• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Journal of the Korean Vacuum Society
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• v.19 no.3
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• pp.199-205
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• 2010

The electrical properties and defect states in ZnO substrates were studied during high-energy electron beam irradiations. 1 MeV and 2 MeV electron-beam with dose of $1{\times}10^{16}$ electrons/$cm^2$ were irradiated on Zn-surface of the sample. In the sample irradiated by 1 MeV, the leakage current was increased by electron-beam induced surface defects, while the enhancement of on/off property and the decrease of leakage current appeared in the 2 MeV irradiated sample. From the deep level transient spectroscopy measurements for these samples, it showed that the defect states with the activation energies of $E_c$-0.33 eV and $E_v$+0.8 eV are generated during the high energy electron-beam irradiation. Especially, it considered that the $E_c$-0.33 eV state related with O-vacancy affects to their electrical properties.

• Journal of IKEEE
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• v.27 no.4
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• pp.556-560
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• 2023

In this study, the impact of Nitrogen implantation process on deep-level defects and lifetime in 4H-SiC Epi surfaces was comparatively analyzed. Deep Level Transient Spectroscopy (DLTS) and Time Resolved Photoluminescence (TR-PL) were employed to measure deep-level defects and carrier lifetime. As-grown Schottky Barrier Diodes (SBDs) exhibited energy levels at 0.16 eV, 0.67 eV, and 1.54 eV, while for implantation SBD, defects at 0.15 eV were observed. This indicates a reduction in defects associated with energy levels Z_1/2 and EH_6/7, known as lifetime killers, as impurities from nitrogen implantation replace titanium and carbon vacancies.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.420-420
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• 2013

We investigated oxygen plasma effect on defect states near the interface of AlGaN/GaN High Electron Mobility Transistor (HEMT) structure grown on a silicon substrate. After the plasma treatment, electrical properties were evaluated using a frequency dependant Capacitance-Voltage (C-V) and a temperature dependant C-V measurements, and a deep level transient spectroscopy (DLTS) method to study the change of defect densities. In the depth profile resulted from the temperature dependant C-V, a sudden decrease in the carrier concentration for two-dimensional electron gas (2DEG) nearby 250 K was observed. In C-V measurement, the interface states were improved in case of the oxygen-plasma treated samples, whereas the interface was degraded in case of the nitrogen-plasma treated sample. In the DLTS measurement, it was observed the two kinds of defects well known in AlGaN/GaN structure grown on sapphire substrate, which have the activation energies of 0.15 eV, 0.25 eV below the conduction band. We speculate that this defect state in AlGaN/GaN on the silicon substrate is caused from the decrease in 2DEG's carrier concentrations. We compared the various DLTS signals with filling pulse times to identify the characteristics of the newly found defect. In the filling pulse time range under the 80 us, the activation energies changed as the potential barrier model. On the other hand, in the filling pulse time range above the 80 us, the activation energies changed as the extended potential model. Therefore, we suggest that the found defect in the AlGaN/GaN/Si structure could be the extended defect related with AlGa/N/GaN interface states.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.09a
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• pp.52-59
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• 2001

The photoluminescence and the photo-current from p-type GaN films were investigated on both room- and low-temperatures for various Mg doping concentrations. At a low Mg doping level, there exists a photoluminescence center of the donor and the acceptor pair transition of the 3.28-eV band. This center is correlated with the defects for a shallow donor of the VGa and for an acceptor of MgGa. The acceptor level shows the binding energy of 0.2-0.25 eV, which was observed by the photon energy of the photo-current signal of 3.02-3.31 eV. At a high Mg doping level, there is a photoluminescence center of a deep donor and an acceptor pair transition of the 2.76-eV blue band. This center is attributed to the defect structures of MgGa-VN for the deep donor and MgGa for the acceptor. For low. doped samples, thermal annealing provides an additional photo-current signal for an unoccupied deep acceptor levels of 0.87-1.35 eV above valence band, indicating the p-type activation.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.201-208
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• 2023

The dependence of the electrical characteristics on the fast neutron fluence of an epitaxial 4H-SiC Schottky barrier diode (SBD) was investigated. The 30 MeV cyclotron was used for fast neutron irradiation. The neutron fluences evaluated through Monte Carlo simulation were in the 2.7 × 10¹¹ to 1.45 × 10¹³ neutrons/cm² range. Current-voltage and capacitance-voltage measurements were performed to characterize the samples by extracting the parameters of the irradiated SBDs. Neutron-induced defects in the epitaxial layer were identified and quantified using a deep-level transient spectroscopy measurement system developed at the Korea Atomic Energy Research Institute. As the neutron fluence increased from 2.7 × 10¹¹ to 1.45 × 10¹³ neutrons/cm², the concentration of the Z_1/2 defects increased by approximately 20 times. The maximum defect concentration was estimated as 1.5 × 10¹⁴ cm^-3 at a neutron fluence of 1.45 × 10¹³ neutrons/cm².

• Korean Journal of Materials Research
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• v.11 no.10
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• pp.889-894
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• 2001

2wt% $Al_2O_3-doped$ ZnO (AZO) thin films were deposited on sapphire (0001) single crystal substrate by parellel type rf magnetron sputtering at 55$0^{\circ}C$. The as-grown AZO thin films was polycrystalline and showed only broad deep defect-level photoluminescence (PL). In order to examine the change of PL property, AZO thin films were annealed in $N_2$ (N-AZO) and $H_2$ (H-AZO) at the temperature of $600^{\circ}C$~$1000^{\circ}C$ through rapid thermal annealing. After annealed at $800^{\circ}C$, N-AZO shows near band edge emission (NBE) with very small deep-level emission, and then N-AZO annealed at $900^{\circ}C$ shows only sharp NBE with 219 meV FWHM. In Comparison with N-AZO, H-AZO exhibits very interesting PL features. After $600^{\circ}C$ annealing, deep defect-level emission was quire quenched and NBE around 382 nm (3.2 eV) was observed, which can be explained by the $H_2$passivation effect. At elevated temperature, two interesting peaks corresponding to violet (406 nm, 3.05 eV) and blue (436 nm, 2.84 eV) emission was firstly observed in AZO thin films. Moreover, peculiar PL peak around 694 nm (1.78 eV) is also firstly observed in all the H-AZO thin films and this is believed good evidence of hydrogenation of AZO. Based on defect-level scheme calculated by using the full potential linear muffin-tin orbital (FP-LMTO), the emission 3.2 eV, 3.05 eV, 3.84 eV and 1.78 eV of H-AZO are substantially deginated as exciton emission, transition from conduction band maximum to $V_{ Zn},$ from $Zn_i$, to valence band maximum $(V_{BM})$ and from $V_{o} to V_BM}$, respectively.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.150-153
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• 2004

본 논문에서는 780 nm 고출력 레이저 다이오드의 신뢰성을 향상시키기 위하여 DLTS(deep level transient spectroscopy)을 이용하여 MOCVD(metalorganic chemical vapor deposition) 성장 조건 변화에 따른 $Al_{0.48}Ga_{0.52}As$와 $Al_{0.1}Ga_{0.9}As$ 물질에서의 깊은준위(deep level)의 거동을 조사하였다. DLTS 측정결과, MOCVD로 성장된 막에서만 나타나는 결함(defect)으로 추정되는 trap A(0.3 eV), DX center로 알려진 trap B, 갈륨(Ga) vacancy와 산소(O2) 원자의 복합체(complex)에 의한 결함인 trap D(0.6 eV) 및 EL2 라고 불리우는 trap E(0.9 eV)의 네 가지 깊은준위들이 관측되었고, 성장 조건의 변화에 따라 깊은 준위들의 농도가 감소하는 것을 관측함으로써 최적 성장 조건을 찾을 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Macromolecular Research
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• v.10 no.2
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• pp.75-79
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• 2002

Organic materials have considerable attention as active semiconductors for device applications such as thin-film transistors (TFTs) and diodes. Pentacene is a p-type organic semiconducting material investigated for TFTs. In this paper, we reported the morphological and electrical characteristics of pentacene TFT films. The pentacene transistors showed the mobility of 0.8 $\textrm{cm}^2$/Vs and the grains larger than 1 ${\mu}{\textrm}{m}$. Deep-level transient spectroscopy (DLTS) measurements were carried out on metal/insulator/organic semiconductor structure devices that had a depletion region at the insulator/organic-semiconductor interface. The duration of the capacitance transient in DLTS signals was several ten of seconds in the pentacene, which was longer than that of inorganic semiconductors such as Si. Based on the DLTS characteristics, the energy levels of hole and electron traps for the pentacene films were approximately 0.24, 1.08, and 0.31 eV above Ev, and 0.69 eV below Ec.