Many Kinds Of Defects Research Articles

Deep Level Transient Fourier Spectroscopy Investigation of Electron Traps on AlGaN/GaN-on-Si Power Diodes

Many kinds of defects are present in AlGaN/GaN-on-Si based power electronics devices. Their identification is the first step to understand and improve device performance. Electron traps are investigated in AlGaN/GaN-on-Si power diodes using deep level transient Fourier spectroscopy (DLTFS) at different bias conditions for two Schottky contact’s etching recipes. This study reveals seven different traps corresponding to point defects. Their energy level ET ranged from 0.4 eV to 0.57 eV below the conduction band. Among them, two new traps are reported and are etching-related: D3 (ET = 0.47–0.48 eV; σ ≈ 10−15 cm2) and D7 (ET = 0.57 eV; σ = 4.45 × 10−12 cm2). The possible origin of the other traps are discussed with respect to the GaN literature. They are proposed to be related to carbon and nitrogen vacancies or to carbon, such as CN-CGa. Some others are likely due to crystal surface recombination, native defects or a related complex, or to the nitrogen antisite: NGa.

Enhancing the thermal stability of n-type Mg3+xSb1.5Bi0.49Te0.01 by defect manipulation

N-type Mg3+x(Sb, Bi)2-based thermoelectrics have quickly attracted considerable interest because of their excellent thermoelectric performance over a wide temperature range. Most studies on these compounds have thus far focused on improving their thermoelectric performance, with little consideration given to the equally essential issue of thermal stability. Mg3+x(Sb, Bi)2 is highly disordered due to having many kinds of defects, resulting in features like low thermal conductivity. However, the lattice distortion introduced by defects and the evolution of non-equilibrium defects both may impair the thermal stability of these thermoelectric materials. Additionally, incorporating Mg as the most prominent element in Mg3+x(Sb, Bi)2 has a significant impact on the compound’s initial defect concentration and its stability performance at high temperatures due to Mg loss resulting from the element’s high vapor pressure. Here we used in situ stability testing to reveal the evolution of intrinsic defects in n-type Mg3+xSb1.5Bi0.49Te0.01. A low-temperature annealing treatment was employed to improve stability by regulating non-equilibrium defects. Results from both experiments and theoretical calculations show that filling vacancy defects with transition metals rather than with additional excess Mg is effective in improving thermal stability due to the resulting enhanced chemical bonding and increased defect formation energy. This study has important implications for understanding and overcoming instability in other similar thermoelectric materials.

Capacitance Temperature Dependence Analysis of GaN-on-Si Power Transistors

Many kinds of defects are present in the different layers of GaN-on-Si epitaxy. Their study is very important, especially because they play a significant role on the device characteristics. This paper investigates the cause of the temperature dependence of the output and Miller capacitance at three temperatures: 25 °C, 75 °C and 150 °C of GaN-on-Si power transistors. In particular, this study focuses on the temperature dependence of the depletion voltage seen in these characteristics due to the progressive depletion of the two-dimensional electron gas (2DEG) under the device field plates. First, variations of the epitaxial growth are studied, showing that the intrinsic carbon concentration does not play a significant role. Secondly, the deep acceptor trap origin of the temperature dependence is analyzed with a TCAD simulation study. Thirdly, by adjusting TCAD parameters and binding them with experimental concentrations to fit experimental data, trap properties were obtained. The comparison of these properties with the acceptor traps in the literature suggests that the origin is a gallium vacancy tied to oxygen atom(s) on the N site.

Printed Surface Defect Detection Model Based on Positive Samples

For a long time, the detection and extraction of printed surface defects has been a hot issue in the print industry. Nowadays, defect detection of a large number of products still relies on traditional image processing algorithms such as scale invariant feature transform (SIFT) and oriented fast and rotated brief (ORB), and researchers need to design algorithms for specific products. At present, a large number of defect detection algorithms based on object detection have been applied but need lots of labeling samples with defects. Besides, there are many kinds of defects in printed surface, so it is difficult to enumerate all defects. Most defect detection based on unsupervised learning of positive samples use generative adversarial networks (GAN) and variational auto-encoders (VAE) algorithms, but these methods are not effective for complex printed surface. Aiming at these problems, In this paper, an unsupervised defect detection and extraction algorithm for printed surface based on positive samples in the complex printed surface is proposed innovatively. We propose a kind of defect detection and extraction network based on image matching network. This network is divided into the full convolution network of feature points extraction, and the graph attention network using self attention and cross attention. Though the key points extraction network, we can get robustness key points in the complex printed images, and the graph network can solve the problem of the deviation because of different camera positions and the influence of defect in the different production lines. Just one positive sample image is needed as the benchmark to detect the defects. The algorithm in this paper has been proved in “The First ZhengTu Cup on Campus Machine Vision AI Competition” and got excellent results in the finals. We are working with the company to apply it in production.

Real-time implementation of fabric defect detection based on variational automatic encoder with structure similarity

Automatic detection of fabric defects based on machine vision is an important topic in the quality control of cotton textile factories. There are many kinds of defects in fabric production, it is very difficult to classify the defects automatically. In recent years, deep learning image processing technology based on a convolutional neural network (CNN) can train and extract features of the target image automatically. Since a large number of defect samples cannot be collected completely, we compared unsupervised learning algorithms based on CNN, including auto encoder (AE), variational automatic encoder (VAE), and generative adversarial networks (GAN). Because of the large amount of calculation and the difficulty of training in GAN, we chose AE and VAE codec networks and then introduced mean structural similarity (MSSIM) as network training loss function to improve the performance that only used $${L}_{p}$$ -distance loss function for image brightness comparison. After training finished, the authors used the trained model to obtain target defects from SSIM residual maps between input and reconstruct images. According to the evaluation results, we finally implemented a fabric defect detection system based on VAE on Jetson TX2 from Nvidia Corporation, USA. The optimized algorithm can meet the real-time requirements of the project and realize its popularization and application.

Measurement of the leakage flux in the vicinity of a transformer core

PurposeThis study presents a new method for the detection of faults in large transformer cores. It is based on the analysis of leakage flux components in the vicinity of the sheet stack. The purpose of this study is to provide a nondestructive analysis tool for transformer cores during the assembly process to detect accidental defects such as inter-laminar short circuits.Design/methodology/approachThe different components of the leakage flux allow localization of the fault in the stack and also permit to assess its severity. Out of the many kinds of defects which may appear in a transformer core, this method only detects those which actually cause an increase in the transformer’s global iron losses, which are thus the most detrimental.FindingsThe proposed method allows a more efficient control of the quality of the cores during their manufacturing process. Until now, it was only possible to know the quality of the core when the transformer was fully assembled.Research limitations/implicationsThe accuracy of the method depends on the size of the defect and may request many measurements to give usable information.Practical implicationsControlling iron losses in a core during its construction avoids heavy dismantling operations, both financially and temporally.Originality/valueThis method can help transformer manufacturers optimize their building process. In addition, the method remains effective regardless of the size of the core considered.

Detection of morphology defects in pipeline based on 3D active stereo omnidirectional vision sensor

There are many kinds of defects in pipes, which are difficult to detect with a low degree of automation. In this work, a novel omnidirectional vision inspection system for detection of the morphology defects is presented. An active stereo omnidirectional vision sensor is designed to obtain the texture and depth information of the inner wall of the pipeline in real time. The camera motion is estimated and the space location information of the laser points are calculated accordingly. Then, the faster region proposal convolutional neural network (Faster R-CNN) is applied to train a detection network on their image database of pipe defects. Experimental results demonstrate that system can measure and reconstruct the 3D space of pipe with high quality and the retrained Faster R-CNN achieves fine detection results in terms of both speed and accuracy.

수정된 Watershed 알고리즘 이용한 빠른 Mura 결함 검출

Many kinds of defects show up during the process of manufacturing display panels. However, mura defects are the most difficult to detect using the conventional image processing algorithms. Many factors cause mura defects to appear in display panels. When images are taken using cameras, mura defects normally show up as relatively dark or bright regions with no definite shape, no clear contours, and very low contrast against their surrounding background. When an imaged mura defect is relatively dark compared to its background, it can be considered a water catchment basin when the whole image is visualized in three dimensions (i.e., is topographically interpreted), and such catchment basins can be detected by watershed algorithms. In this paper, for the accurate segmentation of the mura region, the flooding step of the original watershed algorithm is carefully redesigned to detect the mura defect that exists both inside and at the boundary of an image. The depth of the catchment basins is recorded iteratively and then is used to segment the mura defects. The just noticeable difference (JND) technique is used to quantify the level of the mura defects. It is shown, by extensive experiments, that the proposed algorithm performs well, detecting very low-contrast mura defects, and quickly detects defects located anywhere in the image.

Frustrated crystallization of a monolayer of magnetized beads under geometrical confinement.

We present a systematic experimental study of the confinement effect on the crystallization of a monolayer of magnetized beads. The particles are millimeter-scale grains interacting through the short range magnetic dipole-dipole potential induced by an external magnetic field. The grains are confined by repulsing walls and are homogeneously distributed inside the cell. A two-dimensional (2d) Brownian motion is induced by horizontal mechanical vibrations. Therefore, the balance between magnetic interaction and agitation allows investigating 2d phases through direct visualization. The effect of both confinement size and shape on the grains' organization in the low-energy state has been investigated. Concerning the confinement shape, triangular, square, pentagonal, hexagonal, heptagonal, and circular geometries have been considered. The grain organization was analyzed after a slow cooling process. Through the measurement of the averaged bond order parameter for the different confinement geometries, it has been shown that cell geometry strongly affects the ordering of the system. Moreover, many kinds of defects, whose observation rate is linked to the geometry, have been observed: disclinations, dislocations, defects chain, and also more exotic defects such as a rosette. Finally, the influence of confinement size has been investigated and we point out that no finite-size effect occurs for a hexagonal cell, but the finite-size effect changes from one geometry to another.

Synthesis and characterization of IIa-type S-doped diamond in FeNi catalyst under high pressure and high temperature conditions

In this work, service through nitrogen getter we have successfully synthesized sulfur(S) doped IIa-type diamond single crystals at 1400°C and 5.5GPa in FeNi-C system. We found that the synthetic diamond are mainly composited of the {111} faces because of the addition of S in the synthesis system. In addition, the color of our produced diamond changed from white to light brown and the shape of diamond changed from Cub-Octahedron to Octahedron with increase of S addition in the FeNi-C system. Furthermore, we notice that many kinds of defects, such as stratiform defects, craters and inverted pyramid defects appeared on the surfaces of diamonds induced by the additive of S. The FTIR results show that the obtained diamond crystals are IIa-type diamonds, containing less than 1ppm nitrogen. XPS measurement indicates that S was successfully incorporated into our produced diamond lattice in the SC and CSO forms. Raman spectra reveal that the as-growth S-doped IIa-type diamond single crystals possess a high-quality sp3 structure. Photoluminescence (PL) spectra demonstrate that nitrogen-vacancy is formed during diamond growth. Our work also helpful for understanding the formation of nature diamond.

Correlation between process, microstructure and properties in high pressure die casting aluminium-silicon alloys

Nowadays automotive industry and, in general, transportation one increasingly needs light components in order to reduce total weights and therefore limit harmful emissions and fuel consumption. The die casting process, on one hand, is a versatile and highly productive process but, on the other, the elevated amount of defects found in the castings sometimes compromises the characteristics of the final product. This paper presents the results of the analyses carried out using a Reference Die, referred to as horse shoe-shaped die, specifically designed to generate as many kinds of defects as possible, at different levels of severity. A Design of Experiments method has been applied for analysing the influence of the main process parameters on the casting quality and an innovative sensor network installed on the machine allowed a continuous control of the process itself. Visual inspection, X-ray investigations and micrograph analyses have been carried out in order to assess the casting quality. Correlations between process parameters and casting quality have been deduced analysing the data collected through the equipment installed on the die casting machine: in-cavity sensor network, plunger speed and displacement sensors. Results show the effectiveness of the horse shoe-shaped casting in highlighting the correlations between process and quality and the strong influence of second phase plunger velocity, temperature and pressure on defect formation.

Analysis of mechanism of backflow defect of the aluminum wheel flow forming

Aluminum wheel flow forming is a combined technique of spinning and flow forming, which produces parts with complex axisymmetric geometries and reduces wall thickness. During the process, among many kinds of defects generated, a newly defined defect phenomenon so called backflow has appeared. It is a tendency of metal bulging in the radial direction on the wall as the roller passes through the deformation zone. In this paper, the mechanism of the backflow is studied as well as the process conditions to prevent backflow by establishing a numerical analysis procedure using SHAPE-RR FEM program. Result of FE analysis of the aluminum wheel flow forming is verified with flow line of experimental results. It was shown that bulging due to the backflow had been successfully simulated. It is concluded that the load of headstock is a major influence on the backflow.

Fabrication and simulation of glass micromachining using CO2 laser processing with PDMS protection

Traditional glass micromachining using laser processing in air would produce many kinds of defects, such as bulges, debris, micro-cracks and scorches. In this article, a poly-dimethylsiloxane (PDMS) protection processing has been presented to reduce the temperature gradient and heat-affected zone (HAZ) to achieve crack-free Pyrex glass machining. A good quality of etched surface which is a clear and much-reduced bulge without crack and scorch is achieved using CO2 laser micromachining at 150 μm thick PDMS protection layer and the laser powers of 10–15 W and scanning speeds of 228–342 mm/s for five passes. The PDMS cover layer benefits feature size and bulge height reduction. The alpha-step measured profile shows that the much reduced bulge height around the rims of channel was about 1.2 μm at 150 μm thick PDMS about 13 times smaller than that in air. The ANSYS software was used to analyze the temperature distribution and thermal stress field of glass micromachining in air without and with PDMS cover layer. The smaller temperature gradient observed in PDMS protection processing has the smaller HAZ and diminishes the crack formation during the laser processing.

Experimental observation of defect-induced intrinsic ferromagnetism in III-V nitrides: The case of BN

We report the synthesis and magnetic properties characterizations of defective BN obtained from a modified solid-state reaction. X-ray diffraction analysis indicated the presence of two crystalline phases of BN in products. No magnetic impurities, such as Fe, Co, Mn, and Ni were detected by chemical analysis. Transmission electron microscopy observation and photoluminescence spectrum measurement showed the existence of large-scale defects in BN lattices. Magnetic measurement undoubtedly demonstrated the typical ferromagnetic order was established in undoped BN. We consider that the many kinds of defects should be responsible for the long-range magnetic order in the $sp$ material of defective BN.

Defects Detection of Billet Surface Using Optimized Gabor Filters

This paper deals with a defects detection algorithm for billet surface. To get good performance, detection algorithm has to solve several difficult problems such as shape of a billet, many kinds of defects, much scale. Especially, the scale, that is a metallic oxide on steel surface, makes worse severely the performance of detection. To solve above problems, this paper presents a new effective defects detection algorithm based on Gabor filters optimized by Genetic Algorithm. The experimental results conducted on real billet surface images and demonstrate the good performance of the proposed algorithm.

High Gd Concentration GaGdN Grown at Low Temperatures

GaGdN layers were grown at temperatures below 300°C by radio-frequency plasma-assisted molecular beam epitaxy on sapphire substrates. GaGdN samples with high Gd concentration as high as 12.5% were obtained by lowering the growth temperature. X-ray diffraction results showed no obvious secondary phase, which means that the phase separation can be suppressed by the growth at low temperatures. All samples, including those grown at room temperature, showed ferromagnetic characteristics. Photoluminescence emission was observed, though spectra exhibit broad and sharp luminescence bands related to many kinds of defects. It is suggested that electrons coming from defects, especially, nitrogen vacancy, stabilize ferromagnetism, and that the carrier-induced ferromagnetism occurs in the low-temperature-growth GaGdN.

プラズマ溶射法による遮熱コーティングシステムのセラミックトップコート/金属ボンドコート界面のナノキャラクタリゼーション

Characterization at the ceramic top-coat/metallic bond-coat interfacial region was conducted for several kinds of the plasma sprayed thermal barrier coating (TBC) systems by means of a transmission electron microscope (TEM), an electron probe micro-analysis (EPMA) and so forth, in order to find out the optimum compositional and structural conditions of the coating components together with the optimum coating processing condition for designing the advanced TBC systems. Specimens with different coating features were prepared systematically by using different coating parameters such as the top-coat spraying conditions and reheat-treatment conditions. Especially, the reheat-treatment was applied to the TBC specimen with different temperature either in air or in inert argon (Ar) gas atmosphere. It was found that in the case of reheat-treatment in air the thermally grown oxide (TGO) was developed at the interface as multiple oxide layers; one is Al2O3 layer developed discontinuously at directly above the bond-coat and another is the mixed oxides layer consisting of the Al, Cr, Co, Ni oxide particles on the Al2O3 layer. Such a TGO layer was heterogeneous and imperfect layer with containing many kinds of defects. On the contrary, the TGO layer formed by the reheat-treatment in Ar was composed dominantly of the continuous and fairly purified Al2O3 layer with large grain size and homogeneous layer thickness. The growth mechanism and influencing factors for TGO were discussed in some detail on the basis of the nano-characterization and quantitative evaluation of TGO.

Effects of substrate temperature on nanostructure and band structure of sputtered Co3O4 thin films

Effects of substrate temperature (Ts) on nanostructure and band structure of sputtered Co3O4 thin films were investigated. The lattice constant of Co3O4 sputtered at room temperature was longer than the reported bulk Co3O4 value. It decreased with increasing Ts and approached the reported value. Average grain size of the film formed at Ts=918 K was 13.6 nm which was twice as big as that of the film obtained at Ts=293 K. Intensities of optical absorption peaks increased with increasing Ts. Band gaps corresponding to the charge transfer from Co2+(π*e) to Co2+(π*t2)(0.8 eV), from Co3+(π2t2) to Co2+(σ*t2)(1.3 eV), and from O2−(π*Γ) to Co2+(σ*t2) (2.1 eV) increased as a function of Ts. Detailed analysis of the optical absorption spectra in the infrared region indicated that there were many kinds of defects in the Co3O4 thin film formed at Ts=293 K and there were fewer defects in the film formed at Ts=918 K. The defects, low density, and increasing interface area at intergrains of nanoparticles caused a lowering of Eg at lower substrate temperature.

Nano-Characterization of Ceramic Top-Coat/Metallic Bond-Coat Interface for Thermal Barrier Coating Systems by Plasma Spraying

Characterization at the ceramic top-coat/metallic bond-coat interfacial region was conducted for several kinds of the plasma sprayed thermal barrier coating (TBC) systems by means of a transmission electron microscope (TEM), an electron probe micro-analysis (EPMA) and so forth, in order to find out the optimum compositional and structural conditions of the coating components together with the optimum coating processing condition for designing the advanced TBC systems. Specimens with different coating features were prepared systematically by using different coating parameters such as the top-coat spraying conditions and reheat-treatment conditions. Especially, the reheat-treatment was applied to the TBC specimen with different temperature either in air or in inert argon (Ar) gas atmosphere. It was found that in the case of reheat-treatment in air the thermally grown oxide (TGO) was developed at the interface as multiple oxide layers; one is Al2O3 layer developed discontinuously at directly above the bond-coat and another is the mixed oxides layer consisting of the Al, Cr, Co, Ni oxide particles on the Al2O3 layer. Such a TGO layer was heterogeneous and imperfect layer with containing many kinds of defects. On the contrary, the TGO layer formed by the reheat-treatment in Ar was composed dominantly of the continuous and fairly purified Al2O3 layer with large grain size and homogeneous layer thickness. The growth mechanism and influencing factors for TGO were discussed in some detail on the basis of the nano-characterization and quantitative evaluation of TGO.

First Principles Calculations of Formation Energies and Electronic Structures of Defects in Oxygen-Deficient LiMn2 O 4

The formation energies of many kinds of defects for oxygen-deficient including both oxygen-vacancy types and metal- interstitial types, have been determined by first principles plane-wave pseudopotential calculations. Two kinds of metal-excess defects show the lowest formation energies. They were found to be more stable than the simple oxygen vacancy that exhibits the lowest formation energy among oxygen-vacancy-type defects. In both of the metal-excess defects with the lowest formation energies, excess Li occupies an empty 16c position of spinel. Excess Mn is present either at the 8a position, substituting for Li, or at the empty 16c position, moving one neighboring Li into the next 16c position. The results are consistent with experimental results of density measurements, diffusion experiments, and decomposition reactions at high temperatures. Detailed examination of the electronic structures revealed that formal charges of both interstitial and substituted Mn are +2. © 2002 The Electrochemical Society. All rights reserved.