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Opening new doors with Chemistry THINK SIMULATION! Advances in Thermophysical Property Prediction 24 th Conference October 23-24, 2007 Peiming Wang Ronald.

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Presentation on theme: "Opening new doors with Chemistry THINK SIMULATION! Advances in Thermophysical Property Prediction 24 th Conference October 23-24, 2007 Peiming Wang Ronald."— Presentation transcript:

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

2 Scope OLIs 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 LR Debye-Hückel theory for long-range electrostatic interactions LCLocal composition model (UNIQUAC) for neutral molecule interactions II Ionic interaction term for specific ion-ion and ion- molecule interactions Excess Gibbs energy

7 MSE thermodynamic model: Application highlights Predicting deliquescence of Na – K – Mg – Ca – Cl – NO 3 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 Na – K – Mg – Ca – Cl – NO 3 system Step 1: Binary systems – solubility of solids The model is valid for systems ranging from dilute to the fused salt limit NaNO 3 – H 2 O Mg(NO 3 ) 2 – H 2 O

9 Na – K – Mg – Ca – Cl – NO 3 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 NaNO 3 – KNO 3 – H 2 O at various temperatures Activity of water over saturated NaNO 3 – KNO 3 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 Ca – B(III) – H – OH Mg – B(III) – H – OH

14 Lead chemistry Solubility patterns are strongly influenced by speciation (Pb-Cl and Pb-SO 4 complexation) PbCl 2 + HCl PbSO 4 + H 2 SO 4

15 Lead chemistry With speciation and ionic interactions correctly accounted for, mixed sulfate – chloride systems are accurately predicted PbSO 4 + HCl PbSO 4 + NaCl

16 Transition metal systems Specific effects of anions on the solubility of oxides Prediction of pH – accounting for hydrolysis of cations pH of Cr salts Solubility of WO 3 in acidic Cl - and NO 3 - environments

17 Mixed organic – inorganic systems Solubility of oxalic acid in mineral acid systems HNO 3 H 2 SO 4 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 +, Mg 2+, Ca 2+, Al 3+, NH 4 + Anions: Cl -, F -, NO 3 -, CO 3 2-, SO 4 2-, PO 4 3-, OH - Aqueous acids, associated acid oxides and acid-containing mixtures H 2 SO 4 – SO 3 HNO 3 – N 2 O 5 H 3 PO 4 – H 4 P 2 O 7 – H 5 P 3 O 10 – P 2 O 5 H 3 PO 2 H 3 PO 3 HF HCl HBr HI H 3 BO 3 CH 3 SO 3 H NH 2 SO 3 H HFSO 3 – HF – H 2 SO 4 HI – I 2 – H 2 SO 4 HNO 3 – H 2 SO 4 – SO 3 H 3 PO 4 with calcium phosphates H – Na – Cl – NO 3 H – Na – Cl – F H – Na – PO 4 - OH

19 Inorganic gases in aqueous systems CO 2 + NH 3 + H 2 S SO 2 + H 2 SO 4 N 2 O 2 H 2 Borate chemistry H + - Li + - Na + - Mg 2+ - Ca 2+ - BO 2 - - OH - H + - Li + - Na + - BO 2 - - HCOO - - CH 3 COO - - Cl - - OH - Silica chemistry Si(IV) – H + - O - Na + Hydrogen peroxide chemistry H 2 O 2 – H 2 O – H - Na – OH – SO 4 – NO 3 Chemistry Coverage in the MSEPUB Databank (2)

20 Transition metal aqueous systems Fe(III) – H + – O – Cl -, SO 4 2-, NO 3 - Fe(II) – H + – O – Cl -, SO 4 2-, NO 3 -, Br - Sn(II, IV) – H + – O – CH 3 SO 3 - Zn(II) – H + – Cl -, SO 4 2-, NO 3 - Zn(II) – Li + - Cl - Cu(II) – H + – SO 4 2-, NO 3 - Ni(II) – H + – Cl -, SO 4 2-, NO 3 - Ni(II) – Fe(II) – H + - O – BO 2 - Cr(III) – H + - O – Cl -, SO 4 2-, NO 3 - Cr(VI) – H + - O – NO 3 - Ti(IV) – H + – O – Ba 2+ – Cl -, OH -, BuO - Pb(II) – H + - O – Na + - Cl -, SO 4 2- Mo(VI) – H + – O – Cl -, SO 4 2-, NO 3 - Mo(IV) – H + - O Mo(III) – H + - O W(VI) – H + - O – Na + – Cl -, NO 3 - W(IV) – H + - O Chemistry Coverage in the MSEPUB Databank (3)

21 Miscellaneous inorganic systems in water NH 2 OH NH 4 HS + H 2 S + NH 3 Li + - K + - Mg 2+ - Ca 2+ - Cl - Na 2 S 2 O 3 Na + - BH 4 - – OH - Na + - SO 3 2- - SO 2 - OH - BaCl 2 Most elements from the periodic table in their elemental form Base ions and hydrolyzed forms for the majority of elements from the periodic table Chemistry Coverage in the MSEPUB Databank (4)

22 Organic acids/salts in water and alcohols Formic H + - Li + - Na + - Formate - OH - Formic acid – MeOH - EtOH Acetic H + - Li + - Na + - K + - Ba 2+ - Acetate - OH - Acetic acid – MeOH – EtOH – CO 2 Citric H + - Na + - Citrate - OH - Oxalic H + - Oxalate – Cl - - SO 4 2-, NO 3 -, 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 Chemistry Coverage in the MSEPUB Databank (5)

23 Hydrocarbon systems Hydrocarbon + H 2 O 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 +, NH 4 +, Li +, Na +, K +, Mg 2+, Ca 2+, Cl -, OH -, HCO 3 -, CO 3 2- NO 3 -, SO 4 2- Chemistry Coverage in the MSEPUB Databank (6)

24 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 Chemistry Coverage in the MSEPUB Databank (7)

25 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 Chemistry Coverage in the MSEPUB Databank (8)

26 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 – CO 3 – HCO 3 - CO 2 – H 2 S – H 2 O Methanol - H 2 O + NaCl, HCl Ethanol – LiCl - H 2 O Phenol - acetone - SO 2 - HFo - HCl – H 2 O n-Butylaldehyde – NaCl - H 2 O LiPF 6 – diethylcarbonate – propylene carbonate Mixed-solvent organic systems HAc – tri-N-octylamine – toluene – H 2 O HAc – tri-N-octylamine – methylisobutylketone – H 2 O Dimethylformamide – HFo – H 2 O MEG – EtOH – H 2 O Chemistry Coverage in the MSEPUB Databank (9)

27 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 Chemistry Coverage in the MSEPUB Databank (10)

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- H 2 O 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-H 2 O 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 ms 0 ̶ thermal conductivity of the mixed solvent Δ elec ̶ contribution of electrolyte concentration Derived from a local composition approach contribution of individual ion species-species interaction Thermal Conductivity in Mixed- Solvent Electrolyte Solutions

34 organic + water mixtures at 20ºC cyclohexane + CCl 4 + benzene and cyclohexane + CCl 4 + toluene Thermal conductivity of solvent mixtures

35 KNO 3 +water P 2 O 5 +water Aqueous Electrolytes from Dilute to Concentrated Solutions

36 ZnCl 2 +ethanolZnCl 2 +ethanol+water Electrolytes in Non-aqueous and Mixed Solvents

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 OLIs 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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