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Master'sMASTER OF SCIENCE (ESTATE MANAGEMENT

Space charge modulated electrical breakdown

Electrical breakdown is one of the most important physical phenomena in electrical and electronic engineering. Since the early 20th century, many theories and models of electrical breakdown have been proposed, but the origin of one key issue, that the explanation for dc breakdown strength being twice or higher than ac breakdown strength in insulating materials, remains unclear. Here, by employing a bipolar charge transport model, we investigate the space charge dynamics in both dc and ac breakdown processes. We demonstrate the differences in charge accumulations under both dc and ac stresses and estimate the breakdown strength, which is modulated by the electric field distortion induced by space charge. It is concluded that dc breakdown initializes in the bulk whereas ac breakdown initializes in the vicinity of the sample-electrode interface. Compared with dc breakdown, the lower breakdown strength under ac stress and the decreasing breakdown strength with an increase in applied frequency, are both attributed to the electric field distortion induced by space charges located in the vicinity of the electrodes

Can Deep Learning Approach Be Virtually Cultivated Via Social Learning Network

With the development of information technology especially kinds of social interaction techniques, social learning networks as a new platform have changed students’ learning behaviors and improve their learning performance. However, how this change happens especially how social learning networks change students’ learning approaches were not very clear. To address this gap, in this research, we try to investigate the impacts of social learning network on students’ learning approaches by conducting an experiment. In the experiment, students were randomly divided into two groups: control group and experimental group. We try to investigate the differences of students’ leaning behavior in terms of learning approaches in the two groups. We also present the theoretical, practical implications and future research

A unified framework for STAR-RIS coefficients optimization

Simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS), which serves users located on both sides of the surface, has recently emerged as a promising enhancement to the traditional reflective only RIS. Due to the lack of a unified comparison of communication systems equipped with different modes of STAR-RIS and the performance degradation caused by the constraints involving discrete selection, this paper proposes a unified optimization framework for handling the STAR-RIS operating mode and discrete phase constraints. With a judiciously introduced penalty term, this framework transforms the original problem into two iterative subproblems, with one containing the selection-type constraints, and the other subproblem handling other wireless resource. Convergent point of the whole algorithm is found to be at least a stationary point under mild conditions. As an illustrative example, the proposed framework is applied to a sum-rate maximization problem in the downlink transmission. Simulation results show that the algorithms from the proposed framework outperform other existing algorithms tailored for different STAR-RIS scenarios. Furthermore, it is found that 4 or even 2 discrete phases STAR-RIS could achieve almost the same sum-rate performance as the continuous phase setting, showing for the first time that discrete phase is not necessarily a cause of significant performance degradation

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

Polymer Electret Improves the Performance of the Oxygen-Doped Organic Field-Effect Transistors

Chemical doping is widely used in the electronic devices. In p-type semiconductor thin films, oxygen doping fills the hole traps and increases hole concentrations, improving the performance of the organic field-effect transistors (OFETs). Due to the low ionization potential for p-type semiconductors, the superfluous holes induced by the oxygen doping degrades the OFETs off-state leakage performance. On the other hand, for p-type semiconductors with high ionization potential (up to 5.5-6.0 eV), the limited oxidation of oxygen is hard to achieve satisfactory doping concentrations to fill the trap states. This refers to the well-known intrinsic incompatibility between the oxygen doping and high-performance OFETs. Herein, a novel strategy is introduced to overcome the incompatibility and achieve high-performance OFETs by using the structural polymer electret. That is, moderate hole concentrations induced by low-pressure (30 Pa) oxygen plasma fill the hole traps within semiconductor. And the built-in field resulted from polymer electret accumulates the holes inside semiconductor near the semiconductor/electret interface, thus improving the OFETs performance. Using a model organic semiconductor with high ionization potential-2,7-didodecyl[1]benzothieno [3,2-b][1]benzothiophene (C12-BTBT) as an example, the high-performance OFETs with field-effect mobility (μFET) of 3.5 cm 2 V -1 s -1 , subthreshold-swing (SS) of 110 mV decade -1 , on-off ratio of 10 4 , and widely-tunable threshold voltage (V t ) are realized at a low voltage below 2 V in the open air

Highly efficient blueish-green fluorescent OLEDs based on AIE liquid crystal molecules : From ingenious molecular design to multifunction materials

In order to seek the balance point between liquid crystallinity and high efficiency emission, two novel aggregation-induced emission-based (AIE) liquid crystal materials of TPE-PBN and TPE-2PBN, which contain a tetraphenylethene derivative as the emission core and a 4-cynobiphenyl moiety as the mesogenic unit, were designed and prepared. Both simple molecules showed a mesophase at high temperature as evidenced by polarised optical microscopy (POM), differential scanning calorimetry (DSC) and temperature-dependent X-ray diffraction (XRD). Simultaneously, TPE-PBN and TPE-2PBN presented clear AIE characteristics in the blueish-green region and achieved a high emission quantum efficiency of 71% and 83% in the solid state, respectively. Due to the self-assembly properties of thermotropic liquid crystals, both compounds showed higher hole mobilities in the annealed films than in pristine films. Employing TPE-PBN and TPE-2PBN as the emitting materials, both non-doped devices and doped devices were fabricated. The TPE-PBN-based doped OLEDs showed a better device performance with an external quantum efficiency (EQE) of 4.1% which is among the highest EQEs of blue AIE fluorescent OLEDs

Intelligent Omni-Surfaces: Reflection-Refraction Circuit Model, Full-Dimensional Beamforming, and System Implementation

The intelligent omni-surface (IOS) is a dynamic metasurface that has recently been proposed to achieve full-dimensional communications by realizing the dual function of anomalous reflection and anomalous refraction. Existing research works provide only simplified models for the reflection and refraction responses of the IOS, which do not explicitly depend on the physical structure of the IOS and the angle of incidence of the electromagnetic (EM) wave. Therefore, the available reflection-refraction models are insufficient to characterize the performance of full-dimensional communications. In this paper, we propose a complete and detailed circuit-based reflection-refraction model for the IOS, which is formulated in terms of the physical structure and equivalent circuits of the IOS elements, as well as we validate it against full-wave EM simulations. Based on the proposed circuit-based model for the IOS, we analyze the asymmetry between the reflection and transmission coefficients. Moreover, the proposed circuit-based model is utilized for optimizing the hybrid beamforming of IOS-assisted networks and hence improving the system performance. To verify the circuit-based model, the theoretical findings, and to evaluate the performance of full-dimensional beamforming, we implement a prototype of IOS and deploy an IOS-assisted wireless communication testbed to experimentally measure the beam patterns and to quantify the achievable rate. The obtained experimental results validate the theoretical findings and the accuracy of the proposed circuit-based reflection-refraction model for IOSs.Comment: 33 pages, 20 figure