Denoising time-resolved microscopy image sequences with singular value thresholding.

Time-resolved imaging in microscopy is important for the direct observation of a range of dynamic processes in both the physical and life sciences. However, the image sequences are often corrupted by noise, either as a result of high frame rates or a need to limit the radiation dose received by the sample. Here we exploit both spatial and temporal correlations using low-rank matrix recovery methods to denoise microscopy image sequences. We also make use of an unbiased risk estimator to address the issue of how much thresholding to apply in a robust and automated manner. The performance of the technique is demonstrated using simulated image sequences, as well as experimental scanning transmission electron microscopy data, where surface adatom motion and nanoparticle structural dynamics are recovered at rates of up to 32 frames per second.Junior Research Fellowship from Clare CollegeThis is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ultramic.2016.05.00

Directional Sinogram Inpainting for Limited Angle Tomography

In this paper we propose a new joint model for the reconstruction of tomography data under limited angle sampling regimes. In many applications of Tomography, e.g. Electron Microscopy and Mammography, physical limitations on acquisition lead to regions of data which cannot be sampled. Depending on the severity of the restriction, reconstructions can contain severe, characteristic, artefacts. Our model aims to address these artefacts by inpainting the missing data simultaneously with the reconstruction. Numerically, this problem naturally evolves to require the minimisation of a non-convex and non-smooth functional so we review recent work in this topic and extend results to fit an alternating (block) descent framework. \oldtext{We illustrate the effectiveness of this approach with numerical experiments on two synthetic datasets and one Electron Microscopy dataset.} \newtext{We perform numerical experiments on two synthetic datasets and one Electron Microscopy dataset. Our results show consistently that the joint inpainting and reconstruction framework can recover cleaner and more accurate structural information than the current state of the art methods

Structural and Optical Properties of Discrete Dendritic Pt Nanoparticles on Colloidal Au Nanoprisms.

Catalytic and optical properties can be coupled by combining different metals into nanoscale architectures in which both the shape and the composition provide fine-tuning of functionality. Here, discrete, small Pt nanoparticles (diameter = 3-6 nm) were grown in linear arrays on Au nanoprisms, and the resulting structures are shown to retain strong localized surface plasmon resonances. Multidimensional electron microscopy and spectroscopy techniques (energy-dispersive X-ray spectroscopy, electron tomography, and electron energy-loss spectroscopy) were used to unravel their local composition, three-dimensional morphology, growth patterns, and optical properties. The composition and tomographic analyses disclose otherwise ambiguous details of the Pt-decorated Au nanoprisms, revealing that both pseudospherical protrusions and dendritic Pt nanoparticles grow on all faces of the nanoprisms (the faceted or occasionally twisted morphologies of which are also revealed), and shed light on the alignment of the Pt nanoparticles. The electron energy-loss spectroscopy investigations show that the Au nanoprisms support multiple localized surface plasmon resonances despite the presence of pendant Pt nanoparticles. The plasmonic fields at the surface of the nanoprisms indeed extend into the Pt nanoparticles, opening possibilities for combined optical and catalytic applications. These insights pave the way toward comprehensive nanoengineering of multifunctional bimetallic nanostructures, with potential applications in plasmon-enhanced catalysis and in situ monitoring of chemical processes via surface-enhanced spectroscopy.R. K. L. acknowledges support from a Clare College Junior Research Fellowship. S. M. C. acknowledges support from a Gates Cambridge Scholarship. This work has received funding from the European Union Seventh Framework Programme under Grant Agreement 312483-ESTEEM2 (Integrated Infrastructure Initiative-I3), and support from the European Research Council, Reference 291522 3DIMAGE. J. E. M. acknowledges support from the Research Corporation for Science Advancement.This is the author accepted manuscript. The final version is available from the American Chemical Society via http://dx.doi.org/10.1021/acs.jpcc.6b0210

The rapidly changing face of electron microscopy

This is the final version. It was first published by Elsevier at http://www.sciencedirect.com/science/article/pii/S0009261415003024.This short but wide-ranging review is intended to convey to chemical physicists and others engaged in the interfaces between solid-state chemistry and solid-state physics the growing power and extensive applicability of multiple facets of the technique of electron microscopy.R.K.L. acknowledges a Junior Research Fellowship at Clare College. P.A.M. acknowledges funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007?2013)/ERC grant agreement 291522-3DIMAGE. A.S.E. acknowledges the Royal Society for funding. J.M.T. is grateful for the support of the Kohn Foundation

Directional Sinogram Inpainting for Limited Angle Tomography

In this paper we propose a new joint model for the reconstruction of tomography data under limited angle sampling regimes. In many applications of Tomography, e.g. Electron Microscopy and Mammography, physical limitations on acquisition lead to regions of data which cannot be sampled. Depending on the severity of the restriction, reconstructions can contain severe, characteristic, artefacts. Our model aims to address these artefacts by inpainting the missing data simultaneously with the reconstruction. Numerically, this problem naturally evolves to require the minimisation of a non-convex and non-smooth functional so we review recent work in this topic and extend results to fit an alternating (block) descent framework. \oldtext{We illustrate the effectiveness of this approach with numerical experiments on two synthetic datasets and one Electron Microscopy dataset.} \newtext{We perform numerical experiments on two synthetic datasets and one Electron Microscopy dataset. Our results show consistently that the joint inpainting and reconstruction framework can recover cleaner and more accurate structural information than the current state of the art methods

The dark side of EDX tomography ::modeling detector shadowing to aid 3D elemental signal analysis

A simple model is proposed to account for the loss of collected X-ray signal by the shadowing of X-ray detectors in the scanning transmission electron microscope. The model is intended to aid the analysis of three-dimensional elemental data sets acquired using energy-dispersive X-ray tomography methods where shadow-free specimen holders are unsuitable or unavailable. The model also provides a useful measure of the detection system geometry

Tailoring the framework composition of carbon nitride to improve the catalytic efficiency of the stabilised palladium atoms

ISSN:2050-7488ISSN:2050-749