Electron-beam-induced direct etching of graphene

We present electron-beam-induced oxidation of single- and bilayer graphene devices in a low-voltage scanning electron microscope. We show that the injection of oxygen leads to targeted etching at the focal point, enabling us to pattern graphene with a resolution of better than 20 nm. Voltage-contrast imaging, in conjunction with finite-element simulations, explain the secondary-electron intensities and correlate them to the etch profile. © 2013 Elsevier Ltd. All rights reserved.

Material parameter extraction in THz-TDS using a converging beam transfer function

We demonstrate a parameter extraction algorithm based on a theoretical transfer function, which takes into account a converging THz beam. Using this, we successfully extract material parameters from data obtained for a quartz sample with a THz time domain spectrometer. © 2010 IEEE.

Curvature and wrinkling of premixed flame Kernels comparison between planar laser induced fluorescence (PLIF) and 3D direct numerical simulations (DNS)

A direct comparison between time resolved PLIF measurements of OH and two dimensional slices from a full three dimensional DNS data set of turbulent premixed flame kernels in lean methane/air mixture was presented. The local flame structure and the degree of flame wrinkling were examined in response to differing turbulence intensities and turbulent Reynolds numbers. Simulations were performed using the SEGA DNS code, which is based on the solution of the compressible Navier Stokes, species, and energy equations for a lean hydrocarbon mixture. For the OH PLIF measurements, a cluster of four Nd:YAG laser was fired sequentially at high repetition rates and used to pump a dye laser. The frequency doubled laser beam was formed into a sheet of 40 mm height using a cylindrical telescope. The combination of PLIF and DNS has been demonstrated as a powerful tool for flame analysis. This research will form the basis for the development of sub-grid-scale (SGS) models for LES of lean-premixed combustion systems such as gas turbines. This is an abstract of a paper presented at the 30th International Symposium on Combustion (Chicago, IL 7/25-30/2004).

The preparation, characterization and tribological properties of TA-C : H deposited using an electron cyclotron wave resonance plasma beam source

A compact electron cyclotron wave resonance (ECWR) source has been developed for the high rate deposition of hydrogenated tetrahedral amorphous carbon (ta-C:H). The ECWR provides growth rates of up to 900 Å/min over a 4″ diameter and an independent control of the deposition rate and ion energy. The ta-C:H was deposited using acetylene as the source gas and was characterized in terms of its sp3 content, mass density, intrinsic stress, hydrogen content, C-H bonding, Raman spectra, optical gap, surface roughness and friction coefficient. The results obtained indicated that the film properties were maximized at an ion energy of approximately 167 eV, corresponding to an energy per daughter carbon ion of 76 eV. The relationship between the incident ion energy and film densification was also explained in terms of the subsurface implantation of carbon ions into the growing film.

Fabrication and electrical characteristics of carbon nanotube-based microcathodes for use in a parallel electron-beam lithography system

The development of the Nanolith parallel electron-beam writing head was discussed. The fabrication and electrical characteristics of carbon nanotube-based microcathodes for use in the lithographic system were described. The microcathode exhibited a peak current of 10.5 μA at 48 V when operated with a duty cycle of 0.5 percent.

Efficient line launch for bandwidth improvement of 10 Gbit/s multimode fibre links using elliptical Gaussian beam

A novel elliptical Gaussian beam line launch is shown to allow improved system capacity for high speed multimode fibre links. This launch maintains higher bandwidth than dual launch even with misalignment of ±6 μm despite not requiring testing at installation. ©2010 IEEE.

Fabrication of 25nm wide gold lines using nanometer scale lithography and ionized cluster beam deposition

It becomes increasingly difficult to make continuous metal lines with well defined thickness and edges by the lift-off technique as the line width is decreased. We describe in this paper a technique in which the combination of high resolution electron beam lithography and ionized cluster beam (ICB) deposition has enabled very high quality gold lines ({all equal to}25nm wide) to be obtained on thick single crystal silicon substrates. © 1990.

Tractable nonparametric bayesian inference in poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finitedimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets. Copyright 2009.

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finite-dimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets.