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

Large-Scale Fabrication of Boron Nitride Nanosheets and Their Utilization in Polymeric Composites with Improved Thermal and Mechanical Properties

Functionalization is an important way to breed new properties and applications for a material. This review presents an overview of the progresses in functionalized hexagonal boron nitride (h-BN) nanomaterials. It begins with an introduction of h-BN structural features, physical and chemical properties, followed by an emphasis on the developments of BN functionalization strategies and its emerging properties/applications, and ends with the research perspectives. Different functionalization methods, including physical and chemical routes, are comprehensively described toward fabrication of various BN derivatives, hetero- and porous structures, etc. Novel properties of functionalized BN materials, such as high water solubility, excellent biocompatibility, tunable surface affinities, good processibility, adjustable band gaps, etc., have guaranteed wide applications in biomedical, electronic, composite, environmental and "green" energy-related fields.

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Functionalized hexagonal boron nitride nanomaterials: emerging properties and applications.

Two dimensional hexagonal boron nitride (2D-hBN), an isomorph of graphene with a very similar layered structure, is uniquely featured by its exotic opto-electrical properties together with mechanical robustness, thermal stability, and chemical inertness. It is thus extensively studied for application in field effect transistors (FETs), tunneling devices, deep UV emitters and detectors, photoelectric devices, and nanofillers. 2D-hBN is considered as one of the most promising materials that can be integrated with other 2D materials, such as graphene and transition metal dichalcogenides (TMDCs), for the next generation microelectronic and other technologies. Although it is by itself an insulator, it can well be tuned by several strategies in terms of properties and functionalities, such as by doping, substitution, functionalization and hybridization, making 2D-hBN a truly versatile type of functional materials for a wide range of applications. In this review, the distinct structural characteristics of 2D-hBN, doping- and defect-induced variations in energy bands and structures, and resultant properties, are presented. There are a wide variety of processing routes that have been developed for 2D-hBN, including also those for doping, substitution, functionalization and combination with other materials to form heterostructures or h-BNC hybrid nanosheets, which are systematically elaborated for novel functions. The comprehensive overview provides the types of the state-of-the-art 2D-hBN made by new synthesis strategies, where the mainstream approaches include exfoliation, chemical vapor deposition, and gas phase epitaxy, together with several other new methods that have been successfully developed in the past few years. On the basis of the extraordinary electrical and functional properties and thermal–mechanical stability, the applications of hBN-based nanosheets as substrates and dielectrics, passivation layers, and nanofillers in nanodevices and nanocomposites are discussed, together with the peculiar optical and wetting characteristics.

Two dimensional hexagonal boron nitride (2D-hBN): synthesis, properties and applications

Fracture toughness and failure mechanism of graphene based epoxy composites

New materials with distinctive properties are arising and attracting the scientific community at regular intervals. Stiffness and strength are the important factors in determining stability and lifetime of any technological devices, but defects which are inevitable at the time of production can alter the structural properties of any engineering materials. Developing graphene with specific structural properties depends upon controlling these defects, either by removing or deliberately engineering atomic structure to gain or tailoring specific properties. In this article, a comprehensive review of defective graphene sheets with respect to its mechanical and thermal properties are presented and examined.

Effect of Point and Line Defects on Mechanical and Thermal Properties of Graphene: A Review

Due to their exceptional properties, graphene and hexagonal boron nitride (h-BN) nanofillers are emerging as potential candidates for reinforcing the polymer-based nanocomposites. Graphene and h-BN have comparable mechanical and thermal properties, whereas due to high band gap in h-BN (~5 eV), have contrasting electrical conductivities. Atomistic modeling techniques are viable alternatives to the costly and time-consuming experimental techniques, and are accurate enough to predict the mechanical properties, fracture toughness, and thermal conductivities of graphene and h-BN-based nanocomposites. Success of any atomistic model entirely depends on the type of interatomic potential used in simulations. This review article encompasses different types of interatomic potentials that can be used for the modeling of graphene, h-BN, and corresponding nanocomposites, and further elaborates on developments and challenges associated with the classical mechanics-based approach along with synergic effects of these nano reinforcements on host polymer matrix.

For further resources related to this article, please visit the WIREs website.

Atomistic modeling of graphene/hexagonal boron nitride polymer nanocomposites: a review

Graphene is an elementary unit for various carbon based nanostructures. The recent technological developments have made it possible to manufacture hybrid and sandwich structures with graphene. In order to model these nanostructures in atomistic scale, a compatible interatomic potential is required to successfully model these nanostructures. In this article, an interatomic potential with modified cut-off function for Tersoff potential was proposed to avoid overestimation and also to predict the realistic mechanical behavior of single sheet of graphene. In order to validate the modified form of cut-off function for Tersoff potential, simulations were performed with different set of temperatures and strain rates, and results were made to compare with available experimental data and molecular dynamics simulation results obtained with the help of other empirical interatomic potentials.

https://iopscience.iop.org/article/10.1088/2053-1591/3/3/035011/pdf

Tersoff potential with improved accuracy for simulating graphene in molecular dynamics environment

Due to their exceptional mechanical properties, thermal conductivity and a wide band gap (5–6 eV), boron nitride nanotubes and nanosheets have promising applications in the field of engineering and biomedical science. Accurate modeling of failure or fracture in a nanomaterial inherently involves coupling of atomic domains of cracks and voids as well as a deformation mechanism originating from grain boundaries. This review highlights the recent progress made in the atomistic modeling of boron nitride nanofillers. Continuous improvements in computational power have made it possible to study the structural properties of these nanofillers at the atomistic scale.

Atomistic modeling of BN nanofillers for mechanical and thermal properties: a review

The aim of the research article is to develop a representative volume element using finite elements to study the buckling stability of graphene/polymer nanocomposites. Research work exploring the full potential of graphene as filler for nanocomposites is limited in part due to the complex processes associated with the mixing of graphene in polymer. To overcome some of these issues, a multiscale modeling technique has been proposed in this numerical work. Graphene was herein modeled in the atomistic scale, whereas the polymer deformation was analyzed as a continuum. Separate representative volume element models were developed for investigating buckling in neat polymer and graphene/polymer nanocomposites. Significant improvements in buckling strength were observed under applied compressive loading when compared with the buckling stability of neat polymer.

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Avinash Parashar

Papers

Effect of Point and Line Defects on Mechanical and Thermal Properties of Graphene: A Review

Atomistic modeling of graphene/hexagonal boron nitride polymer nanocomposites: a review

Tersoff potential with improved accuracy for simulating graphene in molecular dynamics environment

Atomistic modeling of BN nanofillers for mechanical and thermal properties: a review

Representative volume element to estimate buckling behavior of graphene/polymer nanocomposite