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: Hybrid pixel direct electron detectors are gaining popularity in electron microscopy due to their excellent properties. Some commercial cameras based on this technology are relatively affordable which makes them attractive tools for experimentation especially in combination with an SEM setup. To support this, a detector characterization (Modulation Transfer Function, Detective Quantum Efficiency) of an Advacam Minipix and Advacam Advapix detector in the 15–30 keV range was made. In the current work we present images of Point Spread Function, plots of MTF/DQE curves and values of DQE(0) for these detectors. At low beam currents, the silicon detector layer behaviour should be dominant, which could make these findings transferable to any other available detector based on either Medipix2, Timepix or Timepix3 provided the same detector layer is used.

Abstract: Thermally induced oxygen release is an intrinsic structural instability in layered cathodes, which causes thermal runaway issues and becomes increasingly critical with the continuous improvement in energy density. Furthermore, thermal runaway events always occur in electrochemically aged cathodes, where the coupling of the thermal and electrochemical effect remains elusive. Herein, we report the anomalous segregation of cobalt metal in an aged LiCoO2 cathode, which is attributed to the local exposure of the high-energy (100) surface of LiCoO2 and weak interface Co-O dangling bonds significantly promoting the diffusion of Co. The presence of the LCO-Co interface severely aggregated the oxygen release in the form of dramatic Co growth. A unique particle-to-particle oxygen release pathway was also found, starting from the isolated high reduction areas induced by the cycling heterogeneity. This study provides atomistic insight into the robust coupling between the intrinsic structural instability and electrochemical cycling.

Abstract: We explore the flatness of conduction and valence bands of interlayer excitons in MoS2/WSe2 van der Waals heterobilayers, tuned by interlayer twist angle, pressure, and external electric field. We employ an efficient continuum model where the moire pattern from lattice mismatch and/or twisting is represented by an equivalent mesoscopic periodic potential. We demonstrate that the mismatch moire potential is too weak to produce significant flattening. Moreover, we draw attention to the fact that the quasi-particle effective masses around the Gamma-point and the band flattening are reduced with twisting. As an alternative approach, we show (i) that reducing the interlayer distance by uniform vertical pressure can significantly increase the effective mass of the moire hole, and (ii) that the moire depth and its band flattening effects are strongly enhanced by accessible electric gating fields perpendicular to the heterobilayer, with resulting electron and hole effective masses increased by more than an order of magnitude – leading to record-flat bands. These findings impose boundaries on the commonly generalized benefits of moire twistronics, while also revealing alternative feasible routes to achieve truly flat electron and hole bands to carry us to strongly correlated excitonic phenomena on demand.

Abstract: High-energy-density nickel (Ni)-rich cathode materials are used in commercial lithium (Li)-ion batteries for electric vehicles, but they suffer from severe structural degradation upon cycling. Planar gliding and microcracking are seeds for fatal mechanical fracture, but their origin remains unclear. Herein, we show that “layer-by -layer delithiation”is activated at high voltages during the charge process when the “lattice collapse”(a characteristic high-voltage lattice evolution in Ni-rich cathodes) occurs. Layer-by-layer deli-thiation is evidenced by direct observation of the consecutive lattice collapse using in situ scanning transmission electron micro-scopy (STEM). The collapsing of the lattice initiates in the expanded planes and consecutively extends to the whole crystal. Localized strain will be induced at lattice-collapsing interface where planar gliding and intragranular microcracks are generated to release this strain. Our study reveals that layer-by-layer delithia-tion during lattice collapse is the fundamental origin of the mechanical instability in single-crystalline Ni-rich cathodes.

Abstract: New & beta;-stabilizedTi-based alloys are highly promising forbone implants, thanks in part to their low elasticity. The natureof this elasticity, however, is as yet unknown. We here present combinedfirst-principles DFT calculations and experiments on the microstructure,structural stability, mechanical characteristics, and electronic structureto elucidate this origin. Our results suggest that the studied & beta;Ti-35Nb-7Zr-5Ta wt % (TNZT) alloy manufacturedby the electron-beam powder bed fusion (E-PBF) method has homogeneousmechanical properties (H = 2.01 & PLUSMN; 0.22 GPa and E = 69.48 & PLUSMN; 0.03 GPa) along the building direction,which is dictated by the crystallographic texture and microstructuremorphologies. The analysis of the structural and electronic properties,as the main factors dominating the chemical bonding mechanism, indicatesthat TNZT has a mixture of strong metallic and weak covalent bonding.Our calculations demonstrate that the softening in the Cauchy pressure(C & PRIME; = 98.00 GPa) and elastic constant C ̅ ( 44 ) = 23.84 GPa is the originof the low elasticity of TNZT. Moreover, the nature of this softeningphenomenon can be related to the weakness of the second and thirdneighbor bonds in comparison with the first neighbor bonds in theTNZT. Thus, the obtained results indicate that a carefully designedTNZT alloy can be an excellent candidate for the manufacturing oforthopedic internal fixation devices. In addition, the current findingscan be used as guidance not only for predicting the mechanical propertiesbut also the nature of elastic characteristics of the newly developedalloys with yet unknown properties.

Abstract: In this theoretical study, we assess the impact of a graphene capping layer on the resistivity of defective, extremely scaled interconnects. We investigate the effect of graphene capping on the electronic transport in ultrascaled interconnects, in the presence of grain boundary defects in the metal layer. We compare the results obtained using our quantum mechanical model to a simple parallel-conductor model and find that the parallel-conductor model does not capture the effect of the graphene cap correctly. At 0.5 nm metal thickness, the parallel-conductor model underestimates the conductivity by 3.0% to 4.0% for single-sided and double sided graphene capping, respectively.

Abstract: Recently, interlayer and intralayer excitons in transition metal dichalcogenide heterobilayers have been studied both experimentally and theoretically. In spite of a growing interest, these layer-resolved excitons in the presence of external stimuli, such as strain, remain not fully understood. Here, using density-functional theory calculations with many-body effects, we explore the excitonic properties of vertically stacked MoSe2/WSe2 heterobilayer in the presence of in-plane biaxial strain of up to 5%. We calculate the strain dependence of exciton absorption spectrum, oscillator strength, wave function, and binding energy by solving the Bethe-Salpeter equation on top of the standard GW approach. We identify the interlayer and intralayer excitons by analyzing their electron-hole weights and spatial wave functions. We show that with the increase in strain magnitude, the absorption spectrum of the interlayer and intralayer excitons is red-shifted and re-ordered, and the binding energies of these layer-resolved excitons decrease monotonically and almost linearly. We derive the sensitivity of exciton binding energy to the applied strain and find that the intralayer excitons are more sensitive to strain than the interlayer excitons. For instance, a sensitivity of -7.9 meV/% is derived for the intra-MoSe2-layer excitons, which is followed by -7.4 meV/% for the intra-WSe2-layer excitons, and by -4.2 meV/% for the interlayer excitons. Our results indicate that interlayer and intralayer excitons in vertically stacked MoSe2/WSe2 heterobilayer are efficiently tunable by in-plane biaxial strain.

Abstract: Hierarchicalassembly of arc-like fractal nanostructures not onlyhas its unique self-similarity feature for stability enhancement butalso possesses the structural advantages of highly exposed surface-activesites for activity enhancement, remaining a great challenge for high-performancemetallic nanocatalyst design. Herein, we report a facile strategyto synthesize a novel arc-like hierarchical fractal structure of PtPdbimetallic nanoparticles (h-PtPd) by using pyridinium-type ionic liquidsas the structure-directing agent. Growth mechanisms of the arc-likenanostructured PtPd nanoparticles have been fully studied, and precisecontrol of the particle sizes and pore sizes has been achieved. Dueto the structural features, such as size control by self-similaritygrowth of subunits, structural stability by nanofusion of subunits,and increased numbers of exposed active atoms by the curved homoepitaxialgrowth, h-PtPd displays outstanding electrocatalytic activity towardoxygen reduction reaction and excellent stability during hydrothermaltreatment and catalytic process.

Abstract: In this work, we have fabricatedan aryl amino-substitutedgraphiticcarbon nitride (g-C3N4) catalyst with atomicallydispersed Mn capable of generating hydrogen peroxide (H2O2) directly from seawater. This new catalyst exhibitedexcellent reactivity, obtaining up to 2230 & mu;M H2O2 in 7 h from alkaline water and up to 1800 & mu;Mfrom seawater under identical conditions. More importantly, the catalystwas quickly recovered for subsequent reuse without appreciable lossin performance. Interestingly, unlike the usual two-electron oxygenreduction reaction pathway, the generation of H2O2 was through a less common two-electron water oxidation reaction(WOR) process in which both the direct and indirect WOR processesoccurred; namely, photoinduced h(+) directly oxidized H2O to H2O2 via a one-step 2e(-) WOR, and photoinduced h(+) first oxidized a hydroxide (OH-) ion to generate a hydroxy radical ((OH)-O-& BULL;), and H2O2 was formed indirectly by thecombination of two (OH)-O-& BULL;. We have characterized thematerial, at the catalytic sites, at the atomic level using electronparamagnetic resonance, X-ray absorption near edge structure, extendedX-ray absorption fine structure, high-resolution transmission electronmicroscopy, X-ray photoelectron spectroscopy, magic-angle spinningsolid-state NMR spectroscopy, and multiscale molecular modeling, combiningclassical reactive molecular dynamics simulations and quantum chemistrycalculations.

Abstract: Two-dimensional (2D) perovskite oxide interfaces are ideal systems to uncover diverse emergent properties, such as the arising polaronic properties from short-range charge-lattice interactions. Thus, a technique to detect this quasiparticle phenomenon at the buried interface is highly coveted. Here, we report the observation of 2D small-polarons at the LaAlO3/SrTiO3 conducting interface using high-resolution spectroscopic ellipsometry. First-principles investigations show that interfacial electron-lattice coupling mediated by the longitudinal phonon mode facilitates the formation of these polarons. This study resolves the long-standing question by attributing the formation of interfacial 2D small polarons to the significant mismatch between experimentally measured interfacial carrier density and theoretical values. Our study sheds light on the complexity of broken periodic lattice-induced quasi-particle effects and its relationship with exotic phenomena at complex oxide interfaces. Meanwhile, this work establishes spectroscopic ellipsometry as a useful technique to detect and locate optical evidence of polaronic states and other emerging quantum properties at the buried interface.

Abstract: Climate change is causing alterations in precipitation patterns, leading to adverse ecological consequences in many ecosystems. Recently, an increasingly persistent weather pattern has emerged, characterized by lengthening the duration of alternating dry and wet periods, which is more complex than exclusively drought or increasing precipitation. It is currently unclear how soil microbial communities respond to these new regimes in relation to their interactions with plants, especially in precipitation-sensitive ecosystems, such as tropical rainforests and grasslands. In this thesis, we explored responses of soil bacterial and fungal communities to increasing weather persistence in rainforests and grasslands, using high throughput sequencing technology. We firstly investigated the resistance and resilience of microbial communities to prolonged drought in a mature seasonal tropical rainforest which experiences unusually intensive dry seasons in the current century. Through excluding rainfall during and after the dry season, a simulated prolongation of the dry season by five months was compared to the control. Our results indicate that as rain exclusion progressed, the microbial communities increasingly diverged from the control, indicating a moderate resistance to prolonged drought. However, when the drought ceased, the composition and co-occurrence patterns of soil microbial communities immediately recovered to that in the control, implying a high resilience. To further investigate the ecological roles of soil microbial communities in response to increasing weather persistence, we set up grassland mesocosm experiments. In these experiments, precipitation frequency was adjusted along a series, ranging from 1 to 60 consecutive days alternating of dry and wet periods, while keeping the total precipitation constant. Our results show that microbial community assembly tended to be more stochastic processes at intermediate persistence of dry and wet alternations while more deterministic processes dominated at low and high persistence within 120 days regime exposure. Moreover, more persistent precipitation reduced the fungal diversity and network connectivity but barely impacted that of bacterial communities. The prior experiences of persistent weather events for one year caused legacy effects. The soil microbial legacy induced by soil microbial communities subjected to prior persistent weather events was more enduring in subsequent fungal communities than bacterial communities, likely due to slower growth of fungi compared to bacteria. However, a minor effect of soil microbial legacy  was observed on plant performance. In addition, we kept the grassland mesocosm experiment for two growing seasons. The effects of precipitation persistence on soil microbial communities increased in the second year. The dissimilarities of microbial communities between the first and second year were less with more persistent precipitation, potentially resulting in more vulnerable microbial communities, due to some taxa disappearing and a reduction in functional redundancy under more persistent weather. To conclude, our findings provide a comprehensive theoretical understanding of soil microbial communities in response to the current and future climate change, drawing from both natural and experimental systems. It helps in predicting and managing the impacts of future climate change on ecosystems mediated by microbial communities. Additionally, the findings of microbe-mediated legacy effects on grassland ecosystems can provide practical guidance for their application in agriculture, specifically for using an inoculum to mitigate the impacts of climate change.

Abstract: In the recent advances towards more sustainable global energy supply, H2 is a possible alternative for large scale energy storage. In this view, Liquid Organic Hydrogen Carriers (LOHC) are a class of molecules that allow for easier long term energy storage compared to conventional H2 technologies. CFD simulations were used to showcase the hydrodynamics of the dehydrogenation of a LOHC in a new reactor unit, via a cold flow mock-up study. This reactor was designed to allow for a swirling motion of the liquid carrier material, favouring the removal of H2 gas from the flow and forcing the equilibrium of the reaction towards dehydrogenation, as well as to keep the catalyst particles in motion. The CFD simulations were validated qualitatively with experimental operation of the reactor, in a system with identical dimensionless numbers (Reynolds and Stokes), in order to use less costly products during the prototyping phase.

Abstract: Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping.