AlGaN/GaN Dual Channel HFETs and Realization of GaN Devices on different substrates

GaN-based HFETs demonstrate ubiquitous high power and high frequency performance and attract tremendous research efforts. Even though significant advances have been achieved, there still exist some critical issues needed to be investigated and solved. In particular, high defect densities due to inhomogeneous growth and operation under high power conditions bring many unique problems which are not so critical in the conventional Si and GaAs materials systems. In order to reduce the defect density and heat dissipation of GaN-based HFETs, research work on the realization of GaN-based HFETs on bulk GaN substrate has been carried out and the key problems have been identified and solved. Hot phonon scattering is the bottleneck which limits the enhancement of electron velocity in the GaN 2DEG channel. It is found that the plasmon-phonon coupling is the mechanism for converting of hot phonons into high group velocity acoustic phonons. In order to push more electrons into the GaN 2DEG channel in the plasmon-phonon coupling regime and to further reduce the hot phonon lifetime, a novel AlGaN/GaN dual channel HFET structure has been proposed. The growth, fabrication and characterization of such a AlGaN/GaN dual channel HFET structure has been carried out. Conventionally GaN-based light emitting diodes and laser diodes are grown and fabricated using the c-plane III-nitride expitaxy layers. In c-plane III-nitride epi-layers, the polarization-induced electric field introduces spatial separation of electron and hole wave functions in quantum wells (QW)s used LEDs and laser diodes LDs and degrades quantum efficiency. As well, blueshift in the emission wavelength becomes inevitable with increasing injection current unless very thin QWs are employed. The use of nonpolar orientations, namely, m-plane or a-plane GaN, would solve this problem. So far, m-plane GaN has been obtained on LiAlO2 (100), m-plane SiC substrates, and m-plane bulk GaN, which all have limited availability and/or high cost. Silicon substrates are very attractive for the growth of GaN due to their high quality, good thermal conductivity, low cost, availability in large size, and ease with which they can be selectively removed before packaging for better light extraction and heat transfer when needed To realize the low cost and improve the internal quantum efficiency of GaN based light emitting diodes, the process for m-plane GaN growth on Si (112) substrates has been studied and optimized. The continuous m-plane GaN film is successfully grown on Si (112) substrates

Symmetry restoration and quantumness reestablishment

A realistic quantum many-body system, characterized by a generic microscopic Hamiltonian, is accessible only through approximation methods. The mean field theories, as the simplest practices of approximation methods, commonly serve as a powerful tool, but unfortunately often violate the symmetry of the Hamiltonian. The conventional BCS theory, as an excellent mean field approach, violates the particle number conservation and completely erases quantumness characterized by concurrence and quantum discord between different modes. We restore the symmetry by using the projected BCS theory and the exact numerical solution and find that the lost quantumness is synchronously reestablished. We show that while entanglement remains unchanged with the particle numbers, quantum discord behaves as an extensive quantity with respect to the system size. Surprisingly, discord is hardly dependent on the interaction strengths. The new feature of discord offers promising applications in modern quantum technologies.Comment: 17 pages and 3 figure

Analysis of flat slabs with various edge supports

This study presents the solution of flat slabs with various edge conditions including T-Beam edge supports, The equations formulated are based on the finite difference method and solved using an electronic computer. The results indicate that the solution of these slabs by the finite difference approximation is a practical method. In addition, this method is more flexible and yields moment values that are considerably more accurate than those obtained using the ACI Code --Abstract, page ii

Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model

Existing neural semantic parsers mainly utilize a sequence encoder, i.e., a sequential LSTM, to extract word order features while neglecting other valuable syntactic information such as dependency graph or constituent trees. In this paper, we first propose to use the \textit{syntactic graph} to represent three types of syntactic information, i.e., word order, dependency and constituency features. We further employ a graph-to-sequence model to encode the syntactic graph and decode a logical form. Experimental results on benchmark datasets show that our model is comparable to the state-of-the-art on Jobs640, ATIS and Geo880. Experimental results on adversarial examples demonstrate the robustness of the model is also improved by encoding more syntactic information.Comment: EMNLP'1