Imaging Of Defects Research Articles

Amplified Detection of Threading Dislocations in n-Type 4H-SiC Epilayers Enabled by Time-Resolved Photoluminescence Mapping.

Threading dislocations (TDs) in epitaxial layers of silicon carbide (SiC) exert a negative impact on the device performance, thereby hampering the commercialization of SiC power devices. Therefore, inspection of TD defects is a crucial step in the fabrication of SiC wafers. In this work, we reported a time-resolved photoluminescence (PL) mapping technique for detecting TDs by extracting PL images at different delay times after pulse excitation along the lifetime decay curve. The results indicate a 2-fold enlargement of the TD PL quenching spot at a later delay time compared to the full delay time, enhancing the precision of TD defect imaging in 4H-SiC epitaxial layers. We postulate that our time-resolved PL mapping technique holds promise for the industrial evaluation of TD defects in SiC epitaxial layers.

Debonding defect imaging of thermal barrier coating with grating laser acoustic spectroscopy

Thermal barrier coatings (TBCs) are crucial for protecting high-temperature components in gas turbines and aeroengines. However, conventional non-destructive testing (NDT) methods, such as infrared thermography, face challenges in precisely detecting and quantifying debonding defects due to limitations in imaging contrast and sensitivity to surface states. In this work, a novel scheme for imaging debonding defects in TBCs using grating laser acoustic spectroscopy is proposed. The scheme, validated by numerical simulations and experimental results, is the first to introduce the mode conversion mechanism of Rayleigh and Lamb waves in the field of TBCs, achieving noncontact photoacoustic imaging of debonding defects for the first report. The all-optical laser ultrasonics system generates velocity maps with enhanced contrast and immunity to surface states, outperforming infrared thermography. Threshold segmentation precisely outlines defect contours, enabling precise quantification of defect size with an error below 5%. This work demonstrates a noncontact, precise, high-contrast imaging and surface-state-immune technique for evaluating the integrity and durability of TBCs, with potential applications in engineering.

Coherent Raman microscopy visualizes ongoing cellular senescence through amide I peak shifts originating from β sheets in disordered nucleolar proteins

Cellular senescence occurs through the accumulation of many kinds of stresses. Senescent cells in tissues also cause various age-related disorders. Therefore, detecting them without labeling is beneficial for medical research and developing diagnostic methods. However, existing biomarkers have limitations of requiring fixation and labeling, or their molecular backgrounds are uncertain. Coherent anti-Stokes Raman scattering (CARS) spectroscopic imaging is a novel option because it can assess and visualize molecular structures based on their molecular fingerprint. Here, we present a new label-free method to visualize cellular senescence using CARS imaging in nucleoli. We found the peak of the nucleolar amide I band shifted to a higher wavenumber in binuclear senescent cells, which reflects changes in the protein secondary structure from predominant α-helices to β-sheets originating from amyloid-like aggregates. Following this, we developed a procedure that can visualize the senescent cells by providing the ratios and subtractions of these two components. We also confirmed that the procedure can visualize nucleolar aggregates due to unfolded/misfolded proteins produced by proteasome inhibition. Finally, we found that this method can help visualize the nucleolar defects in naïve cells even before binucleation. Thus, our method is beneficial to evaluate ongoing cellular senescence through label-free imaging of nucleolar defects.

SAFT imaging for high-density polyethylene using quasi-static components of ultrasonic longitudinal waves

High-density polyethylene (HDPE) is extensively utilized across various industries, including nuclear power, primarily for its exceptional properties. However, there are challenges with traditional linear ultrasound imaging systems due to the significant thicknesses and the highly attenuative of HDPE. High-frequency carrier waves can offer better imaging resolution but also suffer higher acoustic attenuation, which limits the propagation distance of primary longitudinal waves (PLW) and makes it difficult to detect defects within thick HDPEs. On the other hand, using low-frequency PLW for defect detection presents challenges in resolution despite lower attenuation and longer propagation distances. This study proposes a defect imaging method for HDPEs by using quasi-static components (QSC) generated along with high-frequency fundamental wave propagation because of the nonlinear effect. The QSC has the advantage of low attenuation because its carrier frequency is zero, which can propagate a long distance in a high acoustic attention medium like HDPE. A nonlinear ultrasonic imaging approach combining the QSC and synthetic aperture focusing technique is proposed for defect imaging in HDPEs. Experiments on HDPEs with single and multiple defects are conducted to verify the performance of the proposed method. For comparison, the imaging results using traditional linear ultrasounds with high (2.5 MHz) and low (0.5 MHz) carrier frequencies are also provided. The results show the proposed method has better imaging performance over traditional linear ultrasound imaging methods for defect defections in high acoustic attention medium.

Design and implementation of a nondestructive testing system for magnetic field imaging based on machine learning

This study presents the design of a nondestructive testing (NDT) system for detecting metal defects using a magnetic field sensor array. The system integrates a hardware-software detection framework that includes parallel computation and processing cores, along with multiple anisotropic magnetoresistance (AMR) sensors. These AMR sensors capture subtle variations in the magnetic field, which serve as the foundation for defect identification. The system enables synchronized data acquisition from multiple AMR sensors, achieving multi-axis data fusion and parallel signal processing. Furthermore, the detection system gathers defect features to train an NDT system based on machine learning (ML). Subsequently, ML-generated defect imaging features are processed through an imaging framework, producing magnetic field imaging (MFI) for precise defect localization. The study tested six different metal samples with various defect sizes and types to validate the system. The results demonstrate the system’s ability to accurately detect and identify different defects, highlighting the high precision of magnetic field detection and the overall effectiveness of the proposed system for NDT.

Defect detection using integration of ultrasonic least-squares reverse time migration and generative adversarial network

ABSTRACT Accurate detection and characterisation of defects in high-density polyethylene (HDPE) materials are important for the safety of industrially critical structures. Ultrasonic non-destructive evaluation (UNDE) has proven to be a powerful tool for detecting and characterising defects in engineered materials. However, efficient and high-precision defect imaging in these highly attenuating materials remains a significant challenge for UNDE. Least-squares reverse time migration (LSRTM) offers the potential to reconstruct high-precision images of reflectivity. Yet, the conventional LSRTM iteratively updates the reflectivity model by minimising the data residuals, making it computationally expensive. In this paper, an efficient ultrasonic LSRTM algorithm within a deep learning framework is proposed. Building upon this, a generative adversarial network (GAN) is integrated to further enhance the reconstruction results by reducing artefacts in the images. Simulation and experimental results show that the proposed ultrasonic LSRTM-GAN can generate high-quality images, effectively enabling precise defect detection in HDPE.

High-efficiency surface defect detection based on laser ultrasonic state space embedding and compressive sensing

Abstract The laser nonlinear wave modulation spectroscopy(LNWMS) technique has gained considerable attention due to its high sensitivity in detecting small surface defects and its ultra-fast scanning speed. This paper proposes a novel method for synthesizing intact wavefield reference, significantly enhancing the accuracy of surface defect imaging. Moreover, considering the potential for parallel processing of the nonlinearity calculation of ultrasonic signals at scanning points, we incorporate compressive sensing technology to accelerate this process. This innovative approach reduces the computational load to 10% of the original, thereby substantially increasing the imaging speed. The paper validates the method’s superior accuracy and efficiency in defect detection through conducting experiments using a high-speed laser ultrasonic scanning system on aluminum plates and turbine blade, and by comparing with local wavenumber estimation, demonstrating the promising potential of this technology for surface defect analysis.

Near- and remote-field pulsed eddy current integrated testing for enhancement in imaging of buried flaws in layered conductive structures

ABSTRACT In a bid to simultaneously exploit the advantages of Pulsed Eddy Current testing (PEC) and Pulsed Remote-field Eddy Current Testing (PRFEC) for evaluation of buried defects in layered conductors, in this paper the Near- and Remote-field Pulsed Eddy Current integrated testing (NRPEC) alongside an axi-symmetric probe has been proposed. Simulations are conducted to reveal the field characteristics underlying the proposed method and analyse the signal response to hidden flaws. In parallel, an NRPEC system has been built up. Based on the images of near-field and remote-field signal features, a fusion algorithm is proposed to fuse the signal features of near-field and remote-field signals for defect testing with the enhanced signal-to-noise ratio. Results from simulations and experiments indicate that based on the fused signal feature, high-accuracy imaging of hidden defects in a double-layer conductor can be achieved via NRPEC with the improved signal-to-noise ratio.

A fast laser ultrasonic SAFT method with sparse scanning data and F-K based interpolation

ABSTRACT Laser ultrasonic SAFT can be applied for noncontact testing and imaging of defects in structures. However, due to the large demand for signal data by laser scanning, the time consumption of this method would be relatively long. To address this problem, this paper proposes a fast LU-SAFT method with sparse scanning data and F-K based interpolation. It aims to reduce the inspection time but without decreasing the imaging resolution. First, the method determines the minimum number of scanning sparse points using simulation. Then the F-K interpolation method is utilised to recover the full-field unscanned point signal from the sparse scan data. Finally, the reconstructed signal is used for SAFT image reconstruction of the defect. The experimental results show that, for the same scanning area, the proposed method in this paper reduces the number of scanning points by 87.5% and shortens the scanning time by 86.0% compared to conventional LU-SAFT point-by-point scanning. Additionally, the signal-to-noise ratio of the defective SAFT imaging decreases by only about 7.9%.

Cu/Gd co-doped hydroxyapatite/poly lactic-co-glycolic acid composites enhance MRI imaging and bone defect regeneration.

Background: The hydroxyapatite (HA)/poly(lactide-co-glycolide) acid (PLGA) composite material is a widely used orthopedic implant due to its excellent biocompatibility and plasticity. Recent advancements in cation doping have expanded its potential biological applications. However, conventional HA/PLGA composites are not visible under X-rays post-implantation and have limited osteogenic induction capabilities. Copper (Cu) is known to regulate osteoblast proliferation and differentiation, while gadolinium (Gd) can significantly enhance the magnetic resonance imaging (MRI) capabilities of materials. Methods: This study aimed to investigate whether incorporating Cu and Gd into an HA/PLGA composite could enhance the osteogenic properties, in vivo bone defect repair, and MRI characteristics. We prepared a Cu/Gd@HA/PLGA composite and assessed its performance. Results: Material characterization confirmed that Cu/Gd@HA retained the morphology and crystal structure of HA. The Cu/Gd@HA/PLGA composite exhibited excellent nuclear magnetic imaging capabilities, porosity, and hydrophilicity, which are conducive to cell adhesion and implant detection. In vitro experiments demonstrated that the Cu/Gd@HA/PLGA composite enhanced the proliferation, differentiation, and adhesion of MC3T3-E1 cells, and upregulated COL-1 and BMP-2 expression at both gene and protein levels. In vivo studies showed that the Cu/Gd@HA/PLGA composite maintained strong T1-weighted MRI signals and significantly improved the bone defect healing rate in rats. Conclusion: These findings indicate that the Cu/Gd@HA/PLGA composites significantly enhance T1-weighted MRI capabilities, promote osteoblast proliferation and differentiation in vitro, and accelerate bone defect healing in vivo.

Far-focused pixel-based imaging of internal defects in multi-layered media based on attenuation compensation and circular coherence factor

ABSTRACT The multi-layered media composed of layers with different sound velocities exhibit anisotropy, strong attenuation, and interface reflection in terms of sound propagation, posing challenges for conventional ultrasound imaging methods, especially in detecting deep-seated and near-interface defects. In this study, an improved far-focused pixel-based (FPB) imaging method for detecting internal defects in multi-layered media is proposed. First, the time delay calculation in the FPB method is corrected using the shortest path searching method to determine the acoustic time-of-flight. Then, phase information is extracted from the echo signal to construct a circular coherence factor (CCF) that dynamically weights the time-corrected FPB images, addressing the issue of ineffective detection of near-interface defects caused by interface reflection. Finally, considering the sound attenuation in multi-layered media, the directivity coefficient, transmission coefficient, and divergence coefficient are determined through theoretical derivation to compensate for the echo amplitude. Experimental results demonstrate that the improved FPB method significantly enhances the reflection echo from deep-seated defects, reduces the maximum relative localisation error to 0.9%, and the quantisation error to 6.4%. The proposed method also greatly improves the lateral resolution and signal-to-noise ratio (SNR) of internal defect imaging compared to the total focusing method (TFM) and traditional FPB method.

Damage analysis of solid propellants with default defects based on macro-microscopic approach

Solid Rocket Motors (SRMs) rely on solid propellants, directly impacting the energy capacity of launch vehicles. High energy density material (HEDM) propellant exhibits superior energy density owing to the incorporation of a substantial quantity of energetic particles. However, the elevated particle fill ratio makes the formation of pores more prevalent during the manufacturing process of propellants. These pores, representing default defects, are indispensable factors in the investigation of mechanical properties of propellants. This study investigated default defects effects on HEDM propellants, analyzing both microscopic and macroscopic perspectives. Utilizing micro-CT imaging, the microstructure and default defects were characterized. Subsequently, using the cohesive zone model (CZM), microscopic damage evolution was depicted with the representative volume element (RVE) model, allowing in-depth analysis. Furthermore, a damage constitutive model, based on microscopic damage, was developed, with its softening function calibrated using microscopic damage evolution characteristics. Implemented into ABAQUS via user-defined material subroutine (UMAT), this model enabled the prediction of the mechanical response of HEDM propellants with different defects. The results demonstrate that the developed model accurately predicts the mechanical responses of HEDM propellants with different defects, showcasing the potential of macro-microscopic approaches in analyzing propellants with default defects.

Mid-spatial frequency error restraint based on variable optimal angle-step trajectory strategy for the removal attenuation effect of magnetorheological finishing

In the field of ultra-precision manufacturing, such as lithography lenses, achieving nanometer-level errors across the entire frequency range is crucial. Magnetorheological finishing (MRF) technology, a high-precision processing method with high efficiency and low subsurface damage, often introduces mid-spatial frequency (MSF) error due to the removal attenuation effect and regular polishing trajectory in the long continuous polishing process. It causes various imaging and light transmission defects that limit the performance of precision optical instruments. The attenuation of material removal capacity of MRF is characterized by the attenuation of the tool influence function, which is obtained by an equal time interval point removal experiment. The variable optimal angle-step trajectory strategy is proposed to mitigate the removal attenuation effect of MRF and suppress MSF error. To validate the effectiveness and practicability of the proposed method, a uniform polishing experiment is performed on fused silica components. The experimental results show that the 90° grating trajectory introduces significant MSF error on surface shape with PV = 0.008 λ, and the variable optimal angle-step trajectory strategy does not introduce MSF error, which confirms the variable optimal angle-step trajectory strategy effectively eliminates the removal attenuation effect of MRF and suppresses MSF error. The study presents a general approach for ultra-precision optical processing and improves the manufacturing accuracy of optical components.

Non-contact defect imaging of carbon fiber composites using laser excited acoustic shearography

The performance of carbon fiber reinforced polymer (CFRP) composites is significantly affected by the presence of subsurface defects, which originate from manufacturing processes or during operations. Although many non-destructive testing (NDT) methods have been employed to inspect CFRP materials and structures, the existing techniques are often time-consuming and sometimes require contact measurement. This paper presents a non-contact and rapid inspection method utilizing laser-excited acoustic shearography to detect subsurface defects in CFRP composites. In this method, a pulsed nanosecond laser is used to generate ultrasonic waves through thermoacoustic effect, and a shearography sensor is used to image the full-field wave-defect interactions. It is found that the proposed method can efficiently image various subsurface defect sizes in a non-contact way. The identified defects were validated through comparison with X-ray computed tomography (XCT).

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Abstract High-resolution ultrasonic imaging for defects in anisotropic multilayer carbon fiber reinforced polymers (CFRPs) is challenging because of the severe ultrasonic attenuation and the low signal-to-noise ratio (SNR) of echoes. The existing delay-multiply-and-sum (DMAS) beamforming outperforms delay-and-sum (DAS) beamforming in resolution, but with high computational complexity and energy loss. This paper presents a novel delay-sum-and-square (DSAS) beamforming algorithm. It takes full advantage of spatial coherence of captured data in the receiving and transmitting apertures. The non-coherent components caused by background noise are suppressed during the imaging. The back-wall reflection method (BRM) is used to correct the direction-dependent velocity. Full-matrix data is experimentally captured and processed on three different CFRP samples. Compared with DAS and DMAS, DSAS has a significant improvement in resolution, SNR and contrast. It demonstrates excellent defect characterization and noise suppression capability with only 17.4% computation time of DMAS.

Multi-time Lamb waves space wavenumber imaging method based on ultrasonic-guided wavefield

Ultrasonic-guided waves full wavefield scanning technology can realize non-destructive testing with non-contact. The damage detection method based on ultrasonic-guided waves’ full wavefield data is widely used in thin-walled plate structures. The defect imaging method based on full wavefield data faces the challenge of simultaneously obtaining the defect contour and thickness direction information. Based on the ultrasonic-guided waves full wavefield scanning detection technology, this paper proposes a multi-time Lamb waves space wavenumber imaging method. In this method, the analytic signal of Lamb wavefield at each moment is constructed by Hilbert transform, and the phase unwrapping is carried out by amplitude sorting and multi-clustering method. Then the wavenumber information is obtained by calculating the phase gradient. The wavenumber at different times of each measurement point is arranged in descending order, and the median wavenumber is extracted as the wavenumber at each measurement point. Based on the dispersion relationship of the tested specimen, the quantitative detection of the plate thickness in the detection area is realized. This method is first applied to the simulation model. Then it is applied to the defect imaging and quantitative detection of aluminum plates with rectangular groove defects and carbon fiber reinforced plastics (CFRP) plates with delamination defects. In simulation and experiment, the local wavenumber imaging method, the frequency domain instantaneous wavenumber imaging method, and the multi-time Lamb waves space wavenumber imaging method are used for defect imaging and quantification. The imaging results are compared and analyzed. The result shows that the multi-time Lamb waves space wavenumber imaging method can restore the morphology of groove defects in aluminum plates and delamination defects in CFRP plates, and accurately estimate the depth of groove defects and the location of delamination defects.

Towards Atomic Imaging and Spectroscopy of Er defects in ZnO

Towards Atomic Imaging and Spectroscopy of Er defects in ZnO

Defect Imaging of Nickel-Based Superalloy in the SEM Utilizing Tilt-Free EBSD

Defect Imaging of Nickel-Based Superalloy in the SEM Utilizing Tilt-Free EBSD

Effect of light source wavelength on surface defect imaging in deep-water concrete dams

This study explores the relationship between surface defect imaging in deep-water concrete dams and the wavelength of the light source, aiming to improve concrete defect image quality by varying the wavelength. The underwater optical imaging model of concrete dam surfaces was developed by applying the principle of object reflection and the underwater optical propagation model. This model reflects the effect of different light wavelengths on underwater concrete defect imaging. Through a self-designed underwater optical darkroom test platform, defect image acquisition tests were conducted under various color light conditions. The results reveal the significant influence of light source wavelength on images captured in both air and water. Furthermore, under the same initial illuminance, blue light significantly enhanced the average gray value, sharpness, contrast, and the number of feature points in underwater defect images, exhibiting increments of 2.97 times, 0.48 times, 2.70 times, and 2.95 times, respectively, compared to white light. These findings can serve as a reference for the selection of color-light for the non-destructive testing of surface defects in actual underwater concrete dams.

Imaging method of surface defect using leaky Rayleigh wave with ultrasonic phased array

ABSTRACT Leaky Rayleigh wave testing has the advantages of non-contact, high sensitivity, and good beam directivity. However, current leaky Rayleigh wave testing mostly uses monolithic transducers and is seriously affected by acoustic wave attenuation and diffusion, resulting in poor image quality, limited detection range and low imaging efficiency. In this paper, a novel leaky Rayleigh wave testing method using an ultrasonic phased array is developed, and the total focusing method (TFM) is used to achieve high-quality imaging of defects. To improve imaging efficiency, the root-mean-square velocity (RMSV) model is utilised to rapidly acquire an approximate analytical solution for the time of flight of the acoustic wave. To obtain more accurate defect images further, the amplitude of the total focusing imaging signal is calibrated. The experimental results demonstrate that the proposed method achieves a 48% improvement in the imaging accuracy of a 1 mm hole, compared to the traditional Synthetic Aperture Focusing Technique (SAFT) imaging method. The proposed method achieves an 92% reduction in imaging time compared to the conventional TFM. The proposed method provides a new non-contact approach for high-accuracy and high-efficiency defect imaging using leaky Rayleigh wave.