Ultrafast switching liquid crystals for electro-optic transmissive and reflective displays and microscopic lasers

We have used novel liquid crystals with extremely large flexoelectric coefficients in a range of ultra-fast photonic/display modes, namely 1) the uniform lying helix, that leads to in-plain switching, birefringence based displays with 100 μs switching times at low fields, i.e.2-5 V/μm, wide viewing angle and analogue or grey scale capability, 2) the uniform standing helix, using planar surface alignment and in-plane fields, with sub ms response times and optical contrasts in excess of 5000:1 with a perfect black "off state", 3) the wide temperature range blue phase that leads to field controlled reflective color and 4) high slope efficiency, wide wavelength range tunable narrow linewidth microscopic liquid crystal lasers.

Effective handling of dialogue state in the hidden information state POMDP-based dialogue manager

Effective dialogue management is critically dependent on the information that is encoded in the dialogue state. In order to deploy reinforcement learning for policy optimization, dialogue must be modeled as a Markov Decision Process. This requires that the dialogue statemust encode all relevent information obtained during the dialogue prior to that state. This can be achieved by combining the user goal, the dialogue history, and the last user action to form the dialogue state. In addition, to gain robustness to input errors, dialogue must be modeled as a Partially Observable Markov Decision Process (POMDP) and hence, a distribution over all possible states must be maintained at every dialogue turn. This poses a potential computational limitation since there can be a very large number of dialogue states. The Hidden Information State model provides a principled way of ensuring tractability in a POMDP-based dialogue model. The key feature of this model is the grouping of user goals into partitions that are dynamically built during the dialogue. In this article, we extend this model further to incorporate the notion of complements. This allows for a more complex user goal to be represented, and it enables an effective pruning technique to be implemented that preserves the overall system performance within a limited computational resource more effectively than existing approaches. © 2011 ACM.

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Solid-state memories based on ferroelectric tunnel junctions.

Ferroic-order parameters are useful as state variables in non-volatile information storage media because they show a hysteretic dependence on their electric or magnetic field. Coupling ferroics with quantum-mechanical tunnelling allows a simple and fast readout of the stored information through the influence of ferroic orders on the tunnel current. For example, data in magnetic random-access memories are stored in the relative alignment of two ferromagnetic electrodes separated by a non-magnetic tunnel barrier, and data readout is accomplished by a tunnel current measurement. However, such devices based on tunnel magnetoresistance typically exhibit OFF/ON ratios of less than 4, and require high powers for write operations (>1 × 10(6) A cm(-2)). Here, we report non-volatile memories with OFF/ON ratios as high as 100 and write powers as low as ∼1 × 10(4) A cm(-2) at room temperature by storing data in the electric polarization direction of a ferroelectric tunnel barrier. The junctions show large, stable, reproducible and reliable tunnel electroresistance, with resistance switching occurring at the coercive voltage of ferroelectric switching. These ferroelectric devices emerge as an alternative to other resistive memories, and have the advantage of not being based on voltage-induced migration of matter at the nanoscale, but on a purely electronic mechanism.

Switching characteristics of diamond-based m-i-p+ diodes in power electronic applications

Modeling and numerical analysis of diamond m-i-p+ diode have been performed for static and transient analysis using TCAD Sentaurus platform. The simulation results are compared with experimental measurements. Prediction of transient turn-off characteristics of diamond m-i-p+ diode at high temperature is performed for the first time. It was found that unlike conventional Si diode, peak reverse current in diamond m-i-p+ diode reduces with increasing temperature while on-state voltage drop increases. © 2011 IEEE.

Steady-state analytical model for the trench insulated gate bipolar transistor

A steady-state, physically-based analytical model for the Trench Insulated Gate Bipolar Transistor which accounts for a combined PIN diode - PNP transistor carrier dynamics is proposed. Previous models (i.e. PIN model and PNP transistor model) cannot account properly for the carrier dynamics in Trench IGBT since neither the PNP transistor nor the PIN diode effect can be neglected. An optimized Trench IGBT with a large ratio between the accumulation layer and the cell size leads to substantially improved on-state characteristics, which makes the Trench IGBT potentially the most attractive device in the area of high voltage fast switching devices.

Solid-state memories based on ferroelectric tunnel junctions

Ferroic-order parameters are useful as state variables in non-volatile information storage media because they show a hysteretic dependence on their electric or magnetic field. Coupling ferroics with quantum-mechanical tunnelling allows a simple and fast readout of the stored information through the influence of ferroic orders on the tunnel current. For example, data in magnetic random-access memories are stored in the relative alignment of two ferromagnetic electrodes separated by a non-magnetic tunnel barrier, and data readout is accomplished by a tunnel current measurement. However, such devices based on tunnel magnetoresistance typically exhibit OFF/ON ratios of less than 4, and require high powers for write operations (>1 × 10 6 A cm -2). Here, we report non-volatile memories with OFF/ON ratios as high as 100 and write powers as low as ∼1 × 10 4A cm -2 at room temperature by storing data in the electric polarization direction of a ferroelectric tunnel barrier. The junctions show large, stable, reproducible and reliable tunnel electroresistance, with resistance switching occurring at the coercive voltage of ferroelectric switching. These ferroelectric devices emerge as an alternative to other resistive memories, and have the advantage of not being based on voltage-induced migration of matter at the nanoscale, but on a purely electronic mechanism. © 2012 Macmillan Publishers Limited. All rights reserved.

Ultrafast switching liquid crystals for electro-optic transmissive and reflective displays and microscopic lasers

We report on novel liquid crystals with extremely large flexoelectric coefficients in a range of ultra-fast photonic modes, namely 1) the uniform lying helix, that leads to in-plain switching, birefringence phase devices with 100 μs switching times at low fields, i.e.2-5 V/μm, and analogue or grey scale capability, 2) the uniform standing helix, using planar surface alignment and in-plane fields, with sub ms response times and optical contrasts in excess of 5000:1 with a perfect optically isotropic or black "off state", 3) the wide temperature range blue phase that leads to field controlled reflective color, 4) chiral nematic optical reflectors electric field tunable over a wide wavelength range and 5) high slope efficiency, wide wavelength range tunable narrow linewidth microscopic liquid crystal lasers. © 2011 Materials Research Society.

Temperature dependent electron transport in amorphous oxide semiconductor thin film transistors

A temperature-dependent mobility model in amorphous oxide semiconductor (AOS) thin film transistors (TFTs) extracted from measurements of source-drain terminal currents at different gate voltages and temperatures is presented. At low gate voltages, trap-limited conduction prevails for a broad range of temperatures, whereas variable range hopping becomes dominant at lower temperatures. At high gate voltages and for all temperatures, percolation conduction comes into the picture. In all cases, the temperature-dependent mobility model obeys a universal power law as a function of gate voltage. © 2011 IEEE.

A fast 600-V Tandem PiN Schottky (TPS) rectifier with ultra-low on-state voltage

The Tandem PiN Schottky (TPS) rectifier features lowly-doped p-layers in both active and termination regions, and is applied in 600-V rating for the first time. In the active region, the Schottky contact is in series connection with a transparent p-layer, leading to a superior forward performance than the conventional diodes. In addition, due to the benefit of moderate hole injection from the p-layer, the TPS offers a better trade-off between the on-state voltage and the switching speed. The active p-layer also helps to stabilise the Schottky contact, and hence the electrical data distributions are more concentrated. Regarding the floating p-layer in the termination region, its purpose is to reduce the peak electric fields, and the TPS demonstrates a high breakdown voltage with a compact termination width, less than 70% of the state-of-the-art devices on the market. Experimental results have shown that the 600-V TPS rectifier has an ultra-low on-state voltage of 0.98 V at 250 A/cm 2, a fast turn-off time of 75 ns by the standard RG1 test (I F=0.5A, I R=1A, and I RR=0.25A) and a breakdown voltage over 720 V. It is noteworthy that the p-layers in the active and termination regions can be formed at no extra cost for the use of self-alignment process. © 2012 IEEE.

Development of realistic liquid equations of state for multi-phase CFD modelling

Several equations of state (EOS) have been incorporated into a novel algorithm to solve a system of multi-phase equations in which all phases are assumed to be compressible to varying degrees. The EOSs are used to both supply functional relationships to couple the conservative variables to the primitive variables and to calculate accurately thermodynamic quantities of interest, such as the speed of sound. Each EOS has a defined balance of accuracy, robustness and computational speed; selection of an appropriate EOS is generally problem-dependent. This work employs an AUSM+-up method for accurate discretisation of the convective flux terms with modified low-Mach number dissipation for added robustness of the solver. In this paper we show a newly-developed time-marching formulation for temporal discretisation of the governing equations with incorporated time-dependent source terms, as well as considering the system of eigenvalues that render the governing equations hyperbolic.

A finite element model of magnetization of superconducting bulks using a solid-state flux pump

Superconductors have a bright future; they are able to carry very high current densities, switch rapidly in electronic circuits, detect extremely small perturbations in magnetic fields, and sustain very high magnetic fields. Of most interest to large-scale electrical engineering applications are the ability to carry large currents and to provide large magnetic fields. There are many projects that use the first property, and these have concentrated on power generation, transmission, and utilization; however, there are relatively few, which are currently exploiting the ability to sustain high magnetic fields. The main reason for this is that high field wound magnets can and have been made from both BSCCO and YBCO, but currently, their cost is much higher than the alternative provided by low-Tc materials such as Nb3Sn and NbTi. An alternative form of the material is the bulk form, which can be magnetized to high fields. This paper explains the mechanism, which allows superconductors to be magnetized without the need for high field magnets to perform magnetization. A finite-element model is presented, which is based on the E-J current law. Results from this model show how magnetization of the superconductor builds up cycle upon cycle when a traveling magnetic wave is induced above the superconductor. © 2011 IEEE.

State estimation schemes for independent component coupled hidden Markov models

Conventional Hidden Markov models generally consist of a Markov chain observed through a linear map corrupted by additive noise. This general class of model has enjoyed a huge and diverse range of applications, for example, speech processing, biomedical signal processing and more recently quantitative finance. However, a lesser known extension of this general class of model is the so-called Factorial Hidden Markov Model (FHMM). FHMMs also have diverse applications, notably in machine learning, artificial intelligence and speech recognition [13, 17]. FHMMs extend the usual class of HMMs, by supposing the partially observed state process is a finite collection of distinct Markov chains, either statistically independent or dependent. There is also considerable current activity in applying collections of partially observed Markov chains to complex action recognition problems, see, for example, [6]. In this article we consider the Maximum Likelihood (ML) parameter estimation problem for FHMMs. Much of the extant literature concerning this problem presents parameter estimation schemes based on full data log-likelihood EM algorithms. This approach can be slow to converge and often imposes heavy demands on computer memory. The latter point is particularly relevant for the class of FHMMs where state space dimensions are relatively large. The contribution in this article is to develop new recursive formulae for a filter-based EM algorithm that can be implemented online. Our new formulae are equivalent ML estimators, however, these formulae are purely recursive and so, significantly reduce numerical complexity and memory requirements. A computer simulation is included to demonstrate the performance of our results. © Taylor & Francis Group, LLC.

Synchronization with partial state feedback on SO(n)

In this paper we consider the problem of constructing a distributed feedback law to achieve synchronization for a group of k agents whose states evolve on SO(n) and which exchange only partial state information along communication links. The partial state information is given by the action of the state on reference vectors in ℝn. We propose a gradient based control law which achieves exponential local convergence to a synchronization configuration under a rank condition on a generalized Laplacian matrix. Furthermore, we discuss the case of time-varying reference vectors and provide a convergence result for this case. The latter helps reach synchronization, requiring less communication links and weaker conditions on the instantaneous reference vectors. Our methods are illustrated on an attitude synchronization problem where agents exchange only their relative positions observed in the respective body frames. ©2009 IEEE.

Oscillator models and collective motion: Splay state stabilization of self-propelled particles

This paper presents a Lyapunov design for the stabilization of collective motion in a planar kinematic model of N particles moving at constant speed. We derive a control law that achieves asymptotic stability of the splay state formation, characterized by uniform rotation of N evenly spaced particles on a circle. In designing the control law, the particle headings are treated as a system of coupled phase oscillators. The coupling function which exponentially stabilizes the splay state of particle phases is combined with a decentralized beacon control law that stabilizes circular motion of the particles. © 2005 IEEE.