High-resolution Digital Images Research Articles

Strain localization in the Alloy 718 Ni-based superalloy: From room temperature to 650 °C

Irreversible deformation in relation to the microstructure was investigated for a polycrystalline Ni-based superalloy (Alloy 718) from room temperature to 650 °C using high-resolution digital image correlation (HR-DIC) techniques. Interrupted tensile tests were performed under a protective atmosphere to ensure the stability of the speckle pattern to track kinematics fields from surface analyses. In-plane strain localization was captured using HR-DIC on scanning electron microscopy (SEM) images. A statistical analysis of different strain localization events in relation to the microstructural features was conducted, i.e., intragranular slip localization, slip localization parallel to and near Σ3-twin boundaries (Σ3-TB), and grain boundary sliding (GBS). Alloy 718 exhibited slip localization at room temperature and 350 °C. Intense strain localization develops parallel and in the vicinity of Σ3-TB from the onset of the microplasticity. Few intense slip stimulated-grain boundary sliding events were found due to slip localization on both grains adjacent to the grain boundary. At 650 °C, Alloy 718 experienced grain boundary sliding at the onset of the yield without particular slip localization in adjacent grains. At lower temperatures, strain localization parallel to and near Σ3-TB was intense, and intragranular slip localization intensified with increasing macroscopic deformation. Particular microstructural configurations were found at 650 °C leading to premature damage: (i) sub-surface cavitation at grain boundaries, and (ii) grain boundary cracking due to intense shearing near a Σ3-TB.

(005) Immunohistochemical Staining of the 12:00 Vestibule in NPV Patients: First Ever Assessment

Abstract Introduction In 2004, Bornstein and colleagues performed immunohistochemical (IHC) staining of excised vestibular specimens in patients with vestibular pain. They demonstrated that these specimens contained > 8 CD117 immunopositive stained cells per high-power field (HPF), consistent with mast cells, and excess S100 stained immunopositive cells, consistent with nerves-far more compared to control tissue. However, Bornstein et al. only studied the 1:00-11:00 vestibule in this condition, now referred to as neuroproliferative vestibulodynia (NPV). To the best of our knowledge, the 12:00 region of the vestibule, below the clitoral frenulae and above the urethral meatus, has not been examined with IHC staining. Pain in the 12:00 region can be particularly bothersome for patients and poses several challenges for successful treatment. Objective To report IHC staining findings in the excised 12:00 vestibule specimen and associated clinical characteristics of NPV patients. Methods Retrospective chart review performed. Slides of IHC-stained vestibular tissue specimens from the 12:00 vestibule were examined and high-resolution digital microscopy images were captured under 100x and 200x magnification. A least 2 photomicrographs at both magnifications were taken for each slide that included representative areas of epithelial basement membrane and the adjacent subepithelial regions. Fractional area of positive immunostaining in all photomicrographs was assessed and mean values calculated using computer-assisted histometry by ImageJ. Results A total of 50 patients had complete vestibulectomy including 12:00 and 3 had regional vestibulectomy for only the 12:00 area. Using manual counting as applied by Bornstein et al., 53 excised 12:00 specimens stained for CD117 had a median immunopositive cell count, consistent with mast cells, of 29.5, greater than the described 8 mast cells per HPF. Using computer-assisted histometry, tissue stained for CD117 had a median fractional area of 0.73 in the 12:00 region. Tissues stained for PGP9.5 had a median fractional area of 0.31 in the 12:00 region. Overall, there was no difference between lifelong NPV (LNPV) and acquired NPV (ANPV) patients in the cell count or median fractional area for CD117-immunopositive or PGP9.5-immunopositive staining in the 12:00 region. In LNPV patients who had excision of both the 1:00-11:00 and 12:00 regions, the 12:00 region had significantly less PGP9.5 immunopositive fractional area than the 1:00-11:00 region of the vestibule (p = 0.001). Their H&E pathology findings, including severity grading of the subepithelial inflammatory infiltrate, did not predict the IHC assessment of either CD117 or PGP9.5 in the 12:00 region. The median cotton-tipped swab test pain score was 5 out of 10 for the 12:00 region vs 7 for the rest of the vestibule. Conclusions Current surgical practices often do not include the 12:00 region, likely due to lack of data demonstrating excess mast cells and nerves in this specific region. Our results suggest that there are, in fact, a high density of immunopositive histochemical stains consistent with mast cells and nerves in the 12:00 region and high reported pain scores in both 12:00 and 1:00-11:00 vestibule. Thus, NPV surgical treatments should include, when appropriate, the 12:00 vestibule, as NPV is a field disease involving the entire vestibule. Disclosure No.

A Novel Technique Based on Machine Learning for Detecting and Segmenting Trees in Very High Resolution Digital Images from Unmanned Aerial Vehicles

The present study proposes a technique for automated tree crown detection and segmentation in digital images derived from unmanned aerial vehicles (UAVs) using a machine learning (ML) algorithm named Detectron2. The technique, which was developed in the python programming language, receives as input images with object boundary information. After training on sets of data, it is able to set its own object boundaries. In the present study, the algorithm was trained for tree crown detection and segmentation. The test bed consisted of UAV imagery of an agricultural field of tangerine trees in the city of Palermo in Sicily, Italy. The algorithm’s output was the accurate boundary of each tree. The output from the developed algorithm was compared against the results of tree boundary segmentation generated by the Support Vector Machine (SVM) supervised classifier, which has proven to be a very promising object segmentation method. The results from the two methods were compared with the most accurate yet time-consuming method, direct digitalization. For accuracy assessment purposes, the detected area efficiency, skipped area rate, and false area rate were estimated for both methods. The results showed that the Detectron2 algorithm is more efficient in segmenting the relevant data when compared to the SVM model in two out of the three indices. Specifically, the Detectron2 algorithm exhibited a 0.959% and 0.041% fidelity rate on the common detected and skipped area rate, respectively, when compared with the digitalization method. The SVM exhibited 0.902% and 0.097%, respectively. On the other hand, the SVM classification generated better false detected area results, with 0.035% accuracy, compared to the Detectron2 algorithm’s 0.056%. Having an accurate estimation of the tree boundaries from the Detectron2 algorithm, the tree health assessment was evaluated last. For this to happen, three different vegetation indices were produced (NDVI, GLI and VARI). All those indices showed tree health as average. All in all, the results demonstrated the ability of the technique to detect and segment trees from UAV imagery.

Quantifying cracking and strain localisation in a cold spray chromium coating on a zirconium alloy substrate under tensile loading at room temperature

The mechanical and cracking behaviour of a Cr coating, deposited on an Optimized ZIRLOTM substrate using the Cold Spraying (CS) technique, was investigated by in-situ scanning electron microscopy (SEM) tensile testing at room temperature. To achieve this, curved micro-tensile samples were machined from cladding tubes, and a styrene-assisted gold remodelled pattern was applied on the coating surface. The macroscopic crack density of the coating with applied axial strain was quantified through automated SEM image processing, whilst the localisation of strain was monitored with High Resolution Digital Image Correlation (HRDIC). Like with most brittle thin films deposited on ductile substrates, under applied external stress, parallel crack channelling appeared on the coating surface, perpendicular to the loading direction. The first crack was captured at 0.5% axial strain, whilst saturation was observed at 1.5%. Single crack formation in the coating was found to cause relaxation of local strains and redistribution towards the uncracked segment's midpoint. The local fracture strain of the coating was found to increase with the decreasing crack spacing, whilst shear bands appeared on the coating's surface at 35° and 145° with respect to the loading direction, which is evidence of plastic deformation. The crack density of the curved sample geometry was correlated with the tubes using a modified shear-lag model, considering the residual stresses in the coating measured by X-ray Diffraction (XRD). The CS Cr coating showed high levels of bonding and mechanical interlocking with the substrate, even after 3% axial strain.

Micro-strain and cyclic slip accumulation in a polycrystalline nickel-based superalloy

This work provides a comprehensive characterization and analysis of deformation and fatigue damage mechanisms in a nickel-based superalloy during ambient temperature fatigue and points to a fundamental deformation mechanism that results in the onset of crack nucleation. Strain and slip irreversibility are investigated at the nanometer scale using high-resolution digital image correlation and high-resolution electron backscatter diffraction, highlighting distinct deformation mechanisms contributing to crack nucleation. It is observed during early fatigue cycling at relatively low applied stress, the formation of intense slip events that induce grain boundary shearing. This results in intense micro-scale strain in the neighboring grains, producing localized plasticity and stresses. Such stresses facilitate fatigue extrusion–intrusion mechanisms during subsequent cycling, resulting in preferred crack nucleation. Finally, the configurations within the microstructure that promote such deformation and damage mechanisms sequence are highlighted.

Applications of Digital Pathology in Cancer: A Comprehensive Review

Digital pathology, powered by whole-slide imaging technology, has the potential to transform the landscape of cancer research and diagnosis. By converting traditional histopathological specimens into high-resolution digital images, it paves the way for computer-aided analysis, uncovering a new horizon for the integration of artificial intelligence (AI) and machine learning (ML). The accuracy of AI- and ML-driven tools in distinguishing benign from malignant tumors and predicting patient outcomes has ushered in an era of unprecedented opportunities in cancer care. However, this promising field also presents substantial challenges, such as data security, ethical considerations, and the need for standardization. In this review, we delve into the needs that digital pathology addresses in cancer research, the opportunities it presents, its inherent potential, and the challenges it faces. The goal of this review is to stimulate a comprehensive discourse on harnessing digital pathology and AI in health care, with an emphasis on cancer diagnosis and research.

Productivity Analysis of Mid-Size Cable Yarding Operation based on UAV-captured Video Sequences

Cable yarding is one of the most preferred timber extraction methods in steep and mountainous terrain conditions. In recent years in Turkiye, mid-size cable yarders have begun to be used frequently in steep forest areas where intensive forestry is carried out. In order to make more effective use of cable yarders and achieve maximum productivity, timber extraction operations must be planned most appropriately and implemented in the field accordingly. The productivity of mechanized equipment used in harvesting operations is mainly determined by using time study analysis. In traditional methods, time measurements are carried out by observing the work stages with time recording devices (stopwatches) in the area where the machine operates. Since timber extraction by using a cable yarder occur in steep and rugged terrain conditions, difficulties may be encountered in applying time analysis in the field. In this study, it was aimed to obtain high-resolution digital video images of the activities of cable yarding operation with an Unmanned Aerial Vehicle (UAV) and to calculate productivity through time study analysis on these images. For the study, the Tajfun MOZ 500 GR model mid-size cable yarder was evaluated during a timber extraction operation in Köyceğiz Forest Enterprise Chief (FEC), located in Muğla City, Turkiye. Besides, statistical analysis was performed to estimate the effects of factors such as average product length, product diameter, lateral yarding distance, number of pieces, and total product volume per turn on the productivity of the cable yarder. The results indicated that UAV video images can be an effective alternative method to conduct time study analysis and productivity estimations. It was found that the productivity of the mid-size cable yarder was 11.76 m3/hour. During the operation, the pulling mainline to the product and choker setting were the most time-consuming work stages, followed by the time-loaded carriage reaching the landing. The statistical analysis indicated a significant relationship (p<0.001) between product length, product diameter, total volume and productivity of the cable yarder. The results showed that there was a negative relationship between lateral yarding distance and productivity. The regression model regarding the productivity of the cable yarder and the independent variables was also significant.

Position-based anchor optimization for point supervised dense nuclei detection

Nuclei detection is one of the most fundamental and challenging problems in histopathological image analysis, which can localize nuclei to provide effective computer-aided cancer diagnosis, treatment decision, and prognosis. The fully-supervised nuclei detector requires a large number of nuclei annotations on high-resolution digital images, which is time-consuming and needs human annotators with professional knowledge. In recent years, weakly-supervised learning has attracted significant attention in reducing the labeling burden. However, detecting dense nuclei of complex crowded distribution and diverse appearances remains a challenge. To solve this problem, we propose a novel point-supervised dense nuclei detection framework that introduces position-based anchor optimization to complete morphology-based pseudo-label supervision. Specifically, we first generate cellular-level pseudo labels (CPL) for the detection head via a morphology-based mechanism, which can help to build a baseline point-supervised detection network. Then, considering the crowded distribution of the dense nuclei, we propose a mechanism called Position-based Anchor-quality Estimation (PAE), which utilizes the positional deviation between an anchor and its corresponding point label to suppress low-quality detections far from each nucleus. Finally, to better handle the diverse appearances of nuclei, an Adaptive Anchor Selector (AAS) operation is proposed to automatically select positive and negative anchors according to morphological and positional statistical characteristics of nuclei. We conduct comprehensive experiments on two widely used benchmarks, MO and Lizard, using ResNet50 and PVTv2 as backbones. The results demonstrate that the proposed approach has superior capacity compared with other state-of-the-art methods. In particularly, in dense nuclei scenarios, our method can achieve 95.1% performance of the fully-supervised approach. The code is available at https://github.com/NucleiDet/DenseNucleiDet.

Variations of the popliteal artery in human fetuses: preliminary study

IntroductionThis paper provides an in-depth analysis of the anatomical and morphometrical attributes of the popliteal artery (PA) in human fetuses. Additionally, it showcases significant interindividual variation in branching patterns, which are of great clinical importance in the context of vascular surgery and interventional radiology.AimThe purpose of this research was to systematically examine and categorize the anatomical and morphometrical diversities observed in the PA among a 166 sample of human fetuses at various gestational stages, spanning from 16 to 30 weeks of pregnancy.Material and methodsThe latex was injected into the 166 PA within the fetal specimens to visually analyze their anatomical features, and high-resolution digital images were captured at 24-bit color depth for detailed analysis.Results and DiscussionThe PAs were systematically classified into three distinct categories, further subcategorized into specific types. The classification system employed was based on the framework established initially by Lippert and Pabst, with modifications by Kim. The results of the analysis revealed the following distribution: Category I – it was mainly detected in the majority of specimens, comprising 144 cases (86.7%) of the sample population, and represented the most common anatomical configuration; Category II – it was found in 19 specimens (11.4%) of the total sample population (this category represented a less common anatomical variation within the PA); Category III – the rarest anatomical configuration observed in only 3 specimens (1.8%) from the sample population.ConclusionsThe frequent occurrence of short tibiofibular trunks in PA may be due to incidental lesions or postnatal developmental changes, highlighting the need for further research.

High-Resolution Digital Image Correlation Analysis of Layered α/β Two-Phase Ti–12Mo Alloy under Compressive Condition

High-Resolution Digital Image Correlation Analysis of Layered α/β Two-Phase Ti–12Mo Alloy under Compressive Condition

Sediment core analysis using artificial intelligence

Subsurface stratigraphic modeling is crucial for a variety of environmental, societal, and economic challenges. However, the need for specific sedimentological skills in sediment core analysis may constitute a limitation. Methods based on Machine Learning and Deep Learning can play a central role in automatizing this time-consuming procedure. In this work, using a robust dataset of high-resolution digital images from continuous sediment cores of Holocene age that reflect a wide spectrum of continental to shallow-marine depositional environments, we outline a novel deep-learning-based approach to perform automatic semantic segmentation directly on core images, leveraging the power of convolutional neural networks. To optimize the interpretation process and maximize scientific value, we use six sedimentary facies associations as target classes in lieu of ineffective classification methods based uniquely on lithology. We propose an automated model that can rapidly characterize sediment cores, allowing immediate guidance for stratigraphic correlation and subsurface reconstructions.

A comparative analysis of super-resolution techniques for enhancing micro-CT images of carbonate rocks

High-resolution digital rock micro-CT images captured from a wide field of view are essential for various geosystem engineering and geoscience applications. However, the resolution of these images is often constrained by the capabilities of scanners. To overcome this limitation and achieve superior image quality, advanced deep learning techniques have been used. This study compares four different super-resolution techniques, including super-resolution convolutional neural network (SRCNN), efficient sub-pixel convolutional neural networks (ESPCN), enhanced deep residual neural networks (EDRN), and super-resolution generative adversarial networks (SRGAN) to enhance the resolution of micro-CT images obtained from heterogeneous porous media. Our investigation employs a dataset consisting of 5000 micro-CT images acquired from a highly heterogeneous carbonate rock. The performance of each algorithm is evaluated based on its accuracy to reconstruct the pore geometry and connectivity, grain-pore edge sharpness, and preservation of petrophysical properties, such as porosity. Our findings indicate that EDRN outperforms other techniques in terms of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index, increased by nearly 4 dB and 17%, respectively, compared to bicubic interpolation. Furthermore, SRGAN exhibits superior performance compared to other techniques in terms of the learned perceptual image patch similarity (LPIPS) index and porosity preservation error. SRGAN shows a nearly 30% reduction in LPIPS compared to bicubic interpolation. Our results provide deeper insights into the practical applications of these techniques in the domain of porous media characterizations, facilitating the selection of optimal super-resolution CNN-based methodologies.

Evolution of in-plane strain fields onset of a plastically deforming crack in zirconium

Understanding the fracture behaviour of a material is essential for the sustainable design of structural components. The complex nature of microscale mechanical testing techniques makes identifying the fracture behaviour experimentally challenging at a microscopic scale. Validating microscale simulations with experimental studies can be difficult using traditional experimental techniques. High-resolution digital image correlation combined with electron backscatter diffraction describes the total in-plane deformation field at a microstructural scale, which can be compared against finite element models for verification. The present study determines the in-plane strain distribution ahead of a plastically deforming crack during an in-situ experiment. A crystal plasticity-based finite element model is used to simulate the experimental crack tip behaviour, after which quantitative and qualitative comparisons are made. A concentration of normal strains ahead of the crack tip is observed in both experimental and simulated results, defining the fracture process zone. Slip localization behaviour around the crack is also evaluated using Schmid factor analysis. A good correlation between the experimental slip bands and theoretical predictions has been observed. The strain path dependence on slip activation is also identified. Strain localization in deforming zirconium is initially limited with dense and low-intensity slip occurring up to a maximum in-plane shear strain of 0.2. Formation of well-defined equidistant slip bands occurs with further deformation. Equidistant slip bands are observed for prismatic <a> and pyramidal <c+a> slip systems, having an interplane distance of ∼0.60±0.05 µm and ∼0.46±0.04 µm, respectively.

The role of strain rate in microstructure evolution, deformation heterogeneity and cracking mode of high-pressure die-casting Al7Si0.2Mg alloy

The quasi-static and dynamic deformation behaviours of high-pressure die-casting (HPDC) Al7Si0.2 Mg alloy were studied in this work. Competing effects among porosities, α-Al(Fe/Mn)Si phase, eutectic phase and α-Al dendrites on strain concentration and crack propagation at different strain rates were investigated using X-ray computed tomography (CT), scanning electron microscopy (SEM), in-situ electron backscattering diffraction (EBSD), and high-resolution digital image correlation (HR-DIC). The results indicate that yield strength and ductility of Al7Si0.2 Mg alloy were improved at high strain rates compare to quasi-static loading. Weak zones, including porosities and particle interfaces, primarily contributed to deformation heterogeneity under quasi-static tension, whereas both weak zones and Al matrix played a role under dynamic loading. Moreover, crack propagation was hardly observed on porosities during dynamic deformation, thereby reducing the sensitivity of ductility to porosity. The slip and rotation of α-Al dendrites became more pronounced during dynamic deformation. As a result, the area fraction of fractured eutectic phase increased dramatically and surpassed the area fraction of α-Al(Fe/Mn)Si phase, which became the dominant factor of crack propagation during dynamic deformation.

Microplastics' Shape and Morphology Analysis in the Presence of Natural Organic Matter Using Flow Imaging Microscopy.

Ubiquitous microplastics in urban waters have raised substantial public concern due to their high chemical persistence, accumulative effects, and potential adverse effects on human health. Reliable and standardized methods are urgently needed for the identification and quantification of these emerging environmental pollutants in wastewater treatment plants (WWTPs). In this study, we introduce an innovative rapid approach that employs flow imaging microscopy (FlowCam) to simultaneously identify and quantify microplastics by capturing high-resolution digital images. Real-time image acquisition is followed by semi-automated classification using customized libraries for distinct polyethylene (PE) and polystyrene (PS) microplastics. Subsequently, these images are subjected to further analysis to extract precise morphological details of microplastics, providing insights into their behavior during transport and retention within WWTPs. Of particular significance, a systematic investigation was conducted to explore how the presence of natural organic matter (NOM) in WWTPs affects the accuracy of the FlowCam's measurement outputs for microplastics. It was observed that varying concentrations of NOM induced a more curled shape in microplastics, indicating the necessity of employing pre-treatment procedures to ensure accurate microplastic identification when utilizing the FlowCam. These observations offer valuable new perspectives and potential solutions for designing appropriate treatment technologies for removing microplastics within WWTPs.

Three-dimensional configuration of crystal plasticity in stainless steel assessed by high resolution digital image correlation and confocal microscopy

In polycrystalline austenitic stainless steels, a comprehensive three-dimensional configuration of crystal plasticity in relation to microstructure is required to elucidate the deformation behaviors during mechanical loading. In the present work, a combination of backscattered electron image (BSE) based high-resolution digital image correlation (HR-DIC) and laser scanning confocal microscopy (LSCM) was employed to simultaneously investigate in-plane and out-of-plane deformations at the sub-grain scale in 316 stainless steel. The high spatial resolution and precise alignment provided by the three-dimensional deformation assessment enable the identification of specific slip and twinning systems. This is achieved through the minimization of the residual L2 norm between the in-plane components of experimental and theoretical strain tensors. Dominant slip and few mechanical twinning activities are initiated at the early-stage of yielding, and their frequency and intensity increase with the applied load. The hierarchical networks formed by nanotwins, along with the presence of grain and annealing twin boundaries, serve as obstacles for slip glide, leading to substantial twin–slip interaction and grain boundary strengthening. As a consequence of wide mechanical twins formed by parallel nanotwins coalescence and strain localization at the twin boundary, slip transmission occurs, resulting in an effective accommodation of external stress. Furthermore, the consistent observation of out-of-plane roughness, in alignment with twinning Burgers vector predictions, offers valuable insights into the significant deformation gradient occurring in the vicinity of boundaries. This deformation gradient is influenced by the neighboring mechanical twinning activities, indicating strong obstacle to twin transmission and high back-stresses resulting from the highly misoriented grain boundary.

Exploring the hydride-slip interaction in zirconium alloys

Hydrogen pick-up and hydride precipitation can lead to embrittlement and fracture strength reduction of nuclear fuel cladding tubes made of Zircaloy. Plastic deformation of hydride packets and its interaction with local plasticity in the zirconium matrix is a key linkage of microstructure feature to structural integrity of hydrided polycrystalline bulk Zircaloy. This work focuses on explicit representation of hydride packets from high spatial resolution electron backscatter diffraction onto a crystal plasticity finite element model for capturing and understanding slip localisation near hydride-matrix phase boundaries, based on the extracted material property of hydrides. The mechanisms behind slip evolution including slip nucleation, slip transfer, and slip inhibition are studied by combined high-resolution digital image correlation and crystal plasticity results. Through assessing various slip transfer parameters, new slip transfer criterion is proposed for α/δ phase boundaries. Prior to slip transfer criterion, local micromechanical quantities, specifically shear stress and stored energy density, are necessary to drive and provide pathway for subsequent slip transfer at α/δ phase boundaries.

Future Practices of Breast Pathology Using Digital and Computational Pathology.

Pathology clinical practice has evolved by adopting technological advancements initially regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and genomic sequencing. Breast pathology has a critical role as a medical domain, where the patient's pathology diagnosis has significant implications for prognostication and treatment of diseases. The advent of digital and computational pathology has brought about significant advancements in the field, offering new possibilities for enhancing diagnostic accuracy and improving patient care. Digital slide scanning enables to conversion of glass slides into high-fidelity digital images, supporting the review of cases in a digital workflow. Digitization offers the capability to render specimen diagnoses, digital archival of patient specimens, collaboration, and telepathology. Integration of image analysis and machine learning-based systems layered atop the high-resolution digital images offers novel workflows to assist breast pathologists in their clinical, educational, and research endeavors. Decision support tools may improve the detection and classification of breast lesions and the quantification of immunohistochemical studies. Computational biomarkers may help to contribute to patient management or outcomes. Furthermore, using digital and computational pathology may increase standardization and quality assurance, especially in areas with high interobserver variability. This review explores the current landscape and possible future applications of digital and computational techniques in the field of breast pathology.

Revealing the effect of misorientation on the deformation behavior of a Mg-Y alloy from the perspective of local strain

The addition of rare earth (RE) elements in magnesium alloys may significantly enhance the ductility of magnesium alloys, which is generally attributed to the decrease of stacking fault energy, the reduced critical resolved shear stress (CRSS) differences among different deformation modes and the weakening of basal texture. Rare earth elements also change the misorientation between adjacent grains of magnesium alloy, whose effects on the deformation behavior and thus the ductility of magnesium alloy were not emphasized before. In this work, ex-situ high-resolution digital image correlation (HR-DIC) coupled with electron backscatter diffraction (EBSD) was used to reveal the effect of the misorientation on the deformation behavior of a Mg-Y binary alloy from the perspective of local strain. It is shown that the heterogeneity of local strain is largely dependent on the misorientation between adjacent grains. For the intergranular deformation, three scenarios are observed, namely strain transfer, strain concentration and suppressed deformation, which mainly occurs at low misorientation, moderate misorientation and high misorientation, respectively. In addition, much more non-basal slip is found to be activated near the grain boundaries with moderate misorientation angles due to the high geometric compatibility factor (m’B-Pr/Py), which is favorable for the intergranular deformation compatibility, thus reducing the strain concentration near grain boundaries and achieving high ductility. For the intragranular deformation, a wide range of misorientation between adjacent grains in the Mg-Y alloy causes multiple basal slip systems to be activated within a grain, which also facilitates work hardening, thus contributing to improving ductility. Therefore, tailoring the misorientation between adjacent grains may be an effective way to improve the ductility of magnesium alloys.

The role of hydrides and precipitates on the strain localisation behaviour in a zirconium alloy

In service, zirconium alloys undergo aqueous corrosion and hydrogen is absorbed, which can lead to the formation of hydrides. Hydrides, as well as the precipitates in zirconium alloys, affect the mechanical performance, though their contribution to plasticity is not yet well understood. This study uses a combination of high-resolution digital image correlation and electron backscatter diffraction to quantify the strain partitioning between the different phases. Following uniaxial tensile deformation, it was found that the average strain within the δ-ZrH and Zr(Fe,Cr)2 was lower than in the α-Zr. Shear bands in the α-Zr matrix were observed to interact with small and medium sized hydride in multiple ways, such as terminating at the interface, cracking and shear around the interface or causing plastic slip in the hydride. Large hydrides showed a particularly detrimental effect on deformation behavior, with large strain localizations and cracking observed at interfaces, which are typically precursors to failure. In contrast, the Zr(Fe,Cr)2 precipitates remained undeformed and forced the expected metal-matrix lattice rotation. The importance of these observations in context of fuel cladding integrity is discussed.