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Search Publications by: James Alexander Liddle (Fed)

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Displaying 101 - 119 of 119

Theoretical model of errors in micromirror-based three-dimensional particle tracking

June 1, 2010
Author(s)
Andrew J. Berglund, Matthew D. McMahon, Jabez J. McClelland, James A. Liddle
Several recently developed particle-tracking and imaging methods have achieved three-dimensional sensitivity through the introduction of angled micromirrors into the observation volume of an optical microscope. We model the imaging response of such devices

Super-hydrophobic and/or Super-hydrophilic Surfaces Made by Plasma Process

May 8, 2009
Author(s)
Lei Chen, Gerard Henein, James A. Liddle
In this paper, a simple, fast, all-plasma surface modification (APSM) process, which can form super-hydrophobic and/or super-hydrophilic surfaces is introduced. The APSM process includes plasma-induced surface nano-pattern formation, substrate etching and

Imaging Response of Optical Microscopes Containing Angled Micromirrors

April 30, 2009
Author(s)
Andrew J. Berglund, Matthew D. McMahon, Jabez J. McClelland, James A. Liddle
We describe the aberrations induced by introducing micromirrors into the object space of a microscope. These play a critical role in determining the accuracy of recent three-dimensional particle tracking methods based on such devices.

3D Particle Trajectories Observed by Orthogonal Tracking Microscopy

February 9, 2009
Author(s)
Matthew D. McMahon, Andrew J. Berglund, Peter T. Carmichael, Jabez J. McClelland, James A. Liddle
We demonstrate high-resolution, high-speed 3D nanoparticle tracking using angled micromirrors. When angled micromirrors are introduced into the field of view of an optical microscope, reflected side-on views of a diffusing nanoparticle are projected

Fast, bias-free algorithm for tracking single particles with variable size and shape

August 26, 2008
Author(s)
Andrew J. Berglund, Matthew D. McMahon, Jabez J. McClelland, James A. Liddle
We introduce a fast and robust technique for single-particle tracking with nanometer accuracy.We extract the center-of-mass of the image of a single particle with a simple, iterative algorithm that efficiently suppresses background-induced bias in a