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: The success and continued expansion of research on metal-oxo clusters owe largely to their structural richness and wide range of functions. However, while most of them known to date are negatively charged polyoxometalates, there is only a handful of cationic ones, much less functional ones. Here, we show an all-inorganic hydroxyiodide [H(10.)7Sb(32.1)O(44)][H2.1Sb2.1I8O6][Sb0.76I6](2)center dot 25H(2)O (HSbOI), forming a face-centered cubic structure with cationic Sb32O44 clusters and two types of anionic clusters in its interstitial spaces. Although it is submicrometer in size, electron diffraction tomography of HSbOI allowed the construction of the initial structural model, followed by powder Rietveld refinement to reach the final structure. The cationic cluster is characterized by the presence of acidic protons on its surface due to substantial Sb3+ deficiencies, which enables HSbOI to serve as an excellent solid acid catalyst. These results open up a frontier for the exploration and functionalization of cationic metal-oxo clusters containing heavy main group elements.

Abstract: Films of close-packed Au nanoparticles are coupled electrodynamically through their collective plasmon resonances. This collective optical response results in enhanced light–matter interactions, which can be exploited in various applications. Here, we demonstrate their application in sensing volatile organic compounds, using methanol as a test case. Ordered films over several cm2 were obtained by interfacial self-assembly of colloidal Au nanoparticles (∼10 nm diameter) through controlled evaporation of the solvent. Even though isolated nanoparticles of this size are inherently nonscattering, when arranged in a close-packed film the plasmonic coupling results in a strong reflectance and absorbance. The in situ tracking of vapor phase methanol concentration through UV–vis transmission measurements of the nanoparticle film is first demonstrated. Next, in situ ellipsometry of the self-assembled films in the Kretschmann (also known as ATR) configuration is shown to yield enhanced sensitivity, especially with phase difference measurements, Δ. Our study shows the excellent agreement between theoretical models of the spectral response of self-assembled films with experimental in situ sensing experiments. At the same time, the theoretical framework provides the basis for the interpretation of the various observed experimental trends. Combining periodic nanoparticle films with ellipsometry in the Kretschmann configuration is a promising strategy toward highly sensitive and selective plasmonic thin-film devices based on colloidal fabrication methods for volatile organic compound (VOC) sensing applications.

Abstract: Electrochemical energy storage plays a vital role in combating global climate change. Nowadays lithium-ion battery technology remains the most prominent technology for rechargeable batteries. A key performance-limiting factor of lithium-ion batteries is the active material of the positive electrode (cathode). Lithium- and manganese-rich nickel manganese cobalt oxide (LMR-NMC) cathode materials for Li-ion batteries are extensively investigated due to their high specific discharge capacities (>280 mAh/g). However, these materials are prone to severe capacity and voltage fade, which deteriorates the electrochemical performance. Capacity and voltage fade are strongly correlated with the particle morphology and nano- and microstructure of LMR-NMCs. By selecting an adequate synthesis strategy, the particle morphology and structure can be controlled, as such steering the electrochemical properties. In this manuscript we comparatively assessed the morphology and nanostructure of LMR-NMC (Li1.2Ni0.13Mn0.54Co0.13O2) prepared via an environmentally friendly aqueous solution-gel and co-precipitation route, respectively. The solution-gel (SG) synthesized material shows a Ni-enriched spinel-type surface layer at the {200} facets, which, based on our post-mortem high-angle annual dark-field scanning transmission electron microscopy and selected-area electron diffraction analysis, could partly explain the retarded voltage fade compared to the co-precipitation (CP) synthesized material. In addition, deviations in voltage fade and capacity fade (the latter being larger for the SG material) could also be correlated with the different particle morphology obtained for both materials.

Abstract: Self-healing strategies aim at avoiding part repair or even replacement, which is time consuming, expen-sive and generates waste. However, strategies for metallic systems are still under-developed and solid-state solutions for room temperature service are limited to nano-scale damage repair. Here we propose a new healing strategy of micron-sized damage requiring only short and low temperature heating. This new strategy is based on damage localization particles, which can be healed by fast diffusing atoms of the matrix activated during heat treatment. The healing concept was successfully validated with a com-mercial aluminum alloy and manufactured by Friction Stir Processing (FSP). Damage was demonstrated to initiate on particles that were added to the matrix during material processing. In situ 2D and 3D nano -imaging confirmed healing of the damaged material and showed that heating this material for 10 min at 400 degrees C is sufficient to heal incipient damage with complete filling of 70% of all damage (and up to 90% when their initial size is below 0.2 mu m). Furthermore, strength is retained and the work of fracture of the alloy is improved by about 40% after healing. The proposed Programmed Damage and Repair healing strategy could be extended to other metal based systems presenting precipitation. (C) 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Abstract: Submicron-sized quasicrystalline particles were obtained in an Al-Zn-Mg-Cu alloy produced by traditional melting. These particles consist of an Al-Fe-Ni core and a Mg-Cu-Zn shell and were found to be stable and embedded randomly in the Al matrix. The diffraction patterns of these core-shell particles reveal a decagonal core and an icosahedral shell with, respectively, ten- and five-fold axes aligned. High resolution scanning transmission electron microscopy of the Mg-Cu-Zn shell confirms the five-fold symmetry atomic arrangement and the icosahedral structure. It can therefore be concluded that Fe and Ni impurities play an important role in mediating the formation of such an unusual ternary core-shell quasicrystalline particle. These findings provide some novel insights in the formation of quasicrystals in traditional industrial Al alloys.

Abstract: Among all types of discovered crystals, those formed by organic molecules show the greatest diversity, which results from the intrinsic complexity of the organic molecules and the weak interactions between them. Even for a given compound, different crystal structures can exist. This feature is referred to as polymorphism in the modern crystallographic context and those different crystal forms are called polymorphs. In reality, the crystallization of organic molecules is often performed at the surface of a substrate, giving rise to heterogeneous crystallization. Except for the well-known catalyzing effects, the existence of substrates brings more possibilities to the polymorphic behaviors of organic molecules, promoting the formation of new polymorphs that are only stable in the vicinity of the substrates. For this reason, these new polymorphic forms are often described as substrate-induced polymorphs (SIPs). It is of great importance to understand the formation of SIPs for organic molecules as it has been reported that SIPs can show superior properties with respect to their bulk form counterparts. Up to now, most studies focus on the identifying and characterizing the presence of SIPs, which relies mainly on X-ray diffraction techniques. However, a detailed explanation about the origin of SIPs is still missing. In this work, we have combined several powerful experimental characterization techniques, including X-ray diffraction, transmission electron microscopy (TEM) and scanning tunneling microscopy (STM) in order to reach an integrated view over the formation of SIPs. These experimental studies are strongly supported by computational chemistry simulations, such as density functional theory and molecular dynamics. A big advantage of using atomistic simulations is that it enables the possibility to predict a priori the crystal structures of SIPs and to establish a posteriori the general rules for the formation of SIPs. In practice, this thesis employs state-of-art atomistic simulation approaches in order to bridge substrate-induced polymorphism with a conceptually-connected research area: the self-assembly of molecular networks (SAMNs), also called 2D crystallization. Unlike SIPs, which extend at least several molecular layers, SAMNs are composed of a single layer of molecules with ordered packing. Our simulations have enabled a more comprehensive understanding about the role of substrate during the formation of SIPs and we elucidate how the positional and orientational order of molecules propagates from the substrate to the upper 2D and even 3D crystal layers. In this way, a fundamental understanding of the substrate-induced crystallization is gained by connecting 2D and 3D crystallization using substrate-induced approaches.

Abstract: Intragranular amorphization shear lamellae are found in deformed olivine aggregates. The detailed trans-mission electron microscopy analysis of intragranular lamella arrested in the core of a grain provides novel information on the amorphization mechanism. The deformation field is complex and heteroge-neous, corresponding to a shear crack type instability involving mode I, II and III loading components. The formation and propagation of the amorphous lamella is accompanied by the formation of crystal defects ahead of the tip. These defects are geometrically necessary [001] dislocations, characteristics of high-stress deformation in olivine, and rotational nanodomains which are tentatively interpreted as disclinations. We show that these defects play an important role in dictating the path followed by the amorphous lamella. Stress-induced amorphization in olivine would thus result from a direct crystal-to -amorphous transformation associated with a shear instability and not from a mechanical destabilization due to the accumulation of high number of defects from an intense preliminary deformation. The pref-erential alignment of some lamellae along (010) is a proof of the lower ultimate mechanical strength of these planes.(c) 2022 The Authors. Published by Elsevier Ltd on behalf of Acta Materialia Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Abstract: Memristors are considered to be the fourth circuit element and have great potential in areas like logic operations, information storage, and neuromorphic computing. The functional material in a memristor, which has a nonlinear resistance, is the key component to be developed. Herein, resistive switching is demonstrated and the structural evolutions in Ag2Te are examined under an external electric field. It is shown that the electroresistance effect is originating from an electronically triggered phase transition together with directional Ag+-ion diffusion. Using in situ transmission electron microscopy, the phase transition from the monoclinic alpha-Ag2Te into the face-centered cubic beta-Ag2Te, accompanied by a change in resistance, is directly observed. Diffusion of Ag+-ions modulates the localized density of Ag+-ion vacancies, leading to a change in electrical conductivity and influences the threshold voltage to trigger the phase transition. During the electric field-driven phase transition, the spontaneous and localized multiple polarizations from the low-symmetry alpha-Ag2Te (referring to an antiferroelectric structure) are vanishing in the cubic beta-Ag2Te (referring to a paraelectric structure). The abrupt resistance change of thin Ag2Te caused by the phase transition and modulated by the applied electric field demonstrates its great potential as functional material in volatile memory and memristors with a low-energy consumption.

Abstract: Nanoplatelets offer many possibilities to construct advanced materials due to new properties associated with their (semi)two-dimensional shapes. However, precise control of both positional and orientational order of the nanoplatelets in three dimensions, which is required to achieve emerging and collective properties, is challenging to realize. Here, we combine experiments, advanced electron tomography and computer simulations to explore the structure of supraparticles self-assembled from nanoplatelets in slowly drying emulsion droplets. We demonstrate that the rich phase behaviour of nanoplatelets, and its sensitivity to subtle changes in shape and interaction potential can be used to guide the self-assembly into a wide range of different structures, offering precise control over both orientation and position order of the nanoplatelets. Our research is expected to shed light on the design of hierarchically structured metamaterials with distinct shape- and orientation- dependent properties. Nanoplatelets can be used as anisotropic building blocks for constructing novel optoelectronic materials. Here, Wang et al. show a route of assembling nanoplatelets with controllable positional and orientational order in three dimensions facilitated by the surface tension of drying emulsion droplets.

Abstract: Ever since the industrial revolution, the emission of greenhouse gasses dramatically increased, resulting in high CO2 concentration in the atmosphere. The electrochemical conversion of CO2 to value added products, such as carbon monoxide, formic acid, methane, ethylene and ethanol is a very promising strategy to inhibit CO2 emissions. Nevertheless, at the moment, the electrochemical CO2 reduction (eCO2R) is not yet industrially viable, mainly due to the lack of good electrocatalysts. On the other hand, core-shell nanoparticles (NPs) have emerged over the last couple of years as promising candidates. It is believed that bimetallic enhancement effects are behind the improved performance of these core-shell NPs when compared to the individual metals. Although widely investigated, there are still some remaining issues and/or open questions. Indeed, the development of a robust and straightforward synthesis method along with fundamental insight into their resistance towards electrochemical stress remains absent. A good control over morphology, size and composition is key in determining which properties are beneficial for the eCO2R. Since these catalysts are designed to be implemented in electrolyzers, they have to maintain long-term performance. This makes the design of a reproducible method, unveiling structure-performance relationships the effect of electrochemical stress, a crucial aspect. Exploring and modifying existing synthesis methods, have led to the acquisition of a robust and reproducible synthesis method where thermal decomposition of the Cu core is combined with the galvanic replacement of Ag in organic solvents. The implementation of this method has led to the design of a wide variety of Cu-Ag bimetallic NPs and enabled to investigate their composition-selectivity profile. Introducing Ag on Cu suppressed hydrogen and increased the CO formation. CO production was boosted by using Cu@Ag core-shells and was promoted even more by changing the type of electrolyte. As these nanoparticles suffered from degradation, the 3D mapping of the structural changes of Cu@Ag core-shells under operating conditions led to the hypothesis of a two-step degradation mechanism where initially Cu leaching was observed with the subsequent sintering of the Ag shells. One approach to avoid this electrochemical degradation, investigated in this research, was the application of an ultrathin carbon layer to protect the active layer. This ultrathin carbon layer operated as a protective layer, suppressing hydrogen production and increasing the stability of the electrocatalyst. In conclusion, the product selectivity can be tuned by using different Cu-Ag bimetallic nanoparticles synthesized through a robust method. Their unique degradation pathway of Cu@Ag core-shell nanoparticles has led to the proposition of a more accurate stabilization strategy. These findings can contribute significantly in the quest for improved electrocatalysts for the eCO2R.

Abstract: Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose 'A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography' (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST.

Abstract: Tempering is widely applied to make carbon atoms beneficially rearrange in high strength steel microstructures after quenching; though the nano-scale interaction of carbon atoms with crystallographic defects is hard to experimentally observe. To improve, we investigate the redistribution of carbon atoms along martensite grain boundaries in a quenched and tempered low carbon steel. We observe the tempering-induced microstructural evolution by in-situ heating in a transmission electron microscope (TEM) and by compositional analysis through atom probe tomography (APT). Probe volumes for APT originate from a single martensite packet but in different tempering conditions, which is achieved via a sequential lift-out with in-between tempering treatments. The complementary use of TEM and APT provides crystallographic as well as chemical information on carbon segregation and subsequent carbide precipitation at martensite grain boundaries. The results show that the amount of carbon segregation to martensite grain boundaries is influenced by the boundary type, e.g. low-angle lath or high-angle block boundaries. Also, the growth behavior of cementite precipitates from grain boundary nucleation sites into neighboring martensite grains differs at low- and high-angle grain boundaries. This is due to the crystallographic constraints arising from the semi-coherent orientation relationship between cementite and adjacent martensite. We also show that slower quenching stabilizes thin retained austenite films between martensite grains because of enhanced carbon segregation during cooling. Finally, we demonstrate the effect of carbon redistribution along martensite grain boundaries on the mechanical properties. Here, we compare micro-scale Vickers hardness results from boundary-containing probe volumes to nanoindentation results from pure bulk martensite (boundary-free) probe volumes.

Abstract: The hot working of 5xxx series alloys with Mg ≥3.5 wt% is a concern due to the precipitation of β (Al3Mg2) phase at grain boundaries favoring Inter Granular Corrosion (IGC). The mechanical and corrosion properties of a new 5028-H116 Al-Mg-Sc alloy under various β precipitates distribution is analyzed by imposing different cooling rates from the hot forming temperature (i.e. 325 °C). The mechanical properties are maintained regardless of the heat treatment. However, the different nucleation sites and volume fractions of β precipitates for different cooling rates critically affect IGC. Controlled furnace cooling after the 325 °C heat treatment is ideal in 5028-H116 alloy to reduce susceptibility to IGC after sensitization.

Abstract: Lead halide perovskites are promising candidates for applicability is limited by their structural instability toward moisture. Although a deliberate addition of water to the precursor solution has recently been shown to improve the crystallinity and optical properties of perovskites, the corresponding thin films still do not exhibit a near-unity quantum yield. Herein, we report that the direct addition of a minute amount of water to post-treated substantially enhances the stability while achieving a 95% photoluminescence quantum yield in a NC thin film. We unveil the mechanism of how moisture assists in the formation of an additional NH4Br component. Alongside, we demonstrate the crucial role of moisture in assisting localized etching of the perovskite crystal, facilitating the partial incorporation of NH4+, which is key for improved performance under ambient conditions. Finally, as a proof-of-concept, the application of post-treated and watertreated perovskites is tested in LEDs, with the latter exhibiting a superior performance, offering opportunities toward commercial application in moisture-stable optoelectronics.