Joint non-rigid image registration and reconstruction for quantitative atomic resolution scanning transmission electron microscopy

Aberration corrected scanning transmission electron microscopes (STEM) enable to determine local strain fields, composition and bonding states at atomic resolution. The precision to locate atomic columns is often obstructed by scan artifacts limiting the quantitative interpretation of STEM datasets. Here, a novel bias-corrected non-rigid registration approach is presented that compensates for fast and slow scan artifacts in STEM image series. The bias-correction is responsible for the correction of the slow scan artifacts and based on a explicit coupling of the deformations of the individual images in a series via a minimization of the average deformation. This allows to reduce fast scan noise in an image series and slow scan distortions simultaneously. The novel approach is tested on synthetic and experimental images and its implication on atomic resolution strain and elemental mapping is discussed

Structure and hardness of in situ synthesized nano-oxide strengthened CoCrFeNi high entropy alloy thin films

In this study, we report on face-centered cubic structured CoCrFeNi high-entropy alloy thin films with finely dispersed nano-oxide particles which are formed by internal oxidation. Analytical scanning transmission electron microscopy imaging found that the particles are Cr2O3. The oxide particles contribute to the hardening of the film increasing its hardness by 14% compared to that of the film without precipitates, through the Orowan-type strengthening mechanism. Our novel approach paves the way to design medium- and high-entropy alloys with high strength by making use of oxide phases

Automatic Identification of Crystal Structures and Interfaces via Artificial-Intelligence-based Electron Microscopy

Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials. Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision. Here, we present AI-STEM, an automatic, artificial-intelligence based method, for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy (STEM) images of polycrystalline materials. The method is based on a Bayesian convolutional neural network (BNN) that is trained only on simulated images. AI-STEM automatically and accurately identifies crystal structure, lattice orientation, and location of interface regions in synthetic and experimental images. The model is trained on cubic and hexagonal crystal structures, yielding classifications and uncertainty estimates, while no explicit information on structural patterns at the interfaces is included during training. This work combines principles from probabilistic modeling, deep learning, and information theory, enabling automatic analysis of experimental, atomic-resolution images.Comment: Code (https://github.com/AndreasLeitherer/ai4stem) and data (https://doi.org/10.5281/zenodo.7756516) are available for public use. The manuscript contains 32 pages (10 pages main text, 15 pages for Methods & References & 5 Figures & 1 Table, as well as 7 pages Supplementary Information), including 5 main figures and 6 supplementary figure

Stable Nanofacets in [111] Tilt Grain Boundaries of Face-Centered Cubic Metals

Grain boundaries can dissociate into facets if that reduces their excess energy. This, however, introduces line defects at the facet junctions, which present a driving force to grow the facets in order to reduce the total number of junctions and thus the system's energy. Often, micrometer-sized facet lengths are observed and facet growth only arrests for kinetic reasons. So far, energetically stable, finite-sized facets have not been observed, even though theoretical stability conditions have already been proposed. Here, we show a case where nanometer-sized facets are indeed stable compared to longer facets in [111] tilt grain boundaries in Cu by atomistic simulation and transmission electron microscopy. The facet junctions lack a Burgers vector component, which is unusual, but which leads to attractive interactions via line forces. Atomistic simulations predict that the same phenomenon also occurs in at least Al and Ag

Atomic resolution observations of silver segregation in a [111] tilt grain boundary in copper

Alloying a material and hence segregating solutes to grain boundaries is one way to tailor a material to the demands of its application. Direct observation of solute segregation is necessary to understand how the interfacial properties are altered. In this study, we investigate the atomic structure of a high angle grain boundary both in pure copper and upon silver segregation by aberration-corrected scanning transmission electron microscopy and spectroscopy. We further correlate the experiments to atomistic simulations to quantify the local solute excess and its impact on grain boundary properties. We observe that the grain boundary structure remains intact upon silver segregation and up to five different positions within a structural unit serve as segregation sites. By combining the atomic resolution observation with atomistic modelling, we are able to quantify the local silver concentration and elucidate the underlying segregation mechanism

Atomic motifs govern the decoration of grain boundaries by interstitial solutes

Grain boundaries, the two-dimensional (2D) defects between differently oriented crystals, control mechanical and transport properties of materials. Our fundamental understanding of grain boundaries is still incomplete even after nearly a century and a half of research since Sorby first imaged grains. Here, we present a systematic study, over 9 orders of magnitude of size scales, in which we analyze 2D defects between two neighboring crystals across five hierarchy levels and investigate their crystallographic, compositional, and electronic features. The levels are (a) the macroscale interface alignment and grain misorientation (held constant here); (b) the systematic mesoscopic change in the inclination of the grain boundary plane for the same orientation difference; (c) the facets, atomic motifs (structural units), and internal nanoscopic defects within the boundary plane; (d) the grain boundary chemistry; and (e) the electronic structure of the atomic motifs. As a model material, we use Fe alloyed with B and C, exploiting the strong interdependence of interface structure and chemistry in this system. This model system is the basis of the 1.9 billion tons of steel produced annually and has an eminent role as a catalyst. Surprisingly, we find that even a change in the inclination of the GB plane with identical misorientation impacts GB composition and atomic arrangement. Thus, it is the smallest structural hierarchical level, the atomic motifs, which control the most important chemical properties of the grain boundaries. This finding not only closes a missing link between the structure and chemical composition of such defects but also enables the targeted design and passivation of the chemical state of grain boundaries to free them from their role as entry gates for corrosion, hydrogen embrittlement, or mechanical failure

Aluminum depletion induced by complex co-segregation of carbon and boron in a {\Sigma} 5 [3 1 0] bcc-iron grain boundary

The local variation of grain boundary atomic structure and chemistry caused by segregation of impurities influences the macroscopic properties of poylcrystalline materials. Here, the effect of co-segregation of carbon and boron on the depletion of aluminum at a $\Sigma 5\,(3\,1\,0\,) [0\,0\,1]$ tilt grain boundary in a $\alpha-$Fe-$4~at.~\%$Al bicrystal was studied by combining atomic resolution scanning transmission electron microscopy, atom probe tomography and density functional theory calculations. The atomic grain boundary structural units mostly resemble kite-type motifs and the structure appears disrupted by atomic scale defects. Atom probe tomography reveals that carbon and boron impurities are co-segregating to the grain boundary reaching levels of >1.5 at.\%, whereas aluminum is locally depleted by approx. 2~at.\%. First-principles calculations indicate that carbon and boron exhibit the strongest segregation tendency and their repulsive interaction with aluminum promotes its depletion from the grain boundary. It is also predicted that substitutional segregation of boron atoms may contribute to local distortions of the kite-type structural units. These results suggest that the co-segregation and interaction of interstitial impurities with substitutional solutes strongly influences grain boundary composition and with this the properties of the interface.Comment: 26 pages, 10 Figures, 1 Tabl

Direct observation of dislocation plasticity in FeCrCoMnNi high-entropy alloys

In the past decade, high-entropy alloys (HEAs) have been intensively investigated not only because of fundamental scientific interests, but also their outstanding mechanical properties, for example, high ductility and fracture toughness. Among hundreds of different combinations of principal elements, the equiatomic FeCrCoMnNi alloy, the so-called Cantor alloy, has been studied as a model system, which is a single phase material with face-centered cubic (FCC) structure at room temperature and shows outstanding ductility and strain hardening especially at cryogenic temperatures. However, dislocation-based deformation mechanisms of HEAs remain elusive and require a fundamental understanding in order to tailor their mechanical properties. Several models have been suggested possible strengthening mechanisms of HEAs, for instance, the high entropy effect and the lattice distortion effect. In the case of the Cantor alloy, the main strengthening mechanism was identified as deformation twinning with critical twinning stress of 720 MPa. At room temperature, dislocation slip by full dislocations is dominant, however, at strains exceeding 20 % and high flow stresses, deformation twinning was also observed. To reveal the hardening mechanism in more detail, direct observation of dislocation plasticity and deformation dynamics is required. Here, we present a study correlating the microstructure and dislocation plasticity of a single crystalline FeCrCoMnNi FCC single phase HEA by employing in-situ transmission electron microscope (TEM) compression and tensile deformation. Moreover, an atomic-scale chemical analysis is conducted by aberration-corrected scanning TEM energy dispersive X-ray spectroscopy (STEM-EDS) and atom probe tomography to investigate chemical inhomogeneity, for example, precipitate formation or local inhomogeneity. Compression tests with sub-micron pillars with 250 and 120 nm diameter show less pronounced mechanical size effects in the alloy compared to other FCC metals as the size exponent is measured as 0.53. It suggests that relatively strong inherent hardening processes are present which attenuate the FCC reported size scaling exponent, which is typically 0.6 to 1.0 for pure FCC metals. The elemental distribution and lattice strains at the atomic scale are rather uniform without long-range ordering analyzed by high-resolution scanning TEM (STEM) and atom probe tomography. Finally, dislocation glide motion was directly observed during in situ TEM tensile tests. The local shear stress measured from gliding of individual dislocations is exceeding 400 MPa. Kink-pair-like glide behavior and periodic fluctuation in the stacking fault width suggest that local pinning points, severe lattice distortion or short-range ordering hinder dislocation motion in HEAs

Ketogenic diet and fasting diet as Nutritional Approaches in Multiple Sclerosis (NAMS): protocol of a randomized controlled study

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory disease of the central nervous system in young adults that may lead to progressive disability. Since pharmacological treatments may have substantial side effects, there is a need for complementary treatment options such as specific dietary approaches. Ketone bodies that are produced during fasting diets (FDs) and ketogenic diets (KDs) are an alternative and presumably more efficient energy source for the brain. Studies on mice with experimental autoimmune encephalomyelitis showed beneficial effects of KDs and FDs on disease progression, disability, cognition and inflammatory markers. However, clinical evidence on these diets is scarce. In the clinical study protocol presented here, we investigate whether a KD and a FD are superior to a standard diet (SD) in terms of therapeutic effects and disease progression. METHODS: This study is a single-center, randomized, controlled, parallel-group study. One hundred and eleven patients with relapsing-remitting MS with current disease activity and stable immunomodulatory therapy or no disease-modifying therapy will be randomized to one of three 18-month dietary interventions: a KD with a restricted carbohydrate intake of 20-40 g/day; a FD with a 7-day fast every 6 months and 14-h daily intermittent fasting in between; and a fat-modified SD as recommended by the German Nutrition Society. The primary outcome measure is the number of new T2-weighted MRI lesions after 18 months. Secondary endpoints are safety, changes in relapse rate, disability progression, fatigue, depression, cognition, quality of life, changes of gut microbiome as well as markers of inflammation, oxidative stress and autophagy. Safety and feasibility will also be assessed. DISCUSSION: Preclinical data suggest that a KD and a FD may modulate immunity, reduce disease severity and promote remyelination in the mouse model of MS. However, clinical evidence is lacking. This study is the first clinical study investigating the effects of a KD and a FD on disease progression of MS