Cem Özdoğan

Stability of edge states and edge magnetism in graphene nanoribbons

We critically discuss the stability of edge states and edge magnetism in zigzag edge graphene nanoribbons (ZGNRs). We point out that magnetic edge states might not exist in real systems and show that there are at least three very natural mechanisms - edge reconstruction, edge passivation, and edge closure - which dramatically reduce the effect of edge states in ZGNRs or even totally eliminate them. Even if systems with magnetic edge states could be made, the intrinsic magnetism would not be stable at room temperature. Charge doping and the presence of edge defects further destabilize the intrinsic magnetism of such systems.

Structural stability and energetics of single-walled carbon nanotubes under uniaxial strain

A (10x10) single-walled carbon nanotube consisting of 400 atoms with 20 layers is simulated under tensile loading using our developed O(N) parallel tight-binding molecular-dynamics algorithms. It is observed that the simulated carbon nanotube is able to carry the strain up to 122% of the relaxed tube length in elongation and up to 93% for compression. Young s modulus, tensile strength, and the Poisson ratio are calculated and the values found are 0.311 TPa, 4.92 GPa, and 0.287, respectively. The stress-strain curve is obtained. The elastic limit is observed at a strain rate of 0.09 while the breaking point is at 0.23. The frequency of vibration for the pristine (10x10) carbon nanotube in the radial direction is 4.71x10^3 GHz and it is sensitive to the strain rate.

Parallel wavelet-based clustering algorithm on GPUs using CUDA

Abstract There has been a substantial interest in scientific and engineering computing community to speed up the CPU-intensive tasks on graphical processing units (GPUs) with the development of many-core GPUs as having very large memory bandwidth and computational power. Cluster analysis is a widely used technique for grouping a set of objects into classes of “similar” objects and commonly used in many fields such as data mining, bioinformatics and pattern recognition. WaveCluster defines the notion of cluster as a dense region consisting of connected components in the transformed feature space. In this study, we present the implementation of WaveCluster algorithm as a novel clustering approach based on wavelet transform to GPU level parallelization and investigate the parallel performance for very large spatial datasets. The CUDA implementations of two main sub-algorithms of WaveCluster approach; namely extraction of low-frequency component from the signal using wavelet transform and connected component labeling are presented. Then, the corresponding performance evaluations are reported for each sub-algorithm. Divide and conquer approach is followed on the implementation of wavelet transform and multi-pass sliding window approach on the implementation of connected component labeling. The maximum achieved speedup is found in kernel as 107x in the computation of extraction of the low-frequency component and 6x in the computation of connected component labeling with respect to the sequential algorithms running on the CPU.

O(N) parallel tight binding molecular dynamics simulation of carbon nanotubes

Abstract We report an O( N ) parallel tight binding molecular dynamics simulation study of (10×10) structured carbon nanotubes (CNT) at 300 K. We converted a sequential O( N 3 ) TBMD simulation program into an O( N ) parallel code, utilizing the concept of parallel virtual machines (PVM). The code is tested in a distributed memory system consisting of a cluster with 8 PCs that run under Linux (Slackware 2.2.13 kernel). Our results on the speed up, efficiency and system size are given.

Localization of metallicity and magnetic properties of graphene and of graphene nanoribbons doped with boron clusters

As a possible way of modifying the intrinsic properties of graphene, we study the doping of graphene by embedded boron clusters with density functional theory. Cluster doping is technologically relevant as the cluster implantation technique can be readily applied to graphene. We find that B clusters embedded into graphene and graphene nanoribbons are structurally stable and locally metallize the system. This is done both by the reduction of the Fermi energy and by the introduction of boron states near the Fermi level. A linear chain of boron clusters forms a metallic “wire” inside the graphene matrix. In a zigzag edge graphene nanoribbon, the cluster-related states tend to hybridize with the edge and bulk states. The magnetism in boron-doped graphene systems is generally very weak. The presence of boron clusters weakens the edge magnetism in zigzag edge graphene nanoribbon, rather than making the system appropriate for spintronics. Thus, the doping of graphene with the cluster implantation technique might be a viable technique to locally metallize graphene without destroying its attractive bulk properties.

Parallel WaveCluster: A linear scaling parallel clustering algorithm implementation with application to very large datasets

A linear scaling parallel clustering algorithm implementation and its application to very large datasets for cluster analysis is reported. WaveCluster is a novel clustering approach based on wavelet transforms. Despite this approach has an ability to detect clusters of arbitrary shapes in an efficient way, it requires considerable amount of time to collect results for large sizes of multi-dimensional datasets. We propose the parallel implementation of the WaveCluster algorithm based on the message passing model for a distributed-memory multiprocessor system. In the proposed method, communication among processors and memory requirements are kept at minimum to achieve high efficiency. We have conducted the experiments on a dense dataset and a sparse dataset to measure the algorithm behavior appropriately. Our results obtained from performed experiments demonstrate that developed parallel WaveCluster algorithm exposes high speedup and scales linearly with the increasing number of processors.

Effects of hydrogen hosting on cage structures of boron clusters: density functional study of BmHn (m= 5–10 and n≤m) complexes

The structural stability of hydrogen bonded boron microclusters has been studied by using the density functional theory. Effects of the increasing number of hydrogen atoms on the cage geometries of B5–B10 clusters, and the distortion of the cage configurations of the boranes are assessed. The possible stable structures of BmHn (m=5–10 and n≤m) boron hydrides, their binding energies, HOMO–LUMO energy gaps and the total atomic charges of the Bm in the complexes are determined. For the series of B5Hn, B7Hn, and B9Hn major structural changes are observed.

Thermal stability of metallic single-walled carbon nanotubes: an O(N) tight-binding molecular dynamics simulation study

Order(N) tight-binding molecular dynamics (TBMD) simulations are performed to investigate the thermal stability of (10,10) metallic single-walled carbon nanotubes (SWCNTs). Periodic boundary conditions (PBCs) are applied in the axial direction. The velocity Verlet algorithm along with the canonical ensemble molecular dynamics (NVT) is used to simulate the tubes at the targeted temperatures. The effects of slow and rapid temperature increases on the physical characteristics, structural stability and the energetics of the tube are investigated and compared. Simulations are carried out starting from room temperature and the temperature is raised in steps of 300?K. The stability of the simulated metallic SWCNT is examined at each step before it is heated to higher temperatures. The first indication of structural deformation is observed at 600?K. For higher heat treatments the deformations are more pronounced and the bond-breaking temperature is reached around 2500?K. Gradual (slow) heating and thermal equilibrium (fast heating) methods give the value of radial thermal expansion coefficient in the temperature range between 300 and 600?K as 0.31 ? 10?5 and 0.089 ? 10?5?K?1, respectively. After 600?K, both methods give the same value of 0.089 ? 10?5?K?1. The ratio of the total energy per atom with respect to temperature is found to be 3 ? 10?4?eV?K?1.

O ( N ) algorithms in tight-binding molecular-dynamics simulations of the electronic structure of carbon nanotubes

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PARALLELIZATION OF A MOLECULAR DYNAMICS SIMULATION OF AN ION-SURFACE COLLISION SYSTEM: Ar–Ni(100)

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