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: Targeting the redox balance of malignant cells via the delivery of high oxidative stress unlocks a potential therapeutic strategy against glioblastoma (GBM). We investigated a novel reactive oxygen species (ROS)-inducing combination treatment strategy, by increasing exogenous ROS via cold atmospheric plasma and inhibiting the endogenous protective antioxidant system via auranofin (AF), a thioredoxin reductase 1 (TrxR) inhibitor. The sequential combination treatment of AF and cold atmospheric plasma-treated PBS (pPBS), or AF and direct plasma application, resulted in a synergistic response in 2D and 3D GBM cell cultures, respectively. Differences in the baseline protein levels related to the antioxidant systems explained the cell-line-dependent sensitivity towards the combination treatment. The highest decrease of TrxR activity and GSH levels was observed after combination treatment of AF and pPBS when compared to AF and pPBS monotherapies. This combination also led to the highest accumulation of intracellular ROS. We confirmed a ROS-mediated response to the combination of AF and pPBS, which was able to induce distinct cell death mechanisms. On the one hand, an increase in caspase-3/7 activity, with an increase in the proportion of annexin V positive cells, indicates the induction of apoptosis in the GBM cells. On the other hand, lipid peroxidation and inhibition of cell death through an iron chelator suggest the involvement of ferroptosis in the GBM cell lines. Both cell death mechanisms induced by the combination of AF and pPBS resulted in a significant increase in danger signals (ecto-calreticulin, ATP and HMGB1) and dendritic cell maturation, indicating a potential increase in immunogenicity, although the phagocytotic capacity of dendritic cells was inhibited by AF. In vivo, sequential combination treatment of AF and cold atmospheric plasma both reduced tumor growth kinetics and prolonged survival in GBM-bearing mice. Thus, our study provides a novel therapeutic strategy for GBM to enhance the efficacy of oxidative stress-inducing therapy through a combination of AF and cold atmospheric plasma.

Abstract: We present a computational model to model the magnetic structure of two-dimensional (2D) dilute-magnetic-semiconductors (DMS) both the monolayers and multilayers using first-principles density functional theory (DFT), as well as their magnetic phase transition as a function of temperature using Monte-Carlo simulations. Using our method, we model the magnetic structure of bulk, bilayer, and monolayer MoS2 substitutionally doped with Fe atoms. We find that the out-of-plane interaction in bilayer MoS2 is weakly ferromagnetic, whereas in bulk MoS2 it is strongly anti-ferromagnetic. Finally, we show that the magnetic order is more robust in bilayer Fe-doped MoS2 compared to the monolayer and results in a room-temperature FM at an atomic substitution of 14-16%.

Abstract: Heterogeneous catalysts are often & ldquo;black boxes & rdquo; due to the insufficient understanding of the detailed mechanisms at the catalytic sites. An atomic-level elucidation of the processes taking place in those regions is, thus, mandatory to produce robust and selective heterogeneous catalysts. We have improved the description of the whole reactive scenario for polymeric carbon nitrides (PCN) by combining atomic-level characterizations with magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy, classical reactive molecular dynamics (RMD) simulations, and quantum chemistry (QC) calculations. We disclose the structure & minus;property relationships of an ad hoc modified PCN by inserting an aryl amino group that turned out to be very efficient for the production of H2O2. The main advancement of this work is the development of a difluoromethylene-substituted aryl amino PCN to generate H2O2 at a rate of 2.0 mM & middot;h & minus;1 under the irradiation of household blue LEDs and the identification of possible active catalytic sites with the aid of 15N and 19F MAS solid-state NMR without using any expensive labeling reagent. RMD simulations and QC calculations confirm and further extend the experimental descriptions by revealing the role and locations of the identified functionalities, namely, NH linkers, & minus;NH2 terminal groups, and difluoromethylene units, reactants, and products. <comment>Superscript/Subscript Available</comment

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: The physics and chemistry of plasma–surface interaction is a broad domain relevant to various applications and several natural processes, including plasma etching for microelectronics fabrication, plasma deposition, surface functionalization, nanomaterial synthesis, fusion reactors, and some astrophysical and meteorological phenomena. Due to their complex nature, each of these processes is generally investigated in separate subdomains, which are considered to have their own theoretical, modeling, and experimental challenges. In this review, however, we want to emphasize the overarching nature of plasma–surface interaction physics and chemistry, by focusing on the general strategy for its computational simulation. In the first half of the review, we provide a menu card with standard and less standardized computational methods to be used for the multiscale modeling of the underlying processes. In the second half, we illustrate the benefits and potential of the multiscale modeling strategy with a case study of Si and SiO2 etching by fluorocarbon plasmas and identify the gaps in knowledge still present on this intensely investigated plasma–material combination, both on a qualitative and quantitative level. Remarkably, the dominant etching mechanisms remain the least understood. The resulting new insights are of general relevance, for all plasmas and materials, including their various applications. We therefore hope to motivate computational and experimental scientists and engineers to collaborate more intensely on filling the existing gaps in knowledge. In this way, we expect that research will overcome a bottleneck stage in the development and optimization of multiscale models, and thus the fundamental understanding of plasma–surface interaction.

Abstract: 3D characterization of assemblies of nanoparticles is of great importance to determine their structure-property connection. Such investigations become increasingly more challenging when the assemblies become larger and more compact. In this paper, we propose an optimized approach for electron tomography to minimize artefacts related to beam broadening in High Angle Annular Dark-Field Scanning Transmission Electron Microscopy mode. These artefacts are typically present at one side of the reconstructed 3D data set for thick nanoparticle assemblies. To overcome this problem, we propose a procedure in which two tomographic tilt series of the same sample are acquired. After acquiring the first series, the sample is flipped over 180o, and a second tilt series is acquired. By merging the two reconstructions, blurring in the reconstructed volume is minimized. Next, this approach is combined with an advanced three-dimensional reconstruction algorithm yielding quantitative structural information. Here, the approach is applied to a thick and compact assembly of spherical Au nanoparticles, but the methodology can we used to investigate a broad range of samples.

Abstract: Metal halide perovskites are one of the most investigated materials in optoelectronics, with their lead-based counterparts being renowned for their enhanced optoelectronic performance. The 3D CsPbX3 structure has set the standard with many studies currently attempting to substitute lead with other metals while retaining the properties of this material. This effort has led to the fabrication of metal halides with lower dimensionality, wherein particular 2D layered perovskite structures have captured attention as inspiration for the next generation of colloidal semiconductors. Here we report the synthesis of the Ruddlesden-Popper Cs2CdCl4:Sb3+ phase as colloidal nanoplatelets (NPs) using a facile hot injection approach under atmospheric conditions. Through strict adjustment of the synthesis parameters with emphasis on the ligand ratio, we obtained NPs with a relatively uniform size and good morphological control. The particles were characterized through transmission electron microscopy, synchrotron X-ray diffraction, and pair distribution function analysis. The spectroscopic characterization revealed most strikingly an intense cyan emission under UV excitation with a measured PLQY of similar to 20%. The emission was attributed to the Sb3+-doping within the structure.

Abstract: The structural and magnetic properties of LaMnO₃/LaFeO₃(LMO/LFO) heterostructures are characterized using a combination of scanning transmission electron microscopy, electron energy-loss spectroscopy, bulk magnetometry, and resonant x-ray reflectivity. Unlike the relatively abrupt interface when LMO is deposited on top of LFO, the interface with reversed growth order shows significant cation intermixing of Mn³⁺and Fe³⁺, spreading ∼8 unit cells across the interface. The asymmetric interfacial chemical profiles result in distinct magnetic properties. The bilayer with abrupt interface shows a single magnetic hysteresis loop with strongly enhanced coercivity, as compared to the LMO plain film. However, the bilayer with intermixed interface shows a step-like hysteresis loop, associated with the separate switching of the “clean” and intermixed LMO sublayers. Our study illustrates the key role of interfacial chemical profile in determining the functional properties of oxide heterostructures.

Abstract: The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of materials, but electron scattering simulations based on atomistic models are widely used in materials science and structural biology. Since electron scattering is dominated by the nuclear cores, the scattering potential is typically described by the widely applied independent atom model. This approximation is fast and fairly accurate, especially for scanning TEM (STEM) annular dark-field contrast, but it completely neglects valence bonding and its effect on the transmitting electrons. However, an emerging trend in electron microscopy is to use new instrumentation and methods to extract the maximum amount of information from each electron. This is evident in the increasing popularity of techniques such as 4D-STEM combined with ptychography in materials science, and cryogenic microcrystal electron diffraction in structural biology, where subtle differences in the scattering potential may be both measurable and contain additional insights. Thus, there is increasing interest in electron scattering simulations based on electrostatic potentials obtained from first principles, mainly via density functional theory, which was previously mainly required for holography. In this Review, we discuss the motivation and basis for these developments, survey the pioneering work that has been published thus far, and give our outlook for the future. We argue that a physically better justified ab initio description of the scattering potential is both useful and viable for an increasing number of systems, and we expect such simulations to steadily gain in popularity and importance.

Abstract: The interface-dependent electronic, vibrational, piezoelectric, and optical properties of van der Waals heterobilayers, formed by buckled GeO (b-GeO) and Janus MoSO structures, are investigated by means of first-principles calculations. The electronic band dispersions show that O/Ge and S/O interface formations result in a type-II band alignment with direct and indirect band gaps, respectively. In contrast, O/O and S/Ge interfaces give rise to the formation of a type-I band alignment with an indirect band gap. By considering the Bethe-Salpeter equation (BSE) on top of G(0)W(0) approximation, it is shown that different interfaces can be distinguished from each other by means of the optical absorption spectra as a consequence of the band alignments. Additionally, the low- and high-frequency regimes of the Raman spectra are also different for each interface type. The alignment of the individual dipoles, which is interface-dependent, either weakens or strengthens the net dipole of the heterobilayers and results in tunable piezoelectric coefficients. The results indicate that the possible heterobilayers of b-GeO/MoSO asymmetric structures possess various electronic, optical, and piezoelectric properties arising from the different interface formations and can be distinguished by means of various spectroscopic techniques.

Abstract: We study the electronic spectral properties at zero temperature of the one-dimensional (1D) version of the degenerate two-orbital Kanamori-Hubbard model, one of the well-established frameworks to study transition metal compounds, using state-of-the-art numerical techniques based on the density matrix renormalization group. While the system is Mott insulating for the half-filled case, as expected for an interacting 1D system, we find interesting and rich structures in the single-particle density of states (DOS) for the hole-doped system. In particular, we find the existence of in-gap states which are pulled down to lower energies from the upper Hubbard band with increasing the interorbital Coulomb interaction V. We analyze the composition of the DOS by projecting it onto different local excitations, and we observe that for large dopings these in-gap excitations are formed mainly by interorbital holon-doublon (HD) states and their energies follow approximately the HD states in the atomic limit. We observe that the Hund interaction J increases the width of the in-gap band, as expected from the two-particle fluctuations in the Hamiltonian. The observation of a finite density of states within the gap between the Hubbard bands for this extended 1D model indicates that these systems present a rich excitation spectra which could help us understand the microscopic physics behind multiorbital compounds.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

Abstract: We present an extension and revision of the spectroscopic and structural data of the mixed-stack charge-transfer (CT) crystal 3,3 ',5,5 '-tetramethylbenzidine-tetrafluorotetracyano-quinodimethane (TMB-TCNQF4), associated with new electric and dielectric measurements. Refinement of synchrotron structural data at low temperature has led to revise the previously reported C2/m structure. The revised structure is P2(1)/m, with two dimerized stacks per unit cell, and is consistent with the low temperature vibrational data. However, polarized Raman data in the low-frequency region also indicate that by increasing temperature above 200 K, the structure presents an increasing degree of disorder, mainly along the stack axis. X-ray diffraction data at room temperature have confirmed that the correct structure is P2(1)/ m -no phase transitions -but did not allow substantiating the presence of disorder. On the other hand, dielectric measurements have evidenced a typical relaxor ferroelectric behavior already at room temperature, with a peak in the real part of dielectric constant epsilon'(T,v) around 200 K and 0.1 Hz. The relaxor behavior is explained in terms of the presence of spin solitons separating domains of opposite polarity that yield to ferroelectric nanodomains. TMB-TCNQF(4) is confirmed to be a narrow-gap band semiconductor (Ea similar to 0.3 eV) with a room-temperature conductivity of similar to 10(-4) Omega(-1) cm(-1).

Abstract: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.