Nanomaterials coated multiplexed fiber Bragg grating for multiparameter sensing

Fiber Bragg Grating (FBG) sensors have been extensively used for strain and temperature sensing. However, there is still a need to measure multiple environmental parameters with a single sensor system. We demonstrate a multiplexed FBG sensor with various nano materials (polyallylamine-amino-carbon-nanotube, carbon nanotubes, polyelectrolyte and metals) coated onto the surface of the core/cladding FBG for sensing multiple environmental parameters such as pH (64 pm/pH), protein concentration (5 pm/mu g/ml), temperature (15 pm/degrees C), humidity (31 pm/% RH), gas concentration (7 pm/1000 ppm), and light intensity (infrared: 33 pm/mW, visible: 12 pm/mW and UV: 1 pm/mW) utilizing the same FBG based platform.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

A stabilization approach for mesh-free simulations of systems developing shocks or extreme strain localizations

A new stabilization scheme, based on a stochastic representation of the discretized field variables, is proposed with a view to reduce or even eliminate unphysical oscillations in the mesh-free numerical simulations of systems developing shocks or exhibiting localized bands of extreme deformation in the response. The origin of the stabilization scheme may be traced to nonlinear stochastic filtering and, consistent with a class of such filters, gain-based additive correction terms are applied to the simulated solution of the system, herein achieved through the element-free Galerkin method, in order to impose a set of constraints that help arresting the spurious oscillations. The method is numerically illustrated through its Applications to inviscid Burgers' equations, wherein shocks may develop as a result of intersections of the characteristics, and to a gradient plasticity model whose response is often characterized by a developing shear band as the external load is gradually increased. The potential of the method in stabilized yet accurate numerical simulations of such systems involving extreme gradient variations in the response is thus brought forth. (C) 2014 Elsevier Ltd. All rights reserved.

An Optoelectronic Profiling and Ranging Sensor for Monitoring of Perimeters

Electronic monitoring of perimeters plays vital roles in homeland security, management of traffic and of humanwildlife conflict. This paper reports the design and development of an optical beam-interruption-based ranging and profiling sensor for monitoring perimeters. The developed sensor system can determine the distance of the object from the sensing units and its temporal height profile as the object crosses the system. Together, these quantities can also be used to classify the object and to determine its speed. The sensor is designed, fabricated, and evaluated. The design enables compact construction, high sensitivity, and low measurement crosstalk. The evaluation demonstrates accuracy better than 98.5% in the determination of height and over 94% in determination of the distance of an object from the sensing units. Finally, a strategy is proposed to classify the objects based on the obtained height profiles. The strategy is demonstrated to correctly classify the objects despite differences in their speed and the location at which they cross the system.

A rhodamine-based `turn-on' Al3+ ion-selective reporter and the resultant complex as a secondary sensor for F- ion are applicable to living cell staining

A newly designed fluorescent aluminum(III) complex (L'-Al; 2) of a structurally characterized non-fluorescent rhodamine Schiff base (L) has been isolated in pure form and characterized using spectroscopic and physico-chemical methods with theoretical density functional theory (DFT) support. On addition of Al(III) ions to a solution of L in HEPES buffer (1 mM, pH 7.4; EtOH-water, 1 : 3 v/v) at 25 degrees C, the systematic increase in chelation-enhanced fluorescence (CHEF) enables the detection of Al(III) ions as low as 60 nM with high selectivity, unaffected by the presence of competitive ions. Interestingly, the Al(III) complex (L'-Al; 2) is specifically able to detect fluoride ions by quenching the fluorescence in the presence of large amounts of other anions in the HEPES buffer (1 mM, pH 7.4) at 25 degrees C. On the basis of our experimental and theoretical findings, the addition of Al3+ ions to a solution of L helps to generate a new fluorescence peak at 590 nm, due to the selective binding of Al3+ ions with L in a 1 : 1 ratio with a binding constant (K) of 8.13 x 10(4) M-1. The Schiff base L shows no cytotoxic effect, and it can therefore be employed for determining the intracellular concentration of Al3+ and F-ions by 2 in living cells using fluorescence microscopy.

Graphene based multifunctional flame sensor

Recently, graphene has attracted much attention due to its unique electrical and thermal properties along with its high surface area, and hence presents an ideal sensing material. We report a novel configuration of a graphene based flame sensor by exploiting the response of few layer graphene to a flame along two different directions, where flame detection results from a difference in heat transfer mechanisms. A complete sensor module was developed with a signal conditioning circuit that compensates for any drift in the baseline of the sensor, along with a flame detection algorithm implemented in a microcontroller to detect the flame. A pre-defined threshold for either of the sensors is tunable, which can be varied based on the nature of the flame, hence presenting a system that can be used for detection of any kind of flame. This finding also presents a scalable method that opens avenues to modify complicated sensing schemes.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Modeling of Piezocomposites using Variational Asymptotic Method

This work presents the development of piezocomposites made up of Macro Fiber Composites (MFCs) for aerospace applications and specifically involves, their computational analysis, material characterization and certain parametric studies. MFC was developed by NASA Langley Research Center in 1996 and currently is being distributed by Smart Material Co. 1] worldwide and finds applications both as an actuator as well as for sensor in various engineering applications. In this work, MFC is being modeled as an actuator and a theoretical formulation based on Variational Asymptotic Method (VAM) 2] is presented to analyse the laminates made up of MFCs. VAM minimizes the total electro-mechanical energy for the MFC laminate and approaches the exact solution asymptotically by making use of certain small parameters inherent to the problem through dimensional reduction. VAM provides closed form solutions for 1D constitutive law, recovery relations of warpings, 3D stress/strain fields and displacements and hence an ideal tool for carrying out parametric and design studies in such applications. VAM is geometrically exact and offers rigorous material characterization through cross-sectional analysis and dimensional reduction.

Spray: A Multi-Modal Localization System for Stationary Sensor Network Deployment

We present a localization system that targets rapid deployment of stationary wireless sensor networks (WSN). The system uses a particle filter to fuse measurements from multiple localization modalities, such as RF ranging, neighbor information or maps, to obtain position estimations with higher accuracy than that of the individual modalities. The system isolates different modalities into separate components which can be included or excluded independently to tailor the system to a specific scenario. We show that position estimations can be improved with our system by combining multiple modalities. We evaluate the performance of the system in both an indoor and outdoor environment using combinations of five different modalities. Using two anchor nodes as reference points and combining all five modalities, we obtain RMS (Root Mean Square) estimation errors of approximately 2.5m in both cases, while using the components individually results in errors within the range of 3.5 and 9 m.

Relay Selection with Channel Probing in Sleep-Wake Cycling Wireless Sensor Networks

In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has ``custody'' of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a ``reward'' that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continue to wait for further relays to wake up. The forwarder's objective is to select a relay so as to minimize a combination of waiting delay, reward, and probing cost. The local decision problem can be considered as a variant of the asset selling problem studied in the operations research literature. We formulate the local problem as a Markov decision process (MDP) and characterize the solution in terms of stopping sets and probing sets. We provide results illustrating the structure of the stopping sets, namely, the (lower bound) threshold and the stage independence properties. Regarding the probing sets, we make an interesting conjecture that these sets are characterized by upper bounds. Through simulation experiments, we provide valuable insights into the performance of the optimal local forwarding and its use as an end-to-end forwarding heuristic.

Suspended core-shell Pt-PtOx nanostructure for ultrasensitive hydrogen gas sensor

High sensitivity gas sensors are typically realized using metal catalysts and nanostructured materials, utilizing non-conventional synthesis and processing techniques, incompatible with on-chip integration of sensor arrays. In this work, we report a new device architecture, suspended core-shell Pt-PtOx nanostructure that is fully CMOS-compatible. The device consists of a metal gate core, embedded within a partially suspended semiconductor shell with source and drain contacts in the anchored region. The reduced work function in suspended region, coupled with builtin electric field of metal-semiconductor junction, enables the modulation of drain current, due to room temperature Redox reactions on exposure to gas. The device architecture is validated using Pt-PtO2 suspended nanostructure for sensing H-2 down to 200 ppb under room temperature. By exploiting catalytic activity of PtO2, in conjunction with its p-type semiconducting behavior, we demonstrate about two orders of magnitude improvement in sensitivity and limit of detection, compared to the sensors reported in recent literature. Pt thin film, deposited on SiO2, is lithographically patterned and converted into suspended Pt-PtO2 sensor, in a single step isotropic SiO2 etching. An optimum design space for the sensor is elucidated with the initial Pt film thickness ranging between 10 nm and 30 nm, for low power (< 5 mu W), room temperature operation. (C) 2015 AIP Publishing LLC.

Study on effect of optical wavelength on photo induced strain sensitivity in carbon nanotubes using fiber Bragg grating

In this work, the role of optical wavelength on the photo induced strain in carbon nanotubes (CNT) is probed using a Fiber Bragg Grating (FBG), upon exposure to infrared (IR) (21 mu epsilon mW(-1)) and visible (9 mu epsilon mW(-1)) radiations. The strain sensitivity in CNT is monitored over a smaller range (10(-3) to 10(-9) epsilon) by exposing to a low optical power varying in the range 10(-3) to 10(-6) W. In addition, the wavelength dependent response and recovery periods of CNT under IR (tau(rise) = 150 ms, tau(fall) = 280 ms) and visible (tau(rise) = 1.07 s, tau(fall) = 1.18 s) radiations are evaluated in detail. This study can be further extended to measure the sensitivity of nano-scale photo induced strains in nano materials and opens avenues to control mechanical actuation using various optical wavelengths.

Algorithm for Autonomous Reorganization of Mobile Wireless Camera Sensor Networks to Improve Coverage

In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displacement of camera-sensor nodes in the bounded field of interest (FoI), where the network coverage in terms of every point in the FoI is important. The proposed work is first of its kind to study the problem of maximizing coverage of randomly deployed mobile WCSNs which exploits their mobility. We propose an algorithm uncovered region exploration algorithm (UREA-CS) that can be executed in centralized and distributed modes. Further, the work is extended for two special scenarios: 1) to suit autonomous combing operations after initial random WCSN deployments and 2) to improve the network coverage with occlusions in the FoI. The extensive simulation results show that the performance of UREA-CS is consistent, robust, and versatile to achieve maximum coverage, both in centralized and distributed modes. The centralized and distributed modes are further analyzed with respect to the computational and communicational overheads.

Influence of external weld flash on the in-plane plane-strain formability of friction stir welded sheets

The main aim of the present work is to analyze the influence of external weld flash on the formability of friction stir welding sheets through in-plane plane-strain formability tests. The load-extension behavior and forming limit strains are measured to quantify the formability. The influence of friction stir welding parameters on the height of weld flash was also studied. The base materials used for welding trials are AA6061T6 and AA5052H32 alloy sheets of 2.1-mm thickness. It is observed that the influence of external weld flash on the maximum load and total extension for all the friction stir welding conditions is negligible. The effect of weld flash on the limiting major strain is also insignificant. But the presence of weld flash has changed the limiting minor strain, more toward plane-strain condition, indicating the change in strain-path toward plane-strain. This is due to the strain taken by weld flash, along with the major strain, minor strain, and thickness strain in the friction stir welding sheet plane because of constancy of volume. The formation of weld flash and its height are affected synergistically by the axial force and temperature development during friction stir welding. The higher the axial force and temperature, the higher the flash height.

Field induced domain switching as the origin of anomalous lattice strain along non-polar direction in rhombohedral BiScO3-PbTiO3 close to the morphotropic phase boundary

The lattice strain and domain switching behavior of xBiScO(3)-(1-x) PbTiO3 (x = 0.40) was investigated as a function of cyclic field and grain orientation by in situ X-ray diffraction during application of electric fields. The electric field induced 200 lattice strain was measured to be five times larger than the 111 lattice strain in pseudorhombohedral xBiScO(3)-(1-x) PbTiO3 (x = 0.40). It is shown that the anomalous 200 lattice strain is not an intrinsic phenomenon, but arises primarily due to stress associated with the reorientation of the 111 domains in dense polycrystalline ceramic. (C) 2015 AIP Publishing LLC.