Coarse-Grained Modeling of Polymer Nanocomposites: Field-Theoretic Simulations

Koski, Jason; Chao, Huikuan; Tabedzki, Christian; Riggleman, Robert A.

doi:10.1007/978-3-030-60443-1_3

Cited by 4 publications

(10 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In all simulations, we use TILD, 26,27 previously referred to as dynamic mean-field theory (DMFT). 25,33,39,40 TILD is a particle simulation method that is based on a Langevin equation of motion.…”

Section: Model and Methodsmentioning

confidence: 99%

“…The details of the TILD implementation are described in our previous work. [25][26][27]33,39,40 2.1. Model.…”

Section: Model and Methodsmentioning

confidence: 99%

“…In all simulations, we use TILD, , previously referred to as dynamic mean-field theory (DMFT). ,,, TILD is a particle simulation method that is based on a Langevin equation of motion. The bonded interactions are evaluated between discrete particles (monomers and NPs), while the nonbonded interactions are evaluated between species densities, interpolated to a grid using a particle-to-mesh scheme.…”

Section: Model and Methodsmentioning

confidence: 99%

“…The TILD code used in this work is parallelized using OpenMP and thus runs on single nodes but utilizes all the cores on the node. The details of the TILD implementation are described in our previous work. − ,,, …”

Section: Model and Methodsmentioning

confidence: 99%

“…The chains are permanently grafted to specific grafting sites on the NP surfaces and hence not allowed to move. We use a relatively new simulation method, theoretically informed Langevin dynamics (TILD), which uses Langevin dynamics to sample the dynamic partition function of the system. − The coordinates of each polymer and NP are explicitly tracked using a particle representation, while the nonbonded interactions are calculated using density fields generated from a particle-to-mesh scheme. The TILD framework is similar to other methods that implement a particle-to-mesh scheme to interpolate from a particle-based model to a field-based model, such as self-consistent Brownian dynamics, single-chain-in-mean-field, and theoretically informed coarse-grained simulations .…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Self-Assembled Vesicles from Mixed Brush Nanoparticles in Solution

Koski

Frischknecht

2021

Macromolecules

Self Cite

View full text Add to dashboard Cite

The self-assembly of binary polymer-grafted nanoparticles (NPs) in a selective solvent is investigated using coarse-grained simulations. Simulations are performed using theoretically informed Langevin dynamics (TILD), a particle-based method that employs a particle-to-mesh scheme to efficiently calculate the nonbonded interactions. The particles are densely grafted with two immiscible polymers, A and B, that are permanently bound to the NP either at random grafting sites (random-grafted) or with all the A chains on one hemisphere of the NP and all the B chains on the other hemisphere (Janus-grafted). For NPs with random grafting, the polymers phase-separate on the surface of the NP to form Janus-type structures in dilute solution, even though some of the chains have to stretch around the particle to form the Janus structure. When the solvent quality is sufficiently poor for the solvophobic chains, the binary grafted NPs assemble into various structures, including double-walled vesicles. In particular, vesicles are formed when the solvophilic volume fraction is between 0.2 and 0.3, in a similar range to that required for vesicle formation in diblock copolymers in a selective solvent. For mixed-grafted NPs, there is considerable variation in the structure of each individual NP, but nevertheless, these NPs form ordered vesicles, similar to those formed by Janus-grafted NPs.

show abstract

Section: Model and Methodsmentioning

confidence: 99%

“…The details of the TILD implementation are described in our previous work. [25][26][27]33,39,40 2.1. Model.…”

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Self-Assembled Vesicles from Mixed Brush Nanoparticles in Solution

Koski

Frischknecht

2021

Macromolecules

Self Cite

View full text Add to dashboard Cite

show abstract

Phase Behavior of Polymer-Grafted Nanoparticles in Homopolymer Blends from Simulations

Santos

Frischknecht

2022

Macromolecules

View full text Add to dashboard Cite

The phase behavior of polymer-grafted nanoparticles (gNPs) in homopolymer matrices is investigated using coarsegrained simulations. Simulations are performed using theoretically informed Langevin dynamics (TILD), a particle-based method that uses a particle-to-mesh scheme to efficiently calculate the nonbonded interactions. Direct two-phase simulations are used to determine coexistence curves. The phase diagram for NPs densely grafted with short A chains and blended with long B homopolymer chains is significantly shifted compared to that for an AB homopolymer blend with chains of the same lengths. This is due to a loss of chain configurational entropy for the long B matrix chains to penetrate the polymer brushes around the gNPs. Adding additional A homopolymer to the polymer matrix leads to an increase in miscibility of the gNPs on the gNP-rich side of the phase diagram. The extra A homopolymer helps to compatibilize the interface between the gNPs and the matrix B chains. Our results are consistent with both experiments and modeling of poly(methyl methacrylate) (PMMA)-grafted silica NPs in poly(styrene-ran-acrylonititrile) (SAN) and PMMA-NP/SAN/PMMA composites.

show abstract

Increases in Miscibility of a Binary Polymer Blend Confined within a Nanoparticle Packing

et al. 2023

Self Cite

View full text Add to dashboard Cite

Despite various physical and chemical strategies that have been explored, compatibilization of polymer blends has proved elusive. Confinement of polymers has shown to induce substantial and at times unexpected changes in glass-transition temperature, dynamics, and morphology of these materials. Although confinement of blends to thin films have shown to influence phase separation structure and chain mobility, the impact of confinement on the miscibility of polymer mixtures is much less understood. Here, we present a computational study using field-theoretic simulations to understand the thermodynamics of polymer blends that are confined in the interstices of nanoparticle packings where both polymers have neutral interactions with the nanoparticle surfaces. We calculate their binodal phase envelopes and show that two polymers that would undergo macroscopic phase separation become miscible when they are subjected to extreme nanoconfinement. The strength of the repulsion required to induce phase separation increases significantly as confinement increases. We find that this enhanced miscibility is driven by both an increase in entropic penalty upon phase separation and a decrease in enthalpic repulsion with increasing confinement. We relate the change in enthalpy to a reduction in the number of polymer−polymer contacts near nanoparticle surfaces and the change in entropy to a reduction in conformational freedom due to the formation of a polymer−polymer interface near nanoparticle surfaces. Confinement-induced mixing of polymers in nanoparticle packings could enable precise tuning of mechanical and transport properties of nanocomposite films and membranes.

show abstract

Coarse-Grained Modeling of Polymer Nanocomposites: Field-Theoretic Simulations

Cited by 4 publications

References 59 publications

Self-Assembled Vesicles from Mixed Brush Nanoparticles in Solution

Self-Assembled Vesicles from Mixed Brush Nanoparticles in Solution

Phase Behavior of Polymer-Grafted Nanoparticles in Homopolymer Blends from Simulations

Increases in Miscibility of a Binary Polymer Blend Confined within a Nanoparticle Packing

Contact Info

Product

Resources

About