Significant reduction in arc frequency biased solar cells: Observations, diagnostics, and mitigation technique(s)

A variety of experiments were performed which identify key factors contributing to the arcing of negatively biased high voltage solar cells. These efforts have led to reduction of greater than a factor of 100 in the arc frequency of a single cell following proper remediation procedures. Experiments naturally lead to and focussed on the adhesive/encapsulant that is used to bond the protective cover slip to the solar cell. An image-intensified charge coupled device (CCD) camera system recorded UV emission from arc events which occurred exclusively along the interfacial edge between the cover slip and the solar cell. Microscopic inspection of this interfacial region showed a bead of encapsulant along this entire edge. Elimination of this encapsulant bead reduced the arc frequency by two orders of magnitude. Water contamination was also identified as a key contributor which enhances arcing of the encapsulant bead along the solar cell edge. Spectrally resolved measurements of the observable UV light shows a feature assignable to OH(A-X) electronic emission, which is common for water contaminated discharges. Experiments in which the solar cell temperature was raised to 85 C showed a reduced arcing frequency, suggesting desorption of H2O. Exposing the solar cell to water vapor was shown to increase the arcing frequency. Clean dry gases such as O2, N2, and Ar show no enhancement of the arcing rate. Elimination of the exposed encapsulant eliminates any measurable sensitivity to H2O vapor

Overview of recent developments in organic thin-film transistor sensor technology

Bio and chemical sensing represents one of the most attractive applications of organic electronics and of Organic Thin Film Transistors (OTFTs) in particular. The implementation of miniaturized portable systems for the detection of chemical analytes as well as of biological species, is still a challenge for the sensors’ community. In this respect OTFTs appear as a new class of sensors able, in principle, to overcome some of the commercial sensors drawbacks. As far as volatile analytes are concerned, commercially available sensing systems, such as metal oxide based chemi-resistors, offer great stability but rather poor selectivity. In spite of the improved selectivity offered by organic chemi-resistors the reliability of such devices is not yet satisfactorily proven. On the other hand, complex odors recognition, but also explosives or pathogen bacteria detection are currently being addressed by sensor array systems, called “e-noses”, that try to mimic the mammalian olfactory system. Even though potentially very effective, this technology has not yet reached the performance level required by the market mostly because miniaturization and cost effective production issues. OTFT sensors can offer the advantage of room temperature operation and deliver high repeatable responses. Beside, they show very good selectivity properties. In fact, they implement organic active layers, which behave as sensing layers as well. This improves OTFTs sensitivity towards different chemical and biological analytes as organic materials can be properly chemically tailored to achieve differential detection and potentially even discrimination of biological species. In addition to this, OTFTs are also able to offer the unique advantages of a multi-parametric response and a gate bias enhanced sensitivity. Recently thin dielectric low-voltage OTFTs have also been demonstrated. Their implementation in low power consumption devices has attracted the attention of the organic electronic community. But such low power transistors have also a great potential in sensing applications specifically those performed in a liquid environment. In fact, low-voltage OTFTs have been recently demonstrated to deliver reliable responses even when operated in water for hundreds of measurement cycles. This open new perspectives in the field of cheap, low-power and mass-produced aqueous sensors

Time-dependent Hamiltonian estimation for Doppler velocimetry of trapped ions

The time evolution of a closed quantum system is connected to its Hamiltonian through Schroedinger's equation. The ability to estimate the Hamiltonian is critical to our understanding of quantum systems, and allows optimization of control. Though spectroscopic methods allow time-independent Hamiltonians to be recovered, for time-dependent Hamiltonians this task is more challenging. Here, using a single trapped ion, we experimentally demonstrate a method for estimating a time-dependent Hamiltonian of a single qubit. The method involves measuring the time evolution of the qubit in a fixed basis as a function of a time-independent offset term added to the Hamiltonian. In our system the initially unknown Hamiltonian arises from transporting an ion through a static, near-resonant laser beam. Hamiltonian estimation allows us to estimate the spatial dependence of the laser beam intensity and the ion's velocity as a function of time. This work is of direct value in optimizing transport operations and transport-based gates in scalable trapped ion quantum information processing, while the estimation technique is general enough that it can be applied to other quantum systems, aiding the pursuit of high operational fidelities in quantum control.Comment: 10 pages, 8 figure

A structured index describing the ease of disassembly for handcrafted product

Both economic and environmental aspects significantly influence the design process since the early phases of preliminary design. The total Life Cycle Assessment (LCA) and the End of Life (EoL) of products have to be defined in the early design phases too but, for industrial products that are not feasible to automatic production, they are hard issues. However, the EoL of products can be assessed by evaluating the disassembly of joints assembling the product, even when the production process is subject to an important contribute of workmanship. In this paper, a useful method is proposed to analyze the disassembly plant of products, in order to optimize the design process in the early preliminary phases. The method quantitatively evaluates a Disassembly Index that describes the attitude of a product to be disassembled. A case study describes the disassembly attitude of structural subassemblies of a sailboat. In order to test the applicability of the model described to both manual and automated disassembly, a further application of the method is proposed on a Computer CPU. As result, the model demonstrated good sensitiveness to the testing of products quite different for dimensions, number of components, manufacturing processes and, in all cases, it quantified the disassembly easiness with good relevance

A network analysis of the relationship among reading, spelling and maths skills

Background. Skill learning (e.g., reading, spelling and maths) has been predominantly treated separately in the neuropsychological literature. However, skills (as well as their corresponding deficits), tend to partially overlap. We recently proposed a multi-level model of learning skills (based on the distinction among competence, performance, and acquisition) as a framework to provide a unitary account of these learning skills. In the present study, we examined the performance of an unselected group of third-to fifth-grade children on standard reading, spelling, and maths tasks, and tested the relationships among these skills with a network analysis, i.e., a method particularly suited to analysing relations among different domains. Methods. We administered a battery of reading, spelling, and maths tests to 185 third-, fourth-, and fifth-grade children (103 M, 82 F). Results. The network analysis indicated that the different measures of the same ability (i.e., reading, spelling, and maths) formed separate clusters, in keeping with the idea that they are based on different competences. However, these clusters were also related to each other, so that three nodes were more central in connecting them. In keeping with the multi-level model of learning skills, two of these tests (arithmetic facts subtest and spelling words with ambiguous transcription) relied heavily on the ability to recall specific instances, a factor hypothesised to underlie the co-variation among learning skills. Conclusions. The network analysis indicated both elements of association and of partial independence among learning skills. Interestingly, the study was based on standard clinical instruments, indicating that the multi-level model of learning skills might provide a framework for the clinical analysis of these learning skills

Two different quasiparticle scattering rates in vortex line liquid phase of layered d-wave superconductors

We carry out a quantum mechanical analysis of the behavior of nodal quasiparticles in the vortex line liquid phase of planar d-wave superconductors. Applying a novel path integral technique we calculate a number of experimentally relevant observables and demonstrate that in the low-field regime the quasiparticle scattering rates deduced from photoemission and thermal transport data can be markedly different from that extracted from tunneling, specific heat, superfluid stiffness or spin-lattice relaxation time.Comment: Latex, 4 pages, no figure

The pasta phase within density dependent hadronic models

In the present paper we investigate the onset of the pasta phase with different parametrisations of the density dependent hadronic model and compare the results with one of the usual parametrisation of the non-linear Walecka model. The influence of the scalar-isovector virtual delta meson is shown. At zero temperature two different methods are used, one based on coexistent phases and the other on the Thomas-Fermi approximation. At finite temperature only the coexistence phases method is used. npe matter with fixed proton fractions and in beta-equilibrium are studied. We compare our results with restrictions imposed on the the values of the density and pressure at the inner edge of the crust, obtained from observations of the Vela pulsar and recent isospin diffusion data from heavy-ion reactions, and with predictions from spinodal calculations.Comment: 15 pages, 11 figures and 7 table

Sampling protein motion and solvent effect during ligand binding.

An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one

q- Deformed Boson Expansions

A deformed boson mapping of the Marumori type is derived for an underlying $su(2)$ algebra. As an example, we bosonize a pairing hamiltonian in a two level space, for which an exact treatment is possible. Comparisons are then made between the exact result, our q- deformed boson expansion and the usual non - deformed expansion.Comment: 8 pages plus 2 figures (available upon request