Optimizing Photovoltaic Response by Tuning Light-Harvesting Nanocrystal Shape Synthesized Using a Quick Liquid-Gas Phase Reaction

The electron recombination lifetime in a sensitized semiconductor assembly is greatly influenced by the crystal structure and geometric form of the light-harvesting semiconductor nanocrystal. When such light harvesters with varying structural characteristics are configured in a photoanode, its interface with the electrolyte becomes equally important and directly influences the photovoltaic efficiency. We have systematically probed here the influence of nanocrystal crystallographic structure and shape on the electron recombination lifetime and its eventual influence on the light to electricity conversion efficiency of a liquid junction semiconductor sensitized solar cell. The light-harvesting cadmium sulfide (CdS) nanocrystals of distinctly different and controlled shapes are obtained using a novel and simple liquid gas phase synthesis method performed at different temperatures involving very short reaction times. High resolution synchrotron X-ray diffraction and spectroscopic studies respectively exhibit different crystallographic phase content and optical properties. When assembled on a mesoscopic TiO2 film by a linker molecule, they exhibit remarkable variation in electron recombination lifetime by 1 order of magnitude, as determined by ac-impedance spectroscopy. This also drastically affects the photovoltaic efficiency of the differently shaped nanocrystal sensitized solar cells.

PolyMage: Automatic Optimization for Image Processing Pipelines

This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious. The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.

A Stochastic Approximation Algorithm for Quantile Estimation

In this paper, we present two new stochastic approximation algorithms for the problem of quantile estimation. The algorithms uses the characterization of the quantile provided in terms of an optimization problem in 1]. The algorithms take the shape of a stochastic gradient descent which minimizes the optimization problem. Asymptotic convergence of the algorithms to the true quantile is proven using the ODE method. The theoretical results are also supplemented through empirical evidence. The algorithms are shown to provide significant improvement in terms of memory requirement and accuracy.

Conversion of plastic waste into CNTs using Ni/Mo/MgO catalystAn optimization approach by mixture experiment

A combustion technique is used to study the synthesis of carbon nano tubes from waste plastic as a precursor and Ni/Mo/MgO as a catalyst. The catalytic activity of three components Ni, Mo, MgO is measured in terms of amount of carbon product obtained. Different proportions of metal ions are optimized using mixture experiment in Design expert software. D-optimal design technique is adopted due to nonsimplex region and presence of constraints in the mixture experiment. The activity of the components is observed to be interdependent and the component Ni is found to be more effective. The catalyst containing Ni0.8Mo0.1MgO0.1 yields more carbon product. The structure of catalyst and CNTs are studied by using SEM, XRD, and Raman spectroscopy. SEM analysis shows the formation of longer CNTs with average diameter of 40-50 nm.

Design Optimization of Thin-Film Transistors Based on a Metal-Substrate-Semiconductor Architecture for High DC Voltage Sensing

We discuss the potential application of high dc voltage sensing using thin-film transistors (TFTs) on flexible substrates. High voltage sensing has potential applications for power transmission instrumentation. For this, we consider a gate metal-substrate-semiconductor architecture for TFTs. In this architecture, the flexible substrate not only provides mechanical support but also plays the role of the gate dielectric of the TFT. Hence, the thickness of the substrate needs to be optimized for maximizing transconductance, minimizing mechanical stress, and minimizing gate leakage currents. We discuss this optimization, and develop n-type and p-type organic TFTs using polyvinyldene fluoride as the substrate-gate insulator. Circuits are also realized to achieve level shifting, amplification, and high drain voltage operation.

A mode-shape classification technique for robust speech rate estimation and syllable nuclei detection

Acoustic feature based speech (syllable) rate estimation and syllable nuclei detection are important problems in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for both the problems consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem - mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora in a five-fold cross validation setup. The average correlation coefficients for the syllable rate estimation turn out to be 0.6761, 0.6928 and 0.3604 for three corpora respectively, which outperform those obtained by the best of the existing peak detection techniques. Similarly, the average F-scores (syllable level) for the syllable nuclei detection are 0.8917, 0.8200 and 0.7637 for three corpora respectively. (C) 2016 Elsevier B.V. All rights reserved.

Stimuli and shape responsive `boron-containing' luminescent organic materials

Recent advancements of material science and its applications have been immensely influenced by the modern development of organic luminescent materials. Among all organic luminogens, boron containing compounds have already established their stature as one of the indispensable classes of luminescent dyes. Boron, in its various forms e. g. triarylboranes, borate dyes and boron clusters, has attracted considerable attention owing to its several unique and excellent photophysical features. In very recent times, beyond the realms of solution-state studies, luminescent boron-containing compounds have emerged as a large and versatile class of stimuli responsive materials. Based on several fundamental concepts of chemistry, researchers have come up with an admirable variety of boron-containing materials with AIE (aggregation-induced emission), mechano-responsive luminescence, thermoresponsive-luminescence as well as a number of purely organic phosphorescent materials and other standalone examples. The unique chemical as well as physical properties of boron-containing compounds are largely responsible for the development of such materials. In this review these new findings are brought together.

Regulation of Growth, Cell Shape, Cell Division, and Gene Expression by Second Messengers (p)ppGpp and Cyclic Di-GMP in Mycobacterium smegmatis

The alarmone (p)ppGpp regulates transcription, translation, replication, virulence, lipid synthesis, antibiotic sensitivity, biofilm formation, and other functions in bacteria. Signaling nucleotide cyclic di-GMP (c-di-GMP) regulates biofilm formation, motility, virulence, the cell cycle, and other functions. In Mycobacterium smegmatis, both (p) ppGpp and c-di-GMP are synthesized and degraded by bifunctional proteins Rel(Msm) and DcpA, encoded by rel(Msm) and dcpA genes, respectively. We have previously shown that the Delta rel(Msm) and Delta dcpA knockout strains are antibiotic resistant and defective in biofilm formation, show altered cell surface properties, and have reduced levels of glycopeptidolipids and polar lipids in their cell wall (K. R. Gupta, S. Kasetty, and D. Chatterji, Appl Environ Microbiol 81:2571-2578, 2015, http://dx.doi.org/10.1128/AEM.03999-14). In this work, we have explored the phenotypes that are affected by both (p) ppGpp and c-di-GMP in mycobacteria. We have shown that both (p) ppGpp and c-di-GMP are needed to maintain the proper growth rate under stress conditions such as carbon deprivation and cold shock. Scanning electron microscopy showed that low levels of these second messengers result in elongated cells, while high levels reduce the cell length and embed the cells in a biofilm-like matrix. Fluorescence microscopy revealed that the elongated Delta rel(Msm) and Delta dcpA cells are multinucleate, while transmission electron microscopy showed that the elongated cells are multiseptate. Gene expression analysis also showed that genes belonging to functional categories such as virulence, detoxification, lipid metabolism, and cell-wall-related processes were differentially expressed. Our results suggests that both (p) ppGpp and c-di-GMP affect some common phenotypes in M. smegmatis, thus raising a possibility of cross talk between these two second messengers in mycobacteria. IMPORTANCE Our work has expanded the horizon of (p) ppGpp and c-di-GMP signaling in Gram-positive bacteria. We have come across a novel observation that M. smegmatis needs (p) ppGpp and c-di-GMP for cold tolerance. We had previously shown that the Delta rel(Msm) and Delta dcpA strains are defective in biofilm formation. In this work, the overproduction of (p) ppGpp and c-di-GMP encased M. smegmatis in a biofilm-like matrix, which shows that both (p) ppGpp and c-di-GMP are needed for biofilm formation. The regulation of cell length and cell division by (p) ppGpp was known in mycobacteria, but our work shows that c-di-GMP also affects the cell size and cell division in mycobacteria. This is perhaps the first report of c-di-GMP regulating cell division in mycobacteria.

SMO: An Integrated Approach to Intra-array and Inter-array Storage Optimization

The polyhedral model provides an expressive intermediate representation that is convenient for the analysis and subsequent transformation of affine loop nests. Several heuristics exist for achieving complex program transformations in this model. However, there is also considerable scope to utilize this model to tackle the problem of automatic memory footprint optimization. In this paper, we present a new automatic storage optimization technique which can be used to achieve both intra-array as well as inter-array storage reuse with a pre-determined schedule for the computation. Our approach works by finding statement-wise storage partitioning hyper planes that partition a unified global array space so that values with overlapping live ranges are not mapped to the same partition. Our heuristic is driven by a fourfold objective function which not only minimizes the dimensionality and storage requirements of arrays required for each high-level statement, but also maximizes inter statement storage reuse. The storage mappings obtained using our heuristic can be asymptotically better than those obtained by any existing technique. We implement our technique and demonstrate its practical impact by evaluating its effectiveness on several benchmarks chosen from the domains of image processing, stencil computations, and high-performance computing.

Energy conversion in shape memory alloy heat engine - Part II: Simulation

In this paper, a theoretical model proposed in Part I (Zhu et al., 2001a) is used to simulate the behavior of a twin crank NiTi SMA spring based heat engine, which has been experimentally studied by Iwanaga et al. (1988). The simulation results are compared favorably with the measurements. It is found that (1) output torque and heat efficiency decrease as rotation speed increase; (2) both output torque and output power increase with the increase of hot water temperature; (3) at high rotation speed, higher water temperature improves the heat efficiency. On the contrary, at low rotation speed, lower water temperature is more efficient; (4) the effects of initial spring length may not be monotonic as reported. According to the simulation, output torque, output power and heat efficiency increase with the decrease of spring length only in the low rotation speed case. At high rotation speed, the result might be on the contrary.

FEM Simulations and Optimization about Residual Stresses in Coating Structures with Functionally Graded Materials Layer

An elasto-plastic finite element method is developed to predict the residual stresses of thermal spraying coatings with functionally graded material layer. In numerical simulations, temperature sensitivity of various material constants is included and mix

Application of the Conjugate Gradient Optimization Algorithm of Neural Network on Laser Machining

在应用激光技术加工复杂曲面时,通常以采样点集为插值点来建立曲面函数,然后实现曲面上任意坐标点的精确定位。人工神经网络的BP算法能实现函数插值,但计算精度偏低,往往达不到插值精确要求,造成较大的加工误差。提出人工神经网络的共轭梯度最优化插值新算法,并通过实例仿真,证明了这种曲面精确定位方法的可行性,从而为激光加工的三维精确定位提供了一种良好解决方案。这种方法已经应用在实际中。

A Study of Composite Beam with Shape Memory Alloy Arbitrarily Embedded under Thermal and Mechanical Loadings

The constitutive relations and kinematic assumptions on the composite beam with shape memory alloy (SMA) arbitrarily embedded are discussed and the results related to the different kinematic assumptions are compared. As the approach of mechanics of materials is to study the composite beam with the SMA layer embedded, the kinematic assumption is vital. In this paper, we systematically study the kinematic assumptions influence on the composite beam deflection and vibration characteristics. Based on the different kinematic assumptions, the equations of equilibrium/motion are different. Here three widely used kinematic assumptions are presented and the equations of equilibrium/motion are derived accordingly. As the three kinematic assumptions change from the simple to the complex one, the governing equations evolve from the linear to the nonlinear ones. For the nonlinear equations of equilibrium, the numerical solution is obtained by using Galerkin discretization method and Newton-Rhapson iteration method. The analysis on the numerical difficulty of using Galerkin method on the post-buckling analysis is presented. For the post-buckling analysis, finite element method is applied to avoid the difficulty due to the singularity occurred in Galerkin method. The natural frequencies of the composite beam with the nonlinear governing equation, which are obtained by directly linearizing the equations and locally linearizing the equations around each equilibrium, are compared. The influences of the SMA layer thickness and the shift from neutral axis on the deflection, buckling and post-buckling are also investigated. This paper presents a very general way to treat thermo-mechanical properties of the composite beam with SMA arbitrarily embedded. The governing equations for each kinematic assumption consist of a third order and a fourth order differential equation with a total of seven boundary conditions. Some previous studies on the SMA layer either ignore the thermal constraint effect or implicitly assume that the SMA is symmetrically embedded. The composite beam with the SMA layer asymmetrically embedded is studied here, in which symmetric embedding is a special case. Based on the different kinematic assumptions, the results are different depending on the deflection magnitude because of the nonlinear hardening effect due to the (large) deflection. And this difference is systematically compared for both the deflection and the natural frequencies. For simple kinematic assumption, the governing equations are linear and analytical solution is available. But as the deflection increases to the large magnitude, the simple kinematic assumption does not really reflect the structural deflection and the complex one must be used. During the systematic comparison of computational results due to the different kinematic assumptions, the application range of the simple kinematic assumption is also evaluated. Besides the equilibrium study of the composite laminate with SMA embedded, the buckling, post-buckling, free and forced vibrations of the composite beam with the different configurations are also studied and compared.

Depth dependence of nanohardness in a CuAlNi single crystal shape memory alloy

Instrumented nanoindentation was employed to study the depth dependence of nanohardness in a CuAlNi single crystal shape memory alloy that exhibits shape memory effect (SME). A Berkovich indenter and a cube comer indenter were used in this study, and the