Comparison of Analytical and Numerical Methods of Obtaining Coplanar Capacitance of Microelectrodes for Particulate Matter Detection

This work reports a comparative analysis between the analytical and the finite element modelling, for the calculation of the capacitance of microelectrode-based capacitors in both parallel and coplanar architecture. It shows that the inverse-cosine and the Schwartz-Christoffel methods underestimate the capacitance value of the coplanar plate capacitor. It also shows that the parallel architecture closed form solution and the finite element modelling results agree well in all cases. The work finally compares the effects of design parameter change of the microelectrodes on the capacitance obtained from each technique. It shows that finite element modelling provides the best estimate of the capacitance of a coplanar plate capacitor

Portable multi-sensor air quality monitoring platform for personal exposure studies

© 1998-2012 IEEE. Poor air quality is considered among the main causes of millions of premature deaths annually, about 8 million in 2012 according to the World Health Organization [1]. Several epidemiological studies have found a relationship between exposure beyond specified limits and burden of disease [2]. These and many more have led to an increased and urgent need to both monitor and consequently limit personal exposure to harmful pollutants [3]. There is a generalized attention from different governmental agencies globally to limit anthropogenic emissions via legislations and policies. City councils, including for instance in Cambridge, UK, promote new policies that help accelerate switching from combustion engines to electric vehicles both for public and for private transport, accompanied by installation of a distributed urban network of rapid charging points by 2020 [4], along with imposition of road taxes, and exemption from the same based on vehicles' emission of polluting gases and smaller particulate matter (PM2.5). Besides, reduction of indoor wood burning for heating, as one of the largest sources of indoor particulate matter, also has the potential to drastically reduce PM2.5 exposure levels. Citizens are nowadays more conscious of and attentive to their personal exposure to polluting agents and environments and prone to adopt cleaner solutions for living, transport, energy generation and heating. Adoption of personal exposure monitoring devices on an individual level therefore offers multiple benefits and is motivated by the willingness to continue making healthier choices in everyday life consistently. Access to high resolution data of personal exposure with high space and time accuracy is however difficult to achieve with currently available centralized or public network of monitoring stations. Providing individuals with portable devices for air quality monitoring that operate in real time and allow them to monitor and record their personalized exposure levels in combination with conventional geolocation offering a half-meter or less space resolution may become a unique instrument and breakthrough, not only for the individuals, but also for the city councils, and other government agencies to shape and fine-tune their policies for control of air quality in urban, industrial and rural areas. This is possible with the use of both existing and emerging technologies for autonomous sensors, data communication and modern mobile networks, including Internet of Things

OptiJ: Open-source optical projection tomography of large organ samples

The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples

Design, Modeling and Simulation of a Capacitive Size-Discriminating Particulate Matter Sensor for Personal Air Quality Monitoring

We applied the well-established thermophoretic effect to air quality monitoring. We developed a novel method for particulate matter distribution analysis in an in-flow capacitive detection device. The proposed Multiphysics model combines fluid dynamics of particulate matter influenced by thermophoresis with electric field variations in the active volume space of a charged coplanar interdigitated electrodes. The model allows to anticipate the effect of thermophoresis in separating particles of PM10 and PM2.5 size ranges into different streams from a single particle-entrained flow and provides an estimated value of sensitivity for capacitive PM detection. The model is described through the Finite Element Method from the main equations to the simulation run using COMSOL Multiphysics and validated by comparing the results with literature. We obtained high sensor sensitivity of up to 0.48 zF/particle as far as 18 μm from coplanar electrode surface using the Computational Fluid Dynamics and Heat Transfer, Electrostatics and Particle tracing modules. We compare results of the simulations for different particle positions, electrode width and inter-electrode spacing, then we use the results to identify optimal design parameters for a novel architecture of a PM detection system with high sensitivity down to PM2.5 single particles and embedded particle size discrimination by using 10 μm electrode width and 1μm inter-electrode spacing.EP/KO3099X/1, EP/LO15889/1 Innovate UK 71476-481865, 73047-50126

Design, Modeling and Simulation of a Capacitive Size-Discriminating Particulate Matter Sensor for Personal Air Quality Monitoring

We applied the well-established thermophoretic effect to air quality monitoring. We developed a novel method for particulate matter distribution analysis in an in-flow capacitive detection device. The proposed Multiphysics model combines fluid dynamics of particulate matter influenced by thermophoresis with electric field variations in the active volume space of a charged coplanar interdigitated electrodes. The model allows to anticipate the effect of thermophoresis in separating particles of PM10 and PM2.5 size ranges into different streams from a single particle-entrained flow and provides an estimated value of sensitivity for capacitive PM detection. The model is described through the Finite Element Method from the main equations to the simulation run using COMSOL Multiphysics and validated by comparing the results with literature. We obtained high sensor sensitivity of up to 0.48 zF/particle as far as $18~\mu \text{m}$ from coplanar electrode surface using the Computational Fluid Dynamics and Heat Transfer, Electrostatics and Particle tracing modules. We compare results of the simulations for different particle positions, electrode width and inter-electrode spacing, then we use the results to identify optimal design parameters for a novel architecture of a PM detection system with high sensitivity down to PM2.5 single particles and embedded particle size discrimination by using $10~\mu \text{m}$ electrode width and \mu \text{m}$ inter-electrode spacing

Comparison of analytical and numerical methods of obtaining coplanar capacitance of microelectrodes for particulate matter detection

This work reports a comparative analysis between the analytical and the finite element modelling, for the calculation of the capacitance of microelectrode-based capacitors in both parallel and coplanar architecture. It shows that the inverse-cosine and the Schwartz-Christoffel methods underestimate the capacitance value of the coplanar plate capacitor. It also shows that the parallel architecture closed form solution and the finite element modelling results agree well in all cases. The work finally compares the effects of design parameter change of the microelectrodes on the capacitance obtained from each technique. It shows that finite element modelling provides the best estimate of the capacitance of a coplanar plate capacitor

Printable sensors for Nitrogen dioxide and Ammonia sensing at room temperature

© 2019 IEEE. Several studies have found a link between poor air quality and incidences of respiratory and cardiovascular diseases [1]-[6]. A World Health Organisation (WHO) report put the number of deaths caused by household air pollution at 4.3 million in 2012 [7]. Attempts at reducing poor air quality-related mortality have seen specification of safe human exposure limits for daily, and yearly average by government agencies such as Environmental Protection Agency (EPA) and World Health Organisation (WHO). Vehicle exhausts are key sources of Nitrogen dioxide, a key pollutant of ambient air. Other sources of NO2 includes fossil fuels and industrial engines. [8] NO2 is very toxic and causes acid rain. [9] Hence the need for sensitive, but more importantly selective sensors to monitor the levels of NO2 in breathable air. It is also desired that these sensors be able to provide fast response at room temperature. Exhaled breath testing has been known to be a quick, safe and non-intrusive approach to early detection of declining health due to the presence of biomarkers corresponding to underlying diseases in them. Volatile Organic Compounds (VOCs) and ammonia are some of these markers.[10] Ammonia is passed out in urine and the concentrations of ammonia in exhaled breath only increases as health declines and reaches 1ppm in the event of kidney failure[11] Chemiresistors are good candidates for these sensitive and selective sensors and research is ongoing to develop new material composites with the desired properties for this purpose. In this work we present chemiresistors based on two new material composites with potential to for applications in ambient air quality monitoring and breath analysis at room temperature. These composites can be printed or drop-casted on interdigitated electrodes on flexible substrates such as Polyimide (PI) and Polyethylene (PET). The NO2 sensor, with Graphene-Carboxymethylcellulose (CMC) sodium salt active material composite shows sensitivity and selectivity to NO2 at room temperature while the NH3 sensor, based on a Polyaniline - Zinc Oxide composite shows sensitivity at room temperature

Modelling and Simulation of a portable, size-discriminating Capacitive Particulate Matter sensor

© 2019 IEEE. Air pollution causes premature deaths and increased infant mortality. [1] Particulate Matter smaller than 2.5μm in aerodynamic diameter (PM2.5) exposure has been found to be the cause of airway inflammation and other adverse effects. [2], [3] Recent studies have shown that vehicular emissions are even more harmful for children on the roadside. [4] In fact, personal exposure has been found to be dependent on routes taken and transport modes. [5] Hence, air pollution mitigation strategies must be adapted in each location based on the emission sources. [6] A study in Brazil has estimated 400-1700 premature deaths to have been prevented by reducing deforestation, an important source of PM2.5. [7] This approach requires the use of portable sensors to provide high resolution data than obtained in stationary stations. However, smaller sensors are less accurate than the bulky static detectors. [8] Most commercially available portable PM sensors are based on light. But there has been problems with unit to unit deviation and inaccurate measurements. [9] Hence there is a need for portable, yet accurate PM sensors suitable for personal exposure monitoring. This work shows that the statistically relevant information on size distribution of particulate matter entrained in inhalable airflow can be obtained from miniaturised capacitive sensors using thermophoresis. Hence, the impact of a thermal gradient on the particles causes different sizes to separate into different streams and are deposited on corresponding electrodes and detected as capacitive jumps caused by the increase in the dielectric constant of the volume space occupied by the deposited particle. These results were obtained from modeling and simulation of the sensor using COMSOL Multiphysics® modules for computational fluid dynamics, heat transfer, particle tracing and electrostatics and were validated by comparing the simulation results with literature. This possibility to monitor different size ranges at such single particle scale in a portable device suitable for personal exposure studies is extremely important for the development of sensors suitable for non-intrusive personal exposure studies. This is because they provide high resolution measurements that account for spatiotemporal variations in air quality during its period of use in mobile conditions. The method can also be further miniaturized and integrated into MEMS as additional work anticipated elsewhere[10]. More representative information on air pollution will help to enhance the effectiveness of mitigation approaches

"Wear and Forget" patch for ambient assisted living

© 2019 IEEE. Rising cumulative costs of public hospital stay and its impact on government spending and the economy over the years has necessitated the adoption of other options of administering medical care such as home care, care homes and e-health [1]. The possibility of not having a health care personnel physically present in some of these scenarios created a need for remote patient monitoring. This has impacted positively on the development of new technologies for patient monitoring, personalised care, and assisted living especially as the world population age over the next few decades. These devices include hand-held/pocket-sized activity monitors, wearable patches [2], wristbands [3], [4], watches. While these devices are functional and are potentially cheaper when compared with in-hospital care, they have not been widely adopted for several reasons such as intrusiveness - some of them are rigid and inconvenient to be carried around by patients without substantial change to their everyday lives. Another reason is invasiveness - some devices sample patient blood repeatedly. In this work, we present a non-intrusive ("wear and forget") patch platform for patient monitoring. This device, fabricated on a flexible polyimide substrate, is light, flexible and conformable to the human body, has a longer range of detection because of integrated flexible battery and supercapacitor, and transfers data collected from patient wirelessly to an RFID reader located nearby, providing opportunity for both ambient and remote monitoring [2], as well as personalised e-health assistance and continuous monitoring, which enables early detection of declining health [5]

Portable multi-sensor air quality monitoring platform for personal exposure studies

© 1998-2012 IEEE. Poor air quality is considered among the main causes of millions of premature deaths annually, about 8 million in 2012 according to the World Health Organization [1]. Several epidemiological studies have found a relationship between exposure beyond specified limits and burden of disease [2]. These and many more have led to an increased and urgent need to both monitor and consequently limit personal exposure to harmful pollutants [3]. There is a generalized attention from different governmental agencies globally to limit anthropogenic emissions via legislations and policies. City councils, including for instance in Cambridge, UK, promote new policies that help accelerate switching from combustion engines to electric vehicles both for public and for private transport, accompanied by installation of a distributed urban network of rapid charging points by 2020 [4], along with imposition of road taxes, and exemption from the same based on vehicles' emission of polluting gases and smaller particulate matter (PM2.5). Besides, reduction of indoor wood burning for heating, as one of the largest sources of indoor particulate matter, also has the potential to drastically reduce PM2.5 exposure levels. Citizens are nowadays more conscious of and attentive to their personal exposure to polluting agents and environments and prone to adopt cleaner solutions for living, transport, energy generation and heating. Adoption of personal exposure monitoring devices on an individual level therefore offers multiple benefits and is motivated by the willingness to continue making healthier choices in everyday life consistently. Access to high resolution data of personal exposure with high space and time accuracy is however difficult to achieve with currently available centralized or public network of monitoring stations. Providing individuals with portable devices for air quality monitoring that operate in real time and allow them to monitor and record their personalized exposure levels in combination with conventional geolocation offering a half-meter or less space resolution may become a unique instrument and breakthrough, not only for the individuals, but also for the city councils, and other government agencies to shape and fine-tune their policies for control of air quality in urban, industrial and rural areas. This is possible with the use of both existing and emerging technologies for autonomous sensors, data communication and modern mobile networks, including Internet of Things