic table Hydrogen peroxide chemistry ■ H2O2 – H2O – H - Na – OH – SO4 – NO3 40 Parameters in the MSE Databank (4) THINK SIMULATION 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 41 Parameters in the MSE Databank (5) THINK SIMULATION 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 42 Parameters in the MSE Databank (6) THINK SIMULATION 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 43 Parameters in the MSE Databank (7) THINK SIMULATION 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 44 Parameters in the MSE Databank (8) THINK SIMULATION 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 - CO2 – H2S – 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 45 Predictive character of the model THINK SIMULATION Levels of predictivity ■ Prediction of the properties of multicomponent systems based on parameters determined from simpler (especially binary) subsystems ◊Extensively validated for salts and organics ■ Prediction of certain properties based on parameters determined from other properties ◊Extensively validated (e.g., speciation or caloric property predictions) 46 40 MSE (no ternary fits) KH2PO4, weight % 35 30 25 20 15 0C 5C 10C 15C 20C 25C 30C 35C 40C 45C 50C 55C 60C 65C 70C 75C THINK SIMULATION What does it mean for the model to be predictive? 10 5 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 NaH2PO4, weight % 45 Aqueous model (no ternary fits) KH2PO4, weight % 40 35 30 25 20 0C 5C 10C 15C 20C 25C 30C 35C 40C 50C 45C 55C 60C 65C 70C 75C 15 10 Parameters were determined using only binary salt + H2O data SLE for the ternary system was predicted without making any ternary fits MSE is clearly superior even in the applicability range of the aqueous model This can work only when the ternary system does not introduce a chemistry change (e.g., double salts) 5 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 NaH2PO4, weight % 47 Predictive character of the model THINK SIMULATION 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: CosmoTherm estimation » Also has limited applicability to electrolytes as long as dissociation/chemical equilibria can be independently calculated 48 Transport properties in the OLI software THINK SIMULATION Available transport properties: ■ Diffusivity ■ Viscosity ■ Electrical conductivity OLI was the first to develop transport property models for concentrated, multicomponent aqueous solutions More recently, the models have been extended to mixed-solvent systems 49 Modeling diffusivity in electrolyte systems Limiting diffusivity – Di0 Long-range electrostatic interactions – Relaxation effect: k i 1 k i Short-range interactions – Hard-sphere contribution: Combination of the two effects: k i 0 Di Di 1 ki THINK SIMULATION MSA theory: Important in relatively dilute solutions DiHS Di0 DiHS D 0 i Enskog theory: Significant for concentrated solutions 50 THINK SIMULATION Calculation of diffusivity in MSE solutions 2.5 2.5 x LiCl=0 salt-free x NaCl=0.005 x LiCl=0.02 1.5 1.0 2.0 2 x LiCl=0.01 9 2.0 D methanol*10 , m /s D methanol *109, m 2/s x LiCl=0.005 1.5 0.5 0.0 0.0 0.2 0.4 0.6 0.8 1.0 x 'methanol Dmethanol in methanol-water-LiCl system at 25ºC at various LiCl concentrations x NaCl=0.02 1.0 0.5 0.0 x NaCl=0.01 0.0 0.2 0.4 0.6 0.8 1.0 x 'methanol Dmethanol in methanol-water-NaCl system at 25ºC at various NaCl concentrations 51 THINK SIMULATION Computation of diffusion coefficients: Species in NiCl2 solutions 2.0 Ni species - Stokes et al. (1979) 9 2 -1 D 10 (m s ) 2.5 1.5 Ni species - Salmon et al. (1987) 1.0 Cl species - Stokes et al. (1979) 0.5 For complexed species, measured diffusion coefficients are weighted averages of diffusion coefficients of individual complexes: 0.0 0 1 2 3 m NiCl2 4 5 DX T iDQi X i i cQi X i c X T 52 Modeling electrical conductivity THINK SIMULATION The model includes the computation of 1. 2. Limiting conductivities of ions as a function of temperature and solvent composition Dependence of electrical conductivity on electrolyte concentration (the mean spherical approximation theory) Limiting conductivity Dependence of i on electrolyte concentration el v i X 0 i i 1 0 1 X v i electrophoretic correction relaxation effect 53 THINK SIMULATION Electrical conductivity model: H2O – H2SO4 – SO3 specific conductivity (S.cm-1 ) 10 1 0.1 0.01 0.001 0.0001 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 x-SO3 54 THINK SIMULATION Electrolytes in mixed solvents: MgCl2 + ethanol + water 1.0E+00 specific conductivity, S ·cm -1 0% EtOH 1.0E-01 20% 40% 60% 80% 1.0E-02 1.0E-03 1.0E-04 100% EtOH (---□---) 1.0E-05 0.0001 0.001 0.01 0.1 1 10 mol MgCl2/kg solvent 55 THINK SIMULATION Viscosity model In MSE solutions, -0 is found to show regularities with respect to both electrolyte concentrations and solvent composition, and is the most convenient quantity to define the model viscosity of the MSE solution 0 mix long-range electrostatic contribution individual ion interactions contributions between species viscosity of the solvent mixture LR s Dependence of on electrolyte concentration ss 56 THINK SIMULATION Viscosities of solvent mixtures, 0mix 0 Mixing rule mix YiY j ij Viscosity (cP) 2.0 i 20C 1.5 25C 1.0 ij 50C 0.5 0.2 Modified volume fractions 0.0 0.0 1 i0 0j 1 k ij 2 j 0.4 0.6 x-acetone acetone + water 0.8 1.0 x i v i* Yi * xl v l l v i* v i0 x l1 4 v l0 g il l i 57 THINK SIMULATION Effects of electrolyte concentration LR – From the analytical model by Onsager and Fuoss (1932) s – defined for multiple solvents s-s – defined for solvent combinations LR 1 2 N i 2I a T i zi n 4 r c s 0 n i n 0 i calculated using and i0 in the mixed solvent s x j 0j ci Bi , j j = solvent; i = ion or neutral i Bi,jjevaluated based on viscosities of electrolyte in pure solvent Dik,jl(I,T) adjusted based on experimental data s s x 'j x l' 0jl f i f k Dik,jl I 2 j l i k j,l = solvent; i,k = ion or neutral 58 THINK SIMULATION Viscosity of H2O – H2SO4 – SO3 1000 , cP 100 10 1 0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 x-SO3 59 Viscosity of salt – organic - water systems: LiNO3-ethanol-H2O THINK SIMULATION 16 30 w t% 14 EtOH=0 w t% 70 w t% 12 , cP 10 Viscosities of the ternary solutions of LiNO3-ethanol-H2O as a function of the molarity of LiNO3 at 25ºC and at various ethanol weight percent. 100 w t% 8 6 4 2 0 0 5 10 15 c-LiNO3, mol/L 60 Sublimation / calculations sublimation pressure 10 NH4Cl 1 THINK SIMULATION salt point 0.1 0.01 Stull-1947 OLI 0.001 150 200 250 300 350 Solid-gas equilibrium computations for pure NH4Cl and NH4HS t/C sublimation pressure, atm 10 NH4HS 1 0.1 0.01 Stull-1947 P, atm (cal) 0.001 -60 -30 0 30 t/C 60 90 61 HI - I2 - H2O THINK SIMULATION H2O/HI/I2 full range of concentration, T The heart of the IS Process Challenge: presence of more than one LLE region together with regions of VLE and SLE 62 MSE Challenge THINK SIMULATION Will MSE work out-of-the-box? For systems within the AQ model limits, yes ■ Binary systems give reasonable results when water remains the dominant solvent When the 2nd solvent, or different solvent predominates ■ 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 63 Overview of Aspen PLUS OLI (with MSE) THINK SIMULATION Using the Aspen PLUS OLI Chemistry Generator 64 Aspen OLI Chemistry Generator THINK SIMULATION 65 Aspen OLI Chemistry Generator THINK SIMULATION 66 Aspen OLI Chemistry Generator THINK SIMULATION 67 Aspen OLI Chemistry Generator THINK SIMULATION 68 Aspen OLI Chemistry Generator THINK SIMULATION 69 Aspen OLI Chemistry Generator THINK SIMULATION 70 Aspen OLI Chemistry Generator THINK SIMULATION 71 Aspen OLI Chemistry Generator THINK SIMULATION 72 Aspen OLI Chemistry Generator THINK SIMULATION 73 Aspen OLI Chemistry Generator THINK SIMULATION 74 THINK SIMULATION 75 Aspen OLI Chemistry Generator THINK SIMULATION 76 Aspen OLI Chemistry Generator THINK SIMULATION 77 Aspen OLI Chemistry Generator THINK SIMULATION 78 Aspen OLI Chemistry Generator THINK SIMULATION 79 Aspen OLI Chemistry Generator THINK SIMULATION 80 Aspen OLI Chemistry Generator THINK SIMULATION 81 Aspen OLI Chemistry Generator THINK SIMULATION 82 Aspen OLI Chemistry Wizard THINK SIMULATION 83 Aspen OLI Chemistry Wizard THINK SIMULATION 84 Aspen OLI Chemistry Wizard THINK SIMULATION 85 Aspen OLI Chemistry Wizard THINK SIMULATION 86 Aspen OLI Chemistry Wizard THINK SIMULATION 87 Aspen OLI Chemistry Wizard THINK SIMULATION 88 Aspen OLI Chemistry Wizard THINK SIMULATION 89 Aspen OLI Chemistry Wizard THINK SIMULATION 90 Aspen OLI Chemistry Wizard THINK SIMULATION 91 Aspen OLI Chemistry Wizard THINK SIMULATION 92 Aspen OLI Chemistry Wizard THINK SIMULATION 93 Aspen OLI Chemistry Wizard THINK SIMULATION 94 Aspen OLI Chemistry Wizard THINK SIMULATION 95 Aspen OLI Chemistry Wizard THINK SIMULATION 96 Aspen OLI Chemistry Wizard THINK SIMULATION 97 Aspen Plus 2006 THINK SIMULATION 98 Aspen Plus 2006 THINK SIMULATION 99 Aspen Plus 2006 THINK SIMULATION 100 Aspen Plus 2006 THINK SIMULATION 101 Aspen Plus 2006 THINK SIMULATION 102 Aspen Plus 2006 THINK SIMULATION 103 Aspen Plus 2006 THINK SIMULATION 104 Aspen Plus 2006 THINK SIMULATION 105 Aspen Plus 2006 THINK SIMULATION 106 Aspen Plus 2006 THINK SIMULATION 107 Aspen Plus 2006 THINK SIMULATION 108 Aspen Plus 2006 THINK SIMULATION 109 Aspen Plus OLI with EFRACH THINK SIMULATION 110 Aspen Plus OLI with EFRACH THINK SIMULATION 111 Aspen Plus OLI with EFRACH THINK SIMULATION 112 Aspen Plus OLI with EFRACH THINK SIMULATION 113 Aspen Plus OLI with EFRACH THINK SIMULATION 114 Aspen Plus OLI with EFRACH THINK SIMULATION 115 Aspen Plus OLI with EFRACH THINK SIMULATION 116 Aspen Plus OLI with EFRACH THINK SIMULATION 117 Aspen Plus OLI with EFRACH THINK SIMULATION 118 Aspen Plus OLI with EFRACH THINK SIMULATION 119 Aspen Plus OLI with EFRACH THINK SIMULATION 120 Aspen OLI THINK SIMULATION More examples? Live cases? Questions? 121 Conclusion THINK SIMULATION Using MSE in Aspen Plus is very similar to using any property set. The OLI property sets can be used with standard Aspen PLUS unit operations or with OLI unit operations 122
