Abstract: The trapping of positrons at the surface of a material can be exploited to study quite selectively the surface properties of the latter by means of positron annihilation spectroscopy techniques. To support these, it is desirable to be able to theoretically predict the existence of such positronic surface states and to describe their annihilation characteristics with core or valence surface electrons in a reliable way. Here, we build on the well-developed first-principles techniques for the study of positrons in bulk solids as well as on previous models for surfaces, and investigate two schemes that can improve the theoretical description of the interaction of positrons with surfaces. One is based on supplementing the local-density correlation potential with the corrugated image potential at the surface, and the other is based on the weighted-density approximation to correlation. We discuss our results for topological insulators, graphene layers, and quantum dots, with emphasis on the information that can be directly related to experiment. We also discuss some open theoretical problems that should be addressed by future research.

Abstract: In this study, we explore the possibility to use deep learning for the reconstruction of phase images from 4D scanning transmission electron microscopy (4D-STEM) data. The process can be divided into two main steps. First, the complex electron wave function is recovered for a convergent beam electron diffraction pattern (CBED) using a convolutional neural network (CNN). Subsequently, a corresponding patch of the phase object is recovered using the phase object approximation. Repeating this for each scan position in a 4D-STEM dataset and combining the patches by complex summation yields the full-phase object. Each patch is recovered from a kernel of 3x3 adjacent CBEDs only, which eliminates common, large memory requirements and enables live processing during an experiment. The machine learning pipeline, data generation, and the reconstruction algorithm are presented. We demonstrate that the CNN can retrieve phase information beyond the aperture angle, enabling super-resolution imaging. The image contrast formation is evaluated showing a dependence on the thickness and atomic column type. Columns containing light and heavy elements can be imaged simultaneously and are distinguishable. The combination of super-resolution, good noise robustness, and intuitive image contrast characteristics makes the approach unique among live imaging methods in 4D-STEM.

Abstract: Melittin (MEL), a small peptide component of bee venom, has been reported to exhibit anti-cancer effects in vitro and in vivo. However, its clinical applicability is disputed because of its non-specific cytotoxicity and haemolytic activity in high treatment doses. Plasma-treated phosphate buffered saline solution (PT-PBS), a solution rich in reactive oxygen and nitrogen species (RONS) can disrupt the cell membrane integrity and induce cancer cell death through oxidative stress-mediated pathways. Thus, PT-PBS could be used in combination with MEL to facilitate its access into cancer cells and to reduce the required therapeutic dose. The aim of our study is to determine the reduction of the effective dose of MEL required to eliminate cancer cells by its combination with PT-PBS. For this purpose, we have optimised the MEL threshold concentration and tested the combined treatment of MEL and PT-PBS on A375 melanoma and MCF7 breast cancer cells, using in vitro, in ovo and in silico approaches. We investigated the cytotoxic effect of MEL and PT-PBS alone and in combination to reveal their synergistic cytological effects. To support the in vitro and in ovo experiments, we showed by computer simulations that plasma-induced oxidation of the phospholipid bilayer leads to a decrease of the free energy barrier for translocation of MEL in comparison with the non-oxidized bilayer, which also suggests a synergistic effect of MEL with plasma induced oxidation. Overall, our findings suggest that MEL in combination with PT-PBS can be a promising combinational therapy to circumvent the non-specific toxicity of MEL, which may help for clinical applicability in the future.

Abstract: It is generally known that antidiabetic activity is associated with an increased level of glucose uptake in adipocytes and skeletal muscle cells. However, the role of exogenous reactive oxygen and nitrogen species (RONS) in muscle development and more importantly in glucose uptake is largely unknown. We investigate the effect of RONS generated by cold atmospheric plasma (CAP) in glucose uptake. We show that the glucose uptake is significantly enhanced in differentiated L6 skeletal muscle cells after CAP treatment. We also observe a significant increase of the intracellular Ca++ and ROS level, without causing toxicity. One of the possible reasons for an elevated level of glucose uptake as well as intracellular ROS and Ca++ ions is probably the increased oxidative stress leading to glucose transport.

Abstract: The optical response of metal nanoparticles is governed by plasmonic resonances, which are dictated by the particle morphology. A thorough understanding of the link between morphology and optical response requires quantitatively measuring optical and structural properties of the same particle. Here we present such a study, correlating electron tomography and optical micro-spectroscopy. The optical measurements determine the scattering and absorption cross-section spectra in absolute units, and electron tomography determines the 3D morphology. Numerical simulations of the spectra for the individual particle geometry, and the specific optical set-up used, allow for a quantitative comparison including the cross-section magnitude. Silver nanoparticles produced by photochemically driven colloidal synthesis, including decahedra, tetrahedra and bi-tetrahedra are investigated. A mismatch of measured and simulated spectra is found in some cases when assuming pure silver particles, which is explained by the presence of a few atomic layers of tarnish on the surface, not evident in electron tomography. The presented method tightens the link between particle morphology and optical response, supporting the predictive design of plasmonic nanomaterials.