Light-matter interaction in a microcavity-controlled graphene transistor

Graphene has extraordinary electronic and optical properties and holds great promise for applications in photonics and optoelectronics. Demonstrations including high-speed photodetectors, optical modulators, plasmonic devices, and ultrafast lasers have now been reported. More advanced device concepts would involve photonic elements such as cavities to control light-matter interaction in graphene. Here we report the first monolithic integration of a graphene transistor and a planar, optical microcavity. We find that the microcavity-induced optical confinement controls the efficiency and spectral selection of photocurrent generation in the integrated graphene device. A twenty-fold enhancement of photocurrent is demonstrated. The optical cavity also determines the spectral properties of the electrically excited thermal radiation of graphene. Most interestingly, we find that the cavity confinement modifies the electrical transport characteristics of the integrated graphene transistor. Our experimental approach opens up a route towards cavity-quantum electrodynamics on the nanometre scale with graphene as a current-carrying intra-cavity medium of atomic thickness. © 2012 Macmillan Publishers Limited. All rights reserved.

Parameter optimization for automated concrete detection in image data

Several research studies have been recently initiated to investigate the use of construction site images for automated infrastructure inspection, progress monitoring, etc. In these studies, it is always necessary to extract material regions (concrete or steel) from the images. Existing methods made use of material's special color/texture ranges for material information retrieval, but they do not sufficiently discuss how to find these appropriate color/texture ranges. As a result, users have to define appropriate ones by themselves, which is difficult for those who do not have enough image processing background. This paper presents a novel method of identifying concrete material regions using machine learning techniques. Under the method, each construction site image is first divided into regions through image segmentation. Then, the visual features of each region are calculated and classified with a pre-trained classifier. The output value determines whether the region is composed of concrete or not. The method was implemented using C++ and tested over hundreds of construction site images. The results were compared with the manual classification ones to indicate the method's validity.

Three-Dimensional Tracking of Construction Resources using an On-Site Camera System

Vision trackers have been proposed as a promising alternative for tracking at large-scale, congested construction sites. They provide the location of a large number of entities in a camera view across frames. However, vision trackers provide only two-dimensional (2D) pixel coordinates, which are not adequate for construction applications. This paper proposes and validates a method that overcomes this limitation by employing stereo cameras and converting 2D pixel coordinates to three-dimensional (3D) metric coordinates. The proposed method consists of four steps: camera calibration, camera pose estimation, 2D tracking, and triangulation. Given that the method employs fixed, calibrated stereo cameras with a long baseline, appropriate algorithms are selected for each step. Once the first two steps reveal camera system parameters, the third step determines 2D pixel coordinates of entities in subsequent frames. The 2D coordinates are triangulated on the basis of the camera system parameters to obtain 3D coordinates. The methodology presented in this paper has been implemented and tested with data collected from a construction site. The results demonstrate the suitability of this method for on-site tracking purposes.

A matrix-calculation-based algorithm for numerical change propagation analysis

Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.

RFID Tag Location Systems

We describe a methods of locating an RFID tag. One method comprises: transmitting tag location signals from a plurality of different transmit antennas, wherein said antennas are spaced apart by more than a near field limit distance at a frequency of a said signal; receiving a corresponding plurality of receiving return signals from said tag; and processing said tag return signals to determine a range to said tag; wherein said transmitting comprises transmitting at a plurality of different frequencies; wherein said processing comprises determining a phase difference at said plurality of different frequencies to determine said range, and wherein said determining of said phase difference determines a phase difference between either i) two or more of said transmit signals resulting in a maxima in the returned signal RSSI or ii) a first transmit signal and its corresponding return signal; and wherein said determining of said range to said tag uses said return signals weighted responsive to a respective received signal strength of the return signal. Further data which may be used for averaging may be generated by using the above techniques along with changes in the polarisation state of the transmit and receive antennas and/or physical reconfiguration of the antennas (e.g. switch the transmit and receive elements).

Thermal stratification produced by plumes and jets in enclosed spaces

The airflow and thermal stratification produced by a localised heat source located at floor level in a closed room is of considerable practical interest and is commonly referred to as a 'filling box'. In rooms with low aspect ratios H/R ≲ 1 (room height H to characteristic horizontal dimension R) the thermal plume spreads laterally on reaching the ceiling and a descending horizontal 'front' forms separating a stably stratified, warm upper region from cooler air below. The stratification is well predicted for H/R ≲ 1 by the original filling box model of Baines and Turner (J. Fluid. Mech. 37 (1968) 51). This model represents a somewhat idealised situation of a plume rising from a point source of buoyancy alone-in particular the momentum flux at the source is zero. In practical situations, real sources of heating and cooling in a ventilation system often include initial fluxes of both buoyancy and momentum, e.g. where a heating system vents warm air into a space. This paper describes laboratory experiments to determine the dependence of the 'front' formation and stratification on the source momentum and buoyancy fluxes of a single source, and on the location and relative strengths of two sources from which momentum and buoyancy fluxes were supplied separately. For a single source with a non-zero input of momentum, the rate of descent of the front is more rapid than for the case of zero source momentum flux and increases with increasing momentum input. Increasing the source momentum flux effectively increases the height of the enclosure, and leads to enhanced overturning motions and finally to complete mixing for highly momentum-driven flows. Stratified flows may be maintained by reducing the aspect ratio of the enclosure. At these low aspect ratios different long-time behaviour is observed depending on the nature of the heat input. A constant heat flux always produces a stratified interior at large times. On the other hand, a constant temperature supply ultimately produces a well-mixed space at the supply temperature. For separate sources of momentum and buoyancy, the developing stratification is shown to be strongly dependent on the separation of the sources and their relative strengths. Even at small separation distances the stratification initially exhibits horizontal inhomogeneity with localised regions of warm fluid (from the buoyancy source) and cool fluid. This inhomogeneity is less pronounced as the strength of one source is increased relative to the other. Regardless of the strengths of the sources, a constant buoyancy flux source dominates after sufficiently large times, although the strength of the momentum source determines whether the enclosure is initially well mixed (strong momentum source) or stably stratified (weak momentum source). © 2001 Elsevier Science Ltd. All rights reserved.

Fluorine redistribution and incorporation during solid phase epitaxy of preamorphized Si

The redistribution of fluorine during solid phase epitaxial regrowth (SPER) of preamorphized Si has been experimentally investigated, explained, and simulated, for different F concentrations and temperatures. We demonstrate, by a detailed analysis and modeling of F secondary ion mass spectrometry chemical-concentration profiles, that F segregates in amorphous Si during SPER by splitting in three possible states: (i) a diffusive one that migrates in amorphous Si; (ii) an interface segregated state evidenced by the presence of a F accumulation peak at the amorphous-crystal interface; (iii) a clustered F state. The interplay among these states and their roles in the F incorporation into crystalline Si are fully described. It is shown that diffusive F migrates by a trap limited diffusion mechanism and also interacts with the advancing interface by a sticking-release dynamics that regulates the amount of F segregated at the interface. We demonstrate that this last quantity determines the regrowth rate through an exponential law. On the other hand we show that neither the diffusive F nor the one segregated at the interface can directly incorporate into the crystal but F has to cluster in the amorphous phase before being incorporated in the crystal, in agreement with recent experimental observations. The trends of the model parameters as a function of the temperature are shown and discussed obtaining a clear energetic scheme of the F redistribution and incorporation in preamorphized Si. The above physical understanding and the model could have a strong impact on the use of F as a tool for optimizing the doping profiles in the fabrication of ultrashallow junctions. © 2010 The American Physical Society.

Occlusive Components Analysis

We study unsupervised learning in a probabilistic generative model for occlusion. The model uses two types of latent variables: one indicates which objects are present in the image, and the other how they are ordered in depth. This depth order then determines how the positions and appearances of the objects present, specified in the model parameters, combine to form the image. We show that the object parameters can be learnt from an unlabelled set of images in which objects occlude one another. Exact maximum-likelihood learning is intractable. However, we show that tractable approximations to Expectation Maximization (EM) can be found if the training images each contain only a small number of objects on average. In numerical experiments it is shown that these approximations recover the correct set of object parameters. Experiments on a novel version of the bars test using colored bars, and experiments on more realistic data, show that the algorithm performs well in extracting the generating causes. Experiments based on the standard bars benchmark test for object learning show that the algorithm performs well in comparison to other recent component extraction approaches. The model and the learning algorithm thus connect research on occlusion with the research field of multiple-causes component extraction methods.

Prices need no preferences: social trends determine decisions in experimental markets for pain relief.

OBJECTIVE: A standard view in health economics is that, although there is no market that determines the "prices" for health states, people can nonetheless associate health states with monetary values (or other scales, such as quality adjusted life year [QALYs] and disability adjusted life year [DALYs]). Such valuations can be used to shape health policy, and a major research challenge is to elicit such values from people; creating experimental "markets" for health states is a theoretically attractive way to address this. We explore the possibility that this framework may be fundamentally flawed-because there may not be any stable values to be revealed. Instead, perhaps people construct ad hoc values, influenced by contextual factors, such as the observed decisions of others. METHOD: The participants bid to buy relief from equally painful electrical shocks to the leg and arm in an experimental health market based on an interactive second-price auction. Thirty subjects were randomly assigned to two experimental conditions where the bids by "others" were manipulated to follow increasing or decreasing price trends for one, but not the other, pain. After the auction, a preference test asked the participants to choose which pain they prefer to experience for a longer duration. RESULTS: Players remained indifferent between the two pain-types throughout the auction. However, their bids were differentially attracted toward what others bid for each pain, with overbidding during decreasing prices and underbidding during increasing prices. CONCLUSION: Health preferences are dissociated from market prices, which are strongly referenced to others' choices. This suggests that the price of health care in a free-market has the capacity to become critically detached from people's underlying preferences.

Quantifying the uncertainties in life cycle greenhouse gas emissions for UK wheat ethanol

Biofuels are increasingly promoted worldwide as a means for reducing greenhouse gas (GHG) emissions from transport. However, current regulatory frameworks and most academic life cycle analyses adopt a deterministic approach in determining the GHG intensities of biofuels and thus ignore the inherent risk associated with biofuel production. This study aims to develop a transparent stochastic method for evaluating UK biofuels that determines both the magnitude and uncertainty of GHG intensity on the basis of current industry practices. Using wheat ethanol as a case study, we show that the GHG intensity could span a range of 40-110 gCO2e MJ-1 when land use change (LUC) emissions and various sources of uncertainty are taken into account, as compared with a regulatory default value of 44 gCO2e MJ-1. This suggests that the current deterministic regulatory framework underestimates wheat ethanol GHG intensity and thus may not be effective in evaluating transport fuels. Uncertainties in determining the GHG intensity of UK wheat ethanol include limitations of available data at a localized scale, and significant scientific uncertainty of parameters such as soil N2O and LUC emissions. Biofuel polices should be robust enough to incorporate the currently irreducible uncertainties and flexible enough to be readily revised when better science is available. © 2013 IOP Publishing Ltd.

Contraction of monotone phase-coupled oscillators

This paper establishes a global contraction property for networks of phase-coupled oscillators characterized by a monotone coupling function. The contraction measure is a total variation distance. The contraction property determines the asymptotic behavior of the network, which is either finite-time synchronization or asymptotic convergence to a splay state. © 2012 Elsevier B.V. All rights reserved.

Between scylla and charybdis: Hydrophobic graphene-guided water diffusion on hydrophilic substrates

The structure of water confined in nanometer-sized cavities is important because, at this scale, a large fraction of hydrogen bonds can be perturbed by interaction with the confining walls. Unusual fluidity properties can thus be expected in the narrow pores, leading to new phenomena like the enhanced fluidity reported in carbon nanotubes. Crystalline mica and amorphous silicon dioxide are hydrophilic substrates that strongly adsorb water. Graphene, on the other hand, interacts weakly with water. This presents the question as to what determines the structure and diffusivity of water when intercalated between hydrophilic substrates and hydrophobic graphene. Using atomic force microscopy, we have found that while the hydrophilic substrates determine the structure of water near its surface, graphene guides its diffusion, favouring growth of intercalated water domains along the C-C bond zigzag direction. Molecular dynamics and density functional calculations are provided to help understand the highly anisotropic water stripe patterns observed.

Control of material transport through pulse shape manipulation-a development toward designer pulses

The variety of laser systems available to industrial laser users is growing and the choice of the correct laser for a material target application is often based on an empirical assessment. Industrial master oscillator power amplifier systems with tuneable temporal pulse shapes have now entered the market, providing enormous pulse parameter flexibility in an already crowded parameter space. In this paper, an approach is developed to design interaction parameters based on observations of material responses. Energy and material transport mechanisms are studied using pulsed digital holography, post process analysis techniques and finite-difference modelling to understand the key response mechanisms for a variety of temporal pulse envelopes incident on a silicon (1/1/1) substrate. The temporal envelope is shown to be the primary control parameter of the source term that determines the subsequent material response and the resulting surface morphology. A double peak energy-bridged temporal pulse shape designed through direct application of holographic imaging data is shown to substantially improve surface quality. © 2014 IEEE.

Strength and hydration products of reactive MgO-silica pastes

The reaction between MgO and microsilica has been studied by many researchers, who confirmed the formation of magnesium silicate hydrate. The blend was reported to have the potential as a novel material for construction and environment purposes. However, the characteristics of MgO vary significantly, e.g., reactivity and purity, which would have an effect on the hydration process of MgO-silica blend. This paper investigated the strength and hydration products of reactive MgO and silica blend at room temperature up to 90 days. The existence of magnesium silicate hydrate after 7 days' curing was confirmed with the help of infrared spectroscopy, thermogravimetric analysis and X-ray diffraction. The microstructural and elemental analysis of the resulting magnesium silicate hydrate was conducted using scanning electron microscopy and energy dispersive spectroscopy. In addition, the effect of characteristics of MgO on the hydration process was discussed. It was found that the synthesis of magnesium silicate hydrate was highly dependent on the reactivity of the precursors. MgO and silica with higher reactivity resulted in higher formation rate of magnesium silicate hydrate. In addition, the impurity in the MgO affects the pH value of the blends, which in turn determines the solubility of silica and the formation of magnesium silicate hydrate. © 2014 Elsevier Ltd. All rights reserved.