Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Chemical methods developed over the past two decades enable preparation of colloidal nanocrystals with uniform size and shape. These Brownian objects readily order into superlattices. Recently, the range of accessible inorganic cores and tunable surface chemistries dramatically increased, expanding the set of nanocrystal arrangements experimentally attainable. In this review, we discuss efforts to create next-generation materials via bottom-up organization of nanocrystals with preprogrammed functionality and self-assembly instructions. This process is often driven by both interparticle interactions and the influence of the assembly environment. The introduction provides the reader with a practical overview of nanocrystal synthesis, self-assembly, and superlattice characterization. We then summarize the theory of nanocrystal interactions and examine fundamental principles governing nanocrystal self-assembly from hard and soft particle perspectives borrowed from the comparatively established fields of micro...

Self-Assembly of Colloidal Nanocrystals: From Intricate Structures to Functional Materials

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Statistical Mechanics Of Chain Molecules

Molecular modeling and simulations are invaluable tools for the polymer science and engineering community. These computational approaches enable predictions and provide explanations of experimentally observed macromolecular structure, dynamics, thermodynamics, and microscopic and macroscopic material properties. With recent advances in computing power, polymer simulations can synergistically inform, guide, and complement in vitro macromolecular materials design and discovery efforts. To ensure that this growing power of simulations is harnessed correctly, and meaningful results are achieved, care must be taken to ensure the validity and reproducibility of these simulations. With these considerations in mind, in this Perspective we discuss our philosophy for carefully developing or selecting appropriate models, performing, and analyzing polymer simulations. We highlight best practices, key challenges, and important advances in model development/selection, computational method choices, advanced sampling met...

Modeling and Simulations of Polymers: A Roadmap

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 modeling of polymeric materials and how these methods can help us to optimize and design new polymeric materials.

https://www.mdpi.com/2073-4360/5/2/751/pdf

Challenges in Multiscale Modeling of Polymer Dynamics

Over the past two decades polymer nanocomposites have received tremendous interest from industry and academia due to their advanced properties comparative to polymer blends. Many computational studies have revealed that the macroscopic properties of polymer nanocomposites depend strongly on the microscopic polymer structure and conformations. In this article we review computer simulation studies of the fundamental problem of homopolymers structure and dimensions in nanocomposites containing bare or grafted spherical or rod nanoparticles. Experimentally, there is controversy over whether the addition of nanoparticles in a polymer matrix can perturb the polymer chains.

Modeling of Polymer Structure and Conformations in Polymer Nanocomposites from Atomistic to Mesoscale: A Review

We investigate the effect of various spherical nanoparticles on chain dimensions in polymer melts for high nanoparticle loading which is larger than the percolation threshold, using molecular dynamics simulations. We show that polymer chains are unperturbed by the presence of repulsive nanoparticles. In contrast polymer chains can be perturbed by the presence of attractive nanoparticles when the polymer radius of gyration is larger than the nanoparticle radius. At high nanoparticle loading, chains can be stretched and flattened by the nanoparticles, even oligomers can expand under the presence of attractive nanoparticles of very small size.

/pdf/polymer-conformations-in-polymer-nanocomposites-containing-410zokntro.pdf

Polymer conformations in polymer nanocomposites containing spherical nanoparticles

We investigate the topological constraints (entanglements) in polymer–nanorod nanocomposites in comparison to polymer melts using dissipative particle dynamics (DPD) polymer model simulations. The nanorods have a radius smaller than the polymer radius of gyration and an aspect ratio of 7.5. We observe an increase in the number of entanglements (50% decrease of Ne with 11% volume fraction of nanorods dispersed in the polymer matrix) in the nanocomposites as evidenced by larger contour lengths of the primitive paths. The end-to-end distance is essentially unchanged with the nanorod volume fraction (0–11%). Interaction between polymers and nanorods affects the dispersion of nanorods in the nanocomposites.

Topological entanglement length in polymer melts and nanocomposites by a DPD polymer model

We investigate the static properties of monodisperse polymer/single wall carbon nanotube (SWCNT) nanocomposites in comparison to polymer melts by molecular dynamics simulations. The SWCNT has a large aspect ratio and radius smaller than the polymer radius of gyration. We find that although the local chain structure is significantly affected, the overall configuration, as characterized by the radius of gyration, is not perturbed either by the interaction strength between the polymer and the SWCNT or by variations in the SWCNT radius.

Structure and Conformations of Polymer/SWCNT Nanocomposites

We investigate the polymer packing around nanoparticles and polymer/nanoparticle topological constraints (entanglements) in nanocomposites containing spherical nanoparticles in comparison to pure polymer melts using molecular dynamics (MD) simulations. The polymer–nanoparticle attraction leads to good dispersion of nanoparticles. We observe an increase in the number of topological constraints (decrease of total entanglement length Ne with nanoparticle loading in the polymer matrix) in nanocomposites due to nanoparticles, as evidenced by larger contour lengths of the primitive paths. An increase of the nanoparticle radius reduces the polymer–particle entanglements. These studies demonstrate that the interaction between polymers and nanoparticles does not affect the total entanglement length because in nanocomposites with small nanoparticles, the polymer–nanoparticles topological constraints dominate.

/pdf/entanglements-in-polymer-nanocomposites-containing-spherical-4c0qjuxmta.pdf

Argyrios Karatrantos

Papers

Modeling of Polymer Structure and Conformations in Polymer Nanocomposites from Atomistic to Mesoscale: A Review

Polymer conformations in polymer nanocomposites containing spherical nanoparticles

Topological entanglement length in polymer melts and nanocomposites by a DPD polymer model

Structure and Conformations of Polymer/SWCNT Nanocomposites

Entanglements in polymer nanocomposites containing spherical nanoparticles