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.

Kelvin-Helmholtz-like instabilities in turbulent flows over complex surfaces

Riblets are small surface protrusions aligned with the flow direction, which confer an anisotropic roughness to the surface [6]. We have recently reported that the transitional-roughness effect in riblets, which limits their performance, is due to a Kelvin–Helmholtz-like instability of the overlying mean flow [7]. According to our DNSs, the instability sets on as the Reynolds number based on the roughness size of the riblets increases, and coherent, elongated spanwise vortices begin to develop immediately above the riblet tips, causing the degradation of the drag-reduction effect. This is a very novel concept, since prior studies had proposed that the degradation was due to the interaction of riblets with the flow as independent units, either to the lodging of quasi-streamwise vortices in the surface grooves [2] or to the shedding of secondary streamwise vorticity at the riblet peaks [9]. We have proposed an approximate inviscid analysis for the instability, in which the presence of riblets is modelled through an average boundary condition for an overlying, spanwise-independent mean flow. This simplification lacks the accuracy of an exact analysis [4], but in turn applies to riblet surfaces in general. Our analysis succeeds in predicting the riblet size for the onset of the instability, while qualitatively reproducing the wavelengths and shapes of the spanwise structures observed in the DNSs. The analysis also connects the observations with the Kelvin–Helmholtz instability of mixing layers. The fundamental riblet length scale for the onset of the instability is a ‘penetration length,’ which reflects how easily the perturbation flow moves through the riblet grooves. This result is in excellent agreement with the available experimental evidence, and has enabled the identification of the key geometric parameters to delay the breakdown. Although the appearance of elongated spanwise vortices was unexpected in the case of riblets, similar phenomena had already been observed over other rough [3], porous [1] and permeable [11] surfaces, as well as over plant [5,14] and urban [12] canopies, both in the transitional and in the fully-rough regimes. However, the theoretical analyses that support the connection of these observations with the Kelvin–Helmholtz instability are somewhat scarce [7, 11, 13]. It has been recently proposed that Kelvin–Helmholtz-like instabilities are a dominant feature common to “obstructed” shear flows [8]. It is interesting that the instability does not require an inflection point to develop, as is often claimed in the literature. The Kelvin-Helmholtz rollers are rather triggered by the apparent wall-normal-transpiration ability of the flow at the plane immediately above the obstructing elements [7,11]. Although both conditions are generally complementary, if wall-normal transpiration is not present the spanwise vortices may not develop, even if an inflection point exists within the roughness [10]. REFERENCES [1] Breugem, W. P., Boersma, B. J. & Uittenbogaard, R. E. 2006 J. Fluid Mech. 562, 35–72. [2] Choi, H., Moin, P. & Kim, J. 1993 J. Fluid Mech. 255, 503–539. [3] Coceal, O., Dobre, A., Thomas, T. G. & Belcher, S. E. 2007 J. Fluid Mech. 589, 375–409. [4] Ehrenstein, U. 2009 Phys. Fluids 8, 3194–3196. [5] Finnigan, J. 2000 Ann. Rev. Fluid Mech. 32, 519–571. [6] Garcia-Mayoral, R. & Jimenez, J. 2011 Phil. Trans. R. Soc. A 369, 1412–1427. [7] Garcia-Mayoral, R. & Jimenez, J. 2011 J. Fluid Mech. doi: 10.1017/jfm.2011.114. [8] Ghisalberti, M. 2009 J. Fluid Mech. 641, 51–61. [9] Goldstein, D. B. & Tuan, T. C. 1998 J. Fluid Mech. 363, 115–151. [10] Hahn, S., Je, J. & Choi, H. 2002 J. Fluid Mech. 450, 259–285. [11] Jimenez, J., Uhlman, M., Pinelli, A. & G., K. 2001 J. Fluid Mech. 442, 89–117. [12] Letzel, M. O., Krane, M. & Raasch, S. 2008 Atmos. Environ. 42, 8770–8784. [13] Py, C., de Langre, E. & Moulia, B. 2006 J. Fluid Mech. 568, 425–449. [14] Raupach, M. R., Finnigan, J. & Brunet, Y. 1996 Boundary-Layer Meteorol. 78, 351–382.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.

Continuous asr for flexible incremental dialogue

Spoken dialogue systems provide a convenient way for users to interact with a machine using only speech. However, they often rely on a rigid turn taking regime in which a voice activity detection (VAD) module is used to determine when the user is speaking and decide when is an appropriate time for the system to respond. This paper investigates replacing the VAD and discrete utterance recogniser of a conventional turn-taking system with a continuously operating recogniser that is always listening, and using the recogniser 1-best path to guide turn taking. In this way, a flexible framework for incremental dialogue management is possible. Experimental results show that it is possible to remove the VAD component and successfully use the recogniser best path to identify user speech, with more robustness to noise, potentially smaller latency times, and a reduction in overall recognition error rate compared to using the conventional approach. © 2013 IEEE.

On-line policy optimisation of Bayesian spoken dialogue systems via human interaction

A partially observable Markov decision process has been proposed as a dialogue model that enables robustness to speech recognition errors and automatic policy optimisation using reinforcement learning (RL). However, conventional RL algorithms require a very large number of dialogues, necessitating a user simulator. Recently, Gaussian processes have been shown to substantially speed up the optimisation, making it possible to learn directly from interaction with human users. However, early studies have been limited to very low dimensional spaces and the learning has exhibited convergence problems. Here we investigate learning from human interaction using the Bayesian Update of Dialogue State system. This dynamic Bayesian network based system has an optimisation space covering more than one hundred features, allowing a wide range of behaviours to be learned. Using an improved policy model and a more robust reward function, we show that stable learning can be achieved that significantly outperforms a simulator trained policy. © 2013 IEEE.

High-performance nanowire oxide photo-thin film transistor.

A gate-modulated nanowire oxide photosensor is fabricated by electron-beam lithography and conventional dry etch processing.. The device characteristics are good, including endurance of up to 10(6) test cycles, and gate-pulse excitation is used to remove persistent photoconductivity. The viability of nanowire oxide phototransistors for high speed and high resolution applications is demonstrated, thus potentially expanding the scope of exploitation of touch-free interactive displays.

Electrical addressing of polymer stabilized hyper-twisted chiral nematic liquid crystals with interdigitated electrodes: Experiment and model

Electro-optic switching in short-pitch polymer stabilized chiral nematic liquid crystals was studied and the relative contributions of flexoelectric and dielectric coupling were investigated: polymer stabilization was found to effectively suppress unwanted textural transitions of the chiral nematic liquid crystal and thereby enhance the electro-optical performance (high optical contrast for visible light, a near ideal optical hysteresis, fast electro-optic response). Test cells were studied that possessed interdigitated electrodes to electrically address the liquid crystal. Based on simulations, a well-fitted phenomenological description of the electro-optic response was derived considering both flexoelectro-optic and Kerr-effect based electro-optic response. © 2014 AIP Publishing LLC.

Effects of electron-electron interactions on the electronic Raman scattering of graphite in high magnetic fields

We report the observation of strongly temperature (T)-dependent spectral lines in electronic Raman-scattering spectra of graphite in a high magnetic field up to 45 T applied along the c axis. The magnetic field quantizes the in-plane motion, while the out-of-plane motion remains free, effectively reducing the system dimension from 3 to 1. Optically created electron-hole pairs interact with, or shake up, the one-dimensional Fermi sea in the lowest Landau subbands. Based on the Tomonaga-Luttinger liquid theory, we show that interaction effects modify the spectral line shape from (ω-Δ)-1/2 to (ω-Δ)2α-1/2 at T = 0. At finite T, we predict a thermal broadening factor that increases linearly with T. Our model reproduces the observed T-dependent line shape, determining the electron-electron interaction parameter α to be ∼0.05 at 40 T. © 2014 American Physical Society.

Emerging applications of liquid crystals based on nanotechnology

Diverse functionalities of liquid crystals (LCs) offer enormous opportunities for their potential use in advanced mobile and smart displays, as well as novel non-display applications. Here, we present snapshots of the research carried out on emerging applications of LCs ranging from electronics to holography and self-powered systems. In addition, we will show our recent results focused on the development of new LC applications, such as programmable transistors, a transparent and active-type two-dimensional optical array and self-powered display systems based on LCs, and will briefly discuss their novel concepts and basic operating principles. Our research will give insights not only into comprehensively understanding technical and scientific applications of LCs, but also developing new discoveries of other LC-based devices. © 2014 by the authors.

Electrical control of nanoscale functionalization in graphene by the scanning probe technique

Functionalized graphene is a versatile material that has well-known physical and chemical properties depending on functional groups and their coverage. However, selective control of functional groups on the nanoscale is hardly achievable by conventional methods utilizing chemical modifications. We demonstrate electrical control of nanoscale functionalization of graphene with the desired chemical coverage of a selective functional group by atomic force microscopy (AFM) lithography and their full recovery through moderate thermal treatments. Surprisingly, our controlled coverage of functional groups can reach 94.9% for oxygen and 49.0% for hydrogen, respectively, well beyond those achieved by conventional methods. This coverage is almost at the theoretical maximum, which is verified through scanning photoelectron microscope measurements as well as first-principles calculations. We believe that the present method is now ready to realize 'chemical pencil drawing' of atomically defined circuit devices on top of a monolayer of graphene. © 2014 Nature Publishing Group All rights reserved.

Guided self-organization in a dynamic embodied system based on attractor selection mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.