Browsing by Subject "Sensors"

The primary focus of this dissertation is on the assessment of fugitive methane emissions from near and far-field sources. Methane is the second most prevalent greenhouse gas (GHG) emitted in the United States from anthropogenic activities. Due to measurement and model limitations, there is not an accurate assessment of how much methane in the atmosphere is due to anthropogenic sources. This dissertation focuses on measuring the methane emissions from two of the three largest anthropogenic sources -- landfills and natural gas systems. All measurements are made with a single fixed or single mobile sensor. Methods are developed to assess the source strength for both near (i.e. natural gas) and far-field (i.e. landfill) sources using either the fixed or mobile sensor.

For far-field measurements, a standardized version of a mobile tracer correlation measurement method was developed and used for assessment of methane emissions from 15 landfills in 56 field deployments from 2009 to 2013. A total of 1876 mobile tracer correlation measurement transects were attempted over 131 field sampling days.

Transects were analyzed using signal to noise ratio, plume correlation, and emission rate difference method quality indicators. The application of the method quality indicators yield 456 transects (33\%) that pass data acceptance criteria.

For near-field sources, techniques are developed for 1) fixed sensors sampling through time downwind of a source and 2) mobile sensors passing across plumes downwind of a source. For the fixed sensor, the lateral plume geometry is reconstructed from the fluctuating wind direction using a derived relationship between the wind direction and crosswind plume position. The crosswind plume spread is estimated with two different methods (modeled and observed), and subsequently used a Gaussian plume inversion to estimate the source strengths. For the fixed sensor, the sensor takes measurements for about 20 minutes and we are able to reconstruct the ensemble average of the plume.

For the mobile sensor, the vehicle drives through the plume in the crosswind direction.

The measurements show the lateral plume geometry of an instantaneous plume. The instantaneous plume has a narrowed Gaussian structure.

Two techniques are tested using data from controlled methane release experiments; these two techniques are 1) linear-squares and 2) a probabilistic approach. For the probabilistic approach, Bayesian inference tools are applied and special attention is paid to the relevant likelihood functions for both short time averaged concentrations from a single fixed sensor and spatial transects of instantaneous concentration measurements from a mobile sensor. The two techniques are also tested on measurements downwind of multiple natural gas production facilities in Wyoming for the fixed sensor and in Colorado for the moving sensor. The results for both the fixed and mobile techniques show promise for use with gas sensors on industry work trucks, opportunistically providing surveillance over a region of well pads.

With the advent of the internet-of-things (IoT) and a more connected digital ecosystem, new electronic sensors and systems are needed. Printing has been identified as a means of fabricating low-cost electronics on non-rigid, large-area substrates. Printed electronics have been demonstrated to have the required electrical and mechanical properties to facilitate new and unique flexible electronic sensors for the IoT. One printable material that has demonstrated significant promise, specifically when compared to more traditional printed semiconductors, is solution-processed carbon nanotubes (CNTs). While some work has been done to facilitate the fabrication of CNT thin-film transistors (TFTs), little work has been done to assess the viability and potential of CNT-TFTs and other CNT thin films for real-world sensing applications.

The work contained in this dissertation describes the use of aerosol jet printing to fabricate CNT-TFTs, and the resulting study of their capability for various sensing applications. Aerosol jet printing allows for printing all the materials necessary for a fully-functional CNT-TFT, including the semiconducting thin film, conducting contacts and gate, and insulating gate dielectric. Using this system, flexible and fully printed CNT-TFTs were developed and characterized. Fully printed transistors were fabricated with field-effect mobilities as a high as 16 cm2/(Vs). The transistors were also resilient to substantial bending/strain, showing no measurable performance degradation after 1000 bending cycles at a radius of curvature of 1 mm.

The printed CNT-TFTs were evaluated for several sensing applications, including environmental pressure sensing and point-of-care biological sensing. The biological sensors, which were electronically transduced immunoassays, consisted of an antifouling polymer brush layer to enhance the CNT-TFT sensitivity and printed antibodies for detection of target analytes. Unparalleled sensitivity in unfiltered biological milieus was realized with these printed biosensors, detecting protein concentrations as low as 10 pg/ml in whole blood. In addition to demonstrating an electronically transduced TFT-based biosensor, work was done to develop a stable platform with high yield that will provide the means for a deeper understanding of the biosensing mechanisms of transistor-based sensors. As part of this biosensor platform development, novel solution-gated CNT-TFTs were demonstrated, with stable operation in ionic solutions for periods as long as 5 hours.

Another important electronic sensing technique is capacitive-based sensing. Using aerosol jet printed carbon nanotubes, a capacitive sensor has been developed and demonstrated for measuring insulating material thickness. The sensors rely on the fringing field between two adjacent electrodes interacting with the material out-of-plane, and that interaction being perturbed differently based on the thickness of the overlaid material. This sensor was also demonstrated in a one-dimensional array, which can be used to map tire tread thickness from the outside of the tire.

Overall, this dissertation explores the use of printed carbon nanotubes for diverse sensing applications. While this work provides real-world demonstrations that have potential impact for the IoT, there are also substantial scientific advancements made. Namely, insight into biosensing mechanisms, operation of solution-gated nanomaterial-based transistors, and demonstration of porosity and thickness effects on printed capacitive sensor electrodes.

Localization is projected to play a critical role in mobile computing applications. Nevertheless, the state of the art is inadequate especially when operating on mobile devices. More specifically, the on-phone GPS sensor has an unacceptable energy consumption and does not operate indoors. Alternate localization techniques, based on WiFi or GSM, alleviate some of the GPS limitations but provide degraded accuracy and assume pre-installed infrastructure. As a result, these solutions need extensive war-driving for collecting location fingerprints and, in many instances, limit services to regions close to drivable paths. Moreover, when infrastructure is scarce or missing, the localization accuracy is poor. Lastly, relying on hardware deployments is costly and raises scalability concerns when targeting wide regions.

To address the shortcomings of current solutions, we propose four new localization systems: (1) CompAcc enables energy-efficient, war-driving-free localization using the phone inertial sensors and digital maps, (2) Escort provides indoor localization by exploiting the phone inertial sensors and social environments where people are mobile, (3) SurroundSense enables indoor logical localization (e.g., inside Target) by sensing the user ambiance through the phone sensors, and (4) EnLoc proposes energy-efficient localization via personalized mobility profiling and predictions.