Abstract
We present Simu-D, a software suite for the simulation and successive identification of local structures of atomistic systems, based on polymers, under extreme conditions, in the bulk, on surfaces, and at interfaces. The protocol is built around various types of Monte Carlo algorithms, which include localized, chain-connectivity-altering, identity-exchange, and cluster-based moves. The approach focuses on alleviating one of the main disadvantages of Monte Carlo algorithms, which is the general applicability under a wide range of conditions. Present applications include polymer-based nanocomposites with nanofillers in the form of cylinders and spheres of varied concentration and size, extremely confined and maximally packed assemblies in two and three dimensions, and terminally grafted macromolecules. The main simulator is accompanied by a descriptor that identifies the similarity of computer-generated configurations with respect to reference crystals in two or three dimensions. The Simu-D simulator-descriptor can be an especially useful tool in the modeling studies of the entropy- and energy-driven phase transition, adsorption, and self-organization of polymer-based systems under a variety of conditions.
Highlights
The development of new materials with enhanced properties is one of the most interesting and important topics in research in materials science and engineering
We should mention that with respect to jamming, our Simu-D produces very dense and nearly jammed random packings of hard spheres with volume fractions very close to the ones reported in the literature from independent sources on the Random Close-Packed (RCP)/maximally random jammed (MRJ) state: φMRJ ≈ 0.64–0.65, with the exact value and the salient characteristics being very dependent on the employed protocol [112,113,114]
We present the latest implementation of Simu-D, a simulator-descriptor suite used to model and successively analyze/describe polymer-based systems under extreme conditions of concentration, confinement, and nanofiller content
Summary
The development of new materials with enhanced properties is one of the most interesting and important topics in research in materials science and engineering. The Enhanced Monte Carlo code [17,18] is a multi-purpose modular environment for particle simulations using force fields such as COMPASS, CHARMM, or Born This open tool has been used to study the effect of semicrystalline interphase polyethylene under different conditions of tensile deformation [19,20] or chain branching [21]. MC-based open tool that can be applied to general atomistic systems under different force fields and ensembles, as well as introducing transition pathways of umbrella sampling and Wang–Landau [25] It is compatible with the molecular dynamic tool. The suite is further extended to include additional factors: chain stiffness, blends of chains and monomers, spherical or cylindrical confinement, the varied potential for bonded and nonbonded interactions, nanofillers in the form of cylinders and spheres, and combinations of the above. Lcyl Ncyl where dsph and dcyl are the diameter of the nanospheres and nanocylinders, respectively, Lcyl is the nanocylinder length, index i runs over all confined dimensions, index j over all unrestricted ones, and lj is the length of the simulation cell in dimension j
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