8,714 research outputs found

    Steric engineering of metal-halide perovskites with tunable optical band gaps

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    Owing to their high energy-conversion efficiency and inexpensive fabrication routes, solar cells based on metal-organic halide perovskites have rapidly gained prominence as a disruptive technology. An attractive feature of perovskite absorbers is the possibility of tailoring their properties by changing the elemental composition through the chemical precursors. In this context, rational in silico design represents a powerful tool for mapping the vast materials landscape and accelerating discovery. Here we show that the optical band gap of metal-halide perovskites, a key design parameter for solar cells, strongly correlates with a simple structural feature, the largest metal-halide-metal bond angle. Using this descriptor we suggest continuous tunability of the optical gap from the mid-infrared to the visible. Precise band gap engineering is achieved by controlling the bond angles through the steric size of the molecular cation. Based on these design principles we predict novel low-gap perovskites for optimum photovoltaic efficiency, and we demonstrate the concept of band gap modulation by synthesising and characterising novel mixed-cation perovskites.Comment: This manuscript was submitted for publication on March 6th, 2014. Many of the results presented in this manuscript were presented at the International Conference on Solution processed Semiconductor Solar Cells, held in Oxford, UK, on 10-12 September 2014. The manuscript is 37 pages long and contains 8 figure

    Conditional sampling for barrier option pricing under the LT method

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    We develop a conditional sampling scheme for pricing knock-out barrier options under the Linear Transformations (LT) algorithm from Imai and Tan (2006). We compare our new method to an existing conditional Monte Carlo scheme from Glasserman and Staum (2001), and show that a substantial variance reduction is achieved. We extend the method to allow pricing knock-in barrier options and introduce a root-finding method to obtain a further variance reduction. The effectiveness of the new method is supported by numerical results

    Program for computing partial pressures from residual gas analyzer data

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    A computer program for determining the partial pressures of various gases from residual-gas-analyzer data is given. The analysis of the ion currents of 18 m/e spectrometer peaks allows the determination of 12 gases simultaneously. Comparison is made to ion-gage readings along with certain other control information. The output data are presented in both tabular and graphical form

    Universality and Clustering in 1+1 Dimensional Superstring-Bit Models

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    We construct a 1+1 dimensional superstring-bit model for D=3 Type IIB superstring. This low dimension model escapes the problems encountered in higher dimension models: (1) It possesses full Galilean supersymmetry; (2) For noninteracting polymers of bits, the exactly soluble linear superpotential describing bit interactions is in a large universality class of superpotentials which includes ones bounded at spatial infinity; (3) The latter are used to construct a superstring-bit model with the clustering properties needed to define an SS-matrix for closed polymers of superstring-bits.Comment: 11 pages, Latex documen

    Optimal randomized multilevel algorithms for infinite-dimensional integration on function spaces with ANOVA-type decomposition

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    In this paper, we consider the infinite-dimensional integration problem on weighted reproducing kernel Hilbert spaces with norms induced by an underlying function space decomposition of ANOVA-type. The weights model the relative importance of different groups of variables. We present new randomized multilevel algorithms to tackle this integration problem and prove upper bounds for their randomized error. Furthermore, we provide in this setting the first non-trivial lower error bounds for general randomized algorithms, which, in particular, may be adaptive or non-linear. These lower bounds show that our multilevel algorithms are optimal. Our analysis refines and extends the analysis provided in [F. J. Hickernell, T. M\"uller-Gronbach, B. Niu, K. Ritter, J. Complexity 26 (2010), 229-254], and our error bounds improve substantially on the error bounds presented there. As an illustrative example, we discuss the unanchored Sobolev space and employ randomized quasi-Monte Carlo multilevel algorithms based on scrambled polynomial lattice rules.Comment: 31 pages, 0 figure

    Kids Don’t Float…and Their Parents Don’t Either: Using a Family-Centered Approach in Alaska’s Kids Don’t Float Program

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    The goal of this experiential report is to outline the adoption of a family-centered Kids Don’t Float approach. We conducted a critical synthesis of information to reflect the expansion of the Kids Don’t Float program into a more family-centered approach. The critical synthesis provided insights into why we should adopt this approach, how it was implemented, and how it influenced drowning incidents compared to the previously used child-centered approach. The adoption of a family-centered approach may contribute to reducing drowning incidents by targeting parents, providing safety information to families, and promoting parental modelling of life jackets. Program evaluators and water safety advocates may use these insights to strengthen injury prevention programs that target drowning incidents
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