Papers by Julian W Gardner
The key sensor requirements for global-scale environmental monitoring are: low cost; low power; h... more The key sensor requirements for global-scale environmental monitoring are: low cost; low power; high volume production capabilities; miniature size and ubiquitous, self-powered wireless deployment. Based upon these requirements, a new generation of miniature sensors is emerging that employ nano-materials, such as metal oxides, polymers, carbon, graphene -sometimes structured as nanotubes ornanowires. Platform technologies used for depositing these gas sensing materials are commonly based on ceramic substrate, printable polymer, or silicon wafers together with a MEMS processing step. Amongst these, the most promising platform is the silicon substrate. In particular, a silicon substrate can be processed in commercial foundries with integrated CMOS circuits and is considered to be the most attractive option to enable high volume, low cost ubiquitous smart solutions with multi-sensing solutions. In this paper we give some examples of sensors that have been, or are being developed, for commercial environmental monitoring applications. Using CMOS silicon wafers for environmental sensing application offers added benefits that the sensors can be readily incorporated within portable devices such as smartphones, wearables or even in whitegoods including automotive and other purpose-built electronic systems. We also give examples of such sensors and array of sensors and highlight some of the key benefits of using CMOS sensing solutions for future environmental monitoring.
Sensors and Actuators B-chemical, 2019
Custom sensor module developed for use in harsh environments by rescue personnel High-bandwid... more Custom sensor module developed for use in harsh environments by rescue personnel High-bandwidth MOX sensors evaluated to plumes of VOCs inside a wind tunnel PdPt SnO2, WO3 and NiO coated MOX sensors produce fast responses to low ppm plumes Pulse broadening of VOC plumes observed and mapped inside tunnel Performance verified in real world, unit is ready for use in hazardous environments
Sensors and Actuators B-chemical, Nov 1, 2016
MEMS based NDIR system for ppm CO2 detection with lock-in amplifier. Fast 1.3 s response time... more MEMS based NDIR system for ppm CO2 detection with lock-in amplifier. Fast 1.3 s response time for breath-by-breath analysis. Portable breath analyser designed for measuring metabolic rate of subjects. Effect of path length on NDIR system investigated with novel sensor housing. Silicon on insulator IR emitter used for low power, low cost gas detection.
In this work we present a novel multi-sensor unit to detect and discriminate unknown gases in unc... more In this work we present a novel multi-sensor unit to detect and discriminate unknown gases in uncontrolled environments. The unit includes three metal oxide (MOX) sensors with CMOS micro heaters, a plasmonic enhanced nondispersive infra-red (NDIR) sensor, a commercial temperature humidity sensor, and a flow sensor. The proposed sensing unit was evaluated with plumes of gases (propanol, ethanol and acetone) in both, a laboratory setup on a gas testing bench and on-board a mobile robot operating in an indoor workshop. It offers significantly improved performance compared to commercial systems, in terms of power consumption, response time and physical size. We verified the ability to discriminate gases in an unsupervised manner, with data collected on the robot and high accuracy was obtained in the classification of propanol versus acetone (96%), and ethanol versus acetone (90%).
Dairy Farm Ownership and Management Structures: Focus Group Research
ifmaonline.org
The traditional route for individuals in the New Zealand dairy industry is from farm worker to sh... more The traditional route for individuals in the New Zealand dairy industry is from farm worker to sharemilker to owner-operator. In recent years new routes have emerged. The purpose of this research is to gain a clearer understanding of the variety of ownership ...
IEEE Transactions on Electron Devices, Aug 1, 2019
Please refer to published version for the most recent bibliographic citation information. If a pu... more Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.
Sensors, Jan 6, 2023
In recent years, there has been a growing desire to monitor and control harmful substances arisin... more In recent years, there has been a growing desire to monitor and control harmful substances arising from industrial processes that impact upon our health and quality of life. This has led to a large market demand for gas sensors, which are commonly based on sensors that rely upon a chemical reaction with the target analyte. In contrast, thermal conductivity detectors are physical sensors that detect gases through a change in their thermal conductivity. Thermal conductivity gas sensors offer several advantages over their chemical (reactive) counterparts that include higher reproducibility, better stability, lower cost, lower power consumption, simpler construction, faster response time, longer lifetime, wide dynamic range, and smaller footprint. It is for these reasons, despite a poor selectivity, that they are gaining renewed interest after recent developments in MEMS-based silicon sensors allowing CMOS integration and smart application within the emerging Internet of Things (IoT). This timely review focuses on the state-of-the-art in thermal conductivity sensors; it contains a general introduction, theory of operation, interface electronics, use in commercial applications, and recent research developments. In addition, both steady-state and transient methods of operation are discussed with their relative advantages and disadvantages presented. Finally, some of recent innovations in thermal conductivity gas sensors are explored.
Proceedings, Nov 20, 2018
A new signal processing technique has been developed for resistive metal oxide (MOX) gas sensors ... more A new signal processing technique has been developed for resistive metal oxide (MOX) gas sensors to enable high-bandwidth measurements and enhanced selectivity at PPM levels (<50 PPM VOCs). An embedded micro-heater is thermally pulsed from 225 to 350 °C, which enables the chemical reactions in the sensor film (e.g., SnO2, WO3, NiO) to be extracted using a fast Fourier transform. Signal processing is performed in real-time using a low-cost microcontroller integrated into a sensor module. The approach enables the remove of baseline drift and is resilient to environmental temperature changes. Bench-top experimental results are presented for 50 to 200 ppm of ethanol and CO, which demonstrate our sensor system can be used within a mobile robot.
Identification of Urine Odour Using CMOS-Based Metal Oxide Resistive Gas Sensors
2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII)
In this work, three custom-made metal oxide (MOX) sensors were used to identify gaseous headspace... more In this work, three custom-made metal oxide (MOX) sensors were used to identify gaseous headspace of synthetic urine from acetone, ammonia and ethyl acetate. The sensors have chemical coatings of WO3, Pd/Pt doped SnO2 and CuO. Gases were trialled at 1 to 10 ppm for ammonia and ethyl acetate, 1 to 50 ppm for acetone and 5 to 100% for gaseous synthetic urine. A gas sensing unit was used for experiments and the collected data were processed in a two-layered pattern recognition model for gas classification. Five datasets were collected, four used for training and one for testing. The model has an overall accuracy of 91.1% and 100% for identifying synthetic urine.
Thermally Modulated CMOS-Compatible Particle Sensor for Air Quality Monitoring
IEEE Transactions on Instrumentation and Measurement, 2022
Combating the health effects of particulate matter (PM) pollution requires affordable and reliabl... more Combating the health effects of particulate matter (PM) pollution requires affordable and reliable real-time air quality monitoring. The potential for large-scale manufacturing of acoustic-wave-based sensors makes them an interesting option for low-cost, low-power particle sensing applications. This article demonstrates a solidly mounted resonator (SMR) PM sensor with improved sensitivity through thermal modulation of the device. A novel, complementary metal oxide semiconductor (CMOS)-compatible SMR with an integrated microheater was designed, manufactured, and tested. In simulations, it was found that particle deposition increases both the heat loss and the thermal time constant of SMR. The effect of this on the resonant frequency shift of the device caused by particle deposition is investigated closely in this work. The sensitivity of the devices to particle deposition was tested experimentally with and without temperature modulation by placing the device in a test chamber and allowing the randomized settling of aerosolized particles on its surface. The unmodulated sensor demonstrated a particle mass sensitivity of ~40 Hz/ng while the mass sensitivity of the temperature-modulated device was shown to improve by a factor of nearly $\times 5$ to 190 Hz/ng. Temperature modulation also improved the detection limit from 100 to 50 ng. Further experiments were conducted by adding an impactor mechanism to have a more controlled measurement setup. To this effect, a thermophoretic particle deposition mechanism was added to the device to enhance its performance. It was demonstrated that the repeatability of measurements was significantly improved, making the device a promising low-cost technology for air quality monitoring.
Smart City Battery Operated IoT Based Indoor Air Quality Monitoring System
2020 IEEE SENSORS, 2020
Indoor and outdoor air pollution is known to cause many health problems. In order to improve air ... more Indoor and outdoor air pollution is known to cause many health problems. In order to improve air quality it is essential to monitor relevant parameters and identify sources of pollutants. This paper presents the design and development of a low-cost, portable Internet of Things (IoT) Indoor Air Quality (IAQ) monitoring system with 30 hours of battery life. The unit is intended for the monitoring of total VOCs, CO2, PM2.5, PM10, temperature, humidity and illuminance. The system can be used for both real-time measurements as well as hourly and daily averaging, in low power modes, and interfaces with a custom Blynk smartphone app, developed for easy user engagement. The device calculates a qualitative air quality index from measurements taken in-situ, based on United States Environmental Protection Agency (EPA) standards. Environmental data is used by the system to provide recommendations, such as increasing ventilation or reducing activity levels, which can help users improve their air quality. This system can be used as a node to monitor air quality in large scale networks for Smart Cities.
Wearable IoT Electronic Nose for Urinary Incontinence Detection
2020 IEEE SENSORS, 2020
This paper presents the development of a low cost and low power wearable Electronic Nose with IoT... more This paper presents the development of a low cost and low power wearable Electronic Nose with IoT connectivity for detecting synthetic urine. This system was designed with the ultimate aim to relieve the burdens associated with urinary incontinence for both sufferers and healthcare workers in hospitals and care homes. Commercially proven metal oxide (MOX) gas sensors for Volatile Organic Compound (VOC) detection such as the SGP30 and MiCS-5524 series of gas sensors were used, as well as the custom-made WO3, SnO2 and CuO MOX sensors developed at the Microsensors and Bioelectronics laboratory at the University of Warwick. A web-application was created to facilitate real-time monitoring over the MQTT protocol and indicate when urine has been detected. The capabilities of the IoT for this purpose allow for enhanced patient mobility and simultaneous patient monitoring. An artificial neural network was used to classify synthetic urine from other odours. The model was able to identify synthetic urine with 100% accuracy based on prior training and testing datasets.
Japanese Journal of Applied Physics, 2009
High-frequency and wideband surface acoustic wave (SAW) devices have become an important topic in... more High-frequency and wideband surface acoustic wave (SAW) devices have become an important topic in 5G communication systems and beyond. For this purpose, piezoelectric ScAlN thin films deposited on high SAW velocity diamond are studied in SAW resonators on the polycrystalline diamond (PCD) and hetero-epitaxial diamond (HED) substrates. A very strong c-axis orientation of ScAlN on HED was confirmed. Interdigital transducers of 0.8 μm and 0.5 μm were fabricated to realize 2.2 to 3.5 GHz high-frequency resonators. High Q values were obtained for the 2.3-2.5 GHz device on both PCD and HED. Additionally, a high electro-mechanical coupling coefficient (K 2) of 5.40-5.52% and high SAW velocities of 7400-7766 m/s were obtained in the 2.3-2.5 GHz devices. In comparison to the simulated coupling coefficient results of a previous report, ScAlN/diamond might have higher K 2 for the Sezawa wave.
CMOS Compatible Aluminium Nitride Solidly Mounted Resonator with an Integrated Microheater for Temperature Modulation
2021 21st International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), 2021
The increase in air pollution and its effect on human health, is highlighting a growing demand fo... more The increase in air pollution and its effect on human health, is highlighting a growing demand for ubiquitous low-cost air quality monitors. Acoustic resonators have significant potential to satisfy this need. Solidly mounted resonators (SMR) are of special interest, because they have the advantage of being small and can be integrated into smart CMOS systems for air quality monitoring. This paper presents a CMOS-based SMR with a resonant frequency of about 2 GHz and a Q-factor of ca 200. The device comprises an integrated microheater with multi-purpose potential for temperature frequency modulation, temperature control, enhanced device sensitivity, sensor self-cleaning and use of single sensor as a virtual sensor array.
Characterisation of Zinc Oxide Thin-Film Solidly Mounted Resonators for Particle Sensing in Air
2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2020
Monitoring particulate matter concentrations is of particular importance within the overall asses... more Monitoring particulate matter concentrations is of particular importance within the overall assessment of indoor and outdoor air quality and its impact on human health. Bulk acoustic wave (BAW) technology offers low cost, robust alternative to widely employed optical measurements. However, due to its reasonably new application within the area of particulate measurements, an in-depth characterisation of this technology to temperature and humidity variations that are inevitably present within the indoor and outdoor environment is necessary step in order to determine its suitability for possible commercialisation. This work presents the characterisation of the temperature and humidity dependence of solidly mounted resonators for particulate matter sensing. Both theoretical results, obtained through modelling and simulation, and experimental result, obtained within the laboratory conditions, are analysed and compared. A 1.5 GHz resonator with a zinc oxide thin film is modelled using a one-dimensional equivalent circuit model, and finite-element methods based on both two-dimensional model and the three-dimensional model. The simulation results show that the temperature dependence of the resonator is strongly dependent on the material properties and crystal structure of the zinc oxide film. Our models estimate the temperature coefficient of frequency to be -30 to -40 ppm/Centigrade. This theoretical temperature dependence was comparable to experimentally measured value of ca. -49 ppm/Centigrade. In addition to temperature characterisation of discrete devices, the resonator was combined with read-out circuitry, which was also simulated and tested experimentally. The temperature coefficient of frequency in this case was found to be much higher at -220 ppm/Centigrade demonstrating the necessity for temperature control or temperature compensation within the complete system in practical applications. The effect of humidity was also investigated. The experimental mean resonant frequency shift per percent increase in relative humidity of the ambient air was found to be -3.8 kHz/%RH, while the models showed negligible sensitivity to humidity variations. Finally, preliminary experiments were conducted within the controlled lab environment showing promising result for possible application of this technology in particulate matter monitoring. The resonant frequency shift of approximately 300 kHz was measured after mass loading the sensing area of the resonator with estimated 24 ng of standard Arizona dust particles.
2017 IEEE SENSORS, 2017
This document is the author's post-print version, incorporating any revisions agreed during the p... more This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.
AlN FBAR Particle Sensor With a Thermophoretic Sampling Mechanism
IEEE Sensors Journal, 2021
Pollution by particulate matter (PM) poses a serious and growing risk to human health. Film Bulk ... more Pollution by particulate matter (PM) poses a serious and growing risk to human health. Film Bulk Acoustic Resonators (FBARs) have been proposed as a low-cost way to monitor particle concentration. This paper presents particle detection by a 1.1 GHz aluminium nitride based FBAR designed and fabricated by SilTerra Malaysia. The FBARs are used in a differential configuration with one sensing and one reference device in a system comprising a microchannel with an electric microfan and a thermophoretic precipitator microhotplate array for improved sampling. A custom-built test chamber was designed to characterise the device at different levels of particulate matter concentration in air. The particle feed rate into the test chamber was varied between 9.5, 19, 43, 66 and <inline-formula> <tex-math notation="LaTeX">$94~\mu \text{g}/\text{m}^{3}\text{s}$ </tex-math></inline-formula>. The FBAR frequency was found to decrease with increasing particulate matter concentration in the test chamber air. The experiments were conducted with and without the microchannel and it was found that the sampling channel increased sensitivity of FBAR resonant frequency to particle concentration per cubic meter of air from 5 Hz/<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>gm<sup>−3</sup> to 20 Hz/<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>gm<sup>−3</sup>. The detection limit in this test was estimated at ca. <inline-formula> <tex-math notation="LaTeX">$50~\mu \text{g}/\text{m}^{3}$ </tex-math></inline-formula>, which is around current European limits for PM10 pollution. In addition, the use of the sampling microfan to aid cleaning of FBARs after particle measurement was also investigated and found to be feasible especially for lower particle concentration.
Sensors, 2021
Accurate air quality monitoring requires processing of multi-dimensional, multi-location sensor d... more Accurate air quality monitoring requires processing of multi-dimensional, multi-location sensor data, which has previously been considered in centralised machine learning models. These are often unsuitable for resource-constrained edge devices. In this article, we address this challenge by: (1) designing a novel hybrid deep learning model for hourly PM2.5 pollutant prediction; (2) optimising the obtained model for edge devices; and (3) examining model performance running on the edge devices in terms of both accuracy and latency. The hybrid deep learning model in this work comprises a 1D Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) to predict hourly PM2.5 concentration. The results show that our proposed model outperforms other deep learning models, evaluated by calculating RMSE and MAE errors. The proposed model was optimised for edge devices, the Raspberry Pi 3 Model B+ (RPi3B+) and Raspberry Pi 4 Model B (RPi4B). This optimised model reduced file size to ...
Proceedings, 2020
Biosensors play a key role in medical diagnostics, and acoustic wave technology such as solidly m... more Biosensors play a key role in medical diagnostics, and acoustic wave technology such as solidly mounted resonators (SMRs) applied to this field is one of the latest developments with great potential. This study seeks to explore the potential application of SMRs to detect and quantify prostate-specific antigen (PSA) for the screening and diagnosis of prostate cancer. The primary results show promising frequency shift of SMR sensors coated with Polydimethylsiloxane (PDMS) to different liquids. The SMR frequency is 1.082, 1.084 and 1.088 GHz, respectively, to air, deionized water and toluene (liquid) presence. These sensors have great potential as an accurate, low-cost method for measuring PSA and biomarkers for cancer and other diseases.
IEEE Sensors Journal, 2018
The version presented here may differ from the published version or, version of record, if you wi... more The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription.
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Papers by Julian W Gardner