Coarse-graining of polyisoprene melts using inverse Monte Carlo and local density potentials

Shahidi, Nobahar; Chazirakis, Antonis; Harmandaris, Vagelis; Doxastakis, Manolis

doi:10.1063/1.5143245

Cited by 35 publications

(32 citation statements)

References 90 publications

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“…Although not as widely used today as IBI, IMC (and variants) have been employed for CG polymer simulation, such as modeling biopolymers 204,205 and polyisoprene melts. 206…”

Section: Key Equation(s) Key Inputs Advantages Disadvantagesmentioning

confidence: 99%

Chemically specific coarse‐graining of polymers: Methods and prospects

Dhamankar

Webb

2021

Journal of Polymer Science

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Coarse-grained (CG) modeling is an invaluable tool for the study of polymers and other soft matter systems due to the span of spatiotemporal scales that typify their physics and behavior. Given continuing advancements in experimental synthesis and characterization of such systems, there is ever greater need to leverage and expand CG capabilities to simulate diverse soft matter systems with chemical specificity. In this review, we discuss essential modeling techniques, bottom-up coarse-graining methodologies, and outstanding challenges for the chemically specific CG modeling of polymer-based systems. This methodologically oriented discussion is complemented by representative literature examples for polymer simulation; we also offer some advisory practical considerations that should be useful for new researchers. Given its growing importance in the modeling and polymer science community, we further highlight some recent applications of machine learning that enhance CG modeling strategies. Overall, this review provides comprehensive discussion of methods and prospects for the chemically specific coarse-graining of polymers.

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“…Although not as widely used today as IBI, IMC (and variants) have been employed for CG polymer simulation, such as modeling biopolymers 204,205 and polyisoprene melts. 206…”

Section: Key Equation(s) Key Inputs Advantages Disadvantagesmentioning

confidence: 99%

Chemically specific coarse‐graining of polymers: Methods and prospects

Dhamankar

Webb

2021

Journal of Polymer Science

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“…In some occasions it is reasonable to suppose that a particularly well-chosen representation of the system might lead to a substantial simplification of the interactions, e.g., by making many-body terms small or even negligible ( D’Adamo et al, 2015 ): if this were the case, the MB-PMF could be expressed through simple interactions among few constituents, thus making the model simple to parametrize and understand. Alternatively, if the many-body nature of the PMF cannot be reduced or neglected, more complex interactions have to be incorporated, as it is done in the case of density-dependent potentials ( Allen and Rutledge, 2008 ; Sanyal and Shell, 2016 ; Wagner et al, 2017 ; Sanyal and Shell, 2018 ; Rosenberger et al, 2019 ; DeLyser and Noid, 2019 ; Shahidi et al, 2020 ).…”

Section: Coarse-grained Modeling: General Frameworkmentioning

confidence: 99%

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

Giulini

Rigoli

Mattiotti

et al. 2021

Front. Mol. Biosci.

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The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

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“…For bottom-up models, improving the description of the many-body potential of mean force (i.e., the theoretically-ideal CG potential) offers a systematic route toward one important aspect of dynamic (in particular, kinetic) consistency: barrier-crossing dynamics [49]. This link further justifies efforts to improve the structural accuracy of CG models via many-body [42,[50][51][52][53][54][55][56][57][58][59][60] or environmental-dependent [49,59,[61][62][63][64][65][66][67][68] [69]. They found that, despite the nontrivial transformation of dynamical processes upon coarse-graining, several relationships between dynamical modes on very different timescales are preserved for both ionic species.…”

Section: Introductionmentioning

confidence: 99%

Dynamical properties across different coarse-grained models for ionic liquids

Rudzinski

Kloth

Wörner

et al. 2021

J. Phys.: Condens. Matter

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Room-temperature ionic liquids (RTILs) stand out among molecular liquids for their rich physicochemical characteristics, including structural and dynamic heterogeneity. The significance of electrostatic interactions in RTILs results in long characteristic length-and timescales, and has motivated the development of a number of coarse-grained (CG) simulation models. In this study, we aim to better understand the connection between certain CG parameterization strategies and the dynamical properties and transferability of the resulting models. We systematically compare five CG models: a model largely parameterized from experimental thermodynamic observables; a refinement of this model to increase its structural accuracy; and three models that reproduce a given set of structural distribution functions by construction, with varying intramolecular parameterizations and reference temperatures. All five CG models display limited structural transferability over temperature, and also result in various effective dynamical speedup factors, relative to a reference atomistic model. On the other hand, the structure-based CG models tend to result in more consistent cation-anion relative diffusion than the thermodynamic-based models, for a single thermodynamic state point. By linking short-and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different CG models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of RTILs.

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Coarse-graining of polyisoprene melts using inverse Monte Carlo and local density potentials

Cited by 35 publications

References 90 publications

Chemically specific coarse‐graining of polymers: Methods and prospects

Chemically specific coarse‐graining of polymers: Methods and prospects

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

Dynamical properties across different coarse-grained models for ionic liquids

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