The composition, structure and properties of four different glassy carbons
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The recent development of phase-grating moiré neutron interferometry promises a wide range of impactful experiments from dark-field imaging of material microstructure to precise measurements of fundamental constants. However, the contrast of 3% obtained using this moiré interferometer was well below the theoretical prediction of 30% using ideal gratings. It is suspected that non-ideal aspects of the phase-gratings was a leading contributor to this deficiency and that phase-gratings needed to be quantitatively assessed and optimized. Here we characterize neutron diffraction from phase-gratings using Bragg diffraction crystals to determine the optimal phase-grating orientations. We show well-defined diffraction peaks and explore perturbations to the diffraction peaks and the effects on interferometer contrast as a function of grating alignment. This technique promises to improve the contrast of the grating interferometers by providing in-situ aides to grating alignment.
High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.
Diamond’s unique properties on the nanoscale make it one of the most important materials for use in biosensors and quantum computing and for components that can withstand the harsh environments of space. We synthesize oriented, faceted diamond particles by flash laser heating of glassy carbon at 16 GPa and 2300 K. Detailed transmission electron microscopy shows them to consist of a mosaic of diamond nanocrystals frequently joined at twin boundaries forming microtwins. Striking 3-fold translational periodicity was observed in both imaging and diffraction. This periodicity was shown to originate from nanodimensional wedge-shaped overlapping regions of twinned diamond and not from a possible 9R polytype, which has also been reported in other group IVa elements and water ice. Extended bilayers of hexagonal layer stacking were observed, forming lonsdaleite nanolaminates. In conclusion, the particles exhibited optical fluorescence with a rapid quench time (<1 ns) attributed to their unique twinned microstructure.
Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing.
In modeling cometary ice, the properties of clathrate hydrates were used to explain anomalous gas release at large radial distances from the Sun, and the retention of particular gas inventories at elevated temperatures. Clathrates may also have been important early in solar system history. However, there has never been a reasonable mechanism proposed for clathrate formation under the low pressures typical of these environments. For the first time, it was shown that clathrate hydrates can be formed by warming and annealing amorphous mixed molecular ices at low pressures. The complex microstructures which occur as a result of clathrate formation from the solid state may provide an explanation for a variety of unexplained phenomena. The vacuum and imaging systems of an Hitachi H-500H Analytical Electron Microscope was modified to study mixed molecular ices at temperatures between 12 and 373 K. The resulting ices are characterized by low-electron dose Transmission Electron Microscopy (TEM) and Selected Area Electron Diffraction (SAED). The implications of these results for the mechanical and gas release properties of comets are discussed. Laboratory IR data from similar ices are presented which suggest the possibility of remotely observing and identifying clathrates in astrophysical objects.
Here, the effects of strain and strain rate on dynamic grain growth (DGG) and subgrain evolution are reported for an interstitial-free steel deformed at 850 ° C. Microstructures produced during tension tests at true-strain rates of 10 -4 and to 10 -3 s -1 true strains ranging from 0.02 to 0.2 were preserved following deformation. These were characterized using electron backscatter diffraction (EBSD), including the application of spherical harmonic transform indexing to produce high-angular-resolution EBSD (HR-EBSD) data. HR-EBSD data resolved the small misorientation angles of subgrain boundaries while imaging much larger data fields than possible with previously available techniques. The resulting data confirmed that steady-state flow stress is inversely proportional to the average subgrain size and that subgrain boundary misorientation angle increases with strain. The following new observations are reported. The rate of DGG increased with respect to time but decreased with respect to strain as strain rate increased. This behavior is rationalized through a simple model using separate rate parameters for the effects of time and strain. Subgrain size was not constant during steady-state deformation, but decreased slowly with increasing strain. Subgrain size distributions and subgrain boundary misorientation angle distributions were measured, and both remained approximately log-normal during steady-state deformation. Subgrain evolution demonstrated no dependence on parent grain size, crystallographic orientation, or Taylor factor. These new data suggest that steady-state flow stress is more likely controlled by the dislocation density internal to subgrains than by the spacing between subgrain boundaries.
Electron beam microscopy and related characterization techniques play an important role in revealing the microstructural, morphological, physical, and chemical information of halide perovskites and their impact on associated optoelectronic devices. However, electron beam irradiation usually causes damage to these beam-sensitive materials, negatively impacting their device performance, and complicating this interpretation. Here, the electron microscopy and spectroscopy techniques are reviewed that are crucial for the understanding of the crystallization and microstructure of halide perovskites. In addition, special attention is paid to assessing and mitigating the electron beam-induced damage caused by these techniques. Since the halide perovskites are fragile, a protocol involving delicate control of both electron beam dose and dose rate, coupled with careful data analysis, is key to enable the acquisition of reliable structural and compositional information such as atomic-resolution images, chemical elemental mapping and electron diffraction patterns. Limiting the electron beam dose is critical parameter enabling the characterization of various halide perovskites. Novel methods to unveil the mechanisms of device operation, including charge carrier generation, diffusion, and extraction are presented in scanning electron microscopy studies combined with electron-beam-induced current and cathodoluminescence mapping. Future opportunities for electron-beam-related characterizations of halide perovskites are also discussed.
Highlights: • Microstructure investigation of the fatigue behaviour of a Cu-Ni-Si alloy • Use of ECCI and EBSD to investigate the microstructure evolution related to fatigue dislocations structures • Characterisation of local plastic accommodation through EBSD misorientation criteria - Abstract: The present work aims at identifying the evolution of the microstructure of a Cu-Ni-Si (Corson alloy) alloy after low cycle fatigue by means of advanced electron microscopy analysis techniques (SEM-ECCI, Orientation Imaging Microscopy by means of SEM-EBSD and TEM). Deep attention is paid on the material subjected to high cyclic strains where a transient cellular dislocation structure transformed into precipitate free bands. It is shown that the formation of dislocation cells leads to a high GROD and high GOSaera value and its standard deviation. However, the presence of precipitate free bands results in the low GOSarea level and its low standard deviation.
Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.
In this study, the evolution of deformation mechanisms during cyclic loading in an extruded, solution-treated Mg–2Nd–1Y–0.1Zr–0.1Ca alloy was investigated using a combination of in-situ loading, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and focused ion beam (FIB) nanofabrication. The initial microstructure exhibited a random crystallographic texture with no preferred grain orientation. Flat, rectangular dog-bone specimens were subjected to load-controlled, fully reversed fatigue for 50 cycles, during which the same region was sequentially mapped to track microstructural changes. After 10 cycles of loading deformation twins were observed. During tensile reloading detwinning or narrowing of those twinned regions occurred. After 20 cycles, detwinning ceased and residual twins remained in the material. SEM imaging revealed numerous surface slip traces after cyclic loading. EBSD-assisted slip trace analysis identified the activation of prismatic and pyramidal < c+a> slip systems during low-cycle fatigue. Site-specific scanning transmission electron microscopy (STEM) further revealed that deformation was also accommodated by basal < a> slip and the dissociation of < c+a> dislocations. Center-of-symmetry (COS) analysis confirmed that the dissociation of < c+a> dislocations resulted in the formation of I₁ intrinsic stacking faults after cyclic loading. These findings provide new insights into the complex interplay of dislocation mechanisms governing fatigue deformation in rare-earth-containing Mg alloys.
Here, the three-dimensional (3D) microstructure of a friction stir assisted scribe technique (FaST) weld interface consisting of AZ31 magnesium (Mg) alloy and zinc (Zn)-coated DP590 steel was analyzed via synchrotron micro-computed tomography (μ-CT), correlated to synchrotron x-ray diffraction, and electron microscopy. Diffraction assessment of the AZ31/Zn-coated DP590 steel interface revealed the presence of several complex Mg–Zn intermetallic phases and differences in crystalline orientation of the Mg phase at the weld interface. The 3D characterization of the synchrotron μ-CT images of the weld interface revealed: (1) the presence of AZ31 weld nugget material with iron (Fe)-rich particles; (2) the presence of a weld layer at the joining interface with Fe-rich particles; (3) the formation of a thin non-uniform layer between the weld layer and the interface of the scribed DP590 material; and (4) the presence of an Fe–Al-rich intermetallic layer and Fe-rich particles at the interface of the scribed DP590 material. This study also performed a detailed analysis of lump-like features seen in the Zn coating layer at the weld interface. A detailed 3D particle analysis of the Fe-rich particles in the AZ31 weld nugget and the weld layer at the weld interface revealed the presence of several types of particle morphologies (i.e., spherical and irregular).
NiTi-based quaternary alloys are used in a variety of mechanical components, such as bearings, actuators, and dampers, owing to their good hardenability, wear resistance, and corrosion resistance. Additionally, one of the most notable characteristics of NiTi-based alloys is their shape memory effect and pseudoelastic properties. Connecting the macroscopic processing parameters employed in the design of new intermetallic alloys to the nanoscale structural characteristics dictating their behavior is crucial for improving their mechanical properties and expanding the spectrum of potential applications. Here, in this work, an arc melted Ni 50 Ti 21 Hf 25 Al 4 (at%) alloy was solution treated at 1050 °C followed by quenching and aging at 600 °C to investigate the effect of aging time on the microstructure and mechanical properties. Two types of nano-sized precipitates were observed and determined as face-centered orthorhombic H-phase (TiHf)Ni and L2 1 Heusler precipitates Ni 2 TiAl. The morphology and orientation of the H-phase were investigated using scanning and transmission electron microscopy (SEM and TEM), elucidating the coarsening kinetics and strengthening contribution of that phase to the intermetallic mechanical behavior. Following coarsening, the presence of Heusler nanoprecipitates was detected under overaged conditions through TEM imaging and nanobeam electron diffraction patterns. A peak hardness condition of 756 HV was achieved after 70 h of aging, indicating that the co-precipitation of H-phase and Heusler precipitates through a well-designed aging treatment can lead to optimal mechanical performance, thus elevating the alloy’s potential as a viable material for industrial applications.
In this work we develop a deep convolutional architecture to estimate the prior austenite structure from observed martensite electron backscatter diffraction micrographs. A novel data augmentation strategy randomizes the global reference coordinate system which makes it possible to train our model from only four micrographs. The model is much faster than algorithmic approaches and generalizes well when applied to micrographs of a different material. Empirical evidence suggests the efficacy of the model depends on the scale of the microstructure and receptive field of the vision model. Furthermore, this work demonstrates that modern computer vision approaches are well suited for capturing complex spatial-orientation patterns present in orientation imaging micrographs.
Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.
Abstract The microstructural evolution, deformation modes, and fracture mechanisms of zirconium plate produced using ultrasonic additive manufacturing (UAM) are presented. In addition to conventional tensile testing techniques, digital image correlation captured highly variable strain accumulation in specimens loaded perpendicular or parallel to the build height (Z). When tested in parallel to Z, delamination at prior foil/foil interfaces creates strain localization noticeable in strain rate maps, whereas specimens loaded perpendicular to Z illustrate conventional strain hardening until necking accelerates delamination. Although bond strengths are statistically and spatially variable, in situ electron backscattering diffraction tests illustrate the ability for grains near interfaces to accommodate strain with twinning and slip modes consistent with conventionally produced zirconium alloys. Finally, mixtures of ductile and delamination-induced fracture highlight the interface-driven failure modes of UAM zirconium plate in the as-built condition. Graphic abstract
Precipitation age hardening (T6) response of Al-5.8Zn-2.2Mg-2.5Cu alloy in near-net-shaped cast condition was investigated. Cast samples were manufactured using the controlled diffusion solidification (CDS) technology combined with a metallic mold tilt pour gravity casting process. This study was conducted using (1) non-isothermal aging during differential scanning calorimetry (DSC) experiments and (2) isothermal aging during which transient bulk and micro-hardness measurements taken at four aging temperatures of 343, 393, 433 and 473 K. A detailed microstructural investigation combined with a quantitative image analysis was carried out on both DSC and hardness specimens using high-resolution electron microscopy (HREM) and energy-dispersive spectroscopy (EDS) elemental mappings. Hardness measurements were analyzed using a kinetic modeling approach (single state variable combined with a kinetic equation that is valid for the Al-Zn-Mg-Cu alloys). The results confirm the formation of hardening phases of GP zone, intermediate hardening metastable phase η′ and equilibrium phase η. The results of calorimetric measurements, electron microscopy and selected area diffraction patterns are in good agreement and confirm transient precipitation/dissolution sequences. A mean value of activation energy Q{sub A} of 75 kJ/mol was evaluated for combined bulk diffusion rate of alloying elements during precipitation of strengthening phases within Al matrix.
Phase gratings are used as dispersers in a variety of imaging spectroscopic instruments. However, conventional phase gratings provide limited spectral range and flexibility to fully optimize instrument performance for challenging applications. Presented here is a new design method that tailors and optimizes the spectral efficiency by introducing an arbitrary structure into the grating groove profile.