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Description
Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to determine the speed of the plane. A clinical example would be that the flow of a patient's breath which could help determine the state of the patient's lungs. This project is focused on the flow-meter that are used for airflow measurement in human lungs. In order to do these measurements, resistive-type flow-meters are commonly used in respiratory measurement systems. This method consists of passing the respiratory flow through a fluid resistive component, while measuring the resulting pressure drop, which is linearly related to volumetric flow rate. These types of flow-meters typically have a low frequency response but are adequate for most applications, including spirometry and respiration monitoring. In the case of lung parameter estimation methods, such as the Quick Obstruction Method, it becomes important to have a higher frequency response in the flow-meter so that the high frequency components in the flow are measurable. The following three types of flow-meters were: a. Capillary type b. Screen Pneumotach type c. Square Edge orifice type To measure the frequency response, a sinusoidal flow is generated with a small speaker and passed through the flow-meter that is connected to a large, rigid container. True flow is proportional to the derivative of the pressure inside the container. True flow is then compared with the measured flow, which is proportional to the pressure drop across the flow-meter. In order to do the characterization, two LabVIEW data acquisition programs have been developed, one for transducer calibration, and another one that records flow and pressure data for frequency response testing of the flow-meter. In addition, a model that explains the behavior exhibited by the flow-meter has been proposed and simulated. This model contains a fluid resistor and inductor in series. The final step in this project was to approximate the frequency response data to the developed model expressed as a transfer function.
ContributorsHu, Jianchen (Author) / Macia, Narciso (Thesis advisor) / Pollat, Scott (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this work, the vapor transport and aerobic bio-attenuation of compounds from a multi-component petroleum vapor mixture were studied for six idealized lithologies in 1.8-m tall laboratory soil columns. Columns representing different geological settings were prepared using 20-40 mesh sand (medium-grained) and 16-minus mesh crushed granite (fine-grained). The contaminant vapor source was a liquid composed of twelve petroleum hydrocarbons common in weathered gasoline. It was placed in a chamber at the bottom of each column and the vapors diffused upward through the soil to the top where they were swept away with humidified gas. The experiment was conducted in three phases: i) nitrogen sweep gas; ii) air sweep gas; iii) vapor source concentrations decreased by ten times from the original concentrations and under air sweep gas. Oxygen, carbon dioxide and hydrocarbon concentrations were monitored over time. The data allowed determination of times to reach steady conditions, effluent mass emissions and concentration profiles. Times to reach near-steady conditions were consistent with theory and chemical-specific properties. First-order degradation rates were highest for straight-chain alkanes and aromatic hydrocarbons. Normalized effluent mass emissions were lower for lower source concentration and aerobic conditions. At the end of the study, soil core samples were taken every 6 in. Soil moisture content analyses showed that water had redistributed in the soil during the experiment. The soil at the bottom of the columns generally had higher moisture contents than initial values, and soil at the top had lower moisture contents. Profiles of the number of colony forming units of hydrocarbon-utilizing bacteria/g-soil indicated that the highest concentrations of degraders were located at the vertical intervals where maximum degradation activity was suggested by CO2 profiles. Finally, the near-steady conditions of each phase of the study were simulated using a three-dimensional transient numerical model. The model was fit to the Phase I data by adjusting soil properties, and then fit to Phase III data to obtain compound-specific first-order biodegradation rate constants ranging from 0.0 to 5.7x103 d-1.
ContributorsEscobar Melendez, Elsy (Author) / Johnson, Paul C. (Thesis advisor) / Andino, Jean (Committee member) / Forzani, Erica (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Kavazanjian, Edward (Committee member) / Arizona State University (Publisher)
Created2012
Description
Demand for biosensor research applications is growing steadily. According to a new report by Frost & Sullivan, the biosensor market is expected to reach $14.42 billion by 2016. Clinical diagnostic applications continue to be the largest market for biosensors, and this demand is likely to continue through 2016 and beyond. Biosensor technology for use in clinical diagnostics, however, requires translational research that moves bench science and theoretical knowledge toward marketable products. Despite the high volume of academic research to date, only a handful of biomedical devices have become viable commercial applications. Academic research must increase its focus on practical uses for biosensors. This dissertation is an example of this increased focus, and discusses work to advance microfluidic-based protein biosensor technologies for practical use in clinical diagnostics. Four areas of work are discussed: The first involved work to develop reusable/reconfigurable biosensors that are useful in applications like biochemical science and analytical chemistry that require detailed sensor calibration. This work resulted in a prototype sensor and an in-situ electrochemical surface regeneration technique that can be used to produce microfluidic-based reusable biosensors. The second area of work looked at non-specific adsorption (NSA) of biomolecules, which is a persistent challenge in conventional microfluidic biosensors. The results of this work produced design methods that reduce the NSA. The third area of work involved a novel microfluidic sensing platform that was designed to detect target biomarkers using competitive protein adsorption. This technique uses physical adsorption of proteins to a surface rather than complex and time-consuming immobilization procedures. This method enabled us to selectively detect a thyroid cancer biomarker, thyroglobulin, in a controlled-proteins cocktail and a cardiovascular biomarker, fibrinogen, in undiluted human serum. The fourth area of work involved expanding the technique to produce a unique protein identification method; Pattern-recognition. A sample mixture of proteins generates a distinctive composite pattern upon interaction with a sensing platform consisting of multiple surfaces whereby each surface consists of a distinct type of protein pre-adsorbed on the surface. The utility of the "pattern-recognition" sensing mechanism was then verified via recognition of a particular biomarker, C-reactive protein, in the cocktail sample mixture.
ContributorsChoi, Seokheun (Author) / Chae, Junseok (Thesis advisor) / Tao, Nongjian (Committee member) / Yu, Hongyu (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2011
Description
The world of healthcare can be seen as dynamic, often an area where technology and science meet to consummate a greater good for humanity. This relationship has been working well for the last century as evident by the average life expectancy change. For the greater of the last five decades the average life expectancy at birth increased globally by almost 20 years. In the United States specifically, life expectancy has grown from 50 years in 1900 to 78 years in 2009. That is a 76% increase in just over a century. As great as this increase sounds for humanity it means there are soon to be real issues in the healthcare world. A larger older population will need more healthcare services but have fewer young professionals to provide those services. Technology and science will need to continue to push the boundaries in order to develop and provide the solutions needed to continue providing the aging world population sufficient healthcare. One solution sure to help provide a brighter future for healthcare is mobile health (m-health). M-health can help provide a means for healthcare professionals to treat more patients with less work expenditure and do so with more personalized healthcare advice which will lead to better treatments. This paper discusses one area of m-health devices specifically; human breath analysis devices. The current laboratory methods of breath analysis and why these methods are not adequate for common healthcare practices will be discussed in more detail. Then more specifically, mobile breath analysis devices are discussed. The topic will encompass the challenges that need to be met in developing such devices, possible solutions to these challenges, two real examples of mobile breath analysis devices and finally possible future directions for m-health technologies.
ContributorsLester, Bryan (Author) / Forzani, Erica (Thesis advisor) / Xian, Xiaojun (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2012
Description
Volatile Organic Compounds (VOCs) are central to atmospheric chemistry and have significant impacts on the environment. The reaction of oxygenated VOCs with OH radicals was first studied to understand the fate of oxygenated VOCs. The rate constants of the gas-phase reaction of OH radicals with trans-2-hexenal, trans-2-octenal, and trans-2 nonenal were determined using the relative rate technique. Then the interactions between VOCs and ionic liquid surfaces were studied. The goal was to find a material to selectively detect alcohol compounds. Computational chemistry calculations were performed to investigate the interactions of ionic liquids with different classes of VOCs. The thermodynamic data suggest that 1-butyl-3-methylimindazolium chloride (C4mimCl) preferentially interacts with alcohols as compared to other classes of VOCs. Fourier transform infrared spectroscopy was used to probe the ionic liquid surface before and after exposure to the VOCs that were tested. New spectral features were detected after exposure of C4mimCl to various alcohols and a VOC mixture with an alcohol in it. The new features are characteristic of the alcohols tested. No new IR features were detected after exposure of the C4mimCl to the aldehyde, ketone, alkane, alkene, alkyne or aromatic compounds. The experimental results demonstrated that C4mimCl is selective to alcohols, even in complex mixtures. The kinetic study of the association and dissociation of alcohols with C4minCl surfaces was performed. The findings in this work provide information for future gas-phase alcohol sensor design. CO2 is a major contributor to global warming. An ionic liquid functionalized reduced graphite oxide (IL-RGO)/ TiO2 nanocomposite was synthesized and used to reduce CO2 to a hydrocarbon in the presence of H2O vapor. The SEM image revealed that IL-RGO/TiO2 contained separated reduced graphite oxide flakes with TiO2 nanoparticles. Diffuse Reflectance Infrared Fourier Transform Spectroscopy was used to study the conversion of CO2 and H2O vapor over the IL-RGO/TiO2 catalyst. Under UV-Vis irradiation, CH4 was found to form after just 40 seconds of irradiation. The concentration of CH4 continuously increased under longer irradiation time. This research is particularly important since it seems to suggest the direct, selective formation of CH4 as opposed to CO.
ContributorsGao, Tingting (Author) / Andino, Jean M (Thesis advisor) / Forzani, Erica (Committee member) / Kavazanjian, Edward (Committee member) / Arizona State University (Publisher)
Created2012
Description
Vapor intrusion (VI) pathway assessment often involves the collection and analysis of groundwater, soil gas, and indoor air data. There is temporal variability in these data, but little is understood about the characteristics of that variability and how it influences pathway assessment decision-making. This research included the first-ever collection of a long-term high-frequency indoor air data set at a house with VI impacts overlying a dilute chlorinated solvent groundwater plume. It also included periodic synoptic snapshots of groundwater and soil gas data and high-frequency monitoring of building conditions and environmental factors. Indoor air trichloroethylene (TCE) concentrations varied over three orders-of-magnitude under natural conditions, with the highest daily VI activity during fall, winter, and spring months. These data were used to simulate outcomes from common sampling strategies, with the result being that there was a high probability (up to 100%) of false-negative decisions and poor characterization of long-term exposure. Temporal and spatial variability in subsurface data were shown to increase as the sampling point moves from source depth to ground surface, with variability of an order-of-magnitude or more for sub-slab soil gas. It was observed that indoor vapor sources can cause subsurface vapor clouds and that it can take days to weeks for soil gas plumes created by indoor sources to dissipate following indoor source removal. A long-term controlled pressure method (CPM) test was conducted to assess its utility as an alternate approach for VI pathway assessment. Indoor air concentrations were similar to maximum concentrations under natural conditions (9.3 μg/m3 average vs. 13 μg/m3 for 24 h TCE data) with little temporal variability. A key outcome was that there were no occurrences of false-negative results. Results suggest that CPM tests can produce worst-case exposure conditions at any time of the year. The results of these studies highlight the limitations of current VI pathway assessment approaches and demonstrate the need for robust alternate diagnostic tools, such as CPM, that lead to greater confidence in data interpretation and decision-making.
ContributorsHolton, Chase Weston (Author) / Johnson, Paul C (Thesis advisor) / Fraser, Matthew (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2015
Description
Many tasks that humans do from day to day are taken for granted in term of appreciating their true complexity. Humans are the only species on the planet that have developed such an in-depth means of auditory communication. Recreating the mechanisms in the brain that recognize speech patterns is no easy task. This paper compares and contrasts various algorithms used in modern day ASR systems, and focuses primarily on ASR systems in resource constrained environments. The Green colored blocks in Figure 1 will be focused on in greater detail throughout this paper, they are the key to building an exceptional ASR system. Deep Neural Networks (DNNs) are the clear and current leader among ASR technologies; all research in this field is currently revolving around this method. Although DNNs are very effective, many older methods of ASR are used often due to the complexities involved with DNNs; these difficulties include the large amount of hardware resources as well as development resources, such as engineers and money, required for this method.
ContributorsPetersen, Casey Alexander (Author) / Csavina, Kristine (Thesis director) / Pollat, Scott (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Chimeric antigen receptor (CAR)-T cell therapy is a type of cancer immunotherapy has shown promising results in engineering the T cells which targets a specific antigen. Despite their success rate, there are certain limitations to the use of CAR-T therapies that includes cytokine release syndrome (CRS), neurologic toxicity, lack of response in approximately 50% of treated patients, monitoring of patients treated with CAR-T therapy. However, rapid point- of- care testing helps in quantifying the circulating CAR T cells and can enhance the safety of patients, minimize the cost of CAR-T cell therapy, and ease the management process. Currently, the standard method to quantify CAR-T cell in patient blood samples are flow cytometry and quantitative polymerase chain reaction (qPCR). But these techniques are expensive and are not easily accessible and suitable for point- of- care testing to assist real- time clinical decisions. To overcome these hurdles, here I propose a solution to these problems by rapid optical imaging (ROI)- based principle to monitor and detect CAR-T cells. In this project, a microfluidic device is developed and integrated with two functions: (1) Centrifuge free, filter- based separation of white blood cells and plasma; (2) Optical imaging- based technique for digital counting of CAR T- cells. Here, I carried out proof- of- concept test on the laser cut prototype microfluidic chips as well as the surface chemistry for specific capture of CAR-T cells. These data show that the microfluidic chip can specifically capture CAR-T positive cells with concentration dependent counts of captured cells. Further development of the technology could lead to a new tool to monitor the CAR-T cells and help the clinicians to effectively measure the efficacy of CAR-T therapy treatment in a faster and safer manner.
ContributorsElanghovan, Praveena (Author) / Wang, Shaopeng (Thesis advisor) / Forzani, Erica (Committee member) / Nikkhah, Mehdi (Committee member) / Arizona State University (Publisher)
Created2023
Description
Non-invasive biosensors enable rapid, real-time measurement and quantification of biological processes, such as metabolic state. Currently, the most accurate metabolic sensors are invasive, and significant cost is required, with few exceptions, to achieve similar accuracy using non-invasive methods. This research, conducted within the Biodesign Institute Center for Bioelectronics and Biosensors, leverages the selective reactivity of a chemical sensing solution to develop a sensor which measures acetone in the breath for ketosis and ketoacidosis diagnostics, which is relevant to body weight management and type I diabetes. The sensor displays a gradient of color changes, and the absorbance change is proportional to the acetone concentration in the part- per-million range, making applicable for detection ketosis and ketoacidosis in human breath samples. The colorimetric sensor response can be fitted to a Langmuir-like model for sensor calibration. The sensors best performance comes with turbulent, continuous exposure to the samples, rather than batch sample exposure. With that configuration, these novel sensors offer significant improvements to clinical and at- home measurement of ketosis and ketoacidosis.
ContributorsDenham, Landon (Author) / Forzani, Erica (Thesis advisor) / Wang, Shaopeng (Committee member) / Kulick, Doina (Committee member) / Arizona State University (Publisher)
Created2023
Description
Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated through the double invagination of the lipid bilayer membrane of cell. Therefore, they mirror the cell membrane proteins and contain proteins, RNAs, and DNAs that can represent the phenotypic state of their cell of origin, hence considered promising biomarker candidates. Importantly, in most pathological conditions, such as cancer and infection, diseased cells secrete more EVs and the disease associated exosomes have shown great potential to serve as biomarkers for early diagnosis, disease staging, and treatment monitoring. However, using EVs as diagnostic or prognostic tools in the clinic is hindered by the lack of a rapid, sensitive, purification-free technique for their isolation and characterization. Developing standardized assays that can translate the emerging academic EV biomarker discoveries to clinically relevant procedures is a bottleneck that have slowed down advancements in medical research. Integrating widely known immunoassays with plasmonic sensors has shown the promise to detect minute amounts of antigen present in biological sample, based on changes of ambient optical refractive index, and achieve ultra-sensitivity. Plasmonic sensors take advantage of the enhanced interaction of electromagnetic radiations with electron clouds of plasmonic materials at the dielectric-metal interface in tunable wavelengths.
ContributorsAmrollahi, Pouy (Author) / Wang, Xiao (Thesis advisor) / Forzani, Erica (Committee member) / Hu, Tony Ye (Committee member) / Arizona State University (Publisher)
Created2020