3D Defect Research Articles

Extended defects-enhanced oxygen diffusion in ThO[formula omitted]

Oxygen self-diffusion is key to understanding stoichiometry and defect structures in oxide nuclear fuels. Experimentally, low activation-barrier oxygen migration was found in ThO2, a candidate nuclear fuel, possibly due to short-circuit diffusion mechanisms. Here, we perform extensive molecular dynamics simulations to show that various types of extended defects can enhance oxygen self-diffusion with a much-reduced activation barrier in ThO2. In this work, we consider extended defects including 1D (dislocation), 2D (grain boundary), and 3D (void) defects. Due to the distinct characteristics of each type of extended defect, the modulation of oxygen diffusion varies. These results provide a quantitative description of oxygen transport, which is significantly enhanced within a close distance (nanometer scale) from the extended defects. Among all these considered defects, grain boundary, particularly the low-energy Σ3 twin boundary, exhibits the strongest effect on increasing oxygen transport.

Reliability of Manual Measurements Versus Semiautomated Software for Glenoid Bone Loss Quantification in Patients With Anterior Shoulder Instability.

The presence of glenoid bone defects is indicative in the choice of treatment for patients with anterior shoulder instability. In contrast to traditional linear- and area-based measurements, techniques such as the consideration of glenoid concavity have been proposed and validated. To compare the reliability of linear (1-dimensional [1D]), area (2-dimensional [2D]), and concavity (3-dimensional [3D]) measurements to quantify glenoid bone loss performed manually and to analyze how automated measurements affect reliability. Cohort study (diagnosis); Level of evidence, 3. Computed tomography images of 100 patients treated for anterior shoulder instability with differently sized glenoid defects were evaluated independently by 2 orthopaedic surgeons manually using conventional software (OsiriX; Pixmeo) as well as automatically with a dedicated prototype software program (ImFusion Suite; ImFusion). Parameters obtained included 1D (defect diameter, best-fit circle diameter), 2D (defect area, best-fit circle area), and 3D (bony shoulder stability ratio) measurements. Mean values and reliability as expressed by the intraclass correlation coefficient [ICC]) were compared between the manual and automated measurements. When manually obtained, the measurements showed almost perfect agreement for 1D parameters (ICC = 0.83), substantial agreement for 2D parameters (ICC = 0.79), and moderate agreement for the 3D parameter (ICC = 0.48). When measurements were aided by automated software, the agreement between raters was almost perfect for all parameters (ICC = 0.90 for 1D, 2D, and 3D). There was a significant difference in mean values between manually versus automatically obtained measurements for 1D, 2D, and 3D parameters (P < .001 for all). While more advanced measurement techniques that take glenoid concavity into account are more accurate in determining the biomechanical relevance of glenoid bone loss, our study showed that the reliability of manually performed, more complex measurements was moderate.

Imaging in revision total knee arthroplasty: A novel 3D classification system for tibial bone defects.

The primary purpose of the study was to use pre-revision total knee arthroplasty (TKA) computer-tomography (CT)-images to analyse typical tibial bone defects and create a new schematic three-dimensional (3D)-classification system. The secondary purpose was to investigate the association between defect size and implant selection at the time of revision surgery. Eighty-four patients with preoperative CT-scans underwent revision of a primary TKA. CT-image segmentation with the 3D-Slicer Software was performed retrospectively, and a new three-dimensional classification system was used to grade tibial bone defects. The location of tibial bone defects was recorded for all cases. Volumetric 3D bone defect measurements were used to investigate the association between the bone defect volume, the indication for rTKA, and the use of modular revision components. The t-test, the Mann-Whitney-U test, and the Fisher's exact-test were used for group comparisons, and the Kruskal-Wallis test was used for multiple group comparisons. The most common anatomic regions for both contained and uncontained tibial bone defects were the anteromedial epiphysis (N = 50; mean epiphyseal-defect: 5.9 cm³) and metaphysis (N = 15; mean metaphyseal-defect: 9.6 cm³). A significant association was found between patients with preoperative metaphyseal defects (N = 22) and the use of tibial augments (N = 7) (p = 0.04). The use of cones/sleeves was associated with a significantly increased 3D-CT volume of the preoperative metaphyseal bone defects (p = 0.04). Patients with osteoporosis had significantly larger volumetric defects in the metaphysis (p = 0.01). Our results emphasise the importance of considering the three-dimensional nature of tibial defects in rTKA. The findings suggest that an understanding of the volume of the defect size through CT imaging can predict the need for augments and cones/sleeves and, especially in patients with osteoporosis can help the surgeon identify larger metaphyseal defects and ensure optimal metaphyseal fixation through appropriate implant selection. Level III, retrospective cohort study.

Melted grain boundaries in smectic A under imposed bend: role of the anisotropy

ABSTRACT The well-known de Gennes analogy between smectics and superconductors predicts two types of smectic A behaviour under imposed bend. In Type I smectics, the smectic order melts, expelling all of the bend in a bulk nematic region (3D ‘defect’). In Type II smectics, the order melts on 1D defects, edge dislocation lines, which form an Abrikosov-like lattice. Here, I discuss how the strong anisotropy of the smectic coherence lengths influence the smectic A behaviour under imposed bend distortion. I show analytically and numerically that, as proposed previously, a third type of behaviour is possible close to a second-order nematic–smectic A transition, with smectic order melting on the plane of the grain boundary (2D defects). This third kind of behaviour, Melted Grain Boundary (MGB), which has been previously reported experimentally in the smectic A material 9CB, is intermediate between the Type I and Type II behaviours and can be considered as Type ‘one-and-a-half’ smectic A. I define the domain of material parameters in which the planar MGB defect is energetically and topologically stable. I discuss also if similar planar defects may exist, or not, in other anisotropic materials, e.g. superconductors, chiral smectic A, cholesterics and twist-bend nematics.

Laser ultrasonic time-domain synthetic aperture focusing (SAFT) co-overlay software and hardware (COSH) computing system based on ZYNQ

The application of laser ultrasonic technology to defect detection is being widely studied. The Synthetic Aperture Focusing Techniques (SAFTs) is one of the imaging algorithms for detecting and imaging internal defects. SAFT based on Delay and Sum (DAS-SAFT) is known for high-quality imaging results. However, it has the disadvantages of the large calculation amount, which severely restricts its application. This work proposes a Co-Overlay Software and Hardware method (SAFT-COSH) based on Zynq, which uses parallelism and pipeline technology on FPGA and can efficiently accelerate DAS-SAFT operations. It can be found that the result obtained by the SAFT-COSH method is similar to the original method. Moreover, the time consumption of the SAFT-COSH system is 1/28 of that of the I9-13900KF CPU used for DAS-SAFT calculation. Finally, it was found by analyzing the time consumption of the DAS-SAFT procedure that the time consumption of SAFT-COSH system is short enough to support real-time 3D defect imaging. Characteristics of high efficiency and low cost in the SAFT-COSH method make it applicable in fields that require fast imaging using SAFT-based methods.

Defect segmentation with local embedding in industrial 3D point clouds based on transformer

Three-dimensional (3D) defect detection provides an effective method for improving industrial production efficiency. However, the 3D dataset is scarce, which is valuable for the industrial production field. This study proposes a new approach for detecting defect point clouds, which can provide an end-to-end 3D defect detection model. A self-attention mechanism is used to enrich the semantic relationships between local neighborhood features and global features based on the connection between them. Through adding multi-channel features, the rich structural features of the target point cloud are obtained, and the defect areas are accurately segmented to finally complete the 3D point cloud defect detection task. Furthermore, the multi-feature fusion in the model makes the segmented defect regions closer to the ground truth. Our method outperforms four state-of-the-art point cloud segmentation methods in terms of both segmentation region accuracy and defect detection point cloud accuracy. In the field of 3D defect detection, it provides an effective method to detect 3D information of industrial products.

Electrophysical properties, memristive and resistive switching of charged domain walls in lithium niobate

Charged domain walls (CDWs) in ferroelectric materials raise both fundamental and practical interest due to their electrophysical properties differing from bulk ones. On a microstructure level, CDWs in ferroelectrics are 2D defects separating regions with different spontaneous polarization vector directions. Screening of electric field of the CDW's bound ionic charges by mobile carriers leads to the formation of elongated narrow channels with an elevated conductivity in initially dielectric materials. Controlling the position and inclination angle of CDW relative to the spontaneous polarization direction, one can change its conductivity over a wide range thus providing good opportunities for developing memory devices, including neuromorphic systems. This review describes the state of art in the formation and application of CDWs in single crystal uniaxial ferroelectric lithium niobate (LiNbO3, LN), as resistive and memristive switching devices. The main CDWs formation methods in single crystal and thin-film LN have been described, and modern data have been presented on the electrophysical properties and electrical conductivity control methods of CDWs. Prospects of CDWs application in resistive and memristive switching memory devices have been discussed.

Skin Imaging: A Digital Twin for Geometric Deviations on Manufactured Surfaces

Closed-loop manufacturing is crucial in Industry 4.0, since it provides an online detection–correction cycle to optimize the production line by using the live data provided from the product being manufactured. By integrating the inspection system and manufacturing processes, the production line achieves a new level of accuracy and savings on costs. This is far more crucial than only inspecting the finished product as an accepted or rejected part. Modeling the actual surface of the workpiece in production, including the manufacturing errors, enables the potential to process the provided live data and give feedback to production planning. Recently introduced “skin imaging” methodology can generate 2D images as a comprehensive digital twin for geometric deviations on any scanned 3D surface including analytical geometries and sculptured surfaces. Skin-Image has been addressed as a novel methodology for continuous representation of unorganized discrete 3D points, by which the geometric deviation on the surface is shown using image intensity. Skin-Image can be readily used in online surface inspection for automatic and precise 3D defect segmentation and characterization. It also facilitates search-guided sampling strategies. This paper presents the implementation of skin imaging for primary engineering surfaces. The results, supported by several industrial case studies, show high efficiency of skin imaging in providing models of the real manufactured surfaces.

Non-destructive damage detection for steel pipe scaffolds using MFL-based 3D defect visualization

Non-destructive damage detection for steel pipe scaffolds using MFL-based 3D defect visualization

Crystal Growth of Defect-Free Single-Crystalline Fibers in Super-High Supersaturation Solution.

By controlling the supersaturation and choosing high-quality seeds, we successfully suppress the prismatic growth of the tetragonal potassium dihydrogen phosphate (KDP) SCFs, realize the rapid growth along the [001] direction, and obtain SCFs less than 10 μm in width with lengths of centimeters. The experimental results show that there exist critical supersaturation points, 22.40% and 41.41% at 25 °C, for initiating the growth of KDP SCF on its pyramidal and prismatic faces, respectively, which are quite different from those of the bulk crystals. We use the mechanism of 2D nucleation on smooth faces to explain the peculiar phenomena, assuming that there is no 2D or 3D defect on the surfaces of the seed fiber crystal. The assumption is supported by AFM observation of the surface micromorphology of the SCFs. Our solution growth technique developed can be used to grow ultrafine SCFs unable to be achieved by existing melt growth techniques.

Engineering Zinc-Organic Frameworks-Based Artificial Carbonic Anhydrase with Ultrafast Biomimetic Centers for Efficient Hydration Reactions.

Constructing effective and robust biocatalysts with carbonic anhydrase (CA)-mimetic activities offers an alternative and promising pathway for diverse CO2-related catalytic applications. However, there is very limited success has been achieved in controllably synthesizing CA-mimetic biocatalysts. Here, inspired by the 3D coordination environments of CAs, this study reports on the design of an ultrafast ZnN3-OH2 center via tuning the 3D coordination structures and mesoporous defects in a zinc-dipyrazolate framework to serve as new, efficient, and robust CA-mimetic biocatalysts (CABs) to catalyze the hydration reactions. Owing to the structural advantages and high similarity with the active center of natural CAs, the double-walled CAB with mesoporous defects displays superior CA-like reaction kinetics in p-NPA hydrolysis (V0=445.16nMs-1, Vmax=3.83µMs-1, turnover number: 5.97×10-3s-1), which surpasses the by-far-reported metal-organic frameworks-based biocatalysts. This work offers essential guidance in tuning 3D coordination environments in artificial enzymes and proposes a new strategy to create high-performance CA-mimetic biocatalysts for broad applications, such as CO2 hydration/capture, CO2 sensing, and abundant hydrolytic reactions.

Welding defects on new energy batteries based on 2D pre-processing and improved-region-growth method in the small field of view

The assessment of welding quality in battery shell production is a crucial aspect of battery production. Battery surface reconstruction can inspect the quality of the weld instead of relying on human inspection. This paper proposes a defect detection method in the small field of view based on 2D pre-processing and an improved-region-growth method. A novel approximation-based, high-precision, and simple operation method for line structure optical plane calibration under small field of view is presented, with a measurement error within 0.01 mm. By pre-processing the line scan 2D images, the defect location distribution is obtained, and then the images near the abnormal points are reconstructed in third dimensional (3D). The proposed method enables the extraction of the morphology, size, and other information of the defects with high accuracy. The results of various defect detection experiments demonstrate the stable and reliable performance of the system. The experimental results of defect recognition rate are over 95.3% for defects above 0.5 mm in diameter, and the inspection time is less than 1/2 of the direct 3D defect inspection. Overall, this method has proven to be highly effective in the assessment of welding quality in new energy battery production.

On protected defect correlators in 3d N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document}≥ 4 theories

We study and compute supersymmetric observables for line defects in 3d N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} ≥ 4 theories. Our setup is a novel supersymmetric configuration involving line operators and local operators living on a linked circle. The algebra of the local operators is described by a topological quantum mechanics. For operators belonging to conserved current multiplets, we propose an exact formula for their correlation functions based on a Ward identity for integrated correlators. Our formula gives a general recipe to compute the bremsstrahlung function for any 13\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\frac{1}{3} $$\\end{document}-BPS lines in N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 6 SCFTs. We apply our relation to the 12\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\frac{1}{2} $$\\end{document}-BPS Wilson loop in the ABJM model, showing the validity of previous computations. Furthermore, our construction allows us to explore higher points correlators. As an example, we compute the two-point function of the stress tensor multiplet correlators in ABJM theory in the presence of the Wilson line. We also present some perturbative checks of our formulae.

New experimental investigation of 3D defects propagation in mortar under tension loading

Among the construction materials, the mortar is the weakest component, especially against tensile loading and cracking. We propose in this paper an experimental study of the propagation of 3D internal defects in the mortar for different dosages and their effects on the tensile strength of the mortar. We start by deter- mining the tensile strength of a non-cracked specimen for five different dosages. After that, as our first contribution, we calculate the tensile strength and the critical Stress Intensity Factor SIF for the different dosages. Then, as our second contribution, we investigate the effect of the defects shape on the stability limit. Finally, we consolidate, through a comparative study, the obtained experimental results with the numerical ones.

Visualization of concrete internal defects based on unsupervised domain adaptation algorithm for transfer learning of experiment-simulation hybrid dataset of impact echo signals

Detecting concrete internal defects through deep learning analysis of impact echo signals faces two challenges: (1) the traditional signal processing method such as wavelet transform (WT) fails to reflect data-sensitive damage characteristics due to the uncertainty principle and (2) the limited labeled data acquired from real structures impedes network training. To address the first challenge, this paper proposes the WT-based synchrosqueezing transform (WT-SST) for the conversion of time-series data to the time-frequency spectrogram, which can provide effective features for the network in time and frequency domains simultaneously. To overcome the second challenge, numerical simulation data are supplemented for the augment of labeled data. To minimize the effect of data variance between experiments and simulations, this paper uses an unsupervised domain adaptation (DA) network for the transfer training of labeled simulation data (original domain) and unlabeled experimental data (target domain). The DA network extracts domain-invariant features by maximizing the domain recognition error and minimizing the probability distribution distance. The damage probability is calculated by the trained model to produce a 2D defect contour image of concrete specimens, and the three-dimensional visualization of internal defects by estimating the defect depth based on the defect area of contour image. Finally, the recognition precision, recall, F1-score, and accuracy of the model of unsupervised DA network trained by a hybrid dataset reaches 89.4%, 88.4%, 88.9%, and 94.7%, respectively.

Ferroic Phases in Two-Dimensional Materials.

Two-dimensional (2D) ferroics, namely ferroelectric, ferromagnetic, and ferroelastic materials, are attracting rising interest due to their fascinating physical properties and promising functional applications. A variety of 2D ferroic phases, as well as 2D multiferroics and the novel 2D ferrovalleytronics/ferrotoroidics, have been recently predicted by theory, even down to the single atomic layers. Meanwhile, some of them have already been experimentally verified. In addition to the intrinsic 2D ferroics, appropriate stacking, doping, and defects can also artificially regulate the ferroic phases of 2D materials. Correspondingly, ferroic ordering in 2D materials exhibits enormous potential for future high density memory devices, energy conversion devices, and sensing devices, among other applications. In this paper, the recent research progresses on 2D ferroic phases are comprehensively reviewed, with emphasis on chemistry and structural origin of the ferroic properties. In addition, the promising applications of the 2D ferroics for information storage, optoelectronics, and sensing are also briefly discussed. Finally, we envisioned a few possible pathways for the future 2D ferroics research and development. This comprehensive overview on the 2D ferroic phases can provide an atlas for this field and facilitate further exploration of the intriguing new materials and physical phenomena, which will generate tremendous impact on future functional materials and devices.

Intraoperative three-dimensional scanning of head and neck surgical defects: Enhanced communication and documentation of harvested supplemental margins.

We have demonstrated the effectiveness of 3D resection specimen scanning for communicating margin results. We now address the corresponding surgical defect by debuting 3D defect models, which allow for accurate annotations of harvested supplemental margins. Surgical defects were rendered into 3D models, which were annotated to document the precise location of harvested supplemental margins. 3D defect scans were also compared with routine 2D photography and were analyzed for quality, clarity, and the time required to complete the scan. Forty defects were scanned from procedures including segmental mandibulectomy, maxillectomy, and laryngopharyngectomy. Average duration of defect scan was 6 min, 45 s. In six of ten 2D photographs, the surgeon was unable to precisely annotate the extent of at least one supplemental margin. 3D defect scanning offers advantages in that this technique enables documentation of the precise location and breadth of supplemental margins harvested to address margins at-risk.

Novel 3D@2D/2D HHSS@BiOBr/Znln2S4 S-scheme photocatalyst for efficient adsorption-photocatalytic-photosensitization synergistic degradation of organics

Constructing high-performance multifunctional visible-light-driven photocatalysts to remediate organic contaminants from wastewater is of great challenge. Herein, we report a novel 3D@2D/2D hierarchical heterogeneous structured HHSS@BiOBr/Znln2S4 (HBZ) with abundant sulfur vacancies nanocomposite. This unique photocatalyst was fabricated by in situ growth of BiOBr nanosheets on the surface of hierarchical hollow silica spheres (HHSS), followed by epitaxial growth of Znln2S4 nanosheets for effective degradation of TCH and RhB. The optimal sample HBZ-6 (60 wt% Znln2S4) exhibited adsorption-photocatalytic synergistic degradation rate up to 92.36% after 30 min visible light irradiation, which was 2.31 times higher than that of bare BiOBr. It is benefit from the strong adsorption capacity of HHSS and effective carrier separation of 2D/2D S-scheme BiOBr/Znln2S4 in the HBZ-6 photocatalyst. Furthermore, it was surprising to discover that the coloured dye RhB was 100% photodegraded by HBZ-6 photocatalyst in 2 min under visible light, which is much faster than that of TCH with low visible light absorption. This excellent degradation efficiency is attributed to adsorption-photocatalytic-photosensitization synergistic between RhB and HBZ-6, leading to the ultrafast dye-sensitized-assisted electron transfer process. This work provides progressive tactics to design 3D@2D/2D defect heterogeneous structures which can greatly promote the future development of catalytic systems for wider application.

IMU-assisted robotic structured light sensing with featureless registration under uncertainties for pipeline inspection

Laser profilometry and structured light sensors are being increasingly deployed for pipeline inspection as they provide the operator with a precise 3D map that can enable visual detection and direct insight into the integrity of the pipe. The focus of the presented paper is the design of an integrated robotic structured light sensing system used to improve the performance of 3D defect reconstruction for pipeline inspection while accommodating the uncertainty seen in a real-world environment. Point cloud registration of the consecutive 3D frames is a key factor in building this 3D map; therefore, a comprehensive featureless registration approach is proposed first, which is proven more efficient than conventional feature-based registration algorithms. Wheel odometry from the developed robotic platform and inertial measurements are integrated into the registration algorithm to enhance the 3D reconstruction performance for sensor stabilization. An intensity-based threshold searching method is further applied to retrieve the reconstructed defect size. Lastly, the uncertainties of the structured light sensing are investigated for the total reconstruction uncertainty and estimated measurement uncertainty to be quantified in order to illustrate the measurement precision. The efficacy of the proposed algorithms are supported by experimental results of pipeline inspection.

On detailed deviation zone evaluation of scanned surfaces for automatic detection of defected regions

Online inspection and surface characterization including 3D defect detection of surfaces using 3D scanning and coordinate metrology data has crucial applications in today’s Industry 4.0. Although 3D vision-based metrology methods are superior to 2D in providing spatial information, its processing remains challenge. A novel automated Detailed Deviation Zone Evaluation method is proposed in this paper in which 3D unorganized PC is converted into 2D grayscale image such that the intensity variation of image is proportional to the surface topography. This developed image is addressed as “skin Image” of the scanned surface. The considered point clouds include only XYZ-coordinates. No prior knowledge of defects, and no training set is required. The methodology is fully implemented, and verified by inspecting point clouds of several workpieces with predefined defects. The experimental results show high efficiency of the developed methodology in defect detection and 3D-feature identification irrespective of shape and size.