Herramientas computacionales para la modelización y simulación de polímeros en Materials Studio 7.0
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1 Herramientas computacionales para la modelización y simulación de polímeros en Materials Studio 7.0 Javier Ramos Biophysics of Macromolecular Systems group (BIOPHYM) Departamento de Física Macromolecular Instituto de Estructura de la Materia CSIC [email protected] Webinar, 27 de Noviembre 2014
2 Anteriores webinars Introducción a Materials Studio en la Investigación Química y de Ciencias de los Materiales. Mecánica y Dinámica Molecular con Forcite en Materials Studio Herramientas mecano-cuánticas basadas en DFT para el estudio de moléculas y materiales en Materials Studio 7.0 Como conseguir los videos y las presentaciones de anteriores webminars: Linkedin: Grupo de Química Computacional
3 Índice Materials Studio tools for polymers Building and characterizing a polymer crystal Building a repeat unit (monomer) Building a polymer chain Forcite & Compass Force Field (Atomistic simulations) Amorphous builder Example: Solubility parameter of PPDO and PVph from atomistic simulations Blends Module Example: Binary mixtures of PVDF and POSS DPD Simulations of polymer systems Example: Phase behavior of a loaded amphiphilic copolymer Synthia module Example: Properties of an acrylamide random copolymer
4 Materials Studio Tools for Polymers Amorphous Builder Crystal Builder Forcite & Discover Conformers Atomistic tools Compass Force Field Equilibria Blends Mesocite Mesodyn DPD Synthia Mesoscale and coarse-grained tools Statistical tools (QSPR). Bicerano
5 Materials Studio Tools for Polymers Amorphous Builder Crystal Builder Forcite & Discover Conformers Atomistic tools Compass Force Field Equilibria Blends Mesocite Mesodyn DPD Synthia Mesoscale and coarse-grained tools Statistical tools (QSPR). Bicerano
6 Building and characterizing a polymer crystal File import: cr0447.cif Poly(1-butene) Dorset DL et al. Direct determination of polymer crystal structures by electron crystallography Isotactic Poly(1-butene), Form(III), Acta Cryst. 1994, B50, Kaszonyiova M. et al, Polymorphism of isotactic poly(butene-1), J. Macrom. Sci. Part B: Physics 2005, 44:
7 Building and characterizing a polymer crystal Poly(1-butene) Dorset DL et al. Direct determination of polymer crystal structures by electron crystallography Isotactic Poly(1-butene), Form(III), Acta Cryst. 1994, B50, Kaszonyiova M. et al, Polymorphism of isotactic poly(butene-1), J. Macrom. Sci. Part B: Physics 2005, 44:
8 Building and characterizing a polymer crystal Poly(1-butene) Dorset DL et al. Direct determination of polymer crystal structures by electron crystallography Isotactic Poly(1-butene), Form(III), Acta Cryst. 1994, B50, Kaszonyiova M. et al, Polymorphism of isotactic poly(butene-1), J. Macrom. Sci. Part B: Physics 2005, 44:
9 Building and characterizing a polymer crystal Poly(1-butene) Reflex: Powder diffraction Dorset DL et al. Direct determination of polymer crystal structures by electron crystallography Isotactic Poly(1-butene), Form(III), Acta Cryst. 1994, B50, Kaszonyiova M. et al, Polymorphism of isotactic poly(butene-1), J. Macrom. Sci. Part B: Physics 2005, 44:
10 Building and characterizing a polymer crystal Reflex is the module that allows you to simulate and analyze X-ray, electron and neutron diffraction data. Pattern processing: Data processing on experimental power diffraction data. Powder diffraction: Powder diffraction simulation of a polymer crystal. Powder Indexing: Search all possible space groups given an experimental powder diffraction pattern and a unit cell. Powder Refinement: Both Pawley and Rietveld refinement of a crystal structure against experimental data. Powder QPA: Determination of relative amounts of different phases in a mixture. Powder Cristallinity: Determination of the degree of crystallinity of a sample from X-ray powder diffraction pattern. Powder Solve: Simulated annealing to determine the positions, orientations and conformations of molecules within a crystal lattice which minimize the difference between simulated and experimental X-ray or neutron powder diffraction patterns.
11 Building Repeat Unit Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units
12 Building Repeat Unit Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units
13 Building Repeat Unit Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units Building a repeat unit 3,3,4,4 -BPDA-ODA 3,3,4,4 -BisPhenyleneDiamine-Oxydianiline
14 Building Repeat Unit Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units Building a repeat unit 3,3,4,4 -BPDA-ODA 3,3,4,4 -BisPhenyleneDiamine-Oxydianiline
15 Building a polymer chain
16 Building a polymer chain Monomer 1 Monomer 3 Monomer 2
17 Forcite & Compass Force Field (Atomistic simulations) Rigby, et al. Computer Simulations of Poly(ethylene oxide): Forcefield, PVT Diagram and Cyclization Behavior, Polymer International, 1997, 44, Sun, H., COMPASS: An Ab Initio Forcefield Optimized for Condensed-Phase Application-Overview with Details on Alkane and Benzene Compounds, J. Phys. Chem., 1998, B102, Sun, H., Ren, P., and Fried, J. R., The COMPASS Forcefield: Parameterization and Validation for Phosphazenes, Comput. Theor. Polymer Sci., 1998, 8,
18 Forcite & Compass Force Field (Atomistic simulations) Rigby, et al. Computer Simulations of Poly(ethylene oxide): Forcefield, PVT Diagram and Cyclization Behavior, Polymer International, 1997, 44, Sun, H., COMPASS: An Ab Initio Forcefield Optimized for Condensed-Phase Application-Overview with Details on Alkane and Benzene Compounds, J. Phys. Chem., 1998, B102, Sun, H., Ren, P., and Fried, J. R., The COMPASS Forcefield: Parameterization and Validation for Phosphazenes, Comput. Theor. Polymer Sci., 1998, 8,
19 Forcite & Compass Force Field (Atomistic simulations) COMPASS: Condensed-phase Optimized Molecular Potentials for Atomistic Simulation Studies Alkanes, alkanes, alkynes, aromatics, cycloalkanes, Ethers, acetals, alcohols, phenols, amines, ammonia, aldehyde, ketones, acids, esters, carbonates, amides, carbamate, siloxanes, silanes, halides, phosphazenes, nitro groups, nitriles, isocyanides, sulfides, thiols, amineoxides, cyanamides, nitrates, sulfates, solfonates, metals, Rigby, et al. Computer Simulations of Poly(ethylene oxide): Forcefield, PVT Diagram and Cyclization Behavior, Polymer International, 1997, 44, Sun, H., COMPASS: An Ab Initio Forcefield Optimized for Condensed-Phase Application-Overview with Details on Alkane and Benzene Compounds, J. Phys. Chem., 1998, B102, Sun, H., Ren, P., and Fried, J. R., The COMPASS Forcefield: Parameterization and Validation for Phosphazenes, Comput. Theor. Polymer Sci., 1998, 8,
20 Amorphous builder This module allows one to build in a Monte Carlo fashion a 3D-periodic structure of molecular liquids and amorphous polymeric systems. Theodorou D.N and Sutter UW Detailed molecular structure of a vinyl polymer glass, Macromolecules, (7), Ramos J, Peristeras LD, Theodorou D.N. Monte Carlo simulation of short chain branched polyolefins in the molten state Macromolecules, 2007, 40 (26),
21 Amorphous builder This module allows one to build in a Monte Carlo fashion a 3D-periodic structure of molecular liquids and amorphous polymeric systems. Torsions are determined by the selected force field (continuous rather than discrete RIS). If not torsion angles are available the molecule will be treated as a rigid body Boltzmann distribution of the torsional potential Theodorou D.N and Sutter UW Detailed molecular structure of a vinyl polymer glass, Macromolecules, (7), Ramos J, Peristeras LD, Theodorou D.N. Monte Carlo simulation of short chain branched polyolefins in the molten state Macromolecules, 2007, 40 (26),
22 Amorphous builder This module allows one to build in a Monte Carlo fashion a 3D-periodic structure of molecular liquids and amorphous polymeric systems. Torsions are determined by the selected force field (continuous rather than discrete RIS). If not torsion angles are available the molecule will be treated as a rigid body Structure by growing polymers into a box in a stepwise manner using look ahead. New Segment New Segment Boltzmann distribution of the torsional potential Growth chain Growth chain Theodorou D.N and Sutter UW Detailed molecular structure of a vinyl polymer glass, Macromolecules, (7), Ramos J, Peristeras LD, Theodorou D.N. Monte Carlo simulation of short chain branched polyolefins in the molten state Macromolecules, 2007, 40 (26),
23 Amorphous builder This module allows one to build in a Monte Carlo fashion a 3D-periodic structure of molecular liquids and amorphous polymeric systems. Torsions are determined by the selected force field (continuous rather than discrete RIS). If not torsion angles are available the molecule will be treated as a rigid body Structure by growing polymers into a box in a stepwise manner using look ahead. New Segment New Segment Boltzmann distribution of the torsional potential Growth chain Growth chain Close contacts are reject (overlap criterion). If the molecules contain rings -> Check for ring smearing Theodorou D.N and Sutter UW Detailed molecular structure of a vinyl polymer glass, Macromolecules, (7), Ramos J, Peristeras LD, Theodorou D.N. Monte Carlo simulation of short chain branched polyolefins in the molten state Macromolecules, 2007, 40 (26),
24 Amorphous builder poly(etherester) Head Tail poly(p-dioxanone) (PPDO) Build a polymer with 10 repeat units.
25 Amorphous builder poly(etherester) Head Tail poly(p-dioxanone) (PPDO) Build a polymer with 10 repeat units.
26 Amorphous builder poly(etherester) Head Tail poly(p-dioxanone) (PPDO) Build a polymer with 10 repeat units.
27 Amorphous builder => Equilibration
28 Amorphous builder => Equilibration
29 Amorphous builder => Equilibration Before Minimization kcal/mol After Minimization kcal/mol
30 Amorphous builder => Equilibration (Example) 1. Equilibration protocol a) Geometry Optimization b) NVT-MD, 750K, 30 ps c) NVT-MD, 600K, 20 ps d) NVT-MD, 450K, 20 ps e) NVT-MD, 303 K, 100 ps f) NPT-MD, 303K,100 ps 2. Production protocol a) NPT-MD, 303K, 1000 ps or b) NVT-MD, 303K, 1000 ps.
31 Example: Solubility parameter of PPDO and PVph from atomistic simulations NVT 200ps, 298K COMPASS PPDO PVph Martínez de Arenaza I et al. Competing Specific Interactions Investigated by Molecular Dynamics: Analysis of Poly(p dioxanone)/poly(vinylphenol) Blends, J. Phys. Chem. B 2013, 117,
32 Example: Solubility parameter of PPDO and PVph from atomistic simulations NVT 200ps, 298K COMPASS PPDO PVph Martínez de Arenaza I et al. Competing Specific Interactions Investigated by Molecular Dynamics: Analysis of Poly(p dioxanone)/poly(vinylphenol) Blends, J. Phys. Chem. B 2013, 117,
33 Example: Solubility parameter of PPDO and PVph from atomistic simulations NVT 200ps, 298K COMPASS PPDO PVph δ exp = 27.4 (J/cm 3 ) 0.5 (ε = 9%) δ exp = 24.5 (J/cm 3 ) 0.5 (ε = 12%) Martínez de Arenaza I et al. Competing Specific Interactions Investigated by Molecular Dynamics: Analysis of Poly(p dioxanone)/poly(vinylphenol) Blends, J. Phys. Chem. B 2013, 117,
34 Example: Solubility parameter of PPDO and PVph from atomistic simulations NVT 200ps, 298K COMPASS PPDO PVph δ exp = 27.4 (J/cm 3 ) 0.5 (ε = 9%) δ exp = 24.5 (J/cm 3 ) 0.5 (ε = 12%) Martínez de Arenaza I et al. Competing Specific Interactions Investigated by Molecular Dynamics: Analysis of Poly(p dioxanone)/poly(vinylphenol) Blends, J. Phys. Chem. B 2013, 117,
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38 Blends Module Miscibility of polymers => Extended Flory-Huggins model Molecular segments are no longer required to be on a regular lattice (off-lattice) Explicit temperature dependence of χ(t) is taken into account. Fan, C. F.; Olafson, B. D.; Blanco, M.; Hsu, S. L. Application of Molecular Simulation To Derive Phase Diagrams of Binary Mixtures. Macromolecules, 25, 3667 (1992).
39 Blends Module Miscibility of polymers => Extended Flory-Huggins model Molecular segments are no longer required to be on a regular lattice (off-lattice) Explicit temperature dependence of χ(t) is taken into account. Fan, C. F.; Olafson, B. D.; Blanco, M.; Hsu, S. L. Application of Molecular Simulation To Derive Phase Diagrams of Binary Mixtures. Macromolecules, 25, 3667 (1992).
40 Blends Module Miscibility of polymers => Extended Flory-Huggins model Molecular segments are no longer required to be on a regular lattice (off-lattice) Explicit temperature dependence of χ(t) is taken into account. Fan, C. F.; Olafson, B. D.; Blanco, M.; Hsu, S. L. Application of Molecular Simulation To Derive Phase Diagrams of Binary Mixtures. Macromolecules, 25, 3667 (1992).
41 Blends Module Miscibility of polymers => Extended Flory-Huggins model Molecular segments are no longer required to be on a regular lattice (off-lattice) Explicit temperature dependence of χ(t) is taken into account. Fan, C. F.; Olafson, B. D.; Blanco, M.; Hsu, S. L. Application of Molecular Simulation To Derive Phase Diagrams of Binary Mixtures. Macromolecules, 25, 3667 (1992).
42 Blends Module Miscibility of polymers => Extended Flory-Huggins model Molecular segments are no longer required to be on a regular lattice (off-lattice) Explicit temperature dependence of χ(t) is taken into account. Advantages : Quick evaluation of the miscibility of two components Disadvantages: Isolated molecular segment interactions = Bulk polymer interaction????? Fan, C. F.; Olafson, B. D.; Blanco, M.; Hsu, S. L. Application of Molecular Simulation To Derive Phase Diagrams of Binary Mixtures. Macromolecules, 25, 3667 (1992).
43 Blends Module Setting up Blends Module calculations in Materials Studio
44 Blends Module Setting up Blends Module calculations in Materials Studio
45 Blends Module Setting up Blends Module calculations in Materials Studio
46 Example: Binary mixtures of PVDF and POSS Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
47 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
48 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) (ethyl) 8 Si 8 O 12 (E-POSS) (trifluoropropyl) 8 Si 8 O 12 (FP-POSS) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
49 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) (ethyl) 8 Si 8 O 12 (E-POSS) (trifluoropropyl) 8 Si 8 O 12 (FP-POSS) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
50 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) (ethyl) 8 Si 8 O 12 (E-POSS) (trifluoropropyl) 8 Si 8 O 12 (FP-POSS) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
51 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) (ethyl) 8 Si 8 O 12 (E-POSS) (trifluoropropyl) 8 Si 8 O 12 (FP-POSS) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
52 Example: Binary mixtures of PVDF and POSS poly(vinylidene difluoride) (PVDF) (ethyl) 8 Si 8 O 12 (E-POSS) (trifluoropropyl) 8 Si 8 O 12 (FP-POSS) Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50,
53 Dissipative Particle Dynamics (DPD) Simulations of polymer systems
54 Dissipative Particle Dynamics (DPD) Simulations of polymer systems A bead (CG particle) is defined as a set of atoms
55 Dissipative Particle Dynamics (DPD) Simulations of polymer systems A bead (CG particle) is defined as a set of atoms Three forces are considered Conservative force (soft repulsion) Dissipative force Random force
56 Dissipative Particle Dynamics (DPD) Simulations of polymer systems A bead (CG particle) is defined as a set of atoms Three forces are considered Conservative force (soft repulsion) Dissipative force Random force Groot and Warren made a link between the repulsive parameter and the Flory Huggins parameters.
57 Dissipative Particle Dynamics (DPD) Simulations of polymer systems A bead (CG particle) is defined as a set of atoms Three forces are considered Conservative force (soft repulsion) Dissipative force Random force Groot and Warren made a link between the repulsive parameter and the Flory Huggins parameters. A harmonic spring keeps the chain connectivity
58 DPD Simulations of polymer systems Hydrophilic Hydrophobic
59 DPD Simulations of polymer systems Setting up DPD Module calculations in Materials Studio
60 DPD Simulations of polymer systems Setting up DPD Module calculations in Materials Studio
61 DPD Simulations of polymer systems Setting up DPD Module calculations in Materials Studio
62 DPD Simulations of polymer systems Setting up DPD Module calculations in Materials Studio
63 DPD Simulations of polymer systems Setting up DPD Module calculations in Materials Studio
64 Example: Phase behavior of a loaded amphiphilic copolymer Water : 90.2% DMF : 4.7% Paclitaxel : 1.9% EO 11 - LLA 9 : 3.2% Water : 52.2% DMF : 2.8% Paclitaxel : 17.6% EO 11 - LLA 9 : 27.4%
65 Synthia By using empirical correlation methods, large numbers of polymers, or copolymers of varying composition, can be rapidly screened for desired properties. QSPR methods are fast, provide large numbers of properties, and are the easiest modeling tool to use Synthia is based on work conducted by Dr. Bicerano of The Dow Chemical Company, where the methodology has been extensively tested in practical work
66 Synthia By using empirical correlation methods, large numbers of polymers, or copolymers of varying composition, can be rapidly screened for desired properties. QSPR methods are fast, provide large numbers of properties, and are the easiest modeling tool to use Synthia is based on work conducted by Dr. Bicerano of The Dow Chemical Company, where the methodology has been extensively tested in practical work
67 Synthia
68 Synthia
69 Synthia
70 Example: Properties of an acrylamide random copolymer Random copolymer
71 Example: Properties of an acrylamide random copolymer Random copolymer N-benzyl N-benzyl N-methyl N-methyl
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