William R. French

Electron transport properties of carbon nanotube–graphene contacts

The properties of carbon nanotube-graphene junctions are investigated with first-principles electronic structure and electron transport calculations. Contact properties are found to be key factors in determining the performance of nanotube based electronic devices. In a typical single-walled carbon nanotube-metal junction, there is a p-type Schottky barrier of up to ∼0.4 eV which depends on the nanotube diameter. Calculations of the Schottky barrier height in carbon nanotube-graphene contacts indicate that low barriers of 0.09 eV and 0.04 eV are present in nanotube-graphene contacts ((8,0) and (10,0) nanotubes, respectively). Junctions with a finite contact region are investigated with simulations of the current-voltage characteristics. The results suggest the suitability of the junctions for applications and provide insight to explain recent experimental findings.

Structural Origins of Conductance Fluctuations in Gold-Thiolate Molecular Transport Junctions.

We report detailed atomistic simulations combined with high-fidelity conductance calculations to probe the structural origins of conductance fluctuations in thermally evolving Au-benzene-1,4-dithiolate-Au junctions. We compare the behavior of structurally ideal junctions (where the electrodes are modeled as flat surfaces) to structurally realistic, experimentally representative junctions resulting from break-junction simulations. The enhanced mobility of metal atoms in structurally realistic junctions results in significant changes to the magnitude and origin of the conductance fluctuations. Fluctuations are larger by a factor of 2-3 in realistic junctions compared to ideal junctions. Moreover, in junctions with highly deformed electrodes, the conductance fluctuations arise primarily from changes in the Au geometry, in contrast to results for junctions with nondeformed electrodes, where the conductance fluctuations are dominated by changes in the molecule geometry. These results provide important guidance to experimentalists developing strategies to control molecular conductance, and also to theoreticians invoking simplified structural models of junctions to predict their behavior.

Large-scale atomistic simulations of environmental effects on the formation and properties of molecular junctions.

Using an updated simulation tool, we examine molecular junctions composed of benzene-1,4-dithiolate bonded between gold nanotips, focusing on the importance of environmental factors and interelectrode distance on the formation and structure of bridged molecules. We investigate the complex relationship between monolayer density and tip separation, finding that the formation of multimolecule junctions is favored at low monolayer density, while single-molecule junctions are favored at high density. We demonstrate that tip geometry and monolayer interactions, two factors that are often neglected in simulation, affect the bonding geometry and tilt angle of bridged molecules. We further show that the structures of bridged molecules at 298 and 77 K are similar.

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert.

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1–100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.

Probing the Statistical Validity of the Ductile-to-Brittle Transition in Metallic Nanowires Using GPU Computing

We perform a large-scale statistical analysis (>2000 independent simulations) of the elongation and rupture of gold nanowires, probing the validity and scope of the recently proposed ductile-to-brittle transition that occurs with increasing nanowire length [Wu et al. Nano Lett. 2012, 12, 910-914]. To facilitate a high-throughput simulation approach, we implement the second-moment approximation to the tight-binding (TB-SMA) potential within HOOMD-Blue, a molecular dynamics package which runs on massively parallel graphics processing units (GPUs). In a statistical sense, we find that the nanowires obey the ductile-to-brittle model quite well; however, we observe several unexpected features from the simulations that build on our understanding of the ductile-to-brittle transition. First, occasional failure behavior is observed that qualitatively differs from that predicted by the model prediction; this is attributed to stochastic thermal motion of the Au atoms and occurs at temperatures as low as 10 K. In addition, we also find that the ductile-to-brittle model, which was developed using classical dislocation theory, holds for nanowires as small as 3 nm in diameter. Finally, we demonstrate that the nanowire critical length is higher at 298 K relative to 10 K, a result that is not predicted by the ductile-to-brittle model. These results offer practical design strategies for adjusting nanowire failure and structure and also demonstrate that GPU computing is an excellent tool for studies requiring a large number of independent trajectories in order to fully characterize a systems behavior.

Time-dependent density functional study of field emission from nanotubes composed of C, BN, SiC, Si, and GaN.

Field emission from various types of nanotubes is studied by propagating the electronic density in real space and time using time-dependent density functional theory. Capped (5, 5) C, BN, SiC, Si, and GaN nanotubes are considered. The GaN, SiC, and Si nanotubes were found to be significantly better field emitters than C and BN nanotubes, both in terms of current magnitude and sharpness of peaks in the energy spectra. By analyzing the electronic structure of the various systems it is seen that the nanotubes with the highest currents have electron densities that extend significantly from the nanotube in the emission direction.

Towards Portable Large-Scale Image Processing with High-Performance Computing

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called “spiders.” The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.