Mode mixing induced by disorder in graphene PNP junction in a magnetic field

We study the electron transport through the graphene PNP junction under a magnetic field and show that modes mixing plays an essential role. By using the non-equilibrium Green's function method, the space distribution of the scattering state for a specific incident modes as well the elements of the transmission and reflection coefficient matrixes are investigated. All elements of the transmission (reflection) coefficient matrixes are very different for a perfect PNP junction, but they are same at a disordered junction due to the mode mixing. The space distribution of the scattering state for the different incident modes also exhibit the similar behaviors, that they distinctly differ from each other in the perfect junction but are almost same in the disordered junction. For a unipolar junction, when the mode number in the center region is less than that in the left and right regions, the fluctuations of the total transmission and reflection coefficients are zero, although each element has a large fluctuation. These results clearly indicate the occurrence of perfect mode mixing and it plays an essential role in a graphene PNP junction transport

A Double-Track Auction for Substitutes and Complements

We propose a new t^atonnement process called a double-track auction for efficiently allocating multiple heterogeneous indivisible items in two distinct sets S1 and S2 to many buyers who view items in the same set as substitutes but items across the two sets as complements. The auctioneer initially announces sufficiently low prices for items in one set, say S1, but sufficiently high prices for items in the other set S2. In each round, the buyers respond by reporting their demands at the current prices and the auctioneer adjusts prices upwards for items in S1 but downwards for items in S2 based on buyers' reported demands until the market is clear. Unlike any existing auction, this auction is a blend of a multi-item ascending auction and a multi-item descending auction. We prove that the auction finds an efficient allocation and its market-clearing prices in finitely many rounds. Based on the auction we also establish a dynamic, efficient and strategy-proof mechanism.Market design, dynamic auction, t^atonnement process, gross substitutes and complements, Walrasian equilibrium, incentives.

Friction Stir Processing of Aluminum Alloys

Friction stir processing (FSP) has been developed based on the basic principles of friction stir welding (FSW), a solid-state joining process originally developed for aluminum alloys. What is attractive about FSP is that it can be incorporated in the overall manufacturing cycle as a post-processing step during the machining operation to provide localized modification and control of microstructures in near-surface layers of metallic components. FSP has emerged as an important post-processing technique, and has been identified as a process that may have a high impact, and perhaps is a disruptive manufacturing process. In this study, FSP has been applied to Al cast alloy A206, which is a high strength, widely used cast alloy in the manufacturing industry. Motivations behind this work are to (1) investigate the feasibility of FSP on manipulating the cast microstructure and strengthening the material, and (2) to explore the viability of FSP to produce a localized particle reinforced zone in cast A206 aluminum components. The thesis will show that we have optimized FSP for processing of Al alloys to locally manipulate the cast microstructure, eliminate casting defects, and attain grain refinement and second phase homogenization. We have established the mechanism leading to the microstructure evolution and have evaluated the resultant mechanical properties, i.e. hardness, tensile property and fatigue properties. We have also synthesized a localized composite material in the A206 work piece with three different reinforcement materials via FSP. These results will be presented and discussed

Distortion-Tolerant Communications with Correlated Information

This dissertation is devoted to the development of distortion-tolerant communication techniques by exploiting the spatial and/or temporal correlation in a broad range of wireless communication systems under various system configurations. Signals observed in wireless communication systems are often correlated in the spatial and/or temporal domains, and the correlation can be used to facilitate system designs and to improve system performance. First, the optimum node density, i.e., the optimum number of nodes in a unit area, is identified by utilizing the spatial data correlation in the one- and two-dimensional wireless sensor networks (WSNs), under the constraint of fixed power per unit area. The WSNs distortion is quantized as the mean square error between the original and the reconstructed signals. Then we extend the analysis into WSNs with spatial-temporally correlated data. The optimum sampling in the space and time domains is derived. The analytical optimum results can provide insights and guidelines on the design of practical WSNs. Second, distributed source coding schemes are developed by exploiting the data correlation in a wireless network with spatially distributed sources. A new symmetric distributed joint source-channel coding scheme (DJSCC) is proposed by utilizing the spatial source correlation. Then the DJSCC code is applied to spatial-temporally correlated sources. The temporal correlated data is modeled as the Markov chain. Correspondingly, two decoding algorithms are proposed. The first multi-codeword message passing algorithm (MCMP) is designed for spatially correlated memoryless sources. In the second algorithm, a hidden Markov decoding process is added to the MCMP decoder to effectively exploit the data correlation in both the space and time domains. Third, we develop distortion-tolerant high mobility wireless communication systems by considering correlated channel state information (CSI) in the time domain, and study the optimum designs with imperfect CSI. The pilot-assisted channel estimation mean square error is expressed as a closed-form expression of various system parameters through asymptotic analysis. Based on the statistical properties of the channel estimation error, we quantify the impacts of imperfect CSI on system performance by developing the analytical symbol error rate and a spectral efficiency lower bound of the communication system