Backmapping coarse-grained polymer models under sheared nonequilibrium conditions

Chen, Xiaoyu; Carbone, Paola; Santangelo, Giuseppe; Matteo, Andrea Di; Milano, Giuseppe; Müller‐Plathe, Florian

doi:10.1039/b817895j

Cited by 35 publications

(34 citation statements)

References 42 publications

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“…(i) One approach would be to use many of the recently developed coarse-graining formalisms to rigorously relate the coarsegrained interactions to the fine scale potentials. [30][31][32][33][34][35][36][37] While such methodologies provide an in-principle exact means to obtain the coarse-grained interactions, a disadvantage is the need to effect such coarse-graining procedure for every system parameter and condition of interest. Moreover, the coarsegraining formalisms themselves are computationally intensive and involves different approximations.…”

Section: Introductionmentioning

confidence: 99%

Coarse-graining in simulations of multicomponent polymer systems

Sethuraman

Nguyen

Ganesan

2014

The Journal of Chemical Physics

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We investigate the mapping required between the interaction parameters of two different coarse-grained simulation models to ensure a match of the long-range structural characteristics of multicomponent polymeric system. The basis for our studies is the recent work of Morse and workers, which demonstrated the existence of a mapping between the interaction parameters of different coarse-grained simulation models which allow for a matching of the peak of the disordered state structure factor in symmetric diblock copolymers. We investigate the extensibility of their results to other polymeric systems by studying a variety of systems, including, asymmetric diblock copolymers, symmetric triblock copolymers, and diblock copolymer-solvent mixtures. By using the mapping deduced in the context of symmetric diblock copolymers, we observe excellent agreement for peak in the inverse structure between both two popular coarse grained models for all sets of polymeric melt systems investigated, thus showing that the mapping function proposed for diblock copolymer melts is transferable to other polymer melts irrespective of the blockiness or overall composition. Interestingly, for the limited parameter range of polymer-solvent systems investigated in this article, the mapping functions developed for polymer melts are shown to be equally effective in mapping the structure factor of the coarse-grained simulation models. We use our findings to propose a methodology to create ordered morphologies in simulations involving hard repulsive potentials in a computationally efficient manner. We demonstrate the outcomes of methodology by creating lamellar and cylindrical phases of diblock copolymers of long chains in the popularly used Kremer-Grest simulation model.

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Section: Introductionmentioning

confidence: 99%

Coarse-graining in simulations of multicomponent polymer systems

Sethuraman

Nguyen

Ganesan

2014

The Journal of Chemical Physics

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“…As the equilibration of a coarse-grained polymer is much faster and easier than the all-atomistic one, the back-mapping procedure can be used to quickly generate equilibrated all-atomistic models of highly entangled polymers, including polycarbonates [177,235,341], polystyrene [198,201] and polyamide [197,342]. Recently, Chen et al [343] have extended this method to obtain polymer chains under non-equilibrium situations. In this back-mapping protocol, through applying position restraints on the deformed conformations of atactic polystyrene under steady-state shear flow, the atomistic details were reinserted.…”

Section: From Atomistic To Macroscopic Scales and Backmentioning

confidence: 99%

Challenges in Multiscale Modeling of Polymer Dynamics

et al. 2013

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The mechanical and physical properties of polymeric materials originate from the interplay of phenomena at different spatial and temporal scales. As such, it is necessary to adopt multiscale techniques when modeling polymeric materials in order to account for all important mechanisms. Over the past two decades, a number of different multiscale computational techniques have been developed that can be divided into three categories: (i) coarse-graining methods for generic polymers; (ii) systematic coarse-graining methods and (iii) multiple-scale-bridging methods. In this work, we discuss and compare eleven different multiscale computational techniques falling under these categories and assess them critically according to their ability to provide a rigorous link between polymer chemistry and rheological material properties. For each technique, the fundamental ideas and equations are introduced, and the most important results or predictions are shown and discussed. On the one hand, this review provides a comprehensive tutorial on multiscale computational techniques, which will be of interest to readers newly entering this field; on the other, it presents a critical discussion of the future opportunities and key challenges in the multiscale geometric mapping matrix between all-atomistic and coarse-grained models N number of monomers per chain N e entanglement length, which is the number of monomers between two entanglements n v number of polymer chains per unit volume n ij (n 0 (r ij )) entanglement number (at equilibrium) between particle pairs i and j p r , P R configurational probability distributions in all-atomistic and coarse-grained models, respectively R ee end-to-end distance of polymer chain R G radius of gyration of polymer chain s segment index/contour length variable along primitive chain S(q) single chain coherent dynamic scattering function Z number of entanglements per chain, defined as Z = N/N e α exponent in standard Mittag-Leffler function σ

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“…We refer to the process of mapping atomistic coordinates into a coarse-grained model as "finegraining", which is has found extensive use in the investigation of complex proteins [66][67][68], as well as other molecular systems [69][70][71][72][73]. Here, we use fine-graining to inform electronic property calculations, which complement the aforementioned structural analysis.…”

Section: Fine-grainingmentioning

confidence: 99%

Computationally connecting organic photovoltaic performance to atomistic arrangements and bulk morphology

Jones

Jankowski

2017

Molecular Simulation

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Rationally designing roll-to-roll printed organic photovoltaics requires a fundamental understanding of active layer morphologies optimized for charge separation and transport, and which ingredients can be used to self-assemble those morphologies. In this review article we discuss advances in three areas of computational modeling that provide insight into active layer morphology and the charge transport properties that result. We explain the computational bottlenecks prohibiting atomistically-detailed simulations of device-scale active layers and the coarse-graining and hardware acceleration strategies for overcoming them. We review coarse-grained simulations of organic photovoltaic active layers and show that high throughput simulations of experimentally-relevant length scales are now accessible. We describe a new Python package diffractometer that permits grazing-incidence X-ray scattering patterns of simulated active layers to be compared against experiments. We explain the accurate calculation of charge-carrier mobilities from coarse-grained active layer morphologies by using atomistic backmapping, quantum chemical calculations, and kinetic Monte Carlo simulations. We employ these simulations to show that ordering of poly(3-hexylthiophene-2,5-diyl) explains a factor of 1000 improvement in charge mobility. In concert, we present a suite of computational tools enabling large-scale electronic properties of organic photovoltaics to be studied and screened for by molecular simulations.

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Backmapping coarse-grained polymer models under sheared nonequilibrium conditions

Cited by 35 publications

References 42 publications

Coarse-graining in simulations of multicomponent polymer systems

Coarse-graining in simulations of multicomponent polymer systems

Challenges in Multiscale Modeling of Polymer Dynamics

Computationally connecting organic photovoltaic performance to atomistic arrangements and bulk morphology

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