Modeling Key Issues in Post Silicon Semiconductors: Germanium and Gallium Nitride

We are rapidly approaching the end of the semiconductor roadmap with respect to silicon. To continue its growth, the semiconductor industry is therefore looking into new materials. Two primary materials that are of interest for continuing semiconductor development are germanium (Ge) and gallium nitride (GaN). Ge is of interest as a replacement for silicon, in an effort to improve electronics performances because of its high mobility and its ability to grow a native oxide. In addition, Ge is of interest because of its potential use for economical CMOS-based short wave infrared (SWIR) imaging systems. GaN is a nascent wide bandgap semiconductor and has many potential applications in high power electronics and ultraviolet imaging systems. In this thesis, the key material properties and applications of these two ”end of the roadmap” semiconductors are explored. Ge is a semiconductor material with an indirect bandgap of 0.66eV. This bandgap value corresponds to a wavelength of 1.88μm, which lies in the infrared range. The Ge material itself is also compatible with the standard Si CMOS process technology. Because of these advantages, Ge is considered a candidate for the application of photo detecting in the SWIR range. Apart from the indirect bandgap of 0.66eV, Ge also has a direct bandgap of 0.8eV. From early research, the relatively small offset between the indirect and direct bandgaps can be inverted either by applying strain[1, 9, 10, 11] or alloying with tin. GaN is a binary direct wide bandgap material with a direct bandgap of 3.4eV. It has a high breakdown field, and relatively high saturation velocity and carrier mobility. These properties give GaN an advantage in the realm of high power application. GaN can also form a heterostructure with AlGaN, which can give rise to a 2D electron gas (2DEG) layer at the interface without intentionally doping either material. The 2DEG layer has an even higher mobility when compared to the mobility of the bulk GaN, which allows the heterostructure to be utilized for the design of high electron mobility transistors (HEMTs). The formation of the 2DEG layer also gives rise to potential well confinement at the heterostructure interface. The width of the potential well is only a few nanometers, making the interface electron gas subject to quantum confinement along the direction perpendicular to the interface. The detailed shape of the potential well is determined by the configuration of the heterostructure, as well as the applied voltage across the heterostructure. The first set of goals for this research is to investigate how the bandstructure of Ge changes: Part (1) with the applied strain, and Part (2) with alloyed tin (Sn). The empirical pseudopotential method (EPM) was utilized for the band structure calculation, together with the rules for strain translation for the investigation of Part (1). In Part (1), simulation results give the optimal orientation for different types of applied strain and also thoroughly map the influence of strain applied on any arbitrary orientations. It also reveals that for biaxial strain, there exists another orientation that is more robust against misalignment with respect to the originally desired orientation than the optimal plane, with little compromise of bandgap and slightly higher requirements for the sufficient strain. For Part (2), EPM is combined with perturbation theory for the inclusion of the influence of the Sn atoms in the Ge lattice. A new and computationally inexpensive method is developed during the research. Simulation results agree significantly when compared to reported experimental measurements, indicating the capability of the method. The second set of goals is to investigate the electron transport properties of the 2DEG layer at the interface of GaN HEMT and related power transistors. The potential well is approximated and quantified by a triangular potential well and the carrier sheet density is kept the same during the approximation. Thorough simulations are conducted by calculating the band alignment of the heterostructure with different structural configurations. A fixed correlation between the carrier sheet density and the shape of the potential well (slope of the triangular potential well and the height of the well) is revealed. This correlation is used as an input for the Monte Carlo (MC) simulation. The changes to the mobility of the electrons at the 2DEG layer with changing interface potential well shape are investigated and statis- tics of drift velocity, electron energy, and valley occupation are collected. Mobility information is also extracted and compares favorably with reported experimental measurements. The simulation results are used in the device simulations, which compares the performances of two GaN/AlGaN heterostructure based devices: a lateral HEMT and a current aperture vertical electron transistor (CAVET)

Strain improvement of Trichoderma harzianum for enhanced biocontrol capacity: Strategies and prospects

In the control of plant diseases, biocontrol has the advantages of being efficient and safe for human health and the environment. The filamentous fungus Trichoderma harzianum and its closely related species can inhibit the growth of many phytopathogenic fungi, and have been developed as commercial biocontrol agents for decades. In this review, we summarize studies on T. harzianum species complex from the perspective of strain improvement. To elevate the biocontrol ability, the production of extracellular proteins and compounds with antimicrobial or plant immunity-eliciting activities need to be enhanced. In addition, resistance to various environmental stressors should be strengthened. Engineering the gene regulatory system has the potential to modulate a variety of biological processes related to biocontrol. With the rapidly developing technologies for fungal genetic engineering, T. harzianum strains with increased biocontrol activities are expected to be constructed to promote the sustainable development of agriculture

EVM: Incorporating Model Checking into Exploratory Visual Analysis

Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seldom enable explicit checks of the resulting interpretations of data -- e.g., whether patterns can be accounted for by a model that implies a particular structure in the relationships between variables. We present EVM, a data exploration tool that enables users to express and check provisional interpretations of data in the form of statistical models. EVM integrates support for visualization-based model checks by rendering distributions of model predictions alongside user-generated views of data. In a user study with data scientists practicing in the private and public sector, we evaluate how model checks influence analysts' thinking during data exploration. Our analysis characterizes how participants use model checks to scrutinize expectations about data generating process and surfaces further opportunities to scaffold model exploration in VA tools

H-RNet: hybrid rlation network for few-shot learning-based hyperspectral image classification.

Deep network models rely on sufficient training samples to perform reasonably well, which has inevitably constrained their application in classification of hyperspectral images (HSIs) due to the limited availability of labeled data. To tackle this particular challenge, we propose a hybrid relation network, H-RNet, by combining three-dimensional (3-D) convolution neural networks (CNN) and two-dimensional (2-D) CNN to extract the spectral–spatial features whilst reducing the complexity of the network. In an end-to-end relation learning module, the sample pairing approach can effectively alleviate the problem of few labeled samples and learn correlations between samples more accurately for more effective classification. Experimental results on three publicly available datasets have fully demonstrated the superior performance of the proposed model in comparison to a few state-of-the-art methods

Future of Networked Information Society: A Deeply Interconnected “Primitive Society”

Human society is evolving toward the future network information society. In this paper, we identify the interconnected level as the key factor driving the evolution of human society and incorporate it into our proposed evolutionary model of social formation. We show the entire process of social formation evolution at the interconnected level through theoretical analysis and simulation. Our result is consistent with what human beings have gone through. By contrast, the result presents the following four characteristics of the future network information society: the personalization of goods or services, the downsizing of enterprises or organizations, the decentralization of production or life, and the sharing of production or living tools. We regard the future network information society as a deeply interconnected “primitive society”

Numerical study on anti-impact characteristics of energy absorbing column with multicellular square tube filled with aluminum foam

Aiming at the insufficient anti-impact performance of existing components of the energy-absorbing anti-impact support, a foam aluminum filled multicellular square tube structure is proposed. According to the axial energy absorption theory of thin-walled structures filled with foam materials, the formula of average crushing load is obtained. The axial impact simulation of square tube, multicellular square tube and foam aluminum filled multicellular square tube are completed by using ABAQUS/Explicit. On this basis, the impact resistance of ordinary hydraulic column and energy absorbing hydraulic column is analyzed. The results showed that compared with the square tube and multicellular square tube, the foam aluminum filled multicellular square tube has an ideal axisymmetric progressive deformation. The initial load peak value, load bearing-mean and energy absorption are greatly improved, the effective deformation distance is reduced, the load fluctuation is reduced, and the load carrying efficiency is improved. With the increase of foam aluminum filling ratio, the effective deformation distance and energy absorption of the component are reduced. As the porosity of aluminum foam decreases, the force variance decreases, and energy absorption and the load carrying efficiency increase. Aluminum foam-filled multicellular square tube with 60% porosity at 25% filling rate is an ideal energy absorption component. Ordinary column surges after impact load, bending deformation is serious, column relies on its own deformation to absorb energy, supporting effect is poor. After the energy-absorbing column is impacted, the energy absorption component begins to deform and absorb energy. Greatly reduce the load of the column, absorb most of the outside impact energy, avoid the column bending deformation, improve the impact resistance of the support