Matching Items (3)
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- All Subjects: Flexible Electronics
- Creators: Allee, David
Description
This work explores how flexible electronics and display technology can be applied to develop new biomedical devices for medical, biological, and life science applications. It demonstrates how new biomedical devices can be manufactured by only modifying or personalizing the upper layers of a conventional thin film transistor (TFT) display process. This personalization was applied first to develop and demonstrate the world's largest flexible digital x-ray detector for medical and industrial imaging, and the world's first flexible ISFET pH biosensor using TFT technology. These new, flexible, digital x-ray detectors are more durable than conventional glass substrate x-ray detectors, and also can conform to the surface of the object being imaged. The new flexible ISFET pH biosensors are >10X less expensive to manufacture than comparable CMOS-based ISFETs and provide a sensing area that is orders of magnitude larger than CMOS-based ISFETs. This allows for easier integration with area intensive chemical and biological recognition material as well as allow for a larger number of unique recognition sites for low cost multiple disease and pathogen detection.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
ContributorsSmith, Joseph T. (Author) / Allee, David (Thesis advisor) / Goryll, Michael (Committee member) / Kozicki, Michael (Committee member) / Blain Christen, Jennifer (Committee member) / Couture, Aaron (Committee member) / Arizona State University (Publisher)
Created2014
Description
Recently, electric and magnetic field sensing has come of interest to the military for a variety of applications, including imaging circuitry and detecting explosive devices. This thesis describes research at the ASU's Flexible Electronics and Display Center (FEDC) towards the development of a flexible electric and magnetic field imaging blanket. D-dot sensors, which detect changes in electric flux, were chosen for electric field sensing, and a single D-dot sensor in combination with a lock-in amplifier was used to detect individuals passing through an oscillating electric field. This was then developed into a 1 x 16 array of D-dot sensors used to image the field generated by two parallel wires. After the fabrication of a two-dimensional array, it was discovered that commercial field effect transistors did not have a high enough off-resistance to isolate the sensor form the column line. Three alternative solutions were proposed. The first was a one-dimensional array combined with a mechanical stepper to move the array across the E-field pattern. The second was a 1 x 16 strip detector combined with the techniques of computed tomography to reconstruct the image of the field. Such techniques include filtered back projection and algebraic iterative reconstruction (AIR). Lastly, an array of D-dot sensors was fabricated on a flexible substrate, enabled by the high off-resistance of the thin film transistors produced by the FEDC. The research on magnetic field imaging began with a feasibility study of three different types of magnetic field sensors: planar spiral inductors, Hall effect sensors, and giant magnetoresistance (GMR). An experimental array of these sensors was designed and fabricated, and the sensors were used to image the fringe fields of a Helmholtz coil. Furthermore, combining the inductors with the other two types of sensors resulted in three-dimensional sensors. From these measurements, it was determined that planar spiral inductors and Hall effect sensors are best suited for future imaging arrays.
ContributorsLarsen, Brett William (Author) / Allee, David (Thesis director) / Papandreou-Suppappola, Antonia (Committee member) / Barrett, The Honors College (Contributor) / Department of Physics (Contributor) / Electrical Engineering Program (Contributor)
Created2015-05
Description
NGExtract 2 is a complete transistor (MOSFET) parameter extraction solution based upon the original computer program NGExtract by Rahul Shringarpure written in February 2007. NGExtract 2 is written in Java and based around the circuit simulator NGSpice. The goal of the program is to be used to produce accurate transistor models based around real-world transistor data. The program contains numerous improvements to the original program:
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
ContributorsVetrano, Michael Thomas (Author) / Allee, David (Thesis director) / Gorur, Ravi (Committee member) / Bakkaloglu, Bertan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05