Photon Quantum Noise Limited Pixel and Array architectures in a-Si Technology for Large Area Digital Imaging Applications
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A Voltage Controlled Oscillator (VCO) based pixel and array architecture is reported using amorphous silicon (a-Si) technology for large area digital imaging applications. The objectives of this research are to (a) demonstrate photon quantum noise limited pixel operation of less than 30 input referred noise electrons, (b) theoretically explore the use of the proposed VCO pixel architecture for photon quantum noise limited large area imaging applications, more specifically protein crystallography using a-Si, (c) to implement and demonstrate experimentally a quantum noise limited (VCO) pixel, a small prototype of quantum noise limited (VCO) pixelated array and a quantum noise limited (VCO) pixel integrated with direct detection selenium for energies compatible with a protein crystallography application. Electronic noise (phase noise) and metastability performance of VCO pixels in low cost, widely available a-Si technology will be theoretically calculated and measured for the first time in this research. The application of a VCO pixel architecture in thin film technologies to large area imaging modalities will be examined and a small prototype a-Si array integrated with an overlying selenium X-ray converter will be demonstrated for the first time. A-Si and poly-Si transistor technologies are traditionally considered inferior in performance to crystalline silicon, the dominant semiconductor technology today. This work v aims to extend the reach of low cost, thin film transistor a-Si technology to high performance analog applications (i.e. very low input referred noise) previously considered only the domain of crystalline silicon type semiconductor. The proposed VCO pixel architecture can enable large area arrays with quantum noise limited pixels using low cost thin film transistor technologies.
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Mohammad Yeke Yazdandoost (2011). Photon Quantum Noise Limited Pixel and Array architectures in a-Si Technology for Large Area Digital Imaging Applications. UWSpace. http://hdl.handle.net/10012/6220