Searcharxiv⌕ Search

arXiv subjects

Gavin Young

Publications and source records attributed to Gavin Young.

4 recordsLinked to original sources
arXiv2021

Micromirror total internal reflection microscopy for high-performance single particle tracking at interfaces

Single particle tracking has found broad applications in the life and physical sciences, enabling the observation and characterisation of nano- and microscopic motion. Fluorescence-based approaches are ideally suited for high-background environments, such as tracking lipids or proteins in or on cells, due to superior background rejection. Scattering-based detection is preferable when localisation precision and imaging speed are paramount due to the in principle infinite photon budget. Here, we show that micromirror-based total internal reflection dark field microscopy enables background suppression previously only reported for interferometric scattering microscopy, resulting in nm localisation precision at 6 $μ$s exposure time for 20 nm gold nanoparticles with a 25 x 25 $μ$m$^{2}$ field of view. We demonstrate the capabilities of our implementation by characterizing sub-nm deterministic flows of 20 nm gold nanoparticles at liquid-liquid interfaces. Our results approach the optimal combination of background suppression, localisation precision and temporal resolution achievable with pure scattering-based imaging and tracking of nanoparticles at regular interfaces.

physics.optics↗
arXiv2017

Learning Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes

3D convolutional neural networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object. In this paper, we present a 3D-CNN based method to learn distinct local geometric features of interest within an object. In this context, the voxelized representation may not be sufficient to capture the distinguishing information about such local features. To enable efficient learning, we augment the voxel data with surface normals of the object boundary. We then train a 3D-CNN with this augmented data and identify the local features critical for decision-making using 3D gradient-weighted class activation maps. An application of this feature identification framework is to recognize difficult-to-manufacture drilled hole features in a complex CAD geometry. The framework can be extended to identify difficult-to-manufacture features at multiple spatial scales leading to a real-time decision support system for design for manufacturability.

cs.CV↗
arXiv2016

Label-free single molecule imaging with numerical aperture-shaped interferometric scattering microscopy

Our ability to optically interrogate nanoscopic objects is controlled by the difference between their extinction cross sections and the diffraction limited area to which light can be confined in the far field. We show that a partially transmissive spatial mask placed near the back focal plane of a high numerical aperture microscope objective enhances the extinction contrast of a scatterer near an interface by approximately $T^{-1/2}$, where T is the transmissivity of the mask. Numerical aperture based differentiation of background from scattered light represents a general approach to increasing extinction contrast and enables routine label free imaging down to the single molecule level.

physics.optics↗