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OLI s Mixed Solvent Electrolyte with Aspen PLUS

2. Agenda. OLI's basic historyOLI's history with Aspen TechnologiesAdvantages/disadvantages of Aspen PLUS OLIArchitecture of the Aspen PLUS OLI interfaceIntroduction to MSEOverview of Aspen PLUS OLI (with MSE)Demonstration. 3. OLI's basic history. Company founded in 1971 by Marshall RafalFirst electrolyte simulator (ECES) 1973 Developed for OLIN ChemicalFirst commercial sale of ECES 1975DupontThe Environmental Simulation Program developed in 1991Linkage to simulators in 1995Windows 1140

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OLI s Mixed Solvent Electrolyte with Aspen PLUS

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    1. OLIs Mixed Solvent Electrolyte with Aspen PLUS OLI Systems, Inc.

    2. 2 Agenda OLIs basic history OLIs 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

    3. 3 OLIs basic history 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

    4. 4 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

    5. 5 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

    6. 6 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

    7. 7 Architecture of the Aspen PLUS OLI interface

    8. 8 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

    9. 9 Architecture of the Aspen PLUS OLI interface Thermodynamic Properties from OLI used by Aspen PLUS (OLI propset)

    10. 10 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 OLI 2006\Databanks\OLIAspenPlusCompXRef.lis

    11. 11 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

    12. 12 Architecture of the Aspen PLUS OLI interface EFLASH

    13. 13 Architecture of the Aspen PLUS OLI interface EFRACH

    14. 14 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 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

    15. 15 Introduction to MSE Advantages and disadvantages between AE and MSE 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

    16. 16 Introduction to MSE Overview of species coverage between AE and MSE models.

    17. 17 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

    18. Outline of the model: Solution nonideality Overvier of Version 1.1 Page 2 of 2Overvier of Version 1.1 Page 2 of 2

    19. 19 Outline of the model: Chemical equilibrium calculations For a chemical reaction: At equilibrium with

    20. 20 Outline of the model: Constraints

    21. 21 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 and species distribution Enthalpy (?Hdil or ?Hmix) Heat capacity Density

    22. 22 Validity range 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

    23. 23 Representative applications of the MSE thermodynamic model 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

    24. 24 VLE for H2SO4 + SO3 + H2O

    25. 25 Speciation for H2SO4 + SO3 + H2O:

    26. 26 Partial pressures in the H2SO4 + SO3 + H2O system

    27. 27 Salt systems: Na K Mg Ca Cl NO3 Step 1: Binary systems solubility of solids The model is valid for systems ranging from dilute solutions to the fused salt limit

    28. 28 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

    29. 29 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

    30. 30 Step 3: Verification of predictions for multicomponent systems Deliquescence data simultaneously reflect solid solubilities and water activities

    31. 31 Electrolyte + organic systems: Examples

    32. 32 LLE results salt effect

    33. 33 Simultaneous representation of thermodynamic properties: NaCl-methanol-water

    34. 34 LLE in aqueous polymer salt systems

    35. 35 Acid-base and phase equilibria: Treatment of pH in mixed solvents

    36. 36 Treatment of pH in mixed-solvents

    37. 37 Speciation Effects

    38. 38 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

    39. 39 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

    40. 40 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 the periodic table Hydrogen peroxide chemistry H2O2 H2O H - Na OH SO4 NO3

    41. 41 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

    42. 42 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

    43. 43 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

    44. 44 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

    45. 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 - 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

    46. 46 Predictive character of the model 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)

    47. 47 What does it mean for the model to be predictive?

    48. 48 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: CosmoTherm estimation Also has limited applicability to electrolytes as long as dissociation/chemical equilibria can be independently calculated

    49. 49 Transport properties in the OLI software 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

    50. 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:

    51. 51 Calculation of diffusivity in MSE solutions

    52. 52 Computation of diffusion coefficients: Species in NiCl2 solutions For complexed species, measured diffusion coefficients are weighted averages of diffusion coefficients of individual complexes:

    53. 53 Modeling electrical conductivity

    54. 54 Electrical conductivity model: H2O H2SO4 SO3

    55. 55 Electrolytes in mixed solvents: MgCl2 + ethanol + water

    56. 56 Viscosity model

    57. 57 Viscosities of solvent mixtures, h0mix

    58. 58 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

    59. 59 Viscosity of H2O H2SO4 SO3

    60. 60 Viscosity of salt organic - water systems: LiNO3-ethanol-H2O

    61. 61 Sublimation / salt point calculations

    62. 62 HI - I2 - H2O 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

    63. 63 MSE Challenge 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

    64. 64 Overview of Aspen PLUS OLI (with MSE) Using the Aspen PLUS OLI Chemistry Generator

    65. 65 Aspen OLI Chemistry Generator

    66. 66 Aspen OLI Chemistry Generator

    67. 67 Aspen OLI Chemistry Generator

    68. 68 Aspen OLI Chemistry Generator

    69. 69 Aspen OLI Chemistry Generator

    70. 70 Aspen OLI Chemistry Generator

    71. 71 Aspen OLI Chemistry Generator

    72. 72 Aspen OLI Chemistry Generator

    73. 73 Aspen OLI Chemistry Generator

    74. 74 Aspen OLI Chemistry Generator

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    76. 76 Aspen OLI Chemistry Generator

    77. 77 Aspen OLI Chemistry Generator

    78. 78 Aspen OLI Chemistry Generator

    79. 79 Aspen OLI Chemistry Generator

    80. 80 Aspen OLI Chemistry Generator

    81. 81 Aspen OLI Chemistry Generator

    82. 82 Aspen OLI Chemistry Generator

    83. 83 Aspen OLI Chemistry Wizard

    84. 84 Aspen OLI Chemistry Wizard

    85. 85 Aspen OLI Chemistry Wizard

    86. 86 Aspen OLI Chemistry Wizard

    87. 87 Aspen OLI Chemistry Wizard

    88. 88 Aspen OLI Chemistry Wizard

    89. 89 Aspen OLI Chemistry Wizard

    90. 90 Aspen OLI Chemistry Wizard

    91. 91 Aspen OLI Chemistry Wizard

    92. 92 Aspen OLI Chemistry Wizard

    93. 93 Aspen OLI Chemistry Wizard

    94. 94 Aspen OLI Chemistry Wizard

    95. 95 Aspen OLI Chemistry Wizard

    96. 96 Aspen OLI Chemistry Wizard

    97. 97 Aspen OLI Chemistry Wizard

    98. 98 Aspen Plus 2006

    99. 99 Aspen Plus 2006

    100. 100 Aspen Plus 2006

    101. 101 Aspen Plus 2006

    102. 102 Aspen Plus 2006

    103. 103 Aspen Plus 2006

    104. 104 Aspen Plus 2006

    105. 105 Aspen Plus 2006

    106. 106 Aspen Plus 2006

    107. 107 Aspen Plus 2006

    108. 108 Aspen Plus 2006

    109. 109 Aspen Plus 2006

    110. 110 Aspen Plus OLI with EFRACH

    111. 111 Aspen Plus OLI with EFRACH

    112. 112 Aspen Plus OLI with EFRACH

    113. 113 Aspen Plus OLI with EFRACH

    114. 114 Aspen Plus OLI with EFRACH

    115. 115 Aspen Plus OLI with EFRACH

    116. 116 Aspen Plus OLI with EFRACH

    117. 117 Aspen Plus OLI with EFRACH

    118. 118 Aspen Plus OLI with EFRACH

    119. 119 Aspen Plus OLI with EFRACH

    120. 120 Aspen Plus OLI with EFRACH

    121. 121 Aspen OLI More examples? Live cases? Questions?

    122. 122 Conclusion 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

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