High Spatial Resolution Scanning Research Articles

Insight into double twinning behavior of Mg–Gd rolled alloy at the nano scale: Role of micro-texture entropy

101¯1}− {101¯2} double twinning is a classical twinning mode with diverse variants in magnesium and its alloys. However, its variant selection criterion and its influence on the mechanical behaviors are still in debate. In this study, we proposed a view of micro-texture entropy to elucidate the double twinning behavior during large strain rolling of Mg–1.5Gd (wt%) alloy. Combined with the high spatial resolution scanning electron microscopy-transmission Kikuchi diffraction (SEM-TKD) technique, the detailed microstructure and micro-texture of the double twins in early stage of evolution were detected, and new insight into the variant selection and evolution of double twins was obtained. The observations suggest that the nucleation events of different double twin variants are influenced by their micro-texture entropy, the variants with lower micro-texture entropy are preferred. While the growth stage of double twins is affected both by their micro-texture entropy and the geometric factors between the primary and secondary twin systems; the former will influence their growth potential and the later can affect their growth space. A novel {101¯1}− {101¯3} double twin was also triggered to release the high local stress concentration during large strain rolling process.

Analysis of Early Stroke Diagnosis Based on Brain Magnetic Resonance Imaging using Machine Learning

Stroke causes paralysis resulting from a hemorrhage in the brain or blockage of blood flow to the brain. It is third leading cause of death in Malaysia, with at least 32 deaths per day, and poses a major challenge to Malaysia's health services. A recent study showed that he could save a patient's life if he received treatment within six hours of a stroke. Unfortunately, Malaysia is facing a shortage of neuroradiologists, hampering efforts to treat its growing number of stroke patients. In this research, used Magnetic Resonance Imaging which is better compare to CT scan and CBCT because MRI will produce more detailed images of soft tissues, ligaments and organs. So that, advanced imaging using magnetic resonance imaging (MRI) has gained more attention than conventional angiography in the diagnosis of acute stroke due to its high spatial resolution and fast scan times. Traditionally, diagnosis was made manually by neuroradiologists during a highly subjective and time-consuming task. Detecting collaterals from MRI images is a challenging task due to the presence of noise and artifacts, small size, and heterogeneous structure of vessels. By the way, this paper is mainly about the early diagnosis of stroke based on brain magnetic resonance imaging using machine learning. Based on the results, can see that the Fuzzy c-means (FCM) and Watershed Transformation (WT) segmentation of brain infarcts which are original image, output of guided filter, gradient magnitude image, output of watershed transform and final detected infarct with morphological operation.

A Tabletop X-Ray Tomography Instrument for Nanometer-Scale Imaging: Demonstration of the 1,000-Element Transition-Edge Sensor Subarray

We report on the 1,000-element transition-edge sensor (TES) x-ray spectrometer implementation of the TOMographic Circuit Analysis Tool (TOMCAT). TOMCAT combines a high spatial resolution scanning electron microscope (SEM) with a highly efficient and pixelated TES spectrometer to reconstruct three-dimensional maps of nanoscale integrated circuits (ICs). A 240-pixel prototype spectrometer was recently used to reconstruct ICs at the 130 nm technology node, but to increase imaging speed to more practical levels, the detector efficiency needs to be improved. For this reason, we are building a spectrometer that will eventually contain 3,000 TES microcalorimeters read out with microwave superconducting quantum interference device (SQUID) multiplexing, and we currently have commissioned a 1,000 TES subarray. This still represents a significant improvement from the 240-pixel system and allows us to begin characterizing the full spectrometer performance. Of the 992 maximimum available readout channels, we have yielded 818 devices, representing the largest number of TES x-ray microcalorimeters simultaneously read out to date. These microcalorimeters have been optimized for pulse speed rather than purely energy resolution, and we measure a FWHM energy resolution of 14 eV at the 8.0 keV Cu K$\alpha$ line.

Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.

Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis and treatment of CAD. Constrained by Nyquist theorem, dense sampling in IVOCT attains high resolving power to delineate cellular structures/features. There is a trade-off between high spatial resolution and fast scanning rate for coronary imaging. In this paper, we propose a viable spectral-spatial acquisition method that down-scales the sampling process in both spectral and spatial domain while maintaining high quality in image reconstruction. The down-scaling schedule boosts data acquisition speed without any hardware modifications. Additionally, we propose a unified multi-scale reconstruction framework, namely Multiscale-Spectral-Spatial-Magnification Network (MSSMN), to resolve highly down-scaled (compressed) OCT images with flexible magnification factors. We incorporate the proposed methods into Spectral Domain OCT (SD-OCT) imaging of human coronary samples with clinical features such as stent and calcified lesions. Our experimental results demonstrate that spectral-spatial down-scaled data can be better reconstructed than data that are down-scaled solely in either spectral or spatial domain. Moreover, we observe better reconstruction performance using MSSMN than using existing reconstruction methods. Our acquisition method and multi-scale reconstruction framework, in combination, may allow faster SD-OCT inspection with high resolution during coronary intervention.

High spatial resolution observation of Temporin A at cell membranes using scanning ion conductive microscopy

The electrochemical visualization of molecules binding at the plasma membrane of single cells is important, but challenging. Here, the binding of Temporin A at the plasma membrane of a single living A549 cell is imaged using high spatial resolution scanning ion conductive microscopy (SICM). A relatively steep approach curve is observed at the binding region, compared with that at the non-binding cellular membrane. This difference is ascribed to the neutralization of the negative charges at the cellular membrane by the positively charged Temporin A through electrostatic binding. The pit-like structure of the plasma membrane is visualized in the SICM image, exhibiting unhomogeneous binding of Temporin A at the cell, and providing direct evidence about the interaction of Temporin A with certain regions of the membrane. The information will facilitate a deeper understanding of the cytotoxicity of Temporin A for the treatment of lung cancer. Moreover, the successful visualization of this process is an example of an electrochemical strategy that could be used to study other molecular interactions at cellular membranes.

Detection of Collaterals from Cone-Beam CT Images in Stroke.

Collateral vessels play an important role in the restoration of blood flow to the ischemic tissues of stroke patients, and the quality of collateral flow has major impact on reducing treatment delay and increasing the success rate of reperfusion. Due to high spatial resolution and rapid scan time, advance imaging using the cone-beam computed tomography (CBCT) is gaining more attention over the conventional angiography in acute stroke diagnosis. Detecting collateral vessels from CBCT images is a challenging task due to the presence of noises and artifacts, small-size and non-uniform structure of vessels. This paper presents a technique to objectively identify collateral vessels from non-collateral vessels. In our technique, several filters are used on the CBCT images of stroke patients to remove noises and artifacts, then multiscale top-hat transformation method is implemented on the pre-processed images to further enhance the vessels. Next, we applied three types of feature extraction methods which are gray level co-occurrence matrix (GLCM), moment invariant, and shape to explore which feature is best to classify the collateral vessels. These features are then used by the support vector machine (SVM), random forest, decision tree, and K-nearest neighbors (KNN) classifiers to classify vessels. Finally, the performance of these classifiers is evaluated in terms of accuracy, sensitivity, precision, recall, F-Measure, and area under the receiver operating characteristics curve. Our results show that all classifiers achieve promising classification accuracy above 90% and able to detect the collateral and non-collateral vessels from images.

Achieving high spatial resolution in a large field-of-view using lensless x-ray imaging

X-ray ptychography, a powerful scanning lensless imaging technique, has become attractive for nondestructively imaging internal structures at nanoscale. Stage positioning overhead in conventional step-scan ptychography is one of the limiting factors on the imaging throughput. In this work, we demonstrate the use of advanced fly scan ptychography to achieve high-resolution ptychograms of modern integrated circuits on a large field-of-view at millimeter scale. By completely removing stage overheads between scan points, the imaging time for millimeter-size sample can be significantly reduced. Furthermore, we implement the orthogonal probe relaxation technique to overcome the variation of illumination across the large scan area as well as local vibrations. The capability of x-ray ptychography shown here is broadly applicable for various studies, which requires both high spatial resolution and large scan area.

MRI Super-Resolution Through Generative Degradation Learning.

Spatial resolution plays a critically important role in MRI for the precise delineation of the imaged tissues. Unfortunately, acquisitions with high spatial resolution require increased imaging time, which increases the potential of subject motion, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) has recently emerged as a technique that allows for a trade-off between high spatial resolution, high SNR, and short scan duration. Deconvolution-based SRR has recently received significant interest due to the convenience of using the image space. The most critical factor to succeed in deconvolution is the accuracy of the estimated blur kernels that characterize how the image was degraded in the acquisition process. Current methods use handcrafted filters, such as Gaussian filters, to approximate the blur kernels, and have achieved promising SRR results. As the image degradation is complex and varies with different sequences and scanners, handcrafted filters, unfortunately, do not necessarily ensure the success of the deconvolution. We sought to develop a technique that enables accurately estimating blur kernels from the image data itself. We designed a deep architecture that utilizes an adversarial scheme with a generative neural network against its degradation counterparts. This design allows for the SRR tailored to an individual subject, as the training requires the scan-specific data only, i.e., it does not require auxiliary datasets of high-quality images, which are practically challenging to obtain. With this technique, we achieved high-quality brain MRI at an isotropic resolution of 0.125 cubic mm with six minutes of imaging time. Extensive experiments on both simulated low-resolution data and clinical data acquired from ten pediatric patients demonstrated that our approach achieved superior SRR results as compared to state-of-the-art deconvolution-based methods, while in parallel, at substantially reduced imaging time in comparison to direct high-resolution acquisitions.

Characterizing soil piping networks in loess‐derived soils using ground‐penetrating radar

AbstractSoil piping remains a relatively unexplored phenomenon despite its substantial impacts on water and sediment transfer at the watershed scale at numerous locations around the world. One of the main limitations regarding the study of this singular process is the characterization of the pipe networks (in terms of number, position, dimensions, and connectivity of pipes). In this context, noninvasive subsurface imaging using ground‐penetrating radar (GPR) has proven to be a promising technique. This study used two three‐dimensional (3D), high‐resolution GPR surveys performed in loess‐derived soils to characterize small pipe networks with little prior information about their location. The adopted methodology relies on high spatial resolution scanning, 3D subsurface imaging, and automated detection of reflection hyperbolas using a 200‐MHz center‐frequency antenna. Two small watersheds affected by piping were investigated at Sippenaeken and Kluisbergen (Belgium). Over the two scanned zones, results revealed significant subsurface continuous patterns. Even though the most obvious patterns corresponded to recent or past anthropic activities (e.g., artificial drainage pipes), validation tests confirmed that the chosen methodology can be used for pipe network characterization because some important continuity patterns were related to soil piping: for instance, a fairly small pipe (approximately 10–15 cm in diameter) was detected and validated for more than 100 m. Nevertheless, the high variability in size, depth, and orientation of the pipes imply that GPR may only be truly efficient when using very high spatial resolution scanning, which limits its application to specific conditions not always met in piped areas.

Respiratory motion-compensated high-resolution 3D whole-heart T1\u03c1 mapping

BackgroundCardiovascular magnetic resonance (CMR) T1ρ mapping can be used to detect ischemic or non-ischemic cardiomyopathy without the need of exogenous contrast agents. Current 2D myocardial T1ρ mapping requires multiple breath-holds and provides limited coverage. Respiratory gating by diaphragmatic navigation has recently been exploited to enable free-breathing 3D T1ρ mapping, which, however, has low acquisition efficiency and may result in unpredictable and long scan times. This study aims to develop a fast respiratory motion-compensated 3D whole-heart myocardial T1ρ mapping technique with high spatial resolution and predictable scan time.MethodsThe proposed electrocardiogram (ECG)-triggered T1ρ mapping sequence is performed under free-breathing using an undersampled variable-density 3D Cartesian sampling with spiral-like order. Preparation pulses with different T1ρ spin-lock times are employed to acquire multiple T1ρ-weighted images. A saturation prepulse is played at the start of each heartbeat to reset the magnetization before T1ρ preparation. Image navigators are employed to enable beat-to-beat 2D translational respiratory motion correction of the heart for each T1ρ-weighted dataset, after which, 3D translational registration is performed to align all T1ρ-weighted volumes. Undersampled reconstruction is performed using a multi-contrast 3D patch-based low-rank algorithm. The accuracy of the proposed technique was tested in phantoms and in vivo in 11 healthy subjects in comparison with 2D T1ρ mapping. The feasibility of the proposed technique was further investigated in 3 patients with suspected cardiovascular disease. Breath-hold late-gadolinium enhanced (LGE) images were acquired in patients as reference for scar detection.ResultsPhantoms results revealed that the proposed technique provided accurate T1ρ values over a wide range of simulated heart rates in comparison to a 2D T1ρ mapping reference. Homogeneous 3D T1ρ maps were obtained for healthy subjects, with septal T1ρ of 58.0 ± 4.1 ms which was comparable to 2D breath-hold measurements (57.6 ± 4.7 ms, P = 0.83). Myocardial scar was detected in 1 of the 3 patients, and increased T1ρ values (87.4 ± 5.7 ms) were observed in the infarcted region.ConclusionsAn accelerated free-breathing 3D whole-heart T1ρ mapping technique was developed with high respiratory scan efficiency and near-isotropic spatial resolution (1.7 × 1.7 × 2 mm3) in a clinically feasible scan time of ~ 6 mins. Preliminary patient results suggest that the proposed technique may find applications in non-contrast myocardial tissue characterization.

A laboratory study for occupational safety and health on the structure of airborne ultrasound fields

While exposure to airborne ultrasound is increasing in occupational contexts and in public and private spaces, existing demand for reliable and traceable determination of exposure to sound with frequencies above 16 kHz cannot currently be satisfied due to a lack of adequate measurement devices and procedures adapted to the specifics of airborne ultrasound. So that this study may serve as a first step for the development of a novel measurement procedure, its aim is to create a comprehensive database of the structures of airborne ultrasound fields present in occupational contexts. Based on this, the limitations of measurement procedures commonly used in the audible frequency range are clarified and the structural characteristics of airborne ultrasound fields investigated. This paper presents a laboratory study of the structure of the airborne ultrasound field of an ultrasonic welding machine, which can be considered a representative occupational source of airborne ultrasound. For this study, the technical and procedural requirements of a measuring system are derived and used to set up and calibrate a measuring system for three-dimensional, high spatial resolution scans of sound pressure levels in the laboratory. The measurement results reveal complex, extensive and very fine-structured interference patterns, some of which have sound pressure levels of up to 138 dB (re 20 μPa).

Geometrical constraints on the bending deformation of Penta-twinned silver nanowires

Penta-twinned and single crystal silver nanowires were bent in-situ for TEM structural analysis using high spatial resolution scanning precession electron diffraction. Machine learning methods were used to determine the structure of the localised bends in the wires. Single crystal nanowires showed both dispersed large radius bend deformation and abrupt, angular bends with narrow deformation zones accommodated by a high angle boundary plane. The penta-twinned wires were found to display simple in-plane bends with narrow deformation zones in all 5 sub-crystals of the wire, with a common boundary plane. A coincident site lattice model has been developed to explain the bending angles seen in individual nanowires and the observed distribution of angles in a population of penta-twinned nanowires. The geometrical constraints of the model explain the difference in this distribution when compared to that from a population of single crystal nanowires.

Super-Resolution Ultrasound Imaging by Sparse Bayesian Learning Method

Super-resolution ultrasound (SR-US) imaging technique overcomes the acoustic diffraction limit and greatly improves the spatial resolution. Furthermore, by exploiting temporal fluctuations in microbubbles, a super-resolution fluctuation imaging (SOFI) method has also been used to improve the temporal resolution of SR-US. However, this is at the expense of the reduction of spatial resolution. To address this problem, in this paper, a temporally correlated multiple sparse Bayesian learning (TMSBL) method is introduced to SR-US. Since TMSBL takes advantage of both the temporal correlation between successive frames and sparsity priors of microbubbles, it provides the possibility to obtain an enhancement in spatial resolution compared to SOFI (only considering the temporal fluctuations). To evaluate the performance of the proposed method, two types of numerical simulation and one physical phantom experiment were performed. Especially, we also investigate the effect of US imaging modes on the performance of SR-US implemented by TMSBL, where US data were acquired from the plane wave (the high imaging speed and the low spatial resolution) and synthetic transmit aperture (the low imaging speed and the high spatial resolution) scan, respectively. The experimental results show that compared to SOFI method when using the proposed TMSBL method, the imaging spatial resolution of SR-US can be improved. In addition, the imaging performance obtained by TMSBL can be hardly affected by US imaging modes. As a result, by combining with plane wave scan, TMSBL provides the potential in enhancing the spatial resolution of SR-US while maintaining a desired temporal resolution.

Insights into graphene wettability transparency by locally probing its surface free energy.

In this work, we study the surface energy of monolayer, bilayer and multilayer graphene coatings, produced through exfoliation of natural graphite flakes and chemical vapor deposition. We employ bimodal atomic force microscopy and micro-Raman spectroscopy for high spatial resolution and large area scanning of force of adhesion on the regions of the graphene/SiO2 surface with different graphene layers. Our measurements show that the interface conditions between graphene and SiO2 dominate the experimentally observed graphene surface energy. This finding sheds new light on the controversy surrounding graphene transparency studies. By separating the surface energy into polar and non-polar interactions, our findings suggest that monolayer graphene is nearly van der Waals opaque but partially transparent (near 60%) to polar interactions, which is further supported by characterizing graphene on the copper surface and two levels of density functional theory simulation. In addition to providing quantitative insight into the surface interactions of complicated graphene coatings, this work demonstrates a new route to nondestructively monitor the interface between graphene and coated substrates.

Fatigue crack initiation and growth in 43Fe-25Ni-22.5Cr austenitic steel at a temperature of 700 °C

Crack initiation and short crack growth in highly-alloyed austenitic steel Sanicro 25 cyclically strained at a temperature of 700 °C has been studied. Specimens cycled to 10% of the fatigue life and to the fracture were inspected using scanning electron microscopy and electron backscatter diffraction. On the surface, thin lamellae were extracted site-specifically by focused ion beam and then they were further characterized by high spatial resolution scanning transmission electron microscopy and energy dispersive X-ray spectroscopy. The preferential oxidation of grain boundaries was found to play a principal role in the initiation of multiple cracks. The oxide scale was analysed to show the distribution of individual elements during crack initiation and growth. Two types of crack paths were observed: intergranular due to the oxidation and transgranular accompanied by a cyclic plastic zone. Cracks preferentially initiated at the grain boundaries perpendicular to the stress axis and propagated in the bulk of the material. The role of the oxidation in high temperature fatigue crack initiation is discussed as well as the mechanisms of the crack initiation and growth.

High spatial resolution scanning for experimental room-acoustic measurements in scale models

This paper presents an experimental study of low frequency behavior of sound propagation in acoustically coupled volumes. The experiments are carried out in an eighth-scale model of two coupled volumes with an automated high spatial-resolution scanning system. Both sound pressure and three-dimensional sound intensities are automatically measured in terms of room impulse responses at each scanning positions over densely defined two-dimensional grids covering the entire areas of the two coupled rooms that enable the analysis and visualization of sound energy and sound energy flows. Through these measurements, and with the aid of a predictive computational model, this paper will discuss low frequency modal behaviors of sound energy flows within one of two coupled volumes. As such, the distribution of potential and kinetic energies, as well as that of active and reactive sound intensities within the coupled space will be separately analyzed. The distributions of intensity vector fields are compared through computational simulation. Consequently, a discussion on possible discrepancies in modal distributions between the computational and experimental results rounds off this paper.

A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data.

Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

Оценка и структурный анализ наноматериалов на сканирующем электронном микроскопе с высоким пространственным разрешением

Оценка и структурный анализ наноматериалов на сканирующем электронном микроскопе с высоким пространственным разрешением

Оценка и структурный анализ наноматериалов на сканирующем электронном микроскопе с высоким пространственным разрешением. Часть 2

Оценка и структурный анализ наноматериалов на сканирующем электронном микроскопе с высоким пространственным разрешением. Часть 2

Using transmission Kikuchi diffraction to characterise α variants in an α+β titanium alloy.

SummaryTwo phase titanium alloys are important for high‐performance engineering components, such as aeroengine discs. The microstructures of these alloys are tailored during thermomechanical processing to precisely control phase fractions, morphology and crystallographic orientations. In bimodal two phase (α + β) Ti‐6Al‐2Sn‐4Zr‐2Mo (Ti‐6242) alloys there are often three microstructural lengthscales to consider: large (∼10 μm) equiaxed primary α; >200 nm thick plate α with a basketweave morphology; and very fine scaled (<50 nm plate thickness) secondary α that grows between the larger α plates surrounded by retained β. In this work, we utilise high spatial resolution transmission Kikuchi diffraction (TKD, also known as transmission‐based electron backscatter diffraction, t‐EBSD) and scanning electron microscopy (SEM)‐based forward scattering electron imaging to resolve the structures and orientations of basketweave and secondary α in Ti‐6242. We analyse the α variants formed within one prior β grain, and test whether existing theories of habit planes of the phase transformation are upheld. Our analysis is important in understanding both the thermomechanical processing strategy of new bimodal two‐phase titanium alloys, as well as the ultimate performance of these alloys in complex loading regimes such as dwell fatigue. Our paper champions the significant increase in spatial resolution afforded using transmission techniques, combined with the ease of SEM‐based analysis using conventional electron backscatter diffraction (EBSD) systems and forescatter detector (FSD) imaging, to study the nanostructure of real‐world engineering alloys.