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: Current progress in programmable electrostatic phase plates raises questions about their usefulness for specific applications. Here, we explore different designs for such phase plates with the specific goal of correcting spherical aberration in the transmission electron microscope (TEM). We numerically investigate whether a phase plate could provide down to 1 angstrom ngstrom spatial resolution on a conventional uncorrected TEM. Different design aspects (fill factor, pixel pattern, symmetry) were evaluated to understand their effect on the electron probe size and current density. Some proposed designs show a probe size () down to 0.66 angstrom, proving that it should be possible to correct spherical aberration well past the 1 angstrom limit using a programmable phase plate consisting of an array of electrostatic phase-shifting elements.

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: For oxygen conducting materials applied in solid oxide fuel cells and chemical-looping processes, the understanding of the oxygen diffusion mechanism and the materials’ crystal structure at different stages of the redox reactions is a key parameter to control their performance. In this paper we report the first ever in situ 3D ED experiment in a gas environment and with it uncover the structure evolution of SrFeO2.5 as notably different from that reported from in situ X-ray and in situ neutron powder diffraction studies in gas environments. Using in situ 3D ED on submicron sized single crystals obtained from a high quality monodomain SrFeO2.5 single crystal , we observe the transformation under O2 flow of SrFeO2.5 with an intra- and interlayer ordering of the left and right twisted (FeO4) tetrahedral chains (space group Pcmb) into consecutively SrFeO2.75 with space group Cmmm (at 350°C, 33% O2) and SrFeO3-δ with space group Pm3 ̅m (at 400°C, 100% O2). Upon reduction in H2 flow, the crystals return to the brownmillerite structure with intralayer order, but without regaining the interlayer order of the pristine crystals. Therefore, redox cycling of SrFeO2.5 crystals in O2 and H2 introduces stacking faults into the structure, resulting in an I2/m(0βγ)0s symmetry with variable β.

Abstract: In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of 3 nm). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a 3.21 nm median radius).

Abstract: Out-of-equilibrium self-assembly of metal nanoparticles (NPs) has been devised using different types of strategies and fuels, but the achievement of finite 3D structures with a controlled morphology through this assembly mode is still rare. Here we used a spherical peptide-gold superstructure (PAuSS) as a template to control the out-of-equilibrium self-assembly of Au NPs, obtaining a transient 3D branched Au-nanoshell (BAuNS) stabilized by sodium dodecyl sulphate (SDS). The BAuNS dismantled upon concentration gradient equilibration over time in the solution, leading to NPs disassembly. Notably, BAuNS assembly and disassembly favoured temporary interparticle plasmonic coupling, leading to a remarkable oscillation of their optical properties.

Abstract: Although most state-of-the-art Sn-based electrocatalysts yield promising results in terms of selectivity and catalyst activity, their stability remains insufficient to date. Here, we demonstrate the successful application of the recently developed pomegranate-structured SnO2 (Pom. SnO2) and SnO2@C (Pom. SnO2@C) nanocomposite electrocatalysts for the efficient electrochemical conversion of CO2 to formate. With an initial selectivity of 83 and 86% towards formate and an operating potential of -0.72 V and -0.64 V vs. RHE, respectively, these pomegranate SnO2 electrocatalysts are able to compete with most of the current state-of-the-art Sn-based electrocatalysts in terms of activity and selectivity. Given the importance of electrocatalyst stability, long-term experiments (24 h) were performed and a temporary loss in selectivity for the Pom. SnO2@C electrocatalyst was largely restored to its initial selectivity upon drying and exposure to air. Of all the used (24 h) electrocatalysts, the pomegranate SnO2@C had the highest selectivity over a time period of one hour, reaching an average recovered FE of 85%, while the commercial SnO2 and bare pomegranate SnO2 electrocatalysts reached an average of 79 and 80% FE towards formate, respectively. Furthermore, the pomegranate structure of Pom. SnO2@C was largely preserved due to the presence of the heterogeneous carbon shell, which acts as a protective layer, physically inhibiting particle segregation/pulverisation and agglomeration.

Abstract: Electron microscopy is an indispensable tool for the characterization of (nano) materials. Electron microscopes are typically very expensive and their internal operation is often shielded from the user. This situation can provide fast and high quality results for researchers focusing on e.g. materials science if they have access to the relevant instruments. For researchers focusing on technique development, wishing to test novel setups, however, the high entry price can lead to risk aversion and deter researchers from innovating electron microscopy technology further. The closed attitude of commercial entities about how exactly the different parts of electron microscopes work, makes it even harder for newcomers in this field. Here we propose an affordable, easy-to-build electron detector for use in a scanning electron microscope (SEM). The aim of this project is to shed light on the functioning of such detectors as well as show that even a very modest design can lead to acceptable performance while providing high flexibility for experimentation and customization.

Abstract: Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal–organic framework complexes.

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.