Abstract: Ando's surface roughness model is applied to metallic nanowires and extended beyond small roughness size and infinite barrier limit approximations for the wavefunction overlaps, such as the Prange-Nee approximation. Accurate and fast simulations can still be performed without invoking these overlap approximations by averaging over roughness profiles using finite domain distribution functions to obtain an analytic solution for the scattering rates. The simulations indicate that overlap approximations, while predicting a resistivity that agrees more or less with our novel approach, poorly estimate the underlying scattering rates. All methods show that a momentum gap between left- and right-moving electrons at the Fermi level, surpassing a critical momentum gap, gives rise to a substantial decrease in resistivity.

Abstract: The tunneling current between two crossed graphene ribbons is described invoking the empirical pseudopotential approximation and the Bardeen transfer Hamiltonian method. Results indicate that the density of states is the most important factor determining the tunneling current between small (similar to nm) ribbons. The quasi-one dimensional nature of graphene nanoribbons is shown to result in resonant tunneling.

Abstract: A new application which focuses on an artificial sphincter fabricated by Ni-Ti SMAs for human implantation is under investigation by applying the all-round shape memory effect with precise control of the phase transformation temperatures. In this study, a Ni51at.%-Ti alloy was fabricated by arc melting with fast solidification, followed by a proper strained aging which induces the two way shape memory effect needed for this particular application. Differential scanning calorimetry was used to investigate the thermal behavior and transmission electron microscopy was used for studying the microstructure of the alloys. With the latter the novel technique of automated crystal orientation microscopy is used and optimized to obtain phase and orientation mapping of the various structures.

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.