Study of edge states and conductivity in spin-orbit coupled bilayer graphene

We present an elaborate and systematic study of the conductance properties of a zigzag bilayer graphene nanoribbon modeled by a Kane-Mele (KM) Hamiltonian. The interplay of the Rashba and the intrinsic spin-orbit couplings with the edge states, electronic band structures, charge and spin transport are explored in details. We have analytically derived the conditions for the edge states for a bilayer KM nanoribbon and show how these modes decay for lattice sites inside the bulk. It is particularly interesting to note that for a finite-size ribbon an even number of zigzag ribbon hosts a finite energy gap at the Dirac points, while the odd ones do not. This asymmetry is present both in presence and absence of a bias voltage that may exist between the layers. The interlayer Rashba spin-orbit coupling, along with the intralayer intrinsic spin-orbit and intralayer Rashba spin-orbit couplings seem to destroy the quantum spin Hall (QSH) phase where the QSH phase is identified by the presence of a conductance plateau (of magnitude 4e/h) in the vicinity of zero Fermi energy. The plateau is sensitive to the values of the spin-orbit coupling parameters. Further, the spin polarized conductance data reveal that a bilayer KM ribbon is found to be more efficient for spintronic applications compared to a monolayer graphene. Finally, a quick check with experiments is done via computing the effective mass of electrons.Comment: 12 page

Social exclusion and land administration in Orissa, India

The authors report on the first empirical study of its kind to examine - from the perspective of transaction costs - factors that constrain access to land for the rural poor and other socially excluded groups in India. They find that: a) Land reform has reduced large landholdings since the 1950s. Medium size farms have gained most. Formidable obstacles still prevent the poor from gaining access to land. b) The complexity of land revenue administration in Orissa is partly the legacy of distinctly different systems, which produced more or less complete and accurate land records. These not-so-distant historical records can be important in resolving contemporary land disputes. c) Orissa tried legally to abolish land-leasing. Concealed tenancy persisted, with tenants having little protection under the law. d) Women's access to and control over land, and their bargaining power with their husbands about land, may be enhanced through joint land titling, a principle yet to be realized in Orissa. e) Land administration is viewed as a burden on the state rather than a service, and land records and registration systems are not coordinated. Doing so will improve rights for the poor and reduce transaction costs - but only if the system is transparent and the powerful do not retain the leverage over settlement officers that has allowed land grabs. Land in Orissa may be purchased, inherited, rented (leased), or - in the case of public land and the commons - encroached upon. Each type of transaction - and the State's response, through land law and administration - has implications for poor people's access to land. The authors find that: 1) Land markets are thin and transaction costs are high, limiting the amount of agricultural land that changes hands. 2) The fragmentation of landholdings into tiny, scattered plots is a brake on agricultural productivity, but efforts to consolidate land may discriminate against the rural poor. Reducing transaction costs in land markets will help. 3) Protecting the rural poor's rights of access to common land requires raising public awareness and access to information. 4) Liberalizing land-lease markets for the rural poor will help, but only if the poor are ensured access to institutional credit.Banks&Banking Reform,Public Sector Management and Reform,Environmental Economics&Policies,Land Use and Policies,Urban Governance and Management,Public Sector Management and Reform,Environmental Economics&Policies,Banks&Banking Reform,Rural Land Policies for Poverty Reduction,Land Use and Policies

Automatic Leak Detection in Carbon Sequestration Projects

The international commitments for carbon capture will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful carbon sequestration project lies in the long term storage and prevention of leakage of stored carbon dioxide (CO2). In addition to being a greenhouse gas, CO2 leaks reaching the surface can accumulate in low-lying areas resulting in a serious health risk. Among several alternatives, some of the more promising CSS storage formations are the hundreds of thousands of depleted oil and gas reservoirs, whereby definition the reservoirs had good geological seals prior to hydrocarbon extraction. With more CSS wells coming online, it is imperative to implement permanent, automated monitoring tools. In this study, we applied machine learning models to automate the leakage detection process in carbon storage reservoirs using rates of supercritical (CO2) injection and pressure data measured by simple pulse tests. To validate the promise of this machine learning-based work ow, we implemented data from pulse tests carried out in the Cran eld reservoir, Mississippi, USA. The data consist of a series of pulse tests conducted with baseline parameters and with an artificially introduced leak. Here, we pose the leakage detection task as an anomaly detection problem where deviation from the predicted behavior indicates leaks in the reservoir. The results obtained show that different machine learning architectures such as multi-layer feed-forward network, Long Short-Term Memory, convolutional neural network are able to identify leakages and can act as an early warning. These warnings can then be used by human interpreters to take remedial measures

Statistical and deep learning methods for geoscience problems

Machine learning is the new frontier for technology development in geosciences and has developed extremely fast in the past decade. With the increased compute power provided by distributed computing and Graphics Processing Units (GPUs) and their exploitation provided by machine learning (ML) frameworks such as Keras, Pytorch, and Tensorflow, ML algorithms can now solve complex scientific problems. Although powerful, ML algorithms need to be applied to suitable problems conditioned for optimal results. For this reason ML algorithms require not only a deep understanding of the problem but also of the algorithm’s ability. In this dissertation, I show that Simple statistical techniques can often outperform ML-based models if applied correctly. In this dissertation, I show the success of deep learning in addressing two difficult problems. In the first application I use deep learning to auto-detect the leaks in a carbon capture project using pressure field data acquired from the DOE Cranfield site in Mississippi. I use the history of pressure, rates, and cumulative injection volumes to detect leaks as pressure anomaly. I use a different deep learning workflow to forecast high-energy electrons in Earth’s outer radiation belt using in situ measurements of different space weather parameters such as solar wind density and pressure. I focus on predicting electron fluxes of 2 MeV and higher energy and introduce the ensemble of deep learning models to further improve the results as compared to using a single deep learning architecture. I also show an example where a carefully constructed statistical approach, guided by the human interpreter, outperforms deep learning algorithms implemented by others. Here, the goal is to correlate multiple well logs across a survey area in order to map not only the thickness, but also to characterize the behavior of stacked gamma ray parasequence sets. Using tools including maximum likelihood estimation (MLE) and dynamic time warping (DTW) provides a means of generating quantitative maps of upward fining and upward coarsening across the oil field. The ultimate goal is to link such extensive well control with the spectral attribute signature of 3D seismic data volumes to provide a detailed maps of not only the depositional history, but also insight into lateral and vertical variation of mineralogy important to the effective completion of shale resource plays

A 50 GHz SiGe BiCMOS active bandpass filter

Abstract: This paper presents a second-order active bandpass filter (BPF) at millimeter-wave frequency band using 0.13 μm SiGe BiCMOS technology. A complementary cross-coupled pair based negative resistance technique is applied to compensate for the resistive losses of microstrip line resonators. The proposed active BPF is simulated using the Keysight Technologies (formerly Agilent’s Electronic Measurement Group) Advanced Design System 2016.01. The center frequency (fc), 3-dB bandwidth, and fractional bandwidth of the simulated BPF are 53.85 GHz, 14.18 GHz, and 26.33%, respectively. The BPF shows an insertion loss (IL) of 0.33 dB and a return loss (RL) of 18.03 dB at fc. The minimum IL of 0.10 dB and best RL of 26.03 dB are observed in the passband. The noise figure and input 1-dB compression point (PldB) at fc are 7.93 dB and -3.67 dBm, respectively. The power dissipation is 2.62 mW at 1.6 V supply voltage. For the input power level of -10 dBm, the power level of the second harmonic is -46.02 dBc

Millimeter-wave passive bandpass filters

Abstract: This paper presents a comprehensive review of millimeter-wave (mm-wave) passive bandpass filters (BPFs). A detailed discussion is provided on different topologies and architectures, performance comparison, design challenges, and process technologies. Passive BPFs offer the advantages of high operating frequency, good linearity, low noise figure (NF), and no power dissipation. Careful consideration of available process technologies is required for the implementation of high performance mm-wave circuits. Gallium arsenide (GaAs) and indium phosphide (InP) (group III-V) processes provide high cutoff frequencies (fT), good noise performance, and high quality on-chip passives. Complementary metal oxide semiconductor (CMOS) process has the prominent advantages of low cost, a high degree of integration, and high reliability, while silicon germanium bipolar CMOS (SiGe BiCMOS) process demonstrates high fT, a high level of integration, and better noise and power performance

Millimeter-wave active bandpass filters

Abstract: An exhaustive review of millimeter-wave (mm-wave) active bandpass filters (BPFs) is presented in this article. The details of various design approaches and realization techniques for the implementation of active BPFs are provided. The strengths, weaknesses, and design challenges of active BPFs are discussed. The available process technologies are investigated for the development of mm-wave filters. Active BPFs exhibit the merits of low loss, good outof- band rejection, good selectivity, and a high integration level. By applying loss compensation techniques, active BPFs are realized with low losses. The aim of this paper is to motivate research and development of high performance mm-wave BPFs, especially above the 60 GHz frequency band

Re-inventing postgraduate level teaching and learning in nanoelectronics

Abstract: In the world where technology changes almost daily, the field of microelectronics or nanoelectronics is becoming an area driving the future. Therefore, more engineers specializing in micro- and/or nanoelectronics are needed in industry internationally. Globally, a distinct shift in nanoelectronic education has already been observed, where postgraduate coursework and part-coursework degrees in microelectronics and nanoelectronics are now being offered alongside the traditional research or coursework degrees in electronics or electrical engineering (light currents). However, in South Africa the situation is lagging; microelectronic or nanoelectronic specializations are offered either as honors degrees or as the research-based studies mentioned, with no dedicated coursework specialization at the master’s level. The Faculty of Engineering and the Built Environment of the University of Johannesburg (UJ) has, therefore, diversified the program and qualifications mix because of this need to teach nanoelectronics at the master’s level as well, via global partcoursework and a part-research method of delivery. However, approval for a new degree takes a number of years to be completed. Therefore, as an alternative route, nanoelectronic modules with some cross-disciplinary and multi-disciplinary modules are offered as continuing education programs (CEPs) at National Qualification Framework levels 8 and 9. The CEPs bear continuing Engineering Council of South Africa professional development credits, and can be credited as modules in the envisaged master’s degrees. The CEPs are delivered via an online approach, which develops student accessibility and brings about flexibility for students who are studying part-time. Enhanced accessibility and the fastgrowing level of internet access in Africa will allow the UJ to serve students both regionally and internationally. This paper explores the rationale for the chosen content of the CEPs and ultimately the proposed master’s degrees and discusses in detail the online mode of delivery and its benefits, as well as the approach taken to deliver courses according to this model, together with innovative opportunities