Structure and Dynamics of Solvated Polymers near a Silica Surface: On the Different Roles Played by Solvent

Approaches and Perspective of Coarse-Grained Modeling and Simulation for Polymer-Nanoparticle Hybrid Systems

Molecular modeling and simulations have emerged as effective and indispensable tools to characterize polymeric systems. They provide fundamental and essential insights to design a product of the required properties and to improve the understanding of a phenomenon at the molecular level for a particular system. The polymer-nanoparticle hybrids are materials with outstanding properties and correspondingly large applications whose study has benefited from this new paradigm. However, despite the significant expansion of modern day computational powers, investigation of the long time and large length scale phenomenon in polymeric and polymer-nanoparticle systems is still a challenging task to complete through all-atom molecular dynamics (AA-MD) simulations. To circumvent this problem, a variety of coarse-grained (CG) models have been proposed, ranging from the generic CG models for qualitative properties predictions to more realistic chemically specific CG models for quantitative properties predictions. These CG models have already delivered some success stories in the study of several spatial and temporal evolutions of many processes. Some of these studies were beyond the feasibility of traditional atomistic resolution models due to either the size or the time constraints. This review captures the different types of popular CG approaches that are utilized in the investigation of the microscopic behavior of polymer-nanoparticle hybrid systems. The rationale of this article is to furnish an overview of the popular CG approaches and their applications, to review several important and most recent developments, and to delineate the perspectives on future directions in the field.

A Martini Coarse Grained Model of Citrate-Capped Gold Nanoparticles Interacting with Lipid Bilayers

Citrate capping is one of the most common strategies to achieve the colloidal stability of Au nanoparticles (NPs) with diameters ranging from a few to hundreds of nanometers. Citrate-capped Au nanoparticles (CNPs) represent a step of the synthesis of Au NPs with specific functionalities, as CNPs can be further functionalized via ligand-exchange reactions, leading to the replacement of citrate with other organic ligands. In vitro, CNPs are also used to address the fundamental aspects of NP-membrane interactions, as they can directly interact with cells or model cell membranes. Their affinity for the bilayer is again mediated by the exchange of citrate with lipid molecules. Here, we propose a new computational model of CNPs compatible with the coarse grained Martini force field. The model, which we develop and validate through an extensive comparison with new all-atom molecular dynamics (MD) simulations and UV-vis and Fourier transform infrared spectroscopy data, is aimed at the MD simulation of the interaction between citrate-capped NPs and model phosphatidylcholine lipid membranes. As a test application we show that, during the interaction between a single CNP and a flat planar 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer, the citrate coating is spontaneously replaced by lipids on the surface of Au NPs, while the NP size and shape determine the final structural configuration of the NP-bilayer complex.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.

Coarse-Grained Force Field Calibration Based on Multiobjective Bayesian Optimization to Simulate Water Diffusion in Poly-ε-caprolactone

Molecular dynamics at the atomistic scale is increasingly being used to predict material properties and speed up the material design and development process. However, the accuracy of molecular dynamics predictions is sensitively dependent on the force fields. In the traditional force field calibration process, a specific property, predicted by the model, is compared with the experimental observation and the force field parameters are adjusted to minimize the difference. This leads to the issue that the calibrated force fields are not generic and robust enough to predict different properties. Here, a new calibration method based on multiobjective Bayesian optimization is developed to speed up the development of molecular dynamics force fields that are capable of predicting multiple properties accurately. This is achieved by reducing the number of simulation runs to generate the Pareto front with an efficient sequential sampling strategy. The methodology is demonstrated by generating a new coarse-grained force field for polycaprolactone, where the force field can predict the mechanical properties and water diffusion in the polymer.

Martini Coarse-Grained Model for Clay-Polymer Nanocomposites

We have developed a coarse-grained (CG) model of a polymer-clay system consisting of organically modified montmorillonite (oMMT) nanoclay as the nanoparticle in accordance with the MARTINI force field. We have used mechanical properties and cleavage free energy of the clay particle to respectively parameterize bonded and nonbonded interaction parameters for an oMMT clay particle, where intergallery Na⁺ ions are replaced by tetramethylammonium (TMA) ions. The mechanical properties were determined from the slope of the stress-strain curve and cleavage free energy was determined by allowing for full surface reconstruction corresponding to a slow equilibrium cleavage process. Individual dispersive and polar contributions to oMMT cleavage energy were used for determination of appropriate MARTINI bead types for the CG oMMT sheet. The self-consistency of the developed MARTINIFF parameters for the TMA-montmorillonite-polymer system was verified by comparing estimates for select structural, thermodynamic, and dynamic properties obtained in all-atomistic simulations with that obtained in CG simulations. We have determined the influence of clay particles on properties of three polymer melts (polyethylene, polypropylene, and polystyrene) at two temperatures to establish transferability of the developed parameters. We have also shown that the effect of clay-polymer interactions on structure-property relationships in the polymer-clay nanocomposite system is well captured by Rosenfeld's excess entropy scaling.

Nanoparticle-Hydrogel Composites: From Molecular Interactions to Macroscopic Behavior

Hydrogels are materials used in a variety of applications, ranging from tissue engineering to drug delivery. The incorporation of nanoparticles to yield composite hydrogels has gained substantial momentum over the years since these afford tailor-making and extend material mechanical properties far beyond those achievable through molecular design of the network component. Here, we review different procedures that have been used to integrate nanoparticles into hydrogels; the types of interactions acting between polymers and nanoparticles; and how these underpin the improved mechanical and optical properties of the gels, including the self-healing ability of these composite gels, as well as serving as the basis for future development. In a less explored approach, hydrogels have been used as dispersants of nanomaterials, allowing a larger exposure of the surface of the nanomaterial and thus a better performance in catalytic and sensor applications. Furthermore, the reporting capacity of integrated nanoparticles in hydrogels to assess hydrogel properties, such as equilibrium swelling and elasticity, is highlighted.