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Maurizio Fermeglia & Sabrina Pricl

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Presentation on theme: "Maurizio Fermeglia & Sabrina Pricl"— Presentation transcript:

1 COSMO-RS and process simulation: from physical properties to environmental impact …
Maurizio Fermeglia & Sabrina Pricl MOSE Lab, Department of Chemical Engineering, University of Trieste, Italy mose.units.it

2 COSMO-RS and process simulation: from physical properties to environmental impact … and beyond.
Maurizio Fermeglia & Sabrina Pricl MOSE Lab, Department of Chemical Engineering, University of Trieste, Italy mose.units.it

3 Outline of talk Introduction Applications Conclusions
Multiscale Molecular Modeling Applications EOS parameter estimation for pure components and mixtures Physical properties calculations for alternative refrigerants Prediction of solvent effect in enzymatic reactions Prediction of toxicological data to be used in process simulation Direct calculation of mesoscale parameters (DPD and Mesodyn) Conclusions

4 Multiscale Molecular Modeling
Characteristic Time years Engineering design Engineering design Message passing multiscale modeling hours Simulazione di processo FEM Process Simulation FEM minutes seconds Modellazione di mesoscala (insiemi di atomi o molecole) Mesoscale modeling (segments) Reverse mapping microseconds Meccanica molecolare (atomi) Molecular Mechanics (atoms) nanoseconds picoseconds Quantum Mechanics (electrons) Meccanica Quantistica (elettroni) femtoseconds 1nm 1nm 1μm 1μm 1mm 1mm 1m 1m Characteristic Length 4

5 Outline of talk Introduction Applications Conclusions
Multiscale Molecular Modeling Applications EOS parameter estimation for pure components and mixtures Physical properties calculations for alternative refrigerants Prediction of solvent effect in enzymatic reactions Prediction of toxicological data to be used in process simulation Direct calculation of mesoscale parameters (DPD and Mesodyn) Conclusions 5

6 Prediction of EOS parameters
Structural and Physico-chemical Data Molecular Modeling (MM) DFT/COSMO RS Calculations Vapor Pressure & Activity coeff. Estimation Molecular Volume and Surfaces EOS Parameters (PHSCT) pure & mixture Thermophysical Properties M. Fermeglia, S. Pricl, AIChE Journal 47: (2001)

7 PHSCT EOS: pure components
3 parameters: r, a and b recasting 3 parameters: s, e/k and r A* = p r s2NA From molecular area A V* = (p/6) r s3NA From molecular volume V E* = r (e/k) Rg From A*, V* and Ek/Ep From A*, V* and P0

8 The PHSCT EOS – mixtures

9 Simulation Protocol Pure Components Mixtures
Gibbs Energy calculation using COSMO RS for binary mixtures ..  estimation of binary kij Connolly dot surface algorithm corrected for quantum effects Molecular volumes and surfaces of HCCs and HCFCs Molecular volumes and surfaces of CH4 as reference A*, V* P0 at a given T E* DMol3 / Cosmotherm calculations M. Fermeglia, S. Pricl, AIChE Journal 47: (2001)

10 Chloro – Fluoro Hydrocarbons
Pure compounds C3H8 (R290) C3H2F6 (R236fa) C3H2F6 (R236ea) CH2F2 (R32) C2HF5 (R125) C3H3F5 (R245fa) C2H2F4 (R134a) C3OF8 (E218 ) C2SF6 C2OH6 (RE170) Mixtures

11 Pure component prediction
R20 CHCl3 R40 CH3Cl R143a C2H3F3 R114 C2Cl2F4 R125 C2HF5 R13 CClF3

12 Refrigerants: VLE and PVT predictions
Fermeglia and Pricl, Fluid Phase Equilibria, 158, 49-58, 1999 Fermeglia and Pricl, Fluid Phase Equilibria, 166, 21-37, 1999

13 EOS predictions – mixtures
@313.2K M. Fermeglia, S. Pricl, AIChE Journal 47: (2001)

14 EOS predictions – mixtures
@323K M. Fermeglia, S. Pricl, AIChE Journal 47: (2001)

15 Results for mixtures AVERAGE 4.39 0.02095 System T [K] RMSD Pv RMSD Y
hfc32-hfc134a 293 3.7 0.043 343 7.8 0.055 hfc32-hfc236ea 288 2.3 0.011 303 5.4 0.003 318 7.9 0.009 hfc32-hfc236fa 5.6 323 8.6 0.01 hfc125-hfc134a 283 0.8 0.014 hfc125-hfc236ea 0.6 1.1 2.7 0.015 hfc125-hfc236fa 1.3 3.6 0.018 hfc125-hfc245 298 0.7 0.006 313 r290-hfc236fa 1.7 3.1 7.5 0.047 r290-hfc245 5 0.016 17.1 0.103 AVERAGE 4.39 Results for mixtures

16 Process simulation The EOS is applied to simulate the process
Production of R 134a

17 Outline of talk Introduction Applications Conclusions
Multiscale Molecular Modeling Applications EOS parameter estimation for pure components and mixtures Physical properties calculations for alternative refrigerants Prediction of solvent effect in enzymatic reactions Prediction of toxicological data to be used in process simulation Direct calculation of mesoscale parameters (DPD and Mesodyn) Conclusions 17

18 Sustainability evaluation (of a process)…
Society Ecology Economy Sustainable Development Optimize the process at design time Cleaner production no end of pipes Process simulator Toxicological data prediction from MM Fermeglia M., Longo G., Toma L., AIChE J (2009) From Martins, 2006

19 PSP framework Collaboration with

20 PSP framework & Indexes
CAPE OPEN (CoLan) PSP Framework Toxicological data Process Simulators Molecular Modeling Process Design

21 Molecular modeling Fermeglia M., Longo G., Toma L., AIChE J (2009)

22 Human Toxicity Potential
Octanol-water partition coefficient Kow is used to calculate different properties Soil/sediment adsorption coefficients Bioconcentration Ingestion Kow Human Toxicity Potential Inhalation WAR (waste reduction algorithm): is an algorithm developed to evaluate potential environmental impacts for specific chemical processes. It is based upon equations of balance for environmental impact. In this case WAR was implemented with Cape Open (process simulation software) Dermal Exposure Aquatic Toxicity Potential Terrestrial Toxicity Potential Fermeglia M., Longo G., Toma L., Env.Progress (2008)

23 Kow-Results Substance logKow (exp) logKow calculated logKow RAD QSAR
COSMO RS Methanol -0.77 -0.63 -0.73 0.1818 0.0529 Naphthalene 3.3 3.17 3.09 0.0393 0.0625 Phenol 1.46 1.51 1.42 0.0192 Chloroform 1.97 1.52 2.1 0.2284 -0.066 Toluene 2.73 2.54 2.65 0.0696 0.0275 Anisole 2.11 2.07 2.23 0.0189 Methyl Ethyl Chloride 1.25 1.34 1.26 -0.072 0.0073 Benzene 2.13 1.99 0.0657 0.0121 Methane 1.09 0.78 1.02 0.2844 0.0677 Ethane 1.81 1.32 1.63 0.2707 0.0984 Propane 2.36 2.18 0.2330 0.0077 Benzoic Acid 1.87 2.24 The relative absolute deviation (RAD) between the experimental and the predicted method (QSAR e COSMO RS) has been calculated The error has lower values for when Kow is calculated using COSMO RS

24 Thermo-physical property
Available MM methods Used MM methods Results Octanol Water partition coefficient FEP+MC+MD QSAR % FEC+EEM MC CSM COSMO RS % Life time SAR % Reaction rate with Ozone 0-50% Reaction rate with hydroxyl GCM % ab-initio 0-40.2%

25 Processes developed and analyzed with PSP Framework
Acrylic Acid production process Sweetening natural gas by DGA absorption Formaldehyde production process Phthalic Anhydride production process Maleic Anhydride Production process Dimethylether production process Dimethylformamide production process R134a production process Fuel Ethanol production from sugar cane molasses (Cuba) Multiple Effect of Sugar Cane Juice (Mexico) Electroplating wastewater discharge process (Russia)

26 R-134a Production Process
Base Case Case2 Case3 Fermeglia M., Longo G., Toma L., AIChE J (2009)

27 3D Results: production of R-134a
B C D A) Material Intensity B) Energy Intensity C) Potential Chemical Risk D) Potential Environmental Impact

28 3D Results: production of R-134a
B C D A) Iout B) Iout /product mass C) Igen D) Igen/product mass Note: the energy production process is considered

29 Outline of talk Introduction Applications Conclusions
Multiscale Molecular Modeling Applications EOS parameter estimation for pure components and mixtures Physical properties calculations for alternative refrigerants Prediction of solvent effect in enzymatic reactions Prediction of toxicological data to be used in process simulation Direct calculation of mesoscale parameters (DPD and Mesodyn) Conclusions 29

30 Polymer blend PC - ABS Rear lamp of the FIAT Idea
Recycling of industrial scraps PC/ABS blends are promising for rear lamps PC: transparency and good mechanical properties ABS: reflecting properties, lower viscosity Side view Front view

31 Mesoscopic Dynamics (MesoDyn)
4/1/2017 Mesoscopic Dynamics (MesoDyn) real system = ideal system + an effective external potential + non ideal term polymer chain is the fundamental building block of the model The ideal term is described by non interacting Gaussian chains it allows a factorization of the interactions hence is computationally very efficient The non – ideal term takes into account interchain, i.e., non-bonded, interactions Interchain reactions The molecular ensemble is represented by n Gaussian chains, made up of m beads of types J with a total number of N beads per chain Fraaije, J.G.E, et al., J. Chem. Phys. 106(10), 1997 Confidential

32 Mesoscopic Dynamics (MesoDyn)
4/1/2017 Mesoscopic Dynamics (MesoDyn) Free energy equation = ideal + external potential + non ideal The nonideal term (interaction among chains) where εIJ(r-r‘) is a cohesive interaction between beads I and J (Gaussian form) F-H χ Confidential

33 Input parameters for MesoDyn
4/1/2017 Input parameters for MesoDyn The most important parameters for MesoDyn are the bead size and Gaussian chain architecture the bead mobility M, the effective Flory-Huggins interactions e ij Obtained by molecular modeling tools: bead size and Gaussian chain architecture: by Molecular Dynamics from characteristic ratio (C) in terms of Kuhn length mobility: by Molecular Dynamics Bead self diffusion coefficients FH interactions: by COSMO - RS Bead – bead interactions Gibbs Energy with COSMO RS for binary mixtures of molecules containing same groups of beads ..  estimation of binary Xij Fermeglia M., Cosoli P., Ferrone M., Piccarolo S., Mensitieri G., Pricl S. Polymer 47: (2006) Confidential

34 PC and ABS modeling assumptions
Modeling at mesoscale level ABS is modeled by three different structures Styrene Acrylonitrile block copolymer (SAN) Butadiene homopolymer (POLYB) A branched macromolecule SAN-POLYB-SAN (backbone butadiene) PC is modeled by two different fragments Need of constant bead dimensions ABS blend structure Polycarbonate; PC monomer was split in 2 fragments in simulations

35 Mesoscale results Segregation occurs for all the systems investigated
4/1/2017 Mesoscale results AN S B PC Segregation occurs for all the systems investigated Morphology: islands of AN (blue) are surrounded by S (cyan) S enwraps the AN segments S shields PC from unfavorable interactions with the polar AN SAN engulfs the B (purple) domains Shear effect (elongated phases) PC B AN S Lo stesso per tutti gli altri sistemi Confidential

36 Morphology and phase behavior
Validation of multiscale approach with TEM analysis PC/ABS simulations Mesodyn density field compared with TEM (S.Wang et. Al., 2002) Same morphology PC B AN S

37 From beads … to micro: fixed grid
Dissipative Particle Dynamics Micro - FEM Simulation FEM Analysis: Macroscopic properties Soft potentials calculations Fi = f (aii, aij, …, rc ) Characteristic dimension of mesoscopic system Geometry: map cubes to Palmyra tetrahedrons Laplace equation is solved for electric conductance, diffusion and permeability Local deformation allow the calculation of mechanical properties

38 FEM results: properties
PC/ABS 15/85 35/65 55/45 85/15 Young modulus [GPa] 2.40 2.39 2.35 2.34 Shear modulus [GPa] 8.6·10-1 8.5·10-1 8.3·10-1 Bulk modulus [GPa] 4.15 4.38 4.55 4.85 Thermal expansion coefficient [K-1] 6.92·10-5 6.80·10-5 6.72·10-5 6.56·10-5 Bayblend® T 85 (Bayer) 85/15 PC/ABS Young Modulus [Gpa] 2.30 2.34 Thermal expansion coefficient [K-1] 7.5*10-5 6.56*10-5 Calculated material properties (top) and comparison with experimental data* (bottom) *

39 Conclusions: the role of COSMO RS
COSMO RS has a role in Multiscale Modelling Directly At QM level Calculate interaction energy for molecules and fragments AS a ‘message generator’ To avoid long MD and MC calculations .. To mesoscale DPD and Mesodyn (FH parameter) .. To process simulators (EOS parameters) Applications Phase equilibrium Physical properties for PS Toxicological data Polymer blends Diblock copolymers phase behavior

40 Acknowledgements Personeel Research Support: material science
EU MoMo Project, VI FP grant on Molecular Modelling EU MULTIPRO Project,VI FP grant on hybrid material EU MULTIHYBRID IP Project VI FP on PCNs and CNT EU NanoModel Project VII FP on Multiscale Modeling Ministry of University, Italy, PRIN 2002, 03, 05, 06 SIPA Zoppas Ind. research grant Centro Ricerche Plast Optica – FIAT ALRI (Automotive Lighting Rear Lamp) Industrial collaborations: Solvay, Karton, Caffaro, Serichim Collaborations Martin Lisal, Academy of Science, Czech Republic Marek Maly, Purkinje University, Czech Republic Laura Martinelli, Sabino Sinesi, CRP FIAT Research Andrea Danani, SUPSI, Lugano, Switzerland Hans Fraije, Culgi, The NEtherland Fernando DelaVega, Cimananotech, Israel Loredana Incarnato, Giovanna Russo, University of Salerno), Italy Peppe Mensitieri, University of Naples, Italy Stefano Piccarolo, University of Palermo, Italy Gianluca Cicala, University of Catania, Italy Emo Chiellini, University of Pisa, Italy Lucia Comper, Andrea Morellato, Zoppas Ind., Italy …… Personeel 2 Staf: Maurizio Fermeglia - Sabrina Pricl 4 research contracts Marco Ferrone -Andrea Metzgez - Maria Silvia Paneni – Radovan Toth 6 PHD students Letitia Toma - Paolo Cosoli – Giulio Scocchi – Paola Posocco - Giovanni Maria Pavan – Iztok Bajc Variable number of master students (3-5)


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