11,408 research outputs found
Etching Behavior of GaN/GaAs(001) Epilayers Grown by MOVPE
No full textWet etching characteristics of cubic GAN (c-GaN) thin films grown on GaAs(001) by metalorganic vapor phase epitaxy (MOVPE) are investigated. The samples are etched in HCl, H_3PO_4, KOH aqueous solutions, and molten KOH at temperatures in the range of 90～300 ℃. It is found that different solution produces different etch figure on the surfaces of a sample. KOH-based solutions produce rectangular pits rather than square pits. The etch pits elongate in [1(1-bar)0] direction, indicating asymmetric etching behavior in the two orthogonal directions. An explanation based on relative reactivity of the various crystallographic planes is employed to interpret qualitatively the asymmetric etching behavior. In addition, it is found that KOH aqueous solution would be more suitable than molten KOH and the two acids for the evaluation of stacking faults in c-GaN epilayers
Remote temperature mapping of high-power InGaN/GaN MQW flip-chip design LEDs
No full textWe report on the study of heat 2D-distribution in InGaN LEDs with the stress made on local device overheating and
temperature gradients inside the structure. The MQW InGaN/GaN/sapphire blue LEDs are designed as bottom emitting
devices where light escapes the structure through the transparent GaN current spreading layer and sapphire substrate, whereas the LED structure with high-reflectivity Ni/Ag p-contact is bonded to the thermally conductive Si submount by a flip-chip method. The measurements are performed with an IR microscope operating in a time-resolved mode (3-5 μm spectral range, <20 μm spatial and 10 μs temporal resolution), while scanning a heat emission map through a transparent sapphire substrate. We show how current crowding (which is difficult to avoid) causes a local hot region near the n-contact pads and affects the performance of the device at a high injection level
Behavioral modeling of GaN-based power amplifiers: impact of electrothermal feedback on the model accuracy and identification
No full textIn this article, we discuss the accuracy of behavioral models in simulating the intermodulation distortion (IMD) of microwave GaN-based high-power amplifiers in the presence of strong electrothermal (ET) feedback. Exploiting an accurate self-consistent ET model derived from measurements and thermal finite-element method simulations, we show that behavioral models are able to yield accurate results, provided that the model identification is carried out with signals with wide bandwidth and large dynamics
Research on the impact of campus road network form on spatial cognition based on anchor point theory: case studies of Peking University and Tsinghua University
No full textHuman-oriented campus planning and design intended to realize the sustainable development of university campuses is concerned by domestic and foreign experts from planning and design academia. Research in the perspective of spatial cognition can provide important empirical references for human-oriented campus planning and design. Current research on spatial cognition of university campuses lacks both elaborate quantitative description of campus space form and association analysis of space form and spatial cognition of campuses, thus leading to limited reference value for campus planning and design. Therefore, the study takes Peking University and Tsinghua University as study objects and selects road network form, a representative spatial variable, to explore the impact of road network form on spatial cognition. Firstly, the study summarizes the evolution process and the spatial characteristics of road networks in Peking University and Tsinghua University. Based on literature review, the study discovers that the campus space of Peking University is organized with Weiming Lake and Boya Tower as the center and multiple secondary cores distributed in the periphery and the campus space of Tsinghua University is organized along some major design axes. The campus of Peking University is featured with multiple axis intercalation and centrality while the campus space of Tsinghua University is mainly featured with several main roads, such as Huangdao Axis, East District Axis and Xuetang Road. On the basis of literature review, this study conducts a questionnaire survey on the students’ familiarity of the locations in the two campuses and performs a correlation analysis among the students’ familiarity, integration degree, road network density of different locations. The study discovers that in Tsinghua University, locations with high familiarity are located along major axes, such as Xuetang Road while in Peking University locations with high familiarity are mainly located around the core area of the campus. According to correlation analysis, the familiarity with the locations of participants from the two universities will be improved if the global integration degrees of road network around the locations are higher while in Tsinghua University the increase of road density will also contribute to the improvement of participants’ familiarity of different locations. Finally, this research conducts externalization of cognitive map to further explore the impact of road network on spatial cognition of students. This research discovers that participants in Tsinghua University mainly encode spatial information in the perspective of the relationship between cognitive locations and road networks and the auxiliary elements of Tsinghua University in cognitive map are mostly path elements such as major roads (Xuetang Road) as well as design axes (East District Axis). The directions and the dispersion degrees of the cognitive location distortions in Tsinghua University are all highly related to major roads and axis. On the other hand, participants in Peking University mainly encode spatial information in the perspective of the relationship between cognitive locations and major land marks and the auxiliary elements of Peking University in cognitive map are mostly node elements. Additionally, the directions and the dispersion degrees of the cognitive location distortions in Peking University apparently are with center-edge characteristics. Through the analysis, the study discovers that participants from the two universities have the inclination to utilize path elements such as main roads as the anchor points for spatial cognition to master the surrounding environment when the campus space is featured with road network with relatively higher global integration and significant transport axes. Besides, road network with relatively low density and global integration will thus result in the declination of the familiarity of locations and the accuracy of spatial cognition. Through the analysis of the research results, this article suggests that the density and the integration degree of road network form as well as the integration of the main axes should be properly enhanced to improve the familiarity and the accuracy of spatial cognition of university campuses. The research intends to combine the analysis of road network form such as space syntax with the questionnaire on the familiarity of participants as well as the measurement of the distortion of cognitive locations. Through the analysis of research results, this research provides quantitative research evidence from the aspects of the encode and the storage of spatial knowledge on the conditions when residents will select path elements as cognitive anchors. Through the analysis of spatial cognition of campus space, this paper will provide empirical references for campus planning and design
LCT-GAN - Improving the efficiency of tabular data synthesis via latent embeddings
No full textIn the past decade data-driven approaches have been at the core of many business and research models. In critical domains such as healthcare and banking, data privacy issues are very stringent. Synthetic tabular data is an emerging solution to privacy guarantee concerns. Generative Adversarial Networks (GANs) are one of the emerging solutions for synthesizing data. However in order to capture all relevant relationships between columns, tabular data needs to be numerically encoded. As columns might be of different types, this is a challenging task as proven by recent approaches. Throughout this paper, we focus on the dimensionality explosion problem, which leads to high-dimensional datasets alongside computational overhead and increase in training time. We introduce a novel synthesis pipeline - LCT-GAN - an improvement to the current state-of-the-art in tabular data synthesis CTAB-GAN. Our approach addresses the dimensionality explosion problem by introducing a low-dimensional embedding step via an autoencoder prior to training. It is then combined with a novel conditional GAN architecture, operating in latent space. After thorough evaluation, we observe that our solution achieves more than 30\% improvement in certain statistical metrics in comparsion to CTAB-GAN, accompanied by 5 fold decrease in size and 150 times speedup in training time for a single epoch. We successfully show that it is possible to embed data using autoencoders, and that GANs are able to learn complex relationships in latent space in the context of tabular data.CSE3000 Research ProjectComputer Science and Engineerin
FCT-GAN: Fourier Neural Operator for Global Relation Enhancement in Tabular Data Synthesizing using Generative Adversarial Networks
No full textSince the regularization of data privacy (e.g., GDPR), the effectiveness of data sharing has decreased. A promising technique to circumvent this problem is tabular data synthesis (i.e., the generation of fake tabular data that statistically resembles the original data). However, the state-of-the-art tabular data synthesis model, CTAB-GAN, fails at robustly imitating global data dependencies and underperforms when column orders get permuted. CTAB-GAN internally uses Convolutional Neural Networks (CNN) which limits the model’s performance due to a strictly non-global data perspective during iterative training phases. To address this limitation, this paper proposes FCT-GAN which leverages the Fourier Neural Operator to learn global dependencies in the frequency domain. Specifically, it enhances CTAB-GAN by replacing the CNN of the discriminator with a four-layered two-dimensional Fourier Neural Operator. As a consequence of FCT-GAN’s global nature and cross-column relation robustness, it outperforms CTAB-GAN and additionally offers the column permutation invariant property. The evaluation of FCT-GAN on five datasets shows that the generated data, remarkably resembles the real data and reveals an increase in accuracy, by up to 19% for five machine learning algorithms independent of data column order, compared to CTAB-GAN.CSE3000 Research ProjectComputer Science and Engineerin
Degradation and corresponding failure mechanism for GaN-based LEDs
No full textThe degradation behaviors of high power GaN-based vertical blue LEDs on Si substrates were measured using in-situ accelerated life test. The results show that the dominant failure mechanism would be different during the operation. Besides that, the corresponding associated failure mechanisms were investigated systematically by using different analysis technologies, such as Scan Electron Microscopy, Reflectivity spectroscopy, Transient Thermal Analysis, Raman Spectra, etc. It is shown that initially, the failure modes were mainly originated from the semiconductor die and interconnect, while afterwards, the following serious deterioration of the radiant fluxes was attributed to the package. The interface material and quality, such as die attach and frame, play an important role in determining the thermal performance and reliability. In addition, the heating effect during the operation will also release the compressive strain in the chip. These findings will help to improve the reliability of GaN-based LEDs, especially for the LEDs with vertical structure
High-mobility Ga-polarity GaN achieved by NH3-MBE
No full textGaN epilayers were grown on (0001) sapphire substrates by NH3-MBE and RF-MBE (radio frequency plasma). The polarities of the epilayers were investigated by in-situ RHEED, chemical solution etching and AFM surface examination. By using a RF-MBE grown GaN layer as template to deposit GaN epilayer by NH3-MBE method, we found that not only Ga-polarity GaN films were repeatedly obtained, but also the electron mobility of these Ga-polarity films was significantly improved with a best value of 290 cm(2)/V.s at room temperature. Experimental results show it is an easy and stable way for growth of high quality Ga-polarity GaN films
Energy bands and acceptor binding energies of GaN
No full textThe energy bands of zinc-blende and wurtzite GaN are calculated with the empirical pseudopotential method, and the pseudopotential parameters for Ga and N atoms are-given. The calculated energy bands are in agreement with those obtained by the ab initio method. The effective-mass theory for the semiconductors of wurtzite structure is established, and the effective-mass parameters of GaN for both structures are given The binding energies of acceptor states are calculated by solving strictly the effective-mass equations. The binding energies of donor and acceptor are 24 and 142 meV for the zinc-blende structure, 20 and 131, and 97 meV for the wurtzite structure, respectively, which are consistent with recent experimental results. It is proposed that there are two kinds of acceptor in wurtzite GaN. One kind is the general acceptor such as C, which substitutes N, which satisfies the effective-mass theory. The other kind of acceptor includes Mg, Zn, Cd, etc., the binding energy of these accepters is deviated from that given by the effective mass theory. In this report, wurtzite GaN is grown by the molecular-beam epitaxy method, and the photoluminescence spectra were measured. Three main peaks are assigned to the donor-acceptor transitions from two kinds of accepters. Some of the transitions were identified as coming from the cubic phase of GaN, which appears randomly within the predominantly hexagonal material. [S0163-1829(99)15915-0]
Growth of Cubic GaN by MOCVD at High Temperature
No full textHigh quality cubic GaN (c-GaN) is grown by metalorganic vapor deposition (MOCVD) at an increased growth temperature of 900 ℃, with the growth rate of 1.6 μm/h. The full width at half maximum (FWHM) of room temperature photoluminescence (PL) for the high temperature grown GaN film is 48meV. It is smaller than that of the sample grown at 830 ℃. In X-ray diffraction (XRD) measurement, the high temperature grown GaN shows a (002) peak at 20° with a FWHM of 21'. It can be concluded that, although c-GaN is of metastable phase, high growth temperature is still beneficial to the improvement in its crystal quality. The relationship between the growth rate and growth temperature is also discussed
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