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Opening new doors with Chemistry

Peiming Wang Ronald Springer Margaret Lencka Robert Young Jerzy Kosinski Andre Anderko. Advances in Thermophysical Property Prediction. 24 th Conference October 23-24, 2007. THINK SIMULATION!. Opening new doors with Chemistry. Scope. OLI’s two thermodynamic models: aqueous and MSE

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Opening new doors with Chemistry

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  1. Peiming Wang Ronald Springer Margaret Lencka Robert Young Jerzy Kosinski Andre Anderko Advances in Thermophysical Property Prediction 24th Conference October 23-24, 2007 THINK SIMULATION! Opening new doors with Chemistry

  2. Scope • OLI’s two thermodynamic models: aqueous and MSE • Outline of the mixed-solvent electrolyte (MSE) thermodynamic model • Application highlights • Summary of MSE databanks • Predictive character of the model • Modeling transport properties • New model for thermal conductivity • Model and databank development plans

  3. Structure of OLI thermodynamic models (both aqueous and MSE) • 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-Tanger equation for ionic and neutral aqueous species • Standard thermochemistry for solid and gas species • Algorithm for solving phase and chemical equilibria

  4. OLI Thermodynamic Models:Aqueous and MSE • The difference between the models lies in • Solution nonideality model • Methodology for defining and regressing parameters • Aqueous model • Solution nonideality model suitable for solutions with ionic strength below ~30 molal and nonelectrolyte mole fraction below ~0.3 • Extensive track record and large databank • MSE model • Solution nonideality model eliminates composition limitations • Development started in 2000 and model became commercial in early 2006 • Smaller, but rapidly growing databank • Includes many important systems not covered by the aqueous model

  5. MSE Framework • Thermophysical framework to calculate • Phase equilibria and other properties in aqueous and mixed-solvent electrolyte systems • Electrolytes from infinite dilution to the fused-salt limit • Aqueous, non-aqueous and mixed solvents • Temperatures up to 0.9 critical temperature of the system • Chemical equilibria • Speciation of ionic solutions • Reactions in solid-liquid systems

  6. Outline of the MSE model:Solution nonideality Excess Gibbs energy LR Debye-Hückel theory for long-range electrostatic interactions LC Local composition model (UNIQUAC) for neutral molecule interactions II Ionic interaction term for specific ion-ion and ion- molecule interactions

  7. MSE thermodynamic model:Application highlights • Predicting deliquescence of Na – K – Mg – Ca – Cl – NO3 brines • Challenge: Simultaneous representation of water activity and solubility for concentrated multicomponent solutions based on parameters determined from binary and selected ternary data • Phase behavior of borate systems • Challenge: Complexity of SLE patterns; multiple phases • Properties of transition metal systems • Challenge: Interplay between speciation and phase behavior

  8. NaNO3 – H2O Na – K – Mg – Ca – Cl – NO3 system • Step 1: Binary systems – solubility of solids • The model is valid for systems ranging from dilute to the fused salt limit Mg(NO3)2 – H2O

  9. Na – K – Mg – Ca – Cl – NO3 system:Step 1: Binary systems – water activity • Deliquescence experiments • Water activity decreases with salt concentration until the solution becomes saturated with a solid phase (which corresponds to the deliquescence point)

  10. Step 2: Ternary systems • Solubility in the system NaNO3 – KNO3 – H2O at various temperatures • Activity of water over saturated NaNO3 – KNO3 solutions at 90 C: Strong depression at the eutectic point

  11. Step 3: Verification of predictions for multicomponent systems • Deliquescence data simultaneously reflect solid solubilities and water activities • Break points reflect solid-liquid transitions Mixed nitrate systems at 140 C

  12. Borate chemistry:Complexity due to multiple competing solid phases Na – B(III) – H – OH system

  13. Borate chemistry:Complexity due to multiple competing solid phases Mg – B(III) – H – OH Ca – B(III) – H – OH

  14. Lead chemistry PbCl2 + HCl • Solubility patterns are strongly influenced by speciation (Pb-Cl and Pb-SO4 complexation) PbSO4 + H2SO4

  15. Lead chemistry • With speciation and ionic interactions correctly accounted for, mixed sulfate – chloride systems are accurately predicted PbSO4 + HCl PbSO4 + NaCl

  16. Solubility of WO3 in acidic Cl- and NO3- environments Transition metal systems • Specific effects of anions on the solubility of oxides • Prediction of pH – accounting for hydrolysis of cations pH of Cr salts

  17. Mixed organic – inorganic systems H2SO4 • Solubility of oxalic acid in mineral acid systems HNO3 HCl

  18. Chemistry Coverage in the MSEPUB 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-containing 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 • H – Na – PO4 - OH

  19. Chemistry Coverage in the MSEPUB Databank (2) • Inorganic gases in aqueous systems • CO2 + NH3 + H2S • SO2 + H2SO4 • N2 • O2 • H2 • Borate chemistry • H+ - Li+ - Na+ - Mg2+ - Ca2+ - BO2- - OH- • H+ - Li+ - Na+ - BO2- - HCOO- - CH3COO- - Cl- - OH- • Silica chemistry • Si(IV) – H+ - O - Na+ • Hydrogen peroxide chemistry • H2O2 – H2O – H - Na – OH – SO4 – NO3

  20. Chemistry Coverage in the MSEPUB Databank (3) • Transition metal aqueous systems • Fe(III) – H+ – O – Cl-, SO42-, NO3- • Fe(II) – H+ – O – Cl-, SO42-, NO3-, Br- • Sn(II, IV) – H+ – O – CH3SO3- • Zn(II) – H+ – Cl-, SO42-, NO3- • Zn(II) – Li+ - Cl- • Cu(II) – H+ – SO42-, NO3- • Ni(II) – H+ – Cl-, SO42-, NO3- • Ni(II) – Fe(II) – H+ - O – BO2- • Cr(III) – H+ - O – Cl-, SO42-, NO3- • Cr(VI) – H+ - O – NO3- • Ti(IV) – H+ – O – Ba2+ – Cl-, OH-, BuO- • Pb(II) – H+ - O – Na+ - Cl-, SO42- • Mo(VI) – H+ – O – Cl-, SO42-, NO3- • Mo(IV) – H+ - O • Mo(III) – H+ - O • W(VI) – H+ - O – Na+ – Cl-, NO3- • W(IV) – H+ - O

  21. Chemistry Coverage in the MSEPUB Databank (4) • Miscellaneous inorganic systems in water • NH2OH • NH4HS + H2S + NH3 • Li+ - K+ - Mg2+ - Ca2+ - Cl- • Na2S2O3 • Na+ - BH4- – OH- • Na+ - SO32- - SO2-OH- • BaCl2 • Most elements from the periodic table in their elemental form • Base ions and hydrolyzed forms for the majority of elements from the periodic table

  22. Chemistry Coverage in the MSEPUB Databank (5) • Organic acids/salts in water and alcohols • Formic • H+ - Li+ - Na+ - Formate - OH- • Formic acid – MeOH - EtOH • Acetic • H+ - Li+ - Na+ - K+ - Ba2+ - Acetate - OH- • Acetic acid – MeOH – EtOH – CO2 • Citric • H+ - Na+ - Citrate - OH- • Oxalic • H+ - Oxalate – Cl- - SO42-, NO3-, MeOH, EtOH, 1-PrOH • Malic • Glycolic • Adipic • H+ - Na+ - Adipate • Adipic acid – MeOH, EtOH • Nicotinic • H+ - Na+ - Nicotinate • Nicotinic acid - EtOH • Terephthalic • H+ - Na+ - Terephthalate • Terephthalic acid – MeOH, EtOH • Isophthalic • Isophthalic acid - EtOH • Trimellitic • Trimellitic acid - EtOH

  23. Chemistry Coverage in the MSEPUB Databank (6) • Hydrocarbon systems • Hydrocarbon + H2O systems • 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 • Cyclohexane • Hydrocarbon + salt generalized parameters • H+, NH4+, Li+, Na+, K+, Mg2+, Ca2+, Cl-, OH-, HCO3-, CO32- NO3-, SO42-

  24. Chemistry Coverage in the MSEPUB Databank (7) • Organic solvents and their mixtures with water • Alcohols • Methanol, ethanol, 1-propanol, 2-propanol, 1-butanol, cyclohexanol • Glycols • Mono, di- and triethylene glycols, propylene glycol, polyethylene glycols • Phenols • Phenol, catechol • Ketones • Acetone, methylisobutyl ketone • Aldehydes • Butylaldehyde • Carbonates • Diethylcarbonate, propylene carbonate

  25. Chemistry Coverage in the MSEPUB Databank (8) • Organic solvents and their mixtures with water • Amines • Tri-N-octylamine, triethylamine, methyldiethanolamine • Nitriles • Acetonitrile • Amides • Dimethylacetamide, dimethylformamide • Halogen derivatives • Chloroform, carbon tetrachloride • Aminoacids • Methionine • Heterocyclic components • N-methylpyrrolidone, 2,6-dimethylmorpholine

  26. Chemistry Coverage in the MSEPUB Databank (9) • Polyelectrolytes • Polyacrylic acid • Complexes with Cu, Zn, Ca, Fe(II), Fe(III) • Mixed-solvent inorganic/organic system • Mono, di- and triethylene glycols - H – Na – Ca – Cl – CO3 – HCO3 - CO2 – H2S – H2O • Methanol - H2O + NaCl, HCl • Ethanol – LiCl - H2O • Phenol - acetone - SO2 - HFo - HCl – H2O • n-Butylaldehyde – NaCl - H2O • LiPF6 – diethylcarbonate – propylene carbonate • Mixed-solvent organic systems • HAc – tri-N-octylamine – toluene – H2O • HAc – tri-N-octylamine – methylisobutylketone – H2O • Dimethylformamide – HFo – H2O • MEG – EtOH – H2O

  27. Chemistry Coverage in the MSEPUB Databank (10) • GEMSE databank • MSE counterpart of the GEOCHEM databank • Minerals that form on an extended time scale • Contains all species from GEOCHEM • 7 additional silicates and aluminosilicates have been included • CRMSE databank • MSE counterpart of the CORROSION databank • Various oxides and other salts that may form as passive films but are unlikely to form in process environments

  28. Predictive character of the model • Levels of prediction • Prediction of the properties of multicomponent systems based on parameters determined from simpler (especially binary) subsystems • Extensively validated for salts and organics • Subject to limitations due to chemistry changes (e.g. double salts) • Prediction of certain properties based on parameters determined from other properties • Extensively validated (e.g.,speciation or caloric property predictions)

  29. Predictive character of the model • Levels of prediction - 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 predictive character 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

  30. Determining MSE parameters based on COSMOtherm predictions • Solid-liquid-liquid equilibria in the triphenylphosphate-H2O system • Only two data points are available: melting point and solubility at room T • Predictions from COSMOtherm are consistent with the two points and fill the gaps in experimental data

  31. Determining MSE parameters based on COSMOtherm predictions • Solid-liquid-liquid equilibria in the P-H2O system • Predictions from COSMOtherm are shown for comparison

  32. Transport properties in the OLI software • Available transport properties: • Diffusivity • Viscosity • Electrical conductivity • These models were developed first in conjunction with the aqueous model and then extended to mixed-solvent systems • A new model for calculating thermal conductivity has been recently developed

  33. Thermal Conductivity in Mixed-Solvent Electrolyte Solutions lms0̶ thermal conductivity of the mixed solvent Δlelec̶ contribution of electrolyte concentration Derived from a local composition approach contribution of individual ion species-species interaction

  34. Thermal conductivity of solvent mixtures cyclohexane + CCl4 + benzene and cyclohexane + CCl4 + toluene organic + water mixtures at 20ºC

  35. Aqueous Electrolytes from Dilute to Concentrated Solutions KNO3+water P2O5+water

  36. Electrolytes in Non-aqueous and Mixed Solvents ZnCl2+ethanol ZnCl2+ethanol+water

  37. Further Development of MSE • Thermophysical property models • Implementation of thermal conductivity in OLI software • Development of a surface tension model • Major parameter development projects • Refinery overhead consortium (in collaboration with SwRI) • Development of parameters for amines and amine hydrochlorides • Hanford tank chemistry in MSE • Modeling hydrometallurgical systems (University of Toronto) • Transition metal chemistry including complexation • Natural water chemistry (including common scales) with methanol and glycols • Urea chemistry • Other projects as defined by clients

  38. Summary • OLI’s two thermophysical property packages • Mixed-solvent electrolyte model • Thermophysical engine for the future • General, accurate framework for reproducing the properties of electrolyte and nonelectrolyte systems without concentration limits over wide ranges of conditions • Parameter databanks are being rapidly expanded • New thermophysical properties (thermal conductivity, surface tension) are being added • Aqueous model • Widely used and reliable • Continues to be maintained and parameters continue to be added as requested by clients

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