Master of Science (MS), Wright State University, 2013, Computer Science

With sensors, storage, and bandwidth becoming ever cheaper, there has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web and then interpreting their observations is a non-trivial challenge. The Open Geospatial Consortium (OGC) defines a web service specification known as the Sensor Observation Service (SOS) that is designed to standardize the way sensors and sensor data are discovered and accessed on the Web. Though this standard goes a long way in providing interoperability between sensor data producers and consumers, it is predicated on the idea that the consuming application is equipped to handle raw sensor data. Sensor data consuming end-points are generally interested in not just the raw data itself, but rather actionable information regarding their environment. The approaches for dealing with this are either to make each individual consuming application smarter or to make the data served to them smarter. This thesis presents an application of the latter approach, which is accomplished by providing a more meaningful representation of sensor data by leveraging semantic web technologies. Specifically, this thesis describes an approach to sensor data modeling, reasoning, discovery, and query over richer semantic data derived from raw sensor descriptions and observations. The artifacts resulting from this research include: - an implementation of an SOS service which hews to both Sensor Web and Semantic Web standards in order to bridge the gap between syntactic and semantic sensor data consumers and that has been proven by use in a number of research applications storing large amounts of data, which serves as - an example of an approach for designing applications which integrate syntactic services over semantic models and allow for interactions with external reasoning systems. As more sensors and observations move o (open full item for complete abstract)

MS, Kent State University, 2007, College of Arts and Sciences / Department of Computer Science

Wireless sensor networks have found a wide range of applications – from environmental monitoring to automation systems. Developing applications using wireless sensor platforms involves intensive experimentation and testing. Building the experimental system with actual physical components like sensors may not be practical due to high cost or unavailability of the sensors. This problem can be solved by implementing virtual sensors that mimic the real sensors but which are implemented in software. The virtual sensors are abstractions of the physical sensors. They mimic the real sensors in all their functionality but is available at a fraction of the cost. In this thesis we describe Emuli — a method of effectively substituting sensor data by synthetic data on physical wireless nodes (motes). The sensor application is oblivious to this substitution. Emuli generates data on demand from the application. The replies are based on the sensor model which is driven by the data preloaded to the mote before the experiment. Since the preloaded data is an approximation of the sensor behavior rather than raw sensor readings, it is rather compact. Therefore it can be stored in the memory of each individual device. The emulated stimuli can be synchronized and coordinated across multiple motes which allows to experiment with distributed events. Emuli abstracts the sensing component of a complete application and allows the experimenter to focus only on processing and transport function of a wireless sensor networks. We demonstrate statistical and deterministic sensor models. We showcase the use of Emuli in a light measurement and industrial automation system implementation.

Doctor of Philosophy in Engineering, University of Toledo, 2013, Mechanical Engineering

Recently, metal oxide gas sensors have attracted much attention in connection with monitoring of combustible and toxic gases because of their higher sensitivity, fast response and recovery times, low power consumption, and low fabrication cost. Nickel oxide (NiO) is a wide band gap and p-type semiconductor with stable chemical and physical properties. NiO has been recognized as one of the most promising material for optical, electrical and gas sensor application owing to its electronic and catalytic properties. NiO is synthesized using different techniques, such as pulsed laser deposition, RF sputtering, electrochemical deposition and sol-gel. The focus of this research was to synthesize and characterize the gas sensing behavior of nickel oxide metal oxide gas sensors. Thin films of nickel oxide synthesized by a sol-gel method have fine nanostructured grains with a high surface to volume ratio, which is beneficial for gas sensor applications. The effect of thickness, fabricating technique, operating temperature, post laser irradiation and metallization on the gas sensing behavior of nickel oxide have been studied. The microstructure, optical and electrical properties of coated film were studied by XRD, SEM, TEM, EDAX, XPS, UV-Vis spectrometer. The gas sensing properties of NiO based sensors were studied for different explosive and hazardous gases as a function of gas concentration and operating temperature. The dependence of fabrication method, film thickness and operating temperature on the hydrogen gas sensing behavior of NiO thin films was investigated. It was observed that the samples with multi-step annealing possessed smaller grain size, higher porosity and higher gas sensing performance. The sample with lower thickness showed better gas sensing performance in all operating temperatures. Moreover, the operating temperature was an important parameter for nickel oxide thin film, and the maximum gas sensor response was recorded at 175oC for hydrogen gas. The e (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), University of Dayton, 2023, Electrical Engineering

Doping of metal oxide semiconductors with other metal oxides or metal ions is an effective way to improve the sensing performance of gas sensors. In this dissertation, In-doped SnO2 thin film is used in different gas sensing platforms, such as surface acoustic wave (SAW) transducers and impedance spectroscopy, for the detection of volatile organic vapors at room temperature. The properties of the piezoelectric materials play a critical role in determining the sensing response of the SAW based gas sensors. Recently, various ferroelectric materials have been used as piezoelectric materials in the manufacturing of SAW based gas sensors. Among them, Ba0.6Sr0.4TiO3 (BST) has emerged as a potential candidate due to its high acoustic velocity and electromechanical coupling coefficient. In the development of gas sensors, noble metals are extensively used as electrode or transducer materials. However, noble metals are expensive and scarce. On the basis of their favorable electrical conductivity, 2D metallic transition-metal dichalcogenides (VTe2, NbTe2, and TaTe2) are emerging as promising candidates for use in 2D electronic devices. In this dissertation, the design, fabrication, and validation of BST-based SAW and NbTe2- based impedance spectroscopy sensor platforms with the In-doped SnO2 sensing film were demonstrated. Different deposition and photolithography techniques were applied to fabricate the sensors. The morphology, structural, elemental compositions, and electrical properties of the as-deposited samples were characterized by HRSEM, XRD, EDS, and the four-point probe sheet resistance method. The samples exhibited excellent film adhesion. Furthermore, the sensing performances of the SAW and impedance spectroscopy-based gas sensors towards ethanol and humidity were evaluated at room temperature. The SAW sensors exhibited a significant negative frequency shift, which can be attributed to the mass and electric loading effects o (open full item for complete abstract)

PhD, University of Cincinnati, 2022, Engineering and Applied Science: Electrical Engineering

It is commonly acknowledged that the continuous glucose monitor for diabetes management is a historical achievement of modern diagnostics technology. However, it has been the only success despite acute needs for the real-time monitoring of many other molecules across the broader field of human disease management such as cardiac, drug dosing, fertility and other problems. The limitation is that the well-studied commercially available glucose sensors are enzymatic, which makes it very difficult to generalize its working mechanism to other analytes. Meanwhile, unlike enzymatic sensors, electrochemical aptamer-based sensors are broadly generalizable, demonstrated by several examples of real-time, in-vivo molecular monitoring at nanomolar to micromolar concentrations. So far, electrochemical aptamer-based (EAB) sensor demonstrations are highly prevalent for testing in buffer fluid or blood. This should not be surprising because the testing criteria for these fluids are highly applicable and because both fluids are well-buffered in their pH and salinity. Aptamers are known to be sensitive to both salinity and pH, thus affecting sensor output and analyte response. However, some emerging biofluids for biosensing such as human sweat or environmental fluids can have widely ranging pH and salinity. In this dissertation, a novel oil membrane sensor protection technique is reported against changes in pH and salinity for EAB sensors, where a thin, semi-permeable hydrophobic membrane will allow the target hydrophobic analyte diffuse to the sensor through while preventing diffusion of hydrophilic interferents (proteins, acids, bases, etc.). The encapsulated EAB cortisol sensor can perform in a pseudo real-time manner (5-minute concentration-on rise time and 10-minute concentration-off down time) and maintains measurement signal for at least 7 hours even in the extreme acidic solution of pH 3. EAB sensors conventionally bond the aptamer to a gold working electrode via thiol l (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2019, Electrical Engineering

Toxic chemicals have been used as chemical warfare agents since ancient times, but World War 1 saw the beginning of modern chemical proliferation. There are many methods of detecting these agents, but the combination of high sensitivity, specificity, fast response, and small form factor is difficult to achieve. More recently, graphene has been identified as a possible sensing material for ammonia and other substances. This research documents a novel method of using graphene as a chemical sensor, utilizing a radio-frequency approach to sensing. This approach utilizes all available information from the material, such as permittivity and conductivity, instead of simply examining impedance. The development of the sensor is described in depth, as well as the theoretical models used to describe its function. Finally, the overall sensitivity to ammonia, DMMP, Sarin, and VX are examined experimentally.

Master of Science (MS), Ohio University, 2018, Electrical Engineering & Computer Science (Engineering and Technology)

Printed electronic fabrication processes have received much attention in recent years due to its potential applications in creating affordable, flexible, low-waste, and diverse electronic devices. The Fujifilm DMP-2830, a compact inkjet material deposition system new to the electronics fabrication labs at Ohio University, is explored and optimized in this thesis by printing two silver nanoparticle inks on glass, photopaper, and PET substrates. A systematic approach toward the characterization of the two nano-inks and common substrates as well as test devices is provided to develop useful fabrication recipes for future users of the DMP-2830. Various designs of resistors, capacitors, and inductors are fabricated on glass, photopaper and PET. For each test device, effects of process and geometric parameter changes were studied. Two sensor applications were also demonstrated to indicate the potential of inkjet printed sensors for future research. The first sensor was a resistive bend sensor to sense motion/deformation, and the second was a capacitive wax microfluidic sensor with a novel printed fabrication approach. It is believed that the methods employed in the characterization of nano-inks and devices in this thesis can be emulated by other materials and substrates in the future when the DMP-2830 is utilized to print a wide range of advanced sensors and devices.

Doctor of Philosophy, The Ohio State University, 2018, Computer Science and Engineering

Multi-sensor fusion is the method of combining sensor data obtained from multiple sources to estimate the environment. Its common applications are in automated manufacturing, automated navigation, target detection and tracking, environment perception, biometrics, etc. Out of these applications, object detection and tracking is very important in the field of robotics or computer vision and finds application in diverse areas such as video surveillance, person following, autonomous navigation etc. In the context of purely two-dimensional (2-D) camera based tracking, situations such as erratic motion of the object, scene changes, occlusions along with noise and illumination changes are an impediment to successful object tracking. Integration of information from range sensors with cameras helps alleviate some of the issues faced by 2-D tracking. This dissertation aims to explore novel methods to develop a sensor fusion framework to combine depth information from radars, infrared and Kinect sensors with an RGB camera to improve object detection and tracking accuracy. In indoor robotics applications, the use of infrared sensors has mostly been limited to a proximity sensor to avoid obstacles. The first part of the dissertation focuses on extending the use of these low-cost, but extremely fast infrared sensors to accomplish tasks such as identifying the direction of motion of a person and fusing the sparse range data obtained from infrared sensors with a camera to develop a low-cost and efficient indoor tracking sensor system. A linear infrared array network has been used to classify the direction of motion of a human being. A histogram based iterative clustering algorithm segments data into clusters, from which extracted features are fed to a classification algorithm to classify the motion direction. To address the circumstances when a robot tracks an object that executes unpredictable behavior - making abrupt turns, stopping while moving in an irregular wavy track, (open full item for complete abstract)

PhD, University of Cincinnati, 2017, Engineering and Applied Science: Electrical Engineering

Pressure and temperature are parameters essential for brain monitoring. Currently, the intracranial pressure (ICP) and intracranial temperature (ICT) are measured by the separate sensors/catheters in clinic. Although integrated ICP and ICT sensors with low cost and minimal damage to brain is highly favored, the integration of the sensors involves complicate assembly and packaging process, and also increases the diameter of micro-catheters. Researches have been done to develop integrated pressure and temperature sensors on the same platform, especially on flexible substrate, to minimize the damage to brain caused by the device implantation. However, the developed sensors are either merely prove-of-concept or difficult to be manufactured due to the complicate and costly process. This work proposes and explores novel approaches to develop the integrated flexible ICP and ICT sensors with low cost and simple process. High quality polysilicon thin film was directly grown on flexible substrate as the sensing material for both ICP and ICT sensors with simple, fast, and low cost aluminum induced crystallization (AIC) process. A continuous P-type polysilicon film with the crystals' average size of 49 nm was developed and shown. Based on the polysilicon thin film, a flexible thermistor array was designed, developed and characterized. It achieved good in vitro performance with a sensitivity of -0.0031/°C, response time of 1.5 s, resolution of 0.1 °C, thermal hysteresis less than 0.1°C, and long term stability with drift less than 0.3 °C for 3 days in water. In vivo tests of the polysilicon thermistor showed a low noise level of 0.025±0.03 °C and the expected transient temperature increase associated with cortical spreading depolarization. In addition, polysilicon based flexible pressure sensor was developed for ICP measurement. The gauge factor of polysilicon thin film was characterized with a value of 10.316. The dimensions of the flexible piezoresistive pressure (open full item for complete abstract)

MS, University of Cincinnati, 2017, Engineering and Applied Science: Electrical Engineering

Pressure ulcers are a dangerous injury resulting from extensive pressure being applied to the body over a prolonged period of time resulting in a lack of blood flow reaching the affected site. If the pressure is not relieved in a timely manner, the lack of nutrients causes the tissue in the surrounding area to eventually die and decompose creating an open sore that could become infected. Pressure ulcers usually form over areas of the skin where a boney prominence is closest to the skin, such as the hips or ankle bones, so subjects who lose a leg and depend on a prosthetic are at constant risk of developing them due to the residual leg bone left by the surgery. In addition to this, muscle mass is reduced in subjects with a lower limb amputation due to lack of use which brings the bone even closer to the surface of the skin. If a lower limb amputee does form a pressure ulcer, they can no longer rely on their prosthetic for mobility and are reduced to using crutches, a wheelchair, or are bedridden until the wound heals. This thesis presents a low cost, high mobility prototype microcontroller-based pressure sensor that is capable of detecting normal and shear forces with the possibility of said sensor being integrated into a lower limb prosthetic to detect problem areas of high pressure in real time. This information can then alert the user to a potential problem with their prosthetic allowing them to take proactive measures to prevent a pressure ulcer from forming. The proposed device incorporates an off-the-shelf microcontroller that serves as the control unit along with flexible analog piezoresistive sensors. Using the built-in analog-to-digital module and serial peripheral interface, the device is capable of measuring and storing approximately 1,000 data points per second and detecting pressures in the range of 60mmHg to 798mmHg.

Master of Science (MS), Ohio University, 2017, Biomedical Engineering (Engineering and Technology)

The role mechanical properties play in the interconnected network of cellular control mechanisms is becoming better understood. Specifically, mechanical stiffness has been shown to be a marker capable of distinguishing between malignant and benign cancer phenotypes. Traditional techniques to measure cell stiffness share the commonality of low throughput. Microfluidic technology has been used to attain stiffness related data at a high throughput, however data collection and analysis is almost exclusively reliant on video spectroscopy. Through the use of a serial multi-constriction microfluidic device, cell ease of transit, i.e., agility, can be measured by the transit through the serial network developed herein. This measure of agility has the capability to differentiate cells based on phenotype, specifically phenotypes characteristic of the epithelial-to-mesenchymal transition, EMT, which occurs in cancer cells upon initiation of metastasis. By developing a compatible microfluidic sensor, the post processing of cell agility data has the potential to be automated and moved toward a non-video spectroscopy dependent system. These improvements push the technology of cellular mechanical property data analysis toward a faster, more convenient platform, thus allowing a better understanding of how mechanical properties correspond with biological behavior of mammalian cells.

Master of Science (MS), Wright State University, 2011, Computer Science

The emergence of dynamic information sources - like social, mobile and sensors, has led to ginormous streams of real time data on the web also called, the era of Big Data [1]. Research studies suggest, these dynamic networks have created more data in the last three years than in the entire history of civilization, and this trend will only increase in the coming years [1]. Gigaom article on Big data shows, how the total information generated by these dynamic information sources has completely surpassed the total storage capacity. Thus keeping in mind the problem of ever-increasing data, this thesis focuses on semantically integrating and analyzing multiple, multimodal, heterogeneous streams of weather data with the goal of creating meaningful thematic abstractions in real-time. This is accomplished by implementing an infrastructure for creating and mining thematic abstractions over massive amount of real-time sensor streams. Evaluation section shows 69% data reduction with this approach.

PhD, University of Cincinnati, 2001, Arts and Sciences : Physics

This thesis presents the design, fabrication, and testing of novel MEMS pressure and temperature sensors fabricated on optical fiber end faces. A simple micromachining process compatible with MEMS was developed in fabricating sensors directly on optical fibers. The pressure sensor configuration involves anodic bonding of a piece of an extremely thin silicon wafer onto the fiber end face over a cavity etched in the central portion of the fiber end face. Final device diameter is thus the same as that of the optical fiber. The temperature sensor is based on anodically bonding a thin piece of silicon onto the fiber end face.The pressure sensors were fabricated on 400 um diameter fibers while temperature sensors were fabricated on both 200 and 400 um diameter fibers. Pressure measurements were made over the 14 to 80 psi range while temperature measurements were made over the 23 to 300 Celcius range. Pressure sensor sensitivities of 0.1 mV/psi and 0.2 mV/psi were obtained. The pressure sensors were designed with cavity diameter d=150 um, and cavity depth h=0.640 um. Diaphragm thickness for the two sensors were t=7.1, and t=3.4 um. Higher sensitivity was achieved by design of a sensor with the thinner diaphragm. A sensor array fabrication effort demonstrated that our micromachining process could be extended to simultaneous processing of an array of fibers. The temperature sensor was fabricated by bonding 3.1 um thick silicon onto the fiber end face. An oxidant-resistant encapsulation scheme for the temperature sensor was proposed, namely aluminum coated silicon nitride (Al/Si3N4). The uncoated side of silicon was bonded to a fiber end face using the anodic bonding method. The measured values of kf=(lambda)-1x(dlambda/dT) for capped and uncapped sensors were kf=(7.5±0.6)x10-5/Celcius, and kf=(7.2±0.1)x10-5/Celcius respectively. The measured kf value for the uncapped sensor is equal to that which was determined using the published material properties for crystalline silicon (open full item for complete abstract)

MS, University of Cincinnati, 2007, Engineering : Mechanical Engineering

Structural Health Monitoring (SHM) promises to deliver great benefits to many industries. Primarily among them is a potential for large cost savings in maintenance of complex structures such as aircraft and civil infrastructure. However, several large obstacles remain before widespread use on structures can be accomplished. The development of three components would address many of these obstacles: a robust sensor validation procedure, a low-cost active-sensing hardware and an integrated software package for transition to field deployment. The research performed in this thesis directly addresses these three needs and facilitates the adoption of SHM on a larger scale, particularly in the realm of SHM based on piezoelectric (PZT) materials. The first obstacle addressed in this thesis is the validation of the SHM sensor network. PZT materials are used for sensor/actuators because of their unique properties, but their functionality also needs to be validated for meaningful measurements to be recorded. To allow for a robust sensor validation algorithm, the effect of temperature change on sensor diagnostics and the effect of sensor failure on SHM measurements were classified. This classification allowed for the development of a sensor diagnostic algorithm that is temperature invariant and can indicate the amount and type of sensor failure. Secondly, the absence of a suitable commercially-available active-sensing measurement node is addressed in this thesis. A node is a small compact measurement device used in a complete system. Many measurement nodes exist for conventional passive sensing, which does not actively excite the structure, but there are no measurement nodes available that both meet the activesensing requirements and are useable outside the laboratory. This thesis develops hardware that is low-power, active-sensing and field-deployable. This node uses the impedance method for SHM measurements, and can run the sensor diagnostic algorithm also developed here. Fina (open full item for complete abstract)

PhD, University of Cincinnati, 2005, Engineering : Mechanical Engineering

Carbon Nanotubes (CNT) have unique properties that can be used to form smart materials. This is a recent area of research, and little work has been done beyond the invention of buckypaper electrochemical actuators. The objective of this dissertation is to investigate the piezoresistive and electrochemical properties of Single Wall Carbon Nanotubes (SWNT), Multi-Wall Carbon Nanotubes (MWNT) and nanotube polymer composite materials. Based on these properties, a strain sensor, a corrosion sensor, a power transducer, and an actuator were developed in this dissertation. These new nanotube-based smart materials have unique advantages and also limitations when compared to existing smart materials. One nice advantage is the multi-functionality of the material. This is illustrated by a sensor developed in this study that simultaneously uses both the piezoresistivity and electrochemical impedance properties of carbon nanotubes for Structural Health Monitoring (SHM) applications. In addition, a biomimetic Artificial Neural System (ANS) was proposed that can cover large areas and monitor the health of a structure in real time, much like the neural system in the human body. The nanotube based sensor system can be easily installed on large structures using a spray-on technique, making the sensor low cost and practical. The characteristics of the sensors developed were modeled and verified by experiments. Also, Carbon Nanofibers (CNF), which are similar to nanotubes, were investigated for use as a low cost sensor material in the study. Power generation using nanotubes and nanofibers in aqueous and dry environments was also investigated. The aim was to provide autonomous power for a SHM sensor system. The voltage output of the nanotube power cell was determined for a few different ionic liquids and polymers. An interesting mechanism of power generation for the dry CNT material was found. An electrostatically charged material reciprocating perpendicular to the nanotube film produced (open full item for complete abstract)

Master of Science, The Ohio State University, 2002, Electrical Engineering

Unattended sensor networks are becoming increasingly valuable for many military and commercial applications. A number of sensors are distributed in a region of interest. These sensors have the ability to sense and record energy, process data, and communicate with a central information processor. The information gained from signal processing is often used for detecting, tracking, and identifying objects of interest. In certain circumstances, location and orientation information regarding these sensors is unknown after being placed in the scene. The problem considered in this thesis is how to locate and orient these sensors. We present methods for solving this problem using calibration source signals. Sources are distributed in the same region of interest, with their locations and signal emission times being unknown. Each sensor has the ability to generate direction-of-arrival (DOA) and time-of-arrival (TOA) estimates from the source signals. The goal is to estimate the locations and orientations of all sensors using these TOA and DOA measurements. We develop necessary conditions for solving the self-calibration problem and provide a maximum likelihood solution and corresponding location error estimate. A lower bound on calibration accuracy via the Cramer-Rao Bound is found. We also consider the problem of locating and orienting a network of unattended sensors using nominal location information in the form of a prior probability distribution function. We develop a Bayes approach to the calibration problem and compute accuracy bounds on the calibration procedure. A maximum a posteriori estimation algorithm is shown to achieve the accuracy bound. Results using both synthetic data and field measurements are presented.

Doctor of Philosophy, University of Akron, 2012, Chemistry

Exited state intramolecular proton transfer (ESIPT) occurs in aromatic molecules that contain hydrogen bond donor and acceptor groups located at a close distance. In the event of proton transfer, a proton migrates from one group to the other, thereby producing a tautomeric form which emits fluorescence with a large Stokes shift. My research focuses on the development of novel fluorescent sensors with an ESIPT turn-on mechanism, which intends to address some of the problems that we human being are facing today. As a starting point, we choose 2-(2-hydroxyphenyl)benzoxazole (HBO) as a model compound which absorbs at 320 nm and emits at 500 nm. Our strategy is to design a sensor molecule in which either the H-donor or acceptor is masked to block the ESIPT pathway. Upon specific binding with the target analytes, the masked H-donor (or acceptor) can be released, thereby enabling the ESIPT. Such kind of ESIPT turn-on approaches as a sensing event trigger in chemical sensors were rarely reported in literature when we started our research in 2009. My dissertation is devoted to seek fundamental understanding on the ESIPT mechanism, and to utilize the ESIPT in chemical sensor design. First, an efficient method for constructing HBO derivatives has been developed by using palladium (II) mediated oxidative cyclization in Chapter 2. The reaction was carried out in mild conditions with easily-synthesized Schiff base as starting material and was compatible to a wide range of function groups. The Pd (II) involved in the reaction was consumed in the β-hydride elimination step and regenerated in the presence of oxygen. This method opens a path for efficient construction of HBO molecules with various functional groups, which has been used throughout my research to synthesize the HBO derivatives of interest. HBO compounds often exhibit dual fluorescence in polar solvents due to rotamerism around the single bond connecting the benzoxazole to the 2-hydroxyphenyl ring. Although the two r (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2011, Mechanical Engineering

Coulter counters are well established analytical instruments for counting and sizing micro and nano scale particles. One long-standing drawback of microfabricated Coulter counter type devices is their low throughput because they scan each individual particle passing through a fluidic channel where the channel size is comparable to the particle size. To overcome the low detection throughput, in this research, novel Coulter counters that use parallel sensing channels to achieve high throughput detection of microparticles are designed and tested. The sensor uses multiplexed detection to measure a combined signal from all channels using a single pair of electrodes for a microfabricated multichannel sensor. The detection uses frequency division multiplexing based on amplitude modulation of applied AC excitation signals at unique frequencies. The design, fabrication and testing of single and four channel sensors are presented. The single channel devices were used to demonstrate the feasibility of using the amplitude modulation method to detect microscale particles. Numerical analysis based on an electrical equivalent circuit and experimental results confirmed the amplitude modulation concept for the single channel sensor at selected frequencies for 30 µm polystyrene and Juniper pollen particles. A four channel sensor was microfabricated and tested using 30μm polystyrene particles to demonstrate improvement in detection throughput. Four unique and known modulation frequencies were applied to each channel using their central electrodes. A combined response for the sensor was collected at one major electrode and demodulated to obtain the signals for each individual channel. The testing results indicated that using the multiplexing technique, detection throughput of the sensor was improved by 300% in contrast to a single channel sensor. No false positives due to crosstalk among channels were observed. It is possible to extend the design concept to a large number of channels,t (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Materials Science and Engineering

This dissertation presents biochemical sensing systems for wearable, implantable, and high-resolution chemical sensing applications. By integrating biorecognition elements, sensing interfaces, and wireless communication strategies, we aim to provide a low-cost, reliable, and highly accurate platform for real-time biochemical monitoring in clinical and experimental settings. We first demonstrate a wireless sensing system that is miniaturized, lightweight, and compatible with common biochemical sensing interfaces. Inspired by RF tuning circuits, our simple circuit design allows battery-free operation and accurate monitoring of multiple biomarkers. The modular design separates the inductive coupling unit and the electrochemical sensing interface, minimizing strain-induced changes and ensuring accurate recording. This system is compatible with common electrochemical sensing methods, including ion-sensitive membranes (ISM), aptamer-based sensors, and enzymatic interfaces. And allow for the detection of ions, neurotransmitters, and metabolites across different application scenarios. For instance, a "smart necklace" consists of glucose sensors, that are capable of wirelessly detecting sweat glucose during exercise. A wearable skin patch monitored cortisol levels in sweat showcases the functional adaptability for stress-related biomarker detection. Additionally, a miniaturized implant prototype illustrated the potential for continuous in vivo monitoring. Our work also introduces a portable vector network analyzer (pVNA) designed to overcome the size limitations of traditional VNAs. This research provides the design and working principle for a wearable reader, which allows for real-time monitoring of resonance frequency and Q factor of the inductive coupling wireless sensor. Furthermore, we introduce “NeuroThread”, a neurotransmitter-sensing platform that utilizes the cross-section of commercially available ultrathin microwires to serve as microelectrode. This cost (open full item for complete abstract)

Master of Science in Electrical Engineering, University of Dayton, 2024, Electrical Engineering

In this project, we developed new designs for event-based pixel sensors and their related biasing circuits for 130nm, 90nm, and 65nm silicon processes. This was done by selecting new width and length (W/L) ratios for each process, creating a new reset configuration, and modifying the designs of the bias current generators to work for smaller silicon processes. Through our simulations, we found that our design was able to generate the expected output behavior of an event camera to different photocurrent inputs. Additionally, we performed preliminary radiation analysis on the generated design for varying inputs and ion strikes. It was found that OFF event detections were more susceptible to false event triggers than ON events, as weaker ion strikes were able to trigger them.