Indiana University-Purdue University Indianapolis (IUPUI) / Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS, and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO2 and Chip 2: WO3). These sensors were tested at different relative humidity (RH) levels and VOC concentrations. The contact angle which measures hydrophobicity was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.

Phosphorus is needed by living organism including humans and plants, to survive. Imbalance in phosphate concentration in human body can result in numerous diseases or disorders while excess phosphorus levels in water bodies like lakes, and rivers, are responsible for the rise in incidence of algal bloom across world. Current commercial phosphate monitoring systems are dominated by colorimetric measurements while electrochemical sensors including potentiometric, amperometric and voltammetric sensors are still in the research phase. Electrochemical sensors require stable reference electrodes for reliable measurements that pose challenges for miniaturization. Solid state potentiometric sensors are widely explored due to their rapid response, easy fabrication and simple electronic measurement system. However, the sensor miniaturization is dependent both on the working and reference electrode. Metal electrodes like cobalt offers advantages such as reagent-free detection, easy to miniaturize but the sensitivity of zero-current potentiometric sensors is limited by the theoretical Nernstian limit and cobalt sensors also require chemical pretreatment in standard solution before measurement. Here, an in situ electrical pretreatment method is proposed to eliminate the need of chemical pretreatment and enhance the sensitivity of cobalt electrodes to -91.4 mV/ decade of phosphate concentration. However, this electrode still needs a reference electrode for reliable measurements. Therefore, this study has demonstrated a chemiresistive sensing platform for solid state detection of phosphate using both enzyme and enzyme-free methods. A rapid prototyping method was developed to pattern the thin metal films (~100 nm thickness) using a bench top plotter cutter. The method was used to fabricate thin gold film contact electrodes for chemiresistors. The thin gold leaf contact electrodes exhibited low-noise and offered a robust, rapid and reproducible manufacturing process for chemiresistors. The chemiresistive sensor showed a wide measuring range (0.5 ppm to 500 ppm) for hydrogen peroxide detection. The sensor was deposited with glucose oxidase to demonstrate the application of the sensor for peroxidase assays to detect glucose in standard buffer solution and human pooled plasma. Phosphate also is detected using pyruvate oxidase in presence of pyruvate to generate hydrogen peroxide as the detectable molecule. Finally, metal phthalocyanines were used to perform enzyme-free phosphate measurements. This work demonstrated the sensor technologies which could be used for in-field phosphate monitoring to prevent algal bloom and it also provides phosphate monitoring methods for rapid detection in medical diagnostics for early diagnosis for diseases like chronic kidney disease and to improve the patient’s outcomes for such diseases. / Thesis / Doctor of Philosophy (PhD) / Phosphorus is an essential element for the survival of living beings including humans and plants because it is needed in multiple physiological pathways and functions like cellular signalling, energy storage, metabolism and maintenance. Therefore, phosphate in the human body is strictly regulated and in disease conditions like chronic kidney disease, and metabolic disorders. It can increase or decrease resulting in ailments and worsening of diseases. Phosphorus is also extensively used in the agricultural field to improve the growth and crop yield. Excess phosphorus from these fertilizers can enter our water sources via agricultural water run-offs leading to the increasing incidences of algal bloom across world. Current phosphorus measuring systems require chemicals which generates toxic waste, needs manual sample collection and transport, and have narrow measuring ranges. There is an urgent need for sensors which would eliminate the need of sample collection and processing, do not require toxic chemicals and could work over a wide detection range. This study presents two solid-state sensor technologies which would simplify the phosphate detection for both environmental and medical diagnostics samples.

Indiana University-Purdue University Indianapolis (IUPUI) / The link between volatile organic compounds (VOCs) from breath and various diseases and specific conditions has been identified since long by the researchers. Canine studies and breath sample analysis on Gas chromatography/ Mass Spectroscopy has proven that there are VOCs in the breath that can detect and potentially predict hypoglycemia. This project aims at developing a smart nanosensor system to detect hypoglycemia from human breath. The sensor system comprises of 1-Mercapto-(triethylene glycol) methyl ether functionalized goldnanoparticle (EGNPs) sensors coated with polyetherimide (PEI) and poly(vinylidene fluoride -hexafluoropropylene) (PVDF-HFP) and polymer composite sensor made from PVDF-HFP-Carbon Black (PVDF-HFP/CB), an interface circuit that performs signal conditioning and amplification, and a microcontroller with Bluetooth Low Energy (BLE) to control the interface circuit and communicate with an external personal digital assistant. The sensors were fabricated and tested with 5 VOCs in dry air and simulated breath (a mixture of air, small portion of acetone, ethanol at high humidity) to investigate sensitivity and selectivity. The name of the VOCs is not disclosed herein but these VOCs have been identified in-breath and are identified as potential biomarkers for other diseases as well. The sensor hydrophobicity has been studied using contact angle measurement. The GNPs size was verified using Ultra-Violent-Visible (UV-VIS) Spectroscopy. Field Emission Scanning Electron Microscope (FESEM) image is used to show GNPs embedded in the polymer film. The sensors sensitivity increases by more than 400\% in an environment with relative humidity (RH) of 93\% and the sensors show selectivity towards VOCs of interest. The interface circuit was designed on Eagle PCB and was fabricated using a two-layer PCB. The fabricated interface circuit was simulated with variable resistance and was verified with experiments. The system is also tested at different power source voltages and it was found that the system performance is optimum at more than 5 volts. The sensor fabrication, testing methods, and results are presented and discussed along with interface circuit design, fabrication, and characterization. / 2022-05-8

<div>The link between volatile organic compounds (VOCs) from breath and various diseases and specific conditions has been identified since long by the researchers. Canine studies and breath sample analysis on Gas chromatography/ Mass Spectroscopy has proven that there are VOCs in the breath that can detect and potentially predict hypoglycemia. This project aims at developing a smart nanosensor system to detect hypoglycemia from human breath. The sensor system comprises of 1-Mercapto-(triethylene glycol) methyl ether functionalized goldnanoparticle (EGNPs) sensors coated with polyetherimide (PEI) and poly(vinylidene fluoride -hexafluoropropylene) (PVDF-HFP) and polymer composite sensor made from PVDF-HFP-Carbon Black (PVDF-HFP/CB), an interface circuit that performs signal conditioning and amplification, and a microcontroller with Bluetooth Low Energy (BLE) to control the interface circuit and communicate with an external personal digital assistant. The sensors were fabricated and tested with 5 VOCs in dry air and simulated breath (mixture of air, small portion of acetone, ethanol at high humidity) to investigate sensitivity and selectivity. The name of the VOCs is not disclosed herein but these VOCs have been identified in breath and are identified as potential biomarkers for other diseases as well. </div><div> </div><div> The sensor hydrophobicity has been studied using contact angle measurement. The GNPs size was verified using Ultra-Violent-Visible (UV-VIS) Spectroscopy. Field Emission Scanning Electron Microscope (FESEM) image is used to show GNPs embedded in the polymer film. The sensors sensitivity increases by more than 400% in an environment with relative humidity (RH) of 93% and the sensors show selectivity towards VOCs of interest. The interface circuit was designed on Eagle PCB and was fabricated using a two-layer PCB. The fabricated interface circuit was simulated with variable resistance and was verified with experiments. The system is also tested at different power source voltages and it was found that the system performance is optimum at more than 5 volts. The sensor fabrication, testing methods, and results are presented and discussed along with interface circuit design, fabrication, and characterization.</div>

<p>To facilitate indoor air quality (IAQ) monitoring, the research described herein develops and implements methods for the electronic integration of two types of gas sensor, each functionalized with a polymer blend tailored for CO₂ detection. A highly sensitive and tunable electronic chemiresistive sensor interface was developed and experimentally validated. This device achieved analog-to-digital conversion (ADC) through a pulse width modulated (PWM) signal, temporary data storage with an efficient data buffering system, and noise reduction and signal amplification utilizing an instrumentation amplifier integrator circuit. These techniques can used beyond CO₂-specific applications to compensate for certain undesirable chemiresistive sensor characteristics, such as low response magnitude and signal noise. Additionally, resonant mass sensing circuitry was combined with an on-chip field programmable gate array (FPGA) implemented frequency counter. Hz-level resolution was achieved with an Alorium Snō FPGA board and a Verilog data acquisition and communication program. This device can monitor up to 16 sensor channels simultaneously and has a straightforward interface with a controllable output. Furthermore, the functionality of each integrated sensor was experimentally validated. With additional work, these integrated designs have the potential to be inexpensive, low-power, highly sensitive devices that are suitable for practical use in IAQ monitoring applications.</p>

<p>Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. </p><p><br></p><p>Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO₂ and Chip 2: WO₃). These sensors were tested at different relative humidity (RH) levels, and VOC concentrations. Contact angle which measures hydrophobicity, was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.</p>