Device and circuit-level performance of carbon nanotube field-effect transistor with benchmarking against a nano-MOSFET

The performance of a semiconducting carbon nanotube (CNT) is assessed and tabulated for parameters against those of a metal-oxide-semiconductor field-effect transistor (MOSFET). Both CNT and MOSFET models considered agree well with the trends in the available experimental data. The results obtained show that nanotubes can significantly reduce the drain-induced barrier lowering effect and subthreshold swing in silicon channel replacement while sustaining smaller channel area at higher current density. Performance metrics of both devices such as current drive strength, current on-off ratio (Ion/Ioff), energy-delay product, and power-delay product for logic gates, namely NAND and NOR, are presented. Design rules used for carbon nanotube field-effect transistors (CNTFETs) are compatible with the 45-nm MOSFET technology. The parasitics associated with interconnects are also incorporated in the model. Interconnects can affect the propagation delay in a CNTFET. Smaller length interconnects result in higher cutoff frequency. © 2012 Tan et al.

Fabrication of excitonic luminescent inorganic-organic hybrid nano- and microcrystals

Inorganic-organic (IO) hybrid nano- and microcrystals are fabricated by a low-cost, environmentally friendly and easily scaled-up route. Lead(II) iodide (PbI 2) nano/microcrystals are obtained by solvothermal techniques and subsequent IO hybrid (C 12H 25NH 3) 2PbI 4 crystals are produced by intercalation of the organic moiety. The hexagonally shaped crystals obtained range in size from 20 nm to ∼7 μm. Sequential stacking of inorganic/organic layers in these IO hybrid crystals results in strong room-temperature exciton photoluminescence, wherein the excitons are confined within the inorganic sheets. © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Multiple classifier boosting and tree-structured classifiers

Visual recognition problems often involve classification of myriads of pixels, across scales, to locate objects of interest in an image or to segment images according to object classes. The requirement for high speed and accuracy makes the problems very challenging and has motivated studies on efficient classification algorithms. A novel multi-classifier boosting algorithm is proposed to tackle the multimodal problems by simultaneously clustering samples and boosting classifiers in Section 2. The method is extended into an online version for object tracking in Section 3. Section 4 presents a tree-structured classifier, called Super tree, to further speed up the classification time of a standard boosting classifier. The proposed methods are demonstrated for object detection, tracking and segmentation tasks. © 2013 Springer-Verlag Berlin Heidelberg.

A structured modelling approach to simulating dynamic behaviours in complex organisations

This article reports a case study application of a systematic approach to modelling complex organisations, centred on simulation modelling (SM). The approach leads to populated instances of complementary model types, in ways that systematically capture, validate and facilitate various uses of organisational understandings, knowledge and data normally distributed amongst multiple knowledge holders. The model-driven approach to decision making enables improved manufacturing responsiveness. Literature on modelling technologies relevant to manufacturing systems organisation design and change is presented, as is literature on production planning and control. This provides a rationale for the development of a new modelling methodology which combines the use of enterprise, causal loop and SM. Subsequently, this article describes how in the case of a specific manufacturing enterprise the combined modelling techniques have informed the choice of alternative production planning and control policies. An example enterprise model of a capacitor manufacturing company is illustrated as derivative causal-loop models that structure and enable the design and use of a general purpose simulation model.

The role of the surfaces in the photon absorption in Ge nanoclusters embedded in silica.

The usage of semiconductor nanostructures is highly promising for boosting the energy conversion efficiency in photovoltaics technology, but still some of the underlying mechanisms are not well understood at the nanoscale length. Ge quantum dots (QDs) should have a larger absorption and a more efficient quantum confinement effect than Si ones, thus they are good candidate for third-generation solar cells. In this work, Ge QDs embedded in silica matrix have been synthesized through magnetron sputtering deposition and annealing up to 800°C. The thermal evolution of the QD size (2 to 10 nm) has been followed by transmission electron microscopy and X-ray diffraction techniques, evidencing an Ostwald ripening mechanism with a concomitant amorphous-crystalline transition. The optical absorption of Ge nanoclusters has been measured by spectrophotometry analyses, evidencing an optical bandgap of 1.6 eV, unexpectedly independent of the QDs size or of the solid phase (amorphous or crystalline). A simple modeling, based on the Tauc law, shows that the photon absorption has a much larger extent in smaller Ge QDs, being related to the surface extent rather than to the volume. These data are presented and discussed also considering the outcomes for application of Ge nanostructures in photovoltaics.PACS: 81.07.Ta; 78.67.Hc; 68.65.-k.

A Structured Model of Video Reproduces Primary Visual Cortical Organisation

The visual system must learn to infer the presence of objects and features in the world from the images it encounters, and as such it must, either implicitly or explicitly, model the way these elements interact to create the image. Do the response properties of cells in the mammalian visual system reflect this constraint? To address this question, we constructed a probabilistic model in which the identity and attributes of simple visual elements were represented explicitly and learnt the parameters of this model from unparsed, natural video sequences. After learning, the behaviour and grouping of variables in the probabilistic model corresponded closely to functional and anatomical properties of simple and complex cells in the primary visual cortex (V1). In particular, feature identity variables were activated in a way that resembled the activity of complex cells, while feature attribute variables responded much like simple cells. Furthermore, the grouping of the attributes within the model closely parallelled the reported anatomical grouping of simple cells in cat V1. Thus, this generative model makes explicit an interpretation of complex and simple cells as elements in the segmentation of a visual scene into basic independent features, along with a parametrisation of their moment-by-moment appearances. We speculate that such a segmentation may form the initial stage of a hierarchical system that progressively separates the identity and appearance of more articulated visual elements, culminating in view-invariant object recognition.

Hydrogen-induced morphotropic phase transformation of single-crystalline vanadium dioxide nanobeams.

We report a morphotropic phase transformation in vanadium dioxide (VO2) nanobeams annealed in a high-pressure hydrogen gas, which leads to the stabilization of metallic phases. Structural analyses show that the annealed VO2 nanobeams are hexagonal-close-packed structures with roughened surfaces at room temperature, unlike as-grown VO2 nanobeams with the monoclinic structure and with clean surfaces. Quantitative chemical examination reveals that the hydrogen significantly reduces oxygen in the nanobeams with characteristic nonlinear reduction kinetics which depend on the annealing time. Surprisingly, the work function and the electrical resistance of the reduced nanobeams follow a similar trend to the compositional variation due mainly to the oxygen-deficiency-related defects formed at the roughened surfaces. The electronic transport characteristics indicate that the reduced nanobeams are metallic over a large range of temperatures (room temperature to 383 K). Our results demonstrate the interplay between oxygen deficiency and structural/electronic phase transitions, with implications for engineering electronic properties in vanadium oxide systems.

Magnetocaloric effect in nano- and polycrystalline manganite $La_{0.7}Ca_{0.3}MnO_3$

$La_{0.7}Ca_{0.3}MnO_3$ samples were prepared in nano- and polycrystalline forms by sol-gel and solid state reaction methods, respectively, and structurally characterized by synchrotron X-ray diffraction. The magnetic properties determined by ac susceptibility and dc magnetization measurements are discussed. The magnetocaloric effect in this nanocrystalline manganite is spread over a broader temperature interval than in the polycrystalline case. The relative cooling power of the poly- and nanocrystalline manganites is used to evaluate a possible application for magnetic cooling below room temperature.

Magnetocaloric effect in nano- and polycrystalline manganite La 0.7Ca0.3MnO3

La0.7Ca0.3MnO3 samples were prepared in nano- and polycrystalline forms by the sol-gel and solid state reaction methods, respectively, and structurally characterized by synchrotron X-ray diffraction. The magnetic properties determined by ac susceptibility and dc magnetization measurements are discussed. The magnetocaloric effect in this nanocrystalline manganite is spread over a broader temperature interval than in the polycrystalline case. The relative cooling power of the poly- and nanocrystalline manganites is used to evaluate a possible application for magnetic cooling below room temperature. © 2007 Springer-Verlag.

Engineering of micro- and nanostructured surfaces with anisotropic geometries and properties

Widespread approaches to fabricate surfaces with robust micro- and nanostructured topographies have been stimulated by opportunities to enhance interface performance by combining physical and chemical effects. In particular, arrays of asymmetric surface features, such as arrays of grooves, inclined pillars, and helical protrusions, have been shown to impart unique anisotropy in properties including wetting, adhesion, thermal and/or electrical conductivity, optical activity, and capability to direct cell growth. These properties are of wide interest for applications including energy conversion, microelectronics, chemical and biological sensing, and bioengineering. However, fabrication of asymmetric surface features often pushes the limits of traditional etching and deposition techniques, making it challenging to produce the desired surfaces in a scalable and cost-effective manner. We review and classify approaches to fabricate arrays of asymmetric 2D and 3D surface features, in polymers, metals, and ceramics. Analytical and empirical relationships among geometries, materials, and surface properties are discussed, especially in the context of the applications mentioned above. Further, opportunities for new fabrication methods that combine lithography with principles of self-assembly are identified, aiming to establish design principles for fabrication of arbitrary 3D surface textures over large areas. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.