Ultrasensitive hydrogen sensor based on Pd0-loaded SnO2 electrospun nanofibers at room temperature

Pd0-loaded SnO2 nanofibers have been successfully synthesized with different loaded levels via electrospinning process, sintering technology, and in situ reduction. This simple strategy could be expected to extend for the fabrication of similar metal?oxide loaded nanofibers using different precursors. The morphological and structural characteristics of the resultant product were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectra (XPS). To demonstrate the usage of such Pd0-loaded SnO2 nanomaterial, a chemical gas sensor has been fabricated and investigated for H2 detection. The sensing performances versus Pd0-loaded levels have been investigated in detail. An ultralow limit of detection (20 ppb), high response, fast response and recovery, and selectivity have been obtained on the basis of the sensors operating at room temperature. The combination of SnO2 crystal structure and catalytic activity of Pd0-loaded gives a very attractive sensing behavior for applications as real-time monitoring gas sensors.

Monitoring a CuO gas sensor at work: an advanced in situ X-ray absorption spectroscopy study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A novel multicomponent regulatory system mediates H2 sensing in Alcaligenes eutrophus

Oxidation of molecular hydrogen catalyzed by [NiFe] hydrogenases is a widespread mechanism of energy generation among prokaryotes. Biosynthesis of the H2-oxidizing enzymes is a complex process subject to positive control by H2 and negative control by organic energy sources. In this report we describe a novel signal transduction system regulating hydrogenase gene (hox) expression in the proteobacterium Alcaligenes eutrophus. This multicomponent system consists of the proteins HoxB, HoxC, HoxJ*, and HoxA. HoxB and HoxC share characteristic features of dimeric [NiFe] hydrogenases and form the putative H2 receptor that interacts directly or indirectly with the histidine protein kinase HoxJ*. A single amino acid substitution (HoxJ*G422S) in a conserved C-terminal glycine-rich motif of HoxJ* resulted in a loss of H2-dependent signal transduction and a concomitant block in autophosphorylating activity, suggesting that autokinase activity is essential for the response to H2. Whereas deletions in hoxB or hoxC abolished hydrogenase synthesis almost completely, the autokinase-deficient strain maintained high-level hox gene expression, indicating that the active sensor kinase exerts a negative effect on hox gene expression in the absence of H2. Substitutions of the conserved phosphoryl acceptor residue Asp55 in the response regulator HoxA (HoxAD55E and HoxAD55N) disrupted the H2 signal-transduction chain. Unlike other NtrC-like regulators, the altered HoxA proteins still allowed high-level transcriptional activation. The data presented here suggest a model in which the nonphosphorylated form of HoxA stimulates transcription in concert with a yet unknown global energy-responsive factor.

Self-assembled SnO2 micro- and nanosphere-based gas sensor thick films from an alkoxide-derived high purity aqueous colloid precursor

Tin oxide is considered to be one of the most promising semiconductor oxide materials for use as a gas sensor. However, a simple route for the controllable build-up of nanostructured, sufficiently pure and hierarchical SnO2 structures for gas sensor applications is still a challenge. In the current work, an aqueous SnO2 nanoparticulate precursor sol, which is free of organic contaminants and sorbed ions and is fully stable over time, was prepared in a highly reproducible manner from an alkoxide Sn(OR)4 just by mixing it with a large excess of pure neutral water. The precursor is formed as a separate liquid phase. The structure and purity of the precursor is revealed using XRD, SAXS, EXAFS, HRTEM imaging, FTIR, and XRF analysis. An unconventional approach for the estimation of the particle size based on the quantification of the Sn-Sn contacts in the structure was developed using EXAFS spectroscopy and verified using HRTEM. To construct sensors with a hierarchical 3D structure, we employed an unusual emulsification technique not involving any additives or surfactants, using simply the extraction of the liquid phase, water, with the help of dry butanol under ambient conditions. The originally generated crystalline but yet highly reactive nanoparticles form relatively uniform spheres through self-assembly and solidify instantly. The spheres floating in butanol were left to deposit on the surface of quartz plates bearing sputtered gold electrodes, producing ready-for-use gas sensors in the form of ca. 50 μm thick sphere-based-films. The films were dried for 24 h and calcined at 300°C in air before use. The gas sensitivity of the structures was tested in the temperature range of 150-400°C. The materials showed a very quickly emerging and reversible (20-30 times) increase in electrical conductivity as a response to exposure to air containing 100 ppm of H2 or CO and short (10 s) recovery times when the gas flow was stopped.

A forward and backward secure key management in wireless sensor networks for PCS/SCADA

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.