A high temperature SOI CMOS NO2 sensor

For more than 20 years researchers have been interested in developing micro-gas sensors based on silicon technology. Most of the reported devices are based on micro-hotplates, however they use materials that are not CMOS compatible, and therefore are not suitable for large volume manufacturing. Furthermore, they do not allow the circuitry to be integrated on to the chip. CMOS compatible devices have been previously reported. However, these use polysilicon as the heater material, which has long term stability problems at high temperatures. Here we present low power, low cost SOI CMOS NO2 sensors, based on high stability single crystal silicon P+ micro-heaters platforms, capable of measuring gas concentrations down to 0.1 ppm. We have integrated a thin tungsten molybdenum oxide layer as a sensing material with a foundry-standard SOI CMOS micro-hotplate and tested this to NO2. We believe these devices have the potential for use as robust, very low power consumption, low cost gas sensors. © 2011 American Institute of Physics.

A condition monitoring platform using COTS wireless sensor networks - Lessons and experience

Developments in Micro-Electro-Mechanical Systems (MEMS), wireless communication systems and ad-hoc networking have created new dimensions to improve asset management not only during the operational phase but throughout an asset's lifecycle based on using improved quality of information obtained with respect to two key aspects of an asset: its location and condition. In this paper, we present our experience as well as lessons learnt from building a prototype condition monitoring platform to demonstrate and to evaluate the use of COTS wireless sensor networks to develop a prototype condition monitoring platform with the aim of improving asset management by providing accurate and real-time information. © 2010 IEEE.

Magnetic sensor with compensation for lead and coil resistance

A measurement system for magnetic fields or electric currents uses a single-core fluxgate, magneto-inductive or magneto-impedance device driven from a radio frequency excitation source. Flux nulling feedback circuitry is provided to maintain the core of the sensor at substantially zero net flux and improve the linearity and dynamic response of the sensor system. A high pass filter is provided for reducing the dc effects of the ohmic resistance of the coil and lead wires on the effectiveness of the flux nulling feedback.

Fluxgate magnetic sensor with overload detection

A measurement system for magnetic fields and electric currents uses a single-core fluxgate device driven with a radio frequency excitation source and is provided with a means to indicate saturation of the core of the sensor. A means is provided for detecting overload of the sensor as the core approaches continuous saturation using a pair of demodulators and a comparator.

PCB-integrated optical gas sensor

A novel technological platform for multiple gas detection based on the use of PCB-integrated polymer waveguides is presented. A proof-of-principle ammonia sensor is reported integrating onto low-cost FR4 substrates all essential photonic, electronic and chemical components. The device's potential to detect multiple gases is demonstrated. © 2011 IEEE.

High temperature robust SOI ethanol sensor

In this paper we present a robust SOI-CMOS ethanol sensor based on a tungsten-doped lanthanum iron oxide sensing material. The device shows response to gas, has low power consumption, good uniformity, high temperature stability and can be manufactured at low cost and with integrated circuitry. The platform is a tungsten-based CMOS micro-hotplate that has been shown to be stable for over two thousand hours at a high temperature (600°C) in a form of accelerated life test. The tungsten-doped lanthanum iron oxide was deposited on the micro-hotplate as a slurry with terpineol using a syringe, dried and annealed. Preliminary gas testing was done and the material shows response to ethanol vapour. These results are promising and we believe that this combination of a robust CMOS micro-hotplate and a good sensing material can form the basis for a commercial CMOS gas sensor. © 2011 Published by Elsevier Ltd.

Zinc oxide nanowire based hydrogen sensor on SOI CMOS platform

Here we report on the successful low-temperature growth of zinc oxide nanowires (ZnONWs) on silicon-on-insulator (SOI) CMOS micro-hotplates and their response, at different operating temperatures, to hydrogen in air. The SOI micro-hotplates were fabricated in a commercial CMOS foundry followed by a deep reactive ion etch (DRIE) in a MEMS foundry to form ultra-low power membranes. The micro-hotplates comprise p+ silicon micro-heaters and interdigitated metal electrodes (measuring the change in resistance of the gas sensitive nanomaterial). The ZnONWs were grown as a post-CMOS process onto the hotplates using a CMOS friendly hydrothermal method. The ZnONWs showed a good response to 500 to 5000 ppm of hydrogen in air. We believe that the integration of ZnONWs with a MEMS platform results in a low power, low cost, hydrogen sensor that would be suitable for handheld battery-operated gas sensors. © 2011 Published by Elsevier Ltd.

Steady-state modelling of the universal exhaust gas oxygen (UEGO) sensor

The universal exhaust gas oxygen (UEGO) sensor is a well-established device which was developed for the measurement of relative air fuel ratio in internal combustion engines. There is, however, little information available which allows for the prediction of the UEGO's behaviour when exposed to arbitrary gas mixtures, pressures and temperatures. Here we present a steady-state model for the sensor, based on a solution of the Stefan-Maxwell equation, and which includes a momentum balance. The response of the sensor is dominated by a diffusion barrier, which controls the rate of diffusion of gas species between the exhaust and a cavity. Determination of the diffusion barrier characteristics, especially the mean pore size, porosity and tortuosity, is essential for the purposes of modelling, and a measurement technique based on identification of the sensor pressure giving zero temperature sensitivity is shown to be a convenient method of achieving this. The model, suitably calibrated, is shown to make good predictions of sensor behaviour for large variations of pressure, temperature and gas composition. © 2012 IOP Publishing Ltd.

Near-ultraviolet zinc oxide nanowire sensor using low temperature hydrothermal growth.

Two near-ultraviolet (UV) sensors based on solution-grown zinc oxide (ZnO) nanowires (NWs) which are only sensitive to photo-excitation at or below 400 nm wavelength have been fabricated and characterized. Both devices keep all processing steps, including nanowire growth, under 100 °C for compatibility with a wide variety of substrates. The first device type uses a single optical lithography step process to allow simultaneous in situ horizontal NW growth from solution and creation of symmetric ohmic contacts to the nanowires. The second device type uses a two-mask optical lithography process to create asymmetric ohmic and Schottky contacts. For the symmetric ohmic contacts, at a voltage bias of 1 V across the device, we observed a 29-fold increase in current in comparison to dark current when the NWs were photo-excited by a 400 nm light-emitting diode (LED) at 0.15 mW cm(-2) with a relaxation time constant (τ) ranging from 50 to 555 s. For the asymmetric ohmic and Schottky contacts under 400 nm excitation, τ is measured between 0.5 and 1.4 s over varying time internals, which is ~2 orders of magnitude faster than the devices using symmetric ohmic contacts.

GYGAX: Multi-Sensor Software Platform API

CLI .NET 4.0 research prototype platform coded in C# and Windows Presentation Foundation (WPF)

Distributed maximum likelihood for simultaneous self-localization and tracking in sensor networks

We show that the sensor self-localization problem can be cast as a static parameter estimation problem for Hidden Markov Models and we implement fully decentralized versions of the Recursive Maximum Likelihood and on-line Expectation-Maximization algorithms to localize the sensor network simultaneously with target tracking. For linear Gaussian models, our algorithms can be implemented exactly using a distributed version of the Kalman filter and a novel message passing algorithm. The latter allows each node to compute the local derivatives of the likelihood or the sufficient statistics needed for Expectation-Maximization. In the non-linear case, a solution based on local linearization in the spirit of the Extended Kalman Filter is proposed. In numerical examples we demonstrate that the developed algorithms are able to learn the localization parameters. © 2012 IEEE.