Immobilizing bacteriorhodopsin on a single electron transistor

As awareness of potential human and environmental impacts from toxins has increased, so has the development of innovative sensors. Bacteriorhodopsin (bR) is a light activated proton pump contained in the purple membrane (PM) of the bacteria Halobacterium salinarum. Bacteriorhodopsin is a robust protein which can function in both wet and dry states and can withstand extreme environmental conditions. A single electron transistor(SET) is a nano-scale device that exploits the quantum mechanical properties of electrons to switch on and off. SETs have tremendous potential in practical applications due to their size, ultra low power requirements, and electrometer-like sensitivity. The main goal of this research was to create a bionanohybrid device by integrating bR with a SET device. This was achieved by a multidisciplinary approach. The SET devices were created by a combination of sputtering, photolithography, and focused ion beam machining. The bionanomaterial bacteriorhodopsin was created through oxidative fermentation and a series of transmembrane purification processes. The bR was then integrated with the SET by electrophoretic deposition, creating a bionanohybrid device. The bionanohybrid device was then characterized using a semiconductor parametric analyzer. Characterization demonstrated that the bR modulated the operational characteristics of the SET when bR was activated with light within its absorbance spectrum. To effectively integrate bacteriorhodopsin with microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS), it is critical to know the electrical properties of the material and to understand how it will affect the functionality of the device. Tests were performed on dried films of bR to determine if there is a relationship between inductance, capacitance, and resistance (LCR) measurements and orientation, light-on/off, frequency, and time. The results indicated that the LCR measurements of the bR depended on the thickness and area of the film, but not on the orientation, as with other biological materials such as muscle. However, there was a transient LCR response for both oriented and unoriented bR which depended on light intensity. From the impedance measurements an empirical model was suggested for the bionanohybrid device. The empirical model is based on the dominant electrical characteristics of the bR which were the parallel capacitance and resistance. The empirical model suggests that it is possible to integrate bR with a SET without influencing its functional characteristics.

Compressed sensing based cyclic feature spectrum sensing for cognitive radios

Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.