Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: We compare three first-principles methods of calculating the Curie temperature in two-dimensional (2D) ferromagnetic materials (FM), modeled using the Heisenberg model, and propose a simple formula for estimating the Curie temperature with high accuracy that works for all common 2D lattice types. First, we study the effect of exchange anisotropy on the Curie temperature calculated using the Monte Carlo (MC), the Green's function, and the renormalized spin-wave (RNSW) methods. We find that the Green's function method overestimates the Curie temperature in high-anisotropy regimes compared to the MC method, whereas the RNSW method underestimates the Curie temperature compared to the MC and the Green's function methods. Next, we propose a closed-form formula for calculating the Curie temperature of 2D FMs, which provides an estimate of the Curie temperature that is greatly improved over the mean-field expression for magnetic material screening. We apply the closed-form formula to predict the Curie temperature 2D magnets screened from the C2DB database and discover several high Curie temperature FMs, with Fe2F2 and MoI2 emerging as the most promising 2D ferromagnets. Finally, by comparing to experimental results for CrI3, CrCl3, and CrBr3, we conclude that for small effective anisotropies, the Green's-function-based equations are preferable, while for larger anisotropies, MC-based results are more predictive.

Abstract: We investigate the diffusive electron-transport properties of charge-doped graphene ribbons and nanoribbons with imperfect edges. We consider different regimes of edge scattering, ranging from wide graphene ribbons with (partially) diffusive edge scattering to ribbons with large width variations and nanoribbons with atomistic edge roughness. For the latter, we introduce an approach based on pseudopotentials, allowing for an atomistic treatment of the band structure and the scattering potential, on the self-consistent solution of the Boltzmann transport equation within the relaxation-time approximation and taking into account the edge-roughness properties and statistics. The resulting resistivity depends strongly on the ribbon orientation, with zigzag (armchair) ribbons showing the smallest (largest) resistivity and intermediate ribbon orientations exhibiting intermediate resistivity values. The results also show clear resistivity peaks, corresponding to peaks in the density of states due to the confinement-induced subband quantization, except for armchair-edge ribbons that show a very strong width dependence because of their claromatic behavior. Furthermore, we identify a strong interplay between the relative position of the two valleys of graphene along the transport direction, the correlation profile of the atomistic edge roughness, and the chiral valley modes, leading to a peculiar strongly suppressed resistivity regime, most pronounced for the zigzag orientation.

Abstract: Mechanical deformations and ensuing strain are routinely exploited to tune the band gap energy and to enhance the functionalities of two-dimensional crystals. In this Letter, we show that strain leads also to a strong modification of the exciton magnetic moment in WS2 monolayers. Zeeman-splitting measurements under magnetic fields up to 28.5 T were performed on single, one-layer-thick WS2 microbubbles. The strain of the bubbles causes a hybridization of k-space direct and indirect excitons resulting in a sizable decrease in the modulus of they factor of the ground-state exciton. These findings indicate that strain may have major effects on the way the valley number of excitons can be used to process binary information in two-dimensional crystals.

Abstract: Two-dimensional systems of inverse patchy colloids modeled as disks with a central charge and having their surface decorated with oppositely pointlike charged patches are investigated using molecular dynamics simulations. The self-assembly of the patchy colloids leads to diverse ground state configurations ranging from crystalline arrangements of monomers to linear clusters, ramified linear clusters and to percolated configurations. Two structural phase diagrams are constructed: (1) as a function of the net charge and area fraction, and (2) as a function of the net charge and the range of the pair interaction potential. An interesting reentrant percolation transition is obtained as a function of the net charge of the colloids. We identify distinct mechanisms that lead to the percolation transition.

Abstract: Using spin- and angle-resolved photoemission spectroscopy and relativistic many-body calculations, we investigate the evolution of the electronic structure of (Bi1-xInx)(2)Se-3)(2)Se-3 bulk single crystals around the critical point of the trivial to topological insulator quantum-phase transition. By increasing x, we observe how a surface gap opens at the Dirac point of the initially gapless topological surface state of Bi2Se3, leading to the existence of massive fermions. The surface gap monotonically increases for a wide range of x values across the topological and trivial sides of the quantum-phase transition. By means of photon-energy-dependent measurements, we demonstrate that the gapped surface state survives the inversion of the bulk bands which occurs at a critical point near x = 0.055. The surface state exhibits a nonzero in-plane spin polarization which decays exponentially with increasing x, and which persists in both the topological and trivial insulator phases. Our calculations reveal qualitative agreement with the experimental results all across the quantum-phase transition upon the systematic variation of the spin-orbit coupling strength. A non-time-reversal symmetry-breaking mechanism of bulk-mediated scattering processes that increase with decreasing spin-orbit coupling strength is proposed as explanation.

Abstract: Digital disconnection has emerged as a concept describing the actions people take to limit their digital connectivity to enhance their well-being. To date, evidence on its effectiveness is mixed, leading to calls for greater consideration of why, how, when, and for whom digital disconnection works. This article responds to these calls, presenting a framework that differentiates four key harms that contribute to experiences of digital ill-being (time displacement, interference, role blurring, and exposure effects). Using these four harms as a starting point, the framework explains: (1) why people are motivated to digitally disconnect; (2) how specific disconnection strategies (i.e., placing limits on time, access, channels, and contents, interactions and features) may help them; and for whom (3) and under which conditions (when) these strategies can be effective.

Abstract: To sustain human deep space exploration or extra-terrestrial settlements where no resupply from the Earth or other planets is possible, technologies for in situ food production, water, air, and waste recovery need to be developed. The Micro-Ecological Life Support System Alternative (MELiSSA) is such a Regenerative Life Support System (RLSS) and it builds on several bacterial bioprocesses. However, alterations in gravity, temperature, and radiation associated with the space environment can affect survival and functionality of the microorganisms. In this study, representative strains of different carbon and nitrogen metabolisms with application in the MELiSSA were selected for launch and Low Earth Orbit (LEO) exposure. An edible photoautotrophic strain (Arthrospira sp. PCC 8005), a photoheterotrophic strain (Rhodospirillum rubrum S1H), a ureolytic heterotrophic strain (Cupriavidus pinatubonensis 1245), and combinations of C. pinatubonensis 1245 and autotrophic ammonia and nitrite oxidizing strains (Nitrosomonas europaea ATCC19718, Nitrosomonas ureae Nm10, and Nitrobacter winogradskyi Nb255) were sent to the International Space Station (ISS) for 7 days. There, the samples were exposed to 2.8 mGy, a dose 140 times higher than on the Earth, and a temperature of 22 degrees C +/- 1 degrees C. On return to the Earth, the cultures were reactivated and their growth and activity were compared with terrestrial controls stored under refrigerated (5 degrees C +/- 2 degrees C) or room temperature (22 degrees C +/- 1 degrees C and 21 degrees C +/- 0 degrees C) conditions. Overall, no difference was observed between terrestrial and ISS samples. Most cultures presented lower cell viability after the test, regardless of the type of exposure, indicating a harsher effect of the storage and sample preparation than the spaceflight itself. Postmission analysis revealed the successful survival and proliferation of all cultures except for Arthrospira, which suffered from the premission depressurization test. These observations validate the possibility of launching, storing, and reactivating bacteria with essential functionalities for microbial bioprocesses in RLSS.

Abstract: Traditionally, direct imaging of atom diffusion is only available by scanning tunneling microscopy and field ion microscopy on geometry-constrained samples: flat surfaces for STM and needle tips for FIM. Here we show time-resolved atomic-scale HRTEM investigations of CeO2-supported Au nanoparticle surfaces to characterize the surface dynamics of atom columns on gold nanoparticles. The observed surface dynamics have been categorized into four types: layer jumping, layer gliding, re-orientation and surface reconstruction. We successfully captured atoms moving in a concerted manner with a time resolution of 0.1 s. A quantitative approach for measuring the dynamics in various gaseous surroundings at elevated temperatures is presented. An approach for measuring quantitative electron beam effects on the surface dynamics is presented by counting atom column occupation as a function of time under a range of dose rates in high vacuum.

Abstract: In the present work, kelvin probe force microscopy (KPFM) technique has been used to study the CZTSe/CuxSe bilayer interface prepared by multi-step deposition and selenization process of metal precursors. Transmission electron microscopy (TEM) confirmed the bilayer configuration of the CZTSe/CuxSe sample. Two configuration modes (surface mode and junction mode) in KPFM have been employed in order to measure the junction voltage under illumination conditions. The results show that CZTSe/CuxSe has small junction voltage of similar to 21 mV and the presence of CuxSe secondary phase in the CZTSe grain boundaries changes the workfunction of the local grain boundaries region. The negligible photovoltage difference between grain and grain boundaries in photovoltage image indicates that CuxSe phase deteriorates the higher photovoltage at grain boundaries normally observed in CZTSe based device. These results can be important for understanding the role of secondary phases in CZTSe based junction devices.

Abstract: Environmental parameters such as temperature, relative humidity, visible light, UV radiation and pollution influence the deterioration rate of heritage items. To judge on the environmental appropriateness for heritage conservation, it is therefore important to monitor the environment. Often, an incomplete set of environmental parameters is measured, or sporadic or time-averaged measurements are performed. As a result, a wide range of undesirable situations and hazards remain unnoticed. This might lead to an underestimation of environmental dangers (i.e., inaccurate judgement) or to inappropriate mitigation measures (i.e., inaccurate decision making). We present an innovative and user-friendly monitoring device that simultaneously and continuously measures (1) environmental parameters and (2) material behavior. An extended combination of off-the-shelf sensors for temperature, relative humidity, air speed, CO2, NO2, O-3 and particulate matter are connected to a multipurpose datalogger. In-house developed sensors for the shrinkage and expansion behavior of wood, as well as sensors for metal corrosion rates are connected to the same datalogger. Such extended monitoring shows the identification of a wider range of undesirable situations, and it facilitates the search for correlations between such situations and the sources that cause them, i.e., the hazards.

Abstract: Iron mineral containing sensory dendrites in the inner lining of the upper beak of homing pigeons [1] and various bird species [2] are the first candidate structures for an avian magnetic field receptor. A new concept of magnetoreception [3, 4] is based on detailed ultra-structural optical and electron microscopy analyses in combination with synchrotron radiation microscopic X-ray fluorescence analysis (micro-XRF) and microscopic X-ray absorption near edge structures (micro-XANES). Several behavioral experiments [5, 6] and first mathematical simulations [6] affirm our avian magnetoreceptor model. The iron minerals inside the dendrites are housed in three different subcellular compartments (bullets, platelets, vesicles), which could be clearly resolved and identified by electron microscopy on ultrathin sections [1, 3]. Micro-XRF and micro-XANES data obtained at HASYLAB beamline L added information about the elemental distribution and Fe speciation [3], but are averaged over the complete dendrite due to limited spatial resolution. Here we present recently performed micro-XRF maps with sub-micrometer resolution (ESRF ID21), which reveal for the first time subcellular structural information from almost bulk-like dendrite sample material. Due to the thickness of 30 μm the microarchitecture of the dendrites can be considered as undisturbed and artefacts introduced by sectioning might be widely reduced.

Abstract: CO2 dissociation and its subsequent conversion into added-value chemicals is a promising strategy for recycling CO2 gas into reusable products. One of the possible methods is direct plasma-induced dissociation. In this work we study the efficiency of CO2 dissociation in pulsed atmospheric-pressure gas discharge between two conducting electrodes by a 0-D numerical plasma model. The purpose of the study is to provide results on the optimal conditions of CO2 conversion with respect to the energy efficiency and dissociation by varying the maximum power density value and the pulse length. The power density is directly related to the discharge current and the reduced electric field in the discharge. We consider pulse lengths in the range from hundreds of nanosecond up to milliseconds. The results obtained show that the dissociation degree and energy efficiency are sensitive to the pulse length (duration) and the power density, so that a considerable improvement of the discharge performance can be achieved by fine-tuning these parameters. The study is intended to provide guidance in designing an experimental set-up and a power supply with the characteristics necessary to achieve optimal conversion.

Abstract: The study analysed the factors that affect the internal governance quality of corporations in Ethiopia. It performed an ordered logistic regression analysis on a randomly selected sample of 76 corporations to analyse the effect of the ownership structure, form of ownership (private or government), leverage, corporate size, and sales growth on the internal governance quality score (IGQS). The governance quality score was measured using 20 indices categorized into four perspectives: disclosure, board characteristics, ethics, and shareholder rights. In this study, a significant positive effect of the corporate size and sales growth on the IGQS was found. In addition, government-owned corporations were found to perform better than privately owned corporations. It is recommended that appropriate authorities and officials should encourage the use of the corporate governance system in privately owned corporations and the convergence of internal governance quality of the two groups of corporations to the highest level.