18 research outputs found
Conductance distribution in nanometer-sized semiconductor devices due to dopant statistics
Understanding Gold Growth on Magnetite Nanoparticles using Probe-Corrected Scanning Transmission Electron Microscopy
Fluctuation X-ray microscopy: a novel approach for the structural study of disordered materials
Computational Structure Refinement by Hybrid Reverse Monte Carlo Simulation Incorporating Fluctuation Electron Microscopy
Variation of hardness and modulus across the thickness of Zr-Cu-Al metallic glass ribbons
We investigate through-thickness hardness and modulus of Zr50Cu45Al5 metallic glass melt-spun ribbon. Because of their thinness, the ribbons are challenging to measure, so we employ a novel nanoindentation based-method to remove artifacts caused by ribbon flexing and edge effects. Hardness and modulus vary approximately linearly across the thickness but, unlike bulk ingots, the side of the ribbon that cooled most quickly had the highest hardness and modulus. This “inverse” variation may be caused by the fast-moving solidification front, which might conceivably, for instance, push free volume in advance of it. Annealing near T g causes both hardness and modulus to increase and become more uniform across the thickness
Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images
Image registration and non-local Poisson principal component analysis (PCA) denoising improve the quality of characteristic x-ray (EDS) spectrum imaging of Ca-stabilized Nd2/3TiO3 acquired at atomic resolution in a scanning transmission electron microscope. Image registration based on the simultaneously acquired high angle annular dark field image significantly outperforms acquisition with a long pixel dwell time or drift correction using a reference image. Non-local Poisson PCA denoising reduces noise more strongly than conventional weighted PCA while preserving atomic structure more faithfully. The reliability of and optimal internal parameters for non-local Poisson PCA denoising of EDS spectrum images is assessed using tests on phantom data