herramientas computacionales para la modelización y...
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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
j.ramos@iem.cfmac.csic.es
Webinar, 27 de Noviembre 2014
Anteriores webinars
Como conseguir los videos y las presentaciones de anteriores webminars:
Linkedin: Grupo de Química Computacional
http://www.linkedin.com/groups/Química-computacional-7487634
http://www.addlink.es/eventos-materials-studio
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
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
Índice
Materials Studio Tools for Polymers
Synthia
Blends
Mesocite
Mesodyn
DPD
Mesoscale and
coarse-grained tools
Equilibria
Amorphous Builder
Conformers
Forcite & Discover Atomistic tools
Compass Force Field
Statistical tools (QSPR). Bicerano
Crystal Builder
Materials Studio Tools for Polymers
Synthia
Blends
Mesocite
Mesodyn
DPD
Mesoscale and
coarse-grained tools
Equilibria
Amorphous Builder
Conformers
Forcite & Discover Atomistic tools
Compass Force Field
Statistical tools (QSPR). Bicerano
Crystal Builder
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, 201-208
Kaszonyiova M. et al, “Polymorphism of isotactic poly(butene-1)”, J. Macrom. Sci. Part B: Physics 2005, 44:377-396
File import: cr0447.cif
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, 201-208
Kaszonyiova M. et al, “Polymorphism of isotactic poly(butene-1)”, J. Macrom. Sci. Part B: Physics 2005, 44:377-396
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, 201-208
Kaszonyiova M. et al, “Polymorphism of isotactic poly(butene-1)”, J. Macrom. Sci. Part B: Physics 2005, 44:377-396
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, 201-208
Kaszonyiova M. et al, “Polymorphism of isotactic poly(butene-1)”, J. Macrom. Sci. Part B: Physics 2005, 44:377-396
Reflex: Powder diffraction
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.
Building Repeat Unit
Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units
Building Repeat Unit
Materials Studio includes an extensive library of common monomer units, but it can also be used with custom repeat units
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
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
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, 311-330.
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, 7338-7364.
Sun, H., Ren, P., and Fried, J. R.,“The COMPASS Forcefield: Parameterization and Validation for Phosphazenes,” Comput. Theor. Polymer Sci., 1998, 8, 229-246.
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, 311-330.
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, 7338-7364.
Sun, H., Ren, P., and Fried, J. R.,“The COMPASS Forcefield: Parameterization and Validation for Phosphazenes,” Comput. Theor. Polymer Sci., 1998, 8, 229-246.
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, 311-330.
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, 7338-7364.
Sun, H., Ren, P., and Fried, J. R.,“The COMPASS Forcefield: Parameterization and Validation for Phosphazenes,” Comput. Theor. Polymer Sci., 1998, 8, 229-246.
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, …
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, 1985 18 (7), 1467-1478
Ramos J, Peristeras LD, Theodorou D.N . “Monte Carlo simulation of short chain branched polyolefins in the molten state” Macromolecules, 2007, 40 (26), 9640-9650
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, 1985 18 (7), 1467-1478
Ramos J, Peristeras LD, Theodorou D.N . “Monte Carlo simulation of short chain branched polyolefins in the molten state” Macromolecules, 2007, 40 (26), 9640-9650
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
Structure by growing polymers into a box in a stepwise manner using “look ahead”.
Growth chain
New Segment
Growth chain
New Segment
Theodorou D.N and Sutter UW “Detailed molecular structure of a vinyl polymer glass”, Macromolecules, 1985 18 (7), 1467-1478
Ramos J, Peristeras LD, Theodorou D.N . “Monte Carlo simulation of short chain branched polyolefins in the molten state” Macromolecules, 2007, 40 (26), 9640-9650
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
Structure by growing polymers into a box in a stepwise manner using “look ahead”.
Growth chain
New Segment
Growth chain
New Segment
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, 1985 18 (7), 1467-1478
Ramos J, Peristeras LD, Theodorou D.N . “Monte Carlo simulation of short chain branched polyolefins in the molten state” Macromolecules, 2007, 40 (26), 9640-9650
Amorphous builder
poly(p-dioxanone)
(PPDO)
poly(etherester)
Tail
Head
Build a polymer with 10 repeat units.
Amorphous builder
poly(p-dioxanone)
(PPDO)
poly(etherester)
Tail
Head
Build a polymer with 10 repeat units.
Amorphous builder
poly(p-dioxanone)
(PPDO)
poly(etherester)
Tail
Head
Build a polymer with 10 repeat units.
Amorphous builder => Equilibration
Before Minimization 442.4 kcal/mol
After Minimization 332.5 kcal/mol
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.
Amorphous builder => Equilibration (Example)
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, 719−724
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, 719−724
Example: Solubility parameter of PPDO and PVph from atomistic simulations
NVT 200ps, 298K
COMPASS
PPDO PVph
δexp = 27.4 (J/cm3)0.5 (ε = 9%) δexp = 24.5 (J/cm3)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, 719−724
Example: Solubility parameter of PPDO and PVph from atomistic simulations
NVT 200ps, 298K
COMPASS
PPDO PVph
δexp = 27.4 (J/cm3)0.5 (ε = 9%) δexp = 24.5 (J/cm3)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, 719−724
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).
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).
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).
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).
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).
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, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
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, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
(trifluoropropyl)8Si8O12
(FP-POSS)
Example: Binary mixtures of PVDF and POSS
poly(vinylidene difluoride) (PVDF)
(ethyl)8Si8O12
(E-POSS)
Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
(trifluoropropyl)8Si8O12
(FP-POSS)
Example: Binary mixtures of PVDF and POSS
poly(vinylidene difluoride) (PVDF)
(ethyl)8Si8O12
(E-POSS)
Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
(trifluoropropyl)8Si8O12
(FP-POSS)
Example: Binary mixtures of PVDF and POSS
poly(vinylidene difluoride) (PVDF)
(ethyl)8Si8O12
(E-POSS)
Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
(trifluoropropyl)8Si8O12
(FP-POSS)
Example: Binary mixtures of PVDF and POSS
poly(vinylidene difluoride) (PVDF)
(ethyl)8Si8O12
(E-POSS)
Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
(trifluoropropyl)8Si8O12
(FP-POSS)
Example: Binary mixtures of PVDF and POSS
poly(vinylidene difluoride) (PVDF)
(ethyl)8Si8O12
(E-POSS)
Zeng et al. «Molecular simulations of the miscibility in binary mixtures of PVDF and POSS compounds», Modelling Simul. Mater. Sci. Eng., 2009, 17, 075002
Zeng et al. «Nanoindentation, Nanoscratch, and Nanotensile Testing of PVDF-POSS Nanocomposites», J. POL. SCI.: PART B: POL. PHYS. 2012, 50, 1597–161
Dissipative Particle Dynamics (DPD) Simulations of polymer systems
A bead (CG particle) is defined as a set of atoms
Dissipative Particle Dynamics (DPD) Simulations of polymer systems
Three forces are considered
Conservative force (soft repulsion)
Dissipative force Random force
A bead (CG particle) is defined as a set of atoms
Dissipative Particle Dynamics (DPD) Simulations of polymer systems
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 bead (CG particle) is defined as a set of atoms
Dissipative Particle Dynamics (DPD) Simulations of polymer systems
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 bead (CG particle) is defined as a set of atoms
A harmonic spring keeps the chain connectivity
Example: Phase behavior of a loaded amphiphilic copolymer
Water : 90.2%
DMF : 4.7%
Paclitaxel : 1.9%
EO11- LLA9 : 3.2%
Water : 52.2%
DMF : 2.8%
Paclitaxel : 17.6%
EO11- LLA9 : 27.4%
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
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
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