We report state-of-the-art atomistic simulations combined with high-fidelity conductance calculations to probe structure-conductance relationships in Au-benzenedithiolate (BDT)-Au junctions under elongation. Our results demonstrate that large increases in conductance are associated with the formation of monatomic chains (MACs) of Au atoms directly connected to BDT. An analysis of the electronic structure of the simulated junctions reveals that enhancement in the s-like states in Au MACs causes the increases in conductance. Other structures also result in increased conductance but are too short-lived to be detected in experiment, while MACs remain stable for long simulation times. Examinations of thermally evolved junctions with and without MACs show negligible overlap between conductance histograms, indicating that the increase in conductance is related to this unique structural change and not thermal fluctuation. These results, which provide an excellent explanation for a recently observed anomalous experimental result [Bruot et al., Nat. Nanotechnol., 2012, 7, 35-40], should aid in the development of mechanically responsive molecular electronic devices.

We report detailed atomistic simulations combined with high-fidelity conductance calculations to probe the structural origins of conductance fluctuations in thermally evolving Aubenzene-1,4-dithiolate-Au junctions. We compare the behavior of structurally ideal junctions (electrodes with 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 non-deformed 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 for device applications, and also to theoreticians invoking simplified structural models of junctions to predict their behavior.

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.

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.

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.