Pt/Nanograined ZnO/SiC Schottky diode based hydrogen and propene sensor

A nanostructured Schottky diode was fabricated to sense hydrogen and propene gases in the concentration range of 0.06% to 1%. The ZnO sensitive layer was deposited on SiC substrate by pulse laser deposition technique. Scanning electron microscopy and X-ray diffraction characterisations revealed presence of wurtzite structured ZnO nanograins grown in the direction of (002) and (004). The nanostructured diode was investigated at optimum operating temperature of 260 °C. At a constant reverse current of 1 mA, the voltage shifts towards 1% hydrogen and 1% propene were measured as 173.3 mV and 191.8 mV, respectively.

Pt/MoO3 nano-flower/SiC Schottky diode based hydrogen gas sensor

In this paper, we report the development of a novel Pt/MoO3 nano-flower/SiC Schottky diode based device for hydrogen gas sensing applications. The MoO3 nanostructured thin films were deposited on SiC substrates via thermal evaporation. Morphological characterization of the nanostructured MoO3 by scanning electron microscopy revealed randomly orientated thin nanoplatelets in a densely packed formation of nano-flowers with dimensions ranging from 250 nm to 1 μm. Current-voltage characteristics of the sensor were measured at temperatures from 25°C to 250°C. The sensor showed greater sensitivity in a reverse bias condition than in forward bias. Dynamic response of the sensor was investigated towards different concentrations of hydrogen gas in a synthetic air mixture at 250°C and a large voltage shift of 5.7 V was recorded upon exposure to 1% hydrogen.

A comparison of forward and reverse bias operation in a Pt/nanostructured ZnO Schottky diode based hydrogen sensor

A hydrogen gas sensor based on Pt/nanostructured ZnO Schottky diode has been developed. Our proposed theoretical model allows for the explanation of superior dynamic performance of the reverse biased diode when compared to the forward bias operation. The sensor was evaluated with low concentration H2 gas exposures over a temperature range of 280°C to 430°C. Upon exposure to H2 gas, the effective change in free carrier concentration at the Pt/structured ZnO interface is amplified by an enhancement factor, effectively lowering the reverse barrier, producing a large voltage shift. The lowering of the reverse barrier permits a faster response in reverse bias operation, than in forward bias operation.

Pt/Graphene Nano-sheet Based Hydrogen Gas Sensor

In this paper, we present gas sensing properties of Pt/graphene-like nano-sheets towards hydrogen gas. The graphene-like nano-sheets were produced via the reduction of spray-coated graphite oxide deposited on SiC substrates by hydrazine vapor. Structural and morphological characterizations of the graphene sheets were analyzed by scanning electron and atomic force microscopy. Current-voltage and dynamic responses of the sensors were investigated towards different concentrations of hydrogen gas in a synthetic air mixture at 100°C. A voltage shift of 100 mV was recorded at 1 mA reverse bias current.

Graphene-like nano-sheets/36° LiTaO3 surface acoustic wave hydrogen gas sensor

Presented is the material and gas sensing properties of graphene-like nano-sheets deposited on 36° YX lithium tantalate (LiTaO3) surface acoustic wave (SAW) transducers. The graphene-like nano-sheets were characterized via scanning electron microscopy (SEM), atomic force microscopy(AFM)and X-ray photoelectron spectroscopy (XPS). The graphenelike nano-sheet/SAW sensors were exposed to different concentrations of hydrogen (H2) gas in a synthetic air at room temperature. The developed sensors exhibit good sensitivity towards low concentrations of H2 in ambient conditions, as well as excellent dynamic performance towards H2 at room temperature.

Graphene-like nano-sheets based LiTaO3 surface acoustic wave NO2 gas sensor

Thin films consisting of graphene-like nano-sheets were deposited onto LiTaO3 surface acoustic wave transducers. A thickness of less than 10 nm and the existence of C-C bond were observed during the characterization of graphene-like nano-sheets. Frequency shift of 18.7 kHz and 14.9 kHz towards 8.5 ppm NO2 at two different operating temperature, 40°C and 25°C, respectively, was observed.

Pt/SnO2 nanowires/SiC based hydrogen gas sensor

Pt/SnO2 nanowires/SiC based metal-oxidesemiconductor (MOS) devices were fabricated and tested for their gas sensitivity towards hydrogen. Tin oxide (SnO2) nanowires were grown on SiC substrates by the vapour liquid solid growth process. The material properties of the SnO2 nanowires such as its formation and dimensions were analyzed using scanning electron microscopy (SEM). The currentvoltage (I-V) characteristics at different hydrogen concentrations are presented. The effective change in the barrier height for 0.06 and 1% hydrogen were found to be 20.78 and 131.59 meV, respectively. A voltage shift of 310 mV at 530°C for 1% hydrogen was measured.

Effects of pH on pretreatment of sugarcane bagasse using aqueous imidazolium ionic liquids

Pretreatments of sugarcane bagasse for saccharification using different acid-catalysed imidazolium IL solutions (containing 20% water) at 130 °C for 30 min were investigated. At the same solution pH, pretreatment effectiveness in terms of glucan digestibility, delignification and xylan removal were similar for aqueous 1-butyl-3-methylimidazolium methane sulfonate (BMIMCH3SO3), 1-butyl-3-methylimidazolium methyl sulfate (BMIMCH3SO4), 1-ethyl-3-methylimidazolium chloride (EMIMCl) and 1-butyl-3-methylimidazolium chloride (BMIMCl). Decreasing solution pH of aqueous IL systems from 6.0 to 0.4 increased bagasse delignification and xylan removal, and as a result, improved glucan digestibility. The glucan digestibilities for bagasse samples pretreated by IL solutions with pH ≤ 0.9 were > 90% after 72 h of enzymatic hydrolysis. Without pH adjustment, the effectiveness of these aqueous IL solutions (except BMIMCH3SO3 because of its low natural pH of 0.9) to deconstruct the biomass was poor and the glucan digestibilities of pretreated bagasse samples were < 20%. These results show that pretreatment effectiveness of aqueous imidazolium ILs can simply be estimated from solution pH rather than hydrogen bond basicity (β) of the IL solution.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

The formation of gold nanoparticles using hydroquinone as a reducing agent through a localized pH change upon addition of NaOH to a solution of HAuCl4

We demonstrate a rapid synthesis of gold nanoparticles using hydroquinone as a reducing agent under acidic conditions without the need for precursor seed particles. The nanoparticle formation process is facilitated by the addition of NaOH to a solution containing HAuCl4 and hydroquinone to locally change the pH; this enhances the reducing capability of hydroquinone to form gold nucleation centres, after which further growth of gold can take place through an autocatalytic mechanism. The stability of the nanoparticles is highly dependent on the initial solution pH, and both the concentration of added NaOH and hydroquinone present in solution. The gold nanoparticles were characterized by UV–visible spectroscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, atomic force microscopy, dynamic light scattering, and zeta potential measurements. It was found that under optimal conditions that stable aqueous suspensions of 20 nm diameter nanoparticles can be achieved where benzoquinone, the oxidized product of hydroquinone, acts as a capping agent preventing nanoparticles aggregation.

Probing second harmonic components of pH-sensitive Redox processes in a mesoporous TiO2-Nafion film electrode with Fourier-transformed large-amplitude sinusoidally modulated voltammetry

Electrochemical processes in mesoporous TiO2-Nafion thin films deposited on indium tin oxide (ITO) electrodes are inherently complex and affected by capacitance, Ohmic iR-drop, RC-time constant phenomena, and by potential and pH-dependent conductivity. In this study, large-amplitude sinusoidally modulated voltammetry (LASMV) is employed to provide access to almost purely Faradaic-based current data from second harmonic components, as well as capacitance and potential domain information from the fundamental harmonic for mesoporous TiO2-Nafion film electrodes. The LASMV response has been investigated with and without an immobilized one-electron redox system, ferrocenylmethyltrimethylammonium+. Results clearly demonstrate that the electron transfer associated with the immobilized ferrocene derivative follows two independent pathways i) electron hopping within the Nafion network and ii) conduction through the TiO2 backbone. The pH effect on the voltammetric response for the TiO2 reduction pathway (ii) can be clearly identified in the 2nd harmonic LASMV response with the diffusion controlled ferrocene response (i) acting as a pH independent reference. Application of second harmonic data derived from LASMV measurement, because of the minimal contribution from capacitance currents, may lead to reference-free pH sensing with systems like that found for ferrocene derivatives.

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Brain-inspired sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

Effects of wireless sensor network uncertainties on output-only modal-based damage identification

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.