Abstract: Improving the efficiency and longevity of energy storage systems based on Li- and Na-ion rechargeable batteries presents a major challenge. The main problems are essentially capacity loss and limited cyclability. These effects are due to a hierarchy of factors spanning various length and time scales, interconnected in a complex manner. As a consequence, and in spite of several decades of research, a proper understanding of the ageing process has remained somewhat elusive. In recent years, however, combinations of advanced spectroscopy techniques and first-principles simulations have been applied with success to tackle this problem. In this Special Issue, we are pleased to present a selection of articles that, by precisely applying these methods, unravel key aspects of the reduction-oxidation reaction and intercalation processes. Furthermore, the approaches presented provide improvements to standard diagnostic and characterisation techniques, enabling the detection of possible Li-ion flow bottlenecks causing the degradation of capacity and cyclability.

Abstract: High strength 7XXX aluminium series reach exceptional strength, higher than all other industrial aluminium alloys. However, they suffer from a lack of ductility compared to softer series. This work presents a procedure to improve the ductility of 7475 Al alloy in high strength condition, reaching a true fracture strain of 70% at full 500 MPa T6 yield strength. Using friction stir processing (FSP) and post-FSP heat treatments, 100% of industrial rolled material T6 yield stress is maintained but a 180% increase in fracture strain is measured for the processed material. This ductility improvement is studied by in-situ synchrotron X-ray tomography and is explained by the reduction of intermetallic particles size and the homogenization of their spatial distribution. Furthermore, the microstructure after FSP shows equiaxed refined grains which favour crack deviation as opposed to large cracks parallel to the elongated coarse grains in rolled plate. These results are paving the way to better formability and crashworthiness of 7XXX alloys.

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: Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying the degree of chirality in objects with sizes of tens of nanometers is far from straightforward. Electron tomography offers the possibility to faithfully retrieve the three-dimensional morphology of nanomaterials, but only a qualitative interpretation of the morphology of chiral nanoparticles has been possible so far. We introduce herein a methodology that enables us to quantify the helicity of complex chiral nanomaterials, based on the geometrical properties of a helix. We demonstrate that an analysis at the single particle level can provide significant insights into the origin of chiroptical properties.

Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.

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 development of coatings with tunable performances is critical to meet a wide range of technological applications each one with different requirements. Using the plasma-enhanced chemical vapor deposition (PECVD) process, scientists can create hydrogenated amorphous carbon coatings doped with metal (a-C:H:Me) with a broad range of mechanical properties, varying from those resembling polymers to ones resembling diamond. These diverse properties, without clear relations between the different families, make the material selection and optimization difficult but also very rich. An innovative approach is proposed here based on projected performance indices related to fracture energy, strength, and stiffness in order to classify and optimize a-C:H:Me coatings. Four different a-C:H:Cr coatings deposited by PECVD with Ar/C2H2 discharge under different bias voltage and pressures are investigated. A path is found to produce coatings with a selective critical energy release rate between 5–125 J/m2 without compromising yield strength (1.6–2.7 GPa) and elastic limit (≈0.05). Finally, fine-tuned coatings are categorized to meet desired applications under different testing conditions.

Abstract: Electrostriction is a property of dielectric materials whereby an applied electric field induces a mechanical deformation proportional to the square of that field. The magnitude of the effect is usually minuscule (<10(-19) m(2) V-2 for simple oxides). However, symmetry-breaking phenomena at the interfaces can offer an efficient strategy for the design of new properties(1,2). Here we report an engineered electrostrictive effect via the epitaxial deposition of alternating layers of Gd2O3-doped CeO2 and Er2O3-stabilized delta-Bi2O3 with atomically controlled interfaces on NdGaO3 substrates. The value of the electrostriction coefficient achieved is 2.38 x 10(-14) m(2) V-2, exceeding the best known relaxor ferroelectrics by three orders of magnitude. Our theoretical calculations indicate that this greatly enhanced electrostriction arises from coherent strain imparted by interfacial lattice discontinuity. These artificial heterostructures open a new avenue for the design and manipulation of electrostrictive materials and devices for nano/micro actuation and cutting-edge sensors.

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: Vanadium dioxide (VO2) is a popular candidate for electronic and optical switching applications due to its well-known semiconductor-metal transition. Its study is notoriously challenging due to the interplay of long- and short-range elastic distortions, as well as the symmetry change and the electronic structure changes. The inherent coupling of lattice and electronic degrees of freedom opens the avenue toward mechanical actuation of single domains. In this work, we show that we can manipulate and monitor the reversible semiconductor-to-metal transition of VO2 while applying a controlled amount of mechanical pressure by a nanosized metallic probe using an atomic force microscope. At a critical pressure, we can reversibly actuate the phase transition with a large modulation of the conductivity. Direct tunneling through the VO2-metal contact is observed as the main charge carrier injection mechanism before and after the phase transition of VO2. The tunneling barrier is formed by a very thin but persistently insulating surface layer of the VO2. The necessary pressure to induce the transition decreases with temperature. In addition, we measured the phase coexistence line in a hitherto unexplored regime. Our study provides valuable information on pressure-induced electronic modifications of the VO2 properties, as well as on nanoscale metal-oxide contacts, which can help in the future design of oxide electronics.

Abstract: In the last few decades, nanostructuring has driven significant attention towards the development of novel metallic materials with advanced mechanical properties. Nanocrystalline (nc) metals are a class of nanostructured materials with grain sizes smaller than about 100 nm. These exhibit outstanding mechanical strength and fatigue properties compared to their coarse-grained (cg) counterparts. These are promising candidates for application as structural or functional materials. Nc metals in the form of thin films are employed as hard coatings on bulk components, structural components, and conductive layers in various micro-/nanoscale devices. These structural components and devices are often subjected to cyclic stresses or fatigue loading. Under these cyclic stresses, nc metals tend to exhibit the Bauschinger effect (BE). The strength loss during the BE is of great importance concerning the strength-ductility trade-off in nc metals. Furthermore, contact surfaces of the engineering components in service often undergo relative motion and are subject to both friction and wear. These extreme loading conditions demand nc metals with tailored interfacial characteristics for improved tribological performance. Aiming at ensuring high reliability and mechanical robustness for optimum performance of these components, there has been a strong motivation for understanding the mechanical properties and governing deformation mechanisms in nc metallic materials. This thesis aimed at in-depth investigation of microstructures at micro-/nanoscales using state-of-the-art in situ and ex situ transmission electron microscopy (TEM) to develop a closer link between the deformation structure and underlying deformation mechanisms in some nc metallic materials. The thesis has primarily focused on the in situ TEM nanomechanics of the BE and rotational deformation of grains in nc palladium thin films. A sputtered thin film of nc Pd was deformed inside TEM by cyclic loading-unloading experiments and the evolving microstructure was studied in real-time under different TEM imaging modes. The stress-strain response of the film exhibited a characteristic non-linear unloading behavior confirming the BE in the film. The corresponding bright-field TEM imaging revealed evidence of partially reversible dislocation activity. Towards a quantitative understanding of the deformation structure in real-time, in situ nanomechanical testing was coupled with precession-assisted automated crystal orientation mapping in scanning TEM (ACOM-STEM). Global ACOM-STEM analysis offered crystal orientation of a large number of grains at different states of deformation and confirmed partially reversible rotations of nanosized grains fitting to the observed BE during loading and unloading. Analysis of intragranular rotations showed substantial changes in the sub-structure within most of these grains indicating a dominant role of dislocation-based processes in driving these rotations. Globally, an unusually random evolution of texture was seen that demonstrated the influence of deformation heterogeneity and grain interactions on the resulting texture characteristics in nc metals. In the quest of understanding the grain interactions, local investigations based on annular dark-field STEM imaging during loading-unloading showed reversible changes in the contrast of grains with sets of adjoining grains exhibiting a unique cooperative rotation. Local analysis of the density of geometrically necessary dislocations (GNDs) showed the formation of dislocation pile-up at grain boundaries due to the generation of back-stresses during unloading. Critical observations of the evolution of GND density offered greater insights into the mechanism of cooperative grain rotations and these rotations were related to grain structure and grain boundary characteristics. In addition to understanding the influence of grain structure and grain boundaries, the thesis has further investigated the role of heterointerfaces in sputtered Au-Cu and Cu-Cr nanocrystalline multilayered composites (NMCs) deformed under cyclic sliding contact. The microstructural evolution in the NMCs was investigated at different deformation states by classical TEM imaging, ACOM-STEM as well as energy-filtered TEM (EFTEM). Au-Cu NMC with an initial high density of twin boundaries deformed by stress-driven detwinning with a concurrent change in grain structure in both Au and Cu. The formation of a vortex structure was observed due to plastic flow instabilities at Au-Cu interfaces that led to codeformation and mechanical intermixing. Cu-Cr NMC showed a preferential grain growth in Cu layers whereas no noticeable change in the grain sizes was seen in Cr layers. The phase maps revealed sharp interfaces between Cu and Cr layers indicating no intermixing between the immiscible phases. EFTEM results exposed the cracking processes in Cr layers with a concurrent migration of Cu in the cracks. Overall, the thesis has attempted to analyze the competing deformation processes and relate these with the microstructural heterogeneity in terms of grain structure and GB and interfacial characteristics in nc metallic materials.

Abstract: Electron donors are widely exploited in visible-light photocatalytic hydrogen production. As a typical electron donor pair and often the first choice for hydrogen production, the sodium sulfide-sodium sulfite pair has been extensively used. However, the resultant thiosulfate ions consume the photogenerated electrons to form an undesirable pseudocyclic electron transfer pathway during the photocatalytic process, strongly limiting the solar energy conversion efficiency. Here, we report novel and bioinspired electron donor pairs offering a noncyclic electron transfer pathway that provides more electrons without the consumption of the photogenerated electrons. Compared to the state-of-the-art electron donor pair Na2S-Na2SO3, these novel Na2S-NaH2PO2 and Na2S-NaNO2 electron donor pairs enable an unprecedented enhancement of up to 370% and 140% for average photocatalytic H-2 production over commercial CdS nanoparticles, and they are versatile for a large series of photocatalysts for visible-light water splitting. The discovery of these novel electron donor pairs can lead to a revolution in photocatalysis and is of great significance for industrial visible-light-driven H-2 production. [GRAPHICS] .

Abstract: Advanced electron microscopy techniques, including scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), and transmission electron microscopes (TEM), have revolutionized imaging capabilities. However, achieving high-quality experimental images remains a challenge due to various distortions stemming from the instrumentation and external factors. These distortions, introduced at different stages of imaging, hinder the extraction of reliable quantitative insights. In this paper, we will discuss the main sources of distortion in TEM and S(T)EM images, develop models to describe them, and propose a method to correct these distortions using a convolutional neural network. We validate the effectiveness of our method on a range of simulated and experimental images, demonstrating its ability to significantly enhance the signal-to-noise ratio. This improvement leads to a more reliable extraction of quantitative structural information from the images. In summary, our findings offer a robust framework to enhance the quality of electron microscopy images, which in turn supports progress in structural analysis and quantification in materials science and biology.

Abstract: Nanoscience and nanotechnologies are of immense importance across many fields of science and for numerous practical applications. In this context, scanning transmission electron microscopy (STEM) and 4D-STEM are among the most powerful characterization methods at the atomic scale. Annular dark-field (ADF)-STEM can be used to quantify atomic structures in 3D by counting atoms based on a single projection image. In 4D-STEM a full diffraction pattern is recorded at each scan step, which enables more dose efficient imaging and the utilization of various advanced imaging modalities, which can however be complex and slow. Both, STEM and 4D-STEM suffer from noise and distortions. In the first section of this work the most important of these distortions are discussed and it is shown how image restoration with a dedicated convolutional neural network (CNN) can be beneficial for atomic structure quantifications in ADF-STEM. In the second part, a new 4D-STEM imaging method real-time-integrated-centre-of-mass (riCOM) is introduced, which is a very dose-efficient and fast algorithm that enables unprecedented live-imaging capabilities for 4D-STEM. It is based on the integrated centre-of-mass approach, but is reformulated with variable integration ranges and optional filters, which allows for a tunable contrast transfer function. This enables the imaging of light and heavy elements simultaneously at very low doses. In the third part another new 4D-STEM method, coined AIRPI (AI-assisted rapid phase imaging) is introduced, which uses a CNN to retrieve a patch of the specimen's phase image for each scan position, based on the diffraction patterns in the probe's immediate surroundings. This allows also live imaging in principle and surpasses comparable state-of-the-art algorithms in terms of resolution also at low doses. Different atomic columns can be reliably distinguished over a wide range of atomic numbers, enabling a very good image interpretability. Further, AIRPI can recover low frequency image components, which preserves thickness information. This is a unique and important feature which could make quantitative 4D-STEM feasible.