Physics and chemistry of CdTe/CdS thin film heterojunction photovoltaic devices: fundamental and critical aspects

Among the armoury of photovoltaic materials, thin film heterojunction photovoltaics continue to be a promising candidate for solar energy conversion delivering a vast scope in terms of device design and fabrication. Their production does not require expensive semiconductor substrates and high temperature device processing, which allows reduced cost per unit area while maintaining reasonable efficiency. In this regard, superstrate CdTe/CdS solar cells are extensively investigated because of their suitable bandgap alignments, cost effective methods of production at large scales and stability against proton/electron irradiation. The conversion efficiencies in the range of 6-20% are achieved by structuring the device by varying the absorber/window layer thickness, junction activation/annealing steps, with more suitable front/back contacts, preparation techniques, doping with foreign ions, etc. This review focuses on fundamental and critical aspects like: (a) choice of CdS window layer and CdTe absorber layer; (b) drawbacks associated with the device including environmental problems, optical absorption losses and back contact barriers; (c) structural dynamics at CdS-CdTe interface; (d) influence of junction activation process by CdCl2 or HCF2Cl treatment; (e) interface and grain boundary passivation effects; (f) device degradation due to impurity diffusion and stress; (g) fabrication with suitable front and back contacts; (h) chemical processes occurring at various interfaces; (i) strategies and modifications developed to improve their efficiency. The complexity involved in understanding the multiple aspects of tuning the solar cell efficiency is reviewed in detail by considering the individual contribution from each component of the device. It is expected that this review article will enrich the materials aspects of CdTe/CdS devices for solar energy conversion and stimulate further innovative research interest on this intriguing topic.

Estimating the volume of glaciers in the Himalayan-Karakoram region using different methods

Ice volume estimates are crucial for assessing water reserves stored in glaciers. Due to its large glacier coverage, such estimates are of particular interest for the Himalayan-Karakoram (HK) region. In this study, different existing methodologies are used to estimate the ice reserves: three area-volume relations, one slope-dependent volume estimation method, and two ice-thickness distribution models are applied to a recent, detailed, and complete glacier inventory of the HK region, spanning over the period 2000-2010 and revealing an ice coverage of 40 775 km(2). An uncertainty and sensitivity assessment is performed to investigate the influence of the observed glacier area and important model parameters on the resulting total ice volume. Results of the two ice-thickness distribution models are validated with local ice-thickness measurements at six glaciers. The resulting ice volumes for the entire HK region range from 2955 to 4737 km(3), depending on the approach. This range is lower than most previous estimates. Results from the ice thickness distribution models and the slope-dependent thickness estimations agree well with measured local ice thicknesses. However, total volume estimates from area-related relations are larger than those from other approaches. The study provides evidence on the significant effect of the selected method on results and underlines the importance of a careful and critical evaluation.

A critical review of the definition of FRA resonance frequency of transformers as per IEEE Std C57.149-2012

The explanation of resonance given in IEEE Std C57.149-2012 to define resonance during frequency response analysis (FRA) measurements on transformers implicitly uses the conditions prevalent during resonance in a series R-L-C circuit. This dependence is evident from the two assertions made in the definition, viz., resulting in zero net reactive impedance, and, accompanied by a zero value appearing in the phase angle of the frequency response function. These two conditions are satisfied (at resonance) only in a series R-L-C circuit and certainly not in a transformer, as has been assumed in the Standard. This can be proved by considering a ladder-network model. Circuit analysis of this ladder network reveals the origin of this fallacy and proves that, at resonance, neither is the ladder network purely resistive and nor is the phase angle (between input voltage and input current) always zero. Also, during FRA measurements, it is often seen that phase angle does not traverse the conventional cyclic path from +90 degrees to -90 degrees (or vice versa) at all resonant frequencies. This peculiar feature can also be explained using pole-zero maps. Simple derivations, simulations and experimental results on an actual winding are presented. In summary, authors believe that this study dispels existing misconceptions about definition of FRA resonance and provides material for its correction in IEEE Std C57.149-2012. (C) 2014 Elsevier B.V. All rights reserved.

Operand Isolation Circuits with Reduced Overhead for Low Power Data-Path Design

Dynamic power dissipation due to redundant switching is an important metric in data-path design. This paper focuses on the use of ingenious operand isolation circuits for low power design. Operand isolation attempts to reduce switching by clamping or latching the output of a first level of combinational circuit. This paper presents a novel method using power supply switching wherein both PMOS and NMOS stacks of a circuit are connected to the same power supply. Thus, the output gets clamped or latched to the power supply value with minimal leakage. The proposed circuits make use of only two transistors to clamp the entire Multiple Input Multiple Output (MIMO) block. Also, the latch-based designs have higher drive strength in comparison to the existing methods. Simulation results have shown considerable area reduction in comparison to the existing techniques without increasing timing overhead.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

De-DUFing the DUFs: Deciphering distant evolutionary relationships of Domains of Unknown Function using sensitive homology detection methods

Background: In the post-genomic era where sequences are being determined at a rapid rate, we are highly reliant on computational methods for their tentative biochemical characterization. The Pfam database currently contains 3,786 families corresponding to ``Domains of Unknown Function'' (DUF) or ``Uncharacterized Protein Family'' (UPF), of which 3,087 families have no reported three-dimensional structure, constituting almost one-fourth of the known protein families in search for both structure and function. Results: We applied a `computational structural genomics' approach using five state-of-the-art remote similarity detection methods to detect the relationship between uncharacterized DUFs and domain families of known structures. The association with a structural domain family could serve as a start point in elucidating the function of a DUF. Amongst these five methods, searches in SCOP-NrichD database have been applied for the first time. Predictions were classified into high, medium and low-confidence based on the consensus of results from various approaches and also annotated with enzyme and Gene ontology terms. 614 uncharacterized DUFs could be associated with a known structural domain, of which high confidence predictions, involving at least four methods, were made for 54 families. These structure-function relationships for the 614 DUF families can be accessed on-line at http://proline.biochem.iisc.ernet.in/RHD_DUFS/. For potential enzymes in this set, we assessed their compatibility with the associated fold and performed detailed structural and functional annotation by examining alignments and extent of conservation of functional residues. Detailed discussion is provided for interesting assignments for DUF3050, DUF1636, DUF1572, DUF2092 and DUF659. Conclusions: This study provides insights into the structure and potential function for nearly 20 % of the DUFs. Use of different computational approaches enables us to reliably recognize distant relationships, especially when they converge to a common assignment because the methods are often complementary. We observe that while pointers to the structural domain can offer the right clues to the function of a protein, recognition of its precise functional role is still `non-trivial' with many DUF domains conserving only some of the critical residues. It is not clear whether these are functional vestiges or instances involving alternate substrates and interacting partners. Reviewers: This article was reviewed by Drs Eugene Koonin, Frank Eisenhaber and Srikrishna Subramanian.

Search For Critical Slip Surface In Slope Stability Analysis By Spline-Based Ga Method

The stability of a soil slope is usually analyzed by limit equilibrium methods, in which the identification of the critical slip surface is of principal importance. In this study the spline curve in conjunction with a genetic algorithm is used to search the critical slip surface, and Spencer's method is employed to calculate the factor of safety. Three examples are presented to illustrate the reliability and efficiency of the method. Slip surfaces defined by a series of straight lines are compared with those defined by spline curves, and the results indicate that use of spline curves renders better results for a given number of slip surface nodal points comparing with the approximation using straight line segments.

Analytical Methods of Residual Strength in Injecting Water Pipeline

In this paper, common criterions about residual strength evaluation at home and abroad are generalized and seven methods are acquired, namely ASME-B31G, DM, Wes-2805-97, CVDA-84, Burdekin, Irwin and J integral methods. BP neural network are Combined with Genetic Algorithm (GA) named by modified BP-GA methods to successfully predict residual strength and critical pressure of injecting water, corrosion pipelines. Examples are shown that calculation results of every kind of method have great difference and calculating values of Wes-2805-97 criterion, ASME-B31G criterion, CVDA-84 criterion and Irwin fracture mechanics model are conservative and higher than, those of J integral methods while calculating values of Burdiken model and DM fracture mechanics model are dangerous and less than those of J integral methods and calculating values of modified BP-GA methods are close and moderate to those of J integral methods. Therefore modified BP-GA methods and J integral methods are considered better methods to calculate residual strength and critical pressure of injecting water corrosion pipelines

Occurrence of spanning of a submarine pipeline with initial embedment

For better understanding the mechanism of the occurrence of pipeline span for a pipeline with initial embedment, physical and numerical methods are adopted in this study. Experimental observations show that there often exist three characteristic phases in the process of the partially embedded pipeline being suspended: (a) local scour around pipe; (b) onset of soil erosion beneath pipe; and (c) complete suspension of pipe. The effects of local scour on the onset of soil erosion beneath the pipe are much less than those of soil seepage failure induced by the pressure drop. Based on the above observations and analyses, the mechanism of the occurrence of pipeline spanning is analyzed numerically in view of soil seepage failure. In the numerical analyses, the current-induced pressure along the soil surface in the vicinity of the pipe (i.e. the pressure drop) is firstly obtained by solving the N-S equations, thereafter the seepage flow in the soil is calculated with the obtained pressure drop as the boundary conditions along the soil surface. Numerical results indicate that the seepage failure (or piping) may occur at the exit of the seepage path when the pressure gradient gets larger than the critical value. The numerical treatment provides a practical tool for evaluating the potentials for the occurrence of pipe span due to the soil seepage failure.

Advanced density functional theory methods for materials science

In this work we chiefly deal with two broad classes of problems in computational materials science, determining the doping mechanism in a semiconductor and developing an extreme condition equation of state. While solving certain aspects of these questions is well-trodden ground, both require extending the reach of existing methods to fully answer them. Here we choose to build upon the framework of density functional theory (DFT) which provides an efficient means to investigate a system from a quantum mechanics description.

Zinc Phosphide (Zn₃P₂) could be the basis for cheap and highly efficient solar cells. Its use in this regard is limited by the difficulty in n-type doping the material. In an effort to understand the mechanism behind this, the energetics and electronic structure of intrinsic point defects in zinc phosphide are studied using generalized Kohn-Sham theory and utilizing the Heyd, Scuseria, and Ernzerhof (HSE) hybrid functional for exchange and correlation. Novel 'perturbation extrapolation' is utilized to extend the use of the computationally expensive HSE functional to this large-scale defect system. According to calculations, the formation energy of charged phosphorus interstitial defects are very low in n-type Zn₃P₂ and act as 'electron sinks', nullifying the desired doping and lowering the fermi-level back towards the p-type regime. Going forward, this insight provides clues to fabricating useful zinc phosphide based devices. In addition, the methodology developed for this work can be applied to further doping studies in other systems.

Accurate determination of high pressure and temperature equations of state is fundamental in a variety of fields. However, it is often very difficult to cover a wide range of temperatures and pressures in an laboratory setting. Here we develop methods to determine a multi-phase equation of state for Ta through computation. The typical means of investigating thermodynamic properties is via ’classical’ molecular dynamics where the atomic motion is calculated from Newtonian mechanics with the electronic effects abstracted away into an interatomic potential function. For our purposes, a ’first principles’ approach such as DFT is useful as a classical potential is typically valid for only a portion of the phase diagram (i.e. whatever part it has been fit to). Furthermore, for extremes of temperature and pressure quantum effects become critical to accurately capture an equation of state and are very hard to capture in even complex model potentials. This requires extending the inherently zero temperature DFT to predict the finite temperature response of the system. Statistical modelling and thermodynamic integration is used to extend our results over all phases, as well as phase-coexistence regions which are at the limits of typical DFT validity. We deliver the most comprehensive and accurate equation of state that has been done for Ta. This work also lends insights that can be applied to further equation of state work in many other materials.

Signatures of Topological Superconductors

Topological superconductors are particularly interesting in light of the active ongoing experimental efforts for realizing exotic physics such as Majorana zero modes. These systems have excitations with non-Abelian exchange statistics, which provides a path towards topological quantum information processing. Intrinsic topological superconductors are quite rare in nature. However, one can engineer topological superconductivity by inducing effective p-wave pairing in materials which can be grown in the laboratory. One possibility is to induce the proximity effect in topological insulators; another is to use hybrid structures of superconductors and semiconductors.

The proposal of interfacing s-wave superconductors with quantum spin Hall systems provides a promising route to engineered topological superconductivity. Given the exciting recent progress on the fabrication side, identifying experiments that definitively expose the topological superconducting phase (and clearly distinguish it from a trivial state) raises an increasingly important problem. With this goal in mind, we proposed a detection scheme to get an unambiguous signature of topological superconductivity, even in the presence of ordinarily detrimental effects such as thermal fluctuations and quasiparticle poisoning. We considered a Josephson junction built on top of a quantum spin Hall material. This system allows the proximity effect to turn edge states in effective topological superconductors. Such a setup is promising because experimentalists have demonstrated that supercurrents indeed flow through quantum spin Hall edges. To demonstrate the topological nature of the superconducting quantum spin Hall edges, theorists have proposed examining the periodicity of Josephson currents respect to the phase across a Josephson junction. The periodicity of tunneling currents of ground states in a topological superconductor Josephson junction is double that of a conventional Josephson junction. In practice, this modification of periodicity is extremely difficult to observe because noise sources, such as quasiparticle poisoning, wash out the signature of topological superconductors. For this reason, We propose a new, relatively simple DC measurement that can compellingly reveal topological superconductivity in such quantum spin Hall/superconductor heterostructures. More specifically, We develop a general framework for capturing the junction's current-voltage characteristics as a function of applied magnetic flux. Our analysis reveals sharp signatures of topological superconductivity in the field-dependent critical current. These signatures include the presence of multiple critical currents and a non-vanishing critical current for all magnetic field strengths as a reliable identification scheme for topological superconductivity.

This system becomes more interesting as interactions between electrons are involved. By modeling edge states as a Luttinger liquid, we find conductance provides universal signatures to distinguish between normal and topological superconductors. More specifically, we use renormalization group methods to extract universal transport characteristics of superconductor/quantum spin Hall heterostructures where the native edge states serve as a lead. Interestingly, arbitrarily weak interactions induce qualitative changes in the behavior relative to the free-fermion limit, leading to a sharp dichotomy in conductance for the trivial (narrow superconductor) and topological (wide superconductor) cases. Furthermore, we find that strong interactions can in principle induce parafermion excitations at a superconductor/quantum spin Hall junction.

As we identify the existence of topological superconductor, we can take a step further. One can use topological superconductor for realizing Majorana modes by breaking time reversal symmetry. An advantage of 2D topological insulator is that networks required for braiding Majoranas along the edge channels can be obtained by adjoining 2D topological insulator to form corner junctions. Physically cutting quantum wells for this purpose, however, presents technical challenges. For this reason, I propose a more accessible means of forming networks that rely on dynamically manipulating the location of edge states inside of a single 2D topological insulator sheet. In particular, I show that edge states can effectively be dragged into the system's interior by gating a region near the edge into a metallic regime and then removing the resulting gapless carriers via proximity-induced superconductivity. This method allows one to construct rather general quasi-1D networks along which Majorana modes can be exchanged by electrostatic means.

Apart from 2D topological insulators, Majorana fermions can also be generated in other more accessible materials such as semiconductors. Following up on a suggestion by experimentalist Charlie Marcus, I proposed a novel geometry to create Majorana fermions by placing a 2D electron gas in proximity to an interdigitated superconductor-ferromagnet structure. This architecture evades several manufacturing challenges by allowing single-side fabrication and widening the class of 2D electron gas that may be used, such as the surface states of bulk semiconductors. Furthermore, it naturally allows one to trap and manipulate Majorana fermions through the application of currents. Thus, this structure may lead to the development of a circuit that enables fully electrical manipulation of topologically-protected quantum memory. To reveal these exotic Majorana zero modes, I also proposed an interference scheme to detect Majorana fermions that is broadly applicable to any 2D topological superconductor platform.

A computer-aided investigation of motion detection units in the fly

This work deals with two related areas: processing of visual information in the central nervous system, and the application of computer systems to research in neurophysiology.

Certain classes of interneurons in the brain and optic lobes of the blowfly Calliphora phaenicia were previously shown to be sensitive to the direction of motion of visual stimuli. These units were identified by visual field, preferred direction of motion, and anatomical location from which recorded. The present work is addressed to the questions: (1) is there interaction between pairs of these units, and (2) if such relationships can be found, what is their nature. To answer these questions, it is essential to record from two or more units simultaneously, and to use more than a single recording electrode if recording points are to be chosen independently. Accordingly, such techniques were developed and are described.

One must also have practical, convenient means for analyzing the large volumes of data so obtained. It is shown that use of an appropriately designed computer system is a profitable approach to this problem. Both hardware and software requirements for a suitable system are discussed and an approach to computer-aided data analysis developed. A description is given of members of a collection of application programs developed for analysis of neuro-physiological data and operated in the environment of and with support from an appropriate computer system. In particular, techniques developed for classification of multiple units recorded on the same electrode are illustrated as are methods for convenient graphical manipulation of data via a computer-driven display.

By means of multiple electrode techniques and the computer-aided data acquisition and analysis system, the path followed by one of the motion detection units was traced from open optic lobe through the brain and into the opposite lobe. It is further shown that this unit and its mirror image in the opposite lobe have a mutually inhibitory relationship. This relationship is investigated. The existence of interaction between other pairs of units is also shown. For pairs of units responding to motion in the same direction, the relationship is of an excitatory nature; for those responding to motion in opposed directions, it is inhibitory.

Experience gained from use of the computer system is discussed and a critical review of the current system is given. The most useful features of the system were found to be the fast response, the ability to go from one analysis technique to another rapidly and conveniently, and the interactive nature of the display system. The shortcomings of the system were problems in real-time use and the programming barrier—the fact that building new analysis techniques requires a high degree of programming knowledge and skill. It is concluded that computer system of the kind discussed will play an increasingly important role in studies of the central nervous system.

DIFFERENTIAL GEOMETRICAL METHODS IN THE STUDY OF OPTICAL-TRANSMISSION (SCALAR THEORY) .1. STATIC TRANSMISSION CASE

Static optical transmission is restudied by postulation of the optical path as the proper element in a three-dimensional Riemannian manifold (no torsion); this postulation can be applied to describe the light-medium interactive system. On the basis of the postulation, the behaviors of light transmitting through the medium with refractive index n are investigated, the investigation covering the realms of both geometrical optics and wave optics. The wave equation of light in static transmission is studied modally, the postulation being employed to derive the exact form of the optical field equation in a medium (in which the light is viewed as a single-component field). Correspondingly, the relationships concerning the conservation of optical fluid and the dynamic properties are given, and some simple applications of the theories mentioned are presented.

18S rRNA V9 metabarcoding for diet characterization: a critical evaluation with two sympatric zooplanktivorous fish species

The potential of the 18S rRNA V9 metabarcoding approach for diet assessment was explored using MiSeq paired-end (PE; 2 9 150 bp) technology. To critically evaluate the method's performance with degraded/digested DNA, the diets of two zooplanktivorous fish species from the Bay of Biscay, European sardine (Sardina pilchardus) and European sprat (Sprattus sprattus), were analysed. The taxonomic resolution and quantitative potential of the 18S V9 metabarcoding was first assessed both in silico and with mock and field plankton samples. Our method was capable of discriminating species within the reference database in a reliable way providing there was at least one variable position in the 18S V9 region. Furthermore, it successfully discriminated diet between both fish species, including habitat and diel differences among sardines, overcoming some of the limitations of traditional visual-based diet analysis methods. The high sensitivity and semi-quantitative nature of the 18S V9 metabarcoding approach was supported by both visual microscopy and qPCR-based results. This molecular approach provides an alternative cost and time effective tool for food-web analysis.

Do we know the strength of the chorioamnion? A critical review and analysis

The chorioamnion is the membrane that surrounds the fetus during gestation. Normally, it must remain intact for the duration of pregnancy, 37-42 weeks, and only rupture during or just before labour and delivery of the fetus. In a significant number (3%) of all births, this does not happen, and membranes rupture before term, resulting in preterm birth and significant perinatal morbidity. It is known that the material properties of chorioamnion may play a major role in mechanical rupture; a number of studies have been undertaken to characterise the physical nature of chorioamnion and examine factors that may predispose to rupture. However, the existing literature is inconsistent in its choice of both physical testing methods and data analysis techniques, motivating the current review. Experimental data from a large number of chorioamnion mechanical studies were collated, and data were converted to standard engineering quantities. The failure strength of the chorioamnion membrane was found consistently to value approximately 0.9 MPa. It is hoped that past and future studies of membrane mechanics can provide insight into the role of chorioamnion in labour and delivery. In addition, biomechanical approaches can help elucidate the potential causes of early rupture, and suggest future protocols or treatments that could both diagnose and prevent its occurrence. © 2009 Elsevier Ireland Ltd.