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<p>Conventional mass spectrometry sensing has isomorphic nature, which means measure the input mass spectrum abundance function by a resemble of delta function to avoid ambiguity. However, the delta function nature of traditional mass spectrometry sensing approach imposes trade-offs between mass resolution and throughput/mass analysis time. This dissertation proposes a new field of mass spectrometry sensing which combines both computational signal processing and hardware modification to break the above trade-offs. We introduce the concept of generalized sensing matrix/discretized forward model in mass spectrometry filed. The presence of forward model can bridge the cap between sensing system hardware design and computational sensing algorithm including compressive sensing, feature/variable selection machine learning algorithms, and stat-of-art inversion algorithms. </p><p>Throughout this dissertation, the main theme is the sensing matrix/forward model design subject to the physical constraints of varies types of mass analyzers. For quadrupole ion trap systems, we develop a new compressive and multiplexed mass analysis approach mutli Resonant Frequency Excitation (mRFE) ejection which can reduce mass analysis time by a factor 3-6 without losing mass spectra specificity for chemical classification. A new information-theoretical adaptive sensing and classification framework has proposed on quadrupole mass filter systems, and it can significantly reduces the number of measurements needed and achieve a high level of classification accuracy. Furthermore, we present a coded aperture sector mass spectrometry which can yield a order-of-magnitude throughput gain without compromising mass resolution compare to conventional single slit sector mass spectrometer.</p> / Dissertation

In this thesis, a custom quadrupole mass filter setup was established to independently investigate the impact of the most prominent ion species that are present during ion-assisted deposition. The setup was applied to the low temperature epitaxial growth of GaN thin films on 6H-SiC substrates. Atomic nitrogen ions at higher ion kinetic energies were for the first time independently identified to be the predominant cause of deteriorating crystalline qualities during growth. Precise control of the ion beam parameters yielded the capability to vary the average GaN phase content from almost purely wurtzite to the meta-stable zinc blende GaN phase. Even in case of comparably high crystalline quality, the atomic and molecular nitrogen ions were independently determined to yield distinct thin film topographies throughout the entire observed evolution of the thin film formation.:Bibliographical Description 1 Introduction 1.1 Epitaxial Thin Film Growth 1.2 Ion-Beam Assisted Deposition 1.2.1 Influence of Energetic Particles 1.2.2 Ion-atom Arrival Ratio 1.3 Gallium Nitride 2 Methods 2.1 Setup of the Deposition System 2.1.1 Knudsen Effusion Cell 2.1.2 Reflection High-Energy Electron Diffraction 2.1.3 Auger Electron Spectroscopy 2.1.4 Ion Sources 2.2 Quadrupole Mass Filter System 2.2.1 Components 2.2.2 Working Principle of a Quadrupole Mass Filter 2.2.3 Alternative Mass Filters 2.3 X-ray Diffraction and Reflectivity 2.4 Atomic Force Microscopy 2.5 Transmission Electron Microscopy 3 Results and Discussions 3.1 Characterization of the Quadrupole Mass Filter System 3.1.1 Mass Filter Performance and Resolution 3.1.2 Ion Beam Characteristics 3.1.3 Space Charge Considerations 3.1.4 Conclusions 3.2 Influence of the I/A Ratio and Ion Kinetic Energy 3.2.1 Determination of the GaN Phase Composition 3.2.2 Film Topography and Growth Mode 3.2.3 Crystal Structure and Orientation 3.2.4 Microstructure at the Interface 3.2.5 Conclusions 3.3 Impact of the Ion Species on Growth Instabilities 3.3.1 Growth Rates and Thin Film Topography 3.3.2 Crystal Structure 3.3.3 Growth Mode and RHEED pattern evolution 3.3.4 Conclusions 4 Summary and Conclusions Bibliography Complete Publication List of the Author Acknowledgments Declaration of Authorship / In dieser Arbeit wurde ein maßgefertigter Quadrupol-Massenfilteraufbau etabliert, um die Auswirkungen der prominentesten Ionenspezies, die während der ionengestützten Abscheidung vorhanden sind, unabhängig voneinander zu untersuchen. Der Aufbau wurde für das epitaktische Niedertemperatur-Wachstum von GaN-Dünnschichten auf 6H-SiC-Substraten angewendet. Atomare Stickstoffionen bei höheren kinetischen Ionenenergien wurden zum ersten Mal in der Abwesenheit anderer Spezies als die dominierende Ursache für die Verschlechterung der kristallinen Qualität während des Wachstums identifiziert. Eine präzise Kontrolle der Ionenstrahlparameter ergab die Fähigkeit, den durchschnittlichen GaN-Phasengehalt von der fast reinen Wurtzit- bis zur metastabilen Zinkblende-GaN-Phase zu variieren. Selbst bei vergleichbar hoher kristalliner Qualität weisen die mit atomaren und molekularen Stickstoffionen hergestellten Schichten unabhängig voneinander verschiedene Topographien auf, die sich während der gesamten beobachteten Entwicklung der Dünnschichtbildung deutlich abzeichneten.:Bibliographical Description 1 Introduction 1.1 Epitaxial Thin Film Growth 1.2 Ion-Beam Assisted Deposition 1.2.1 Influence of Energetic Particles 1.2.2 Ion-atom Arrival Ratio 1.3 Gallium Nitride 2 Methods 2.1 Setup of the Deposition System 2.1.1 Knudsen Effusion Cell 2.1.2 Reflection High-Energy Electron Diffraction 2.1.3 Auger Electron Spectroscopy 2.1.4 Ion Sources 2.2 Quadrupole Mass Filter System 2.2.1 Components 2.2.2 Working Principle of a Quadrupole Mass Filter 2.2.3 Alternative Mass Filters 2.3 X-ray Diffraction and Reflectivity 2.4 Atomic Force Microscopy 2.5 Transmission Electron Microscopy 3 Results and Discussions 3.1 Characterization of the Quadrupole Mass Filter System 3.1.1 Mass Filter Performance and Resolution 3.1.2 Ion Beam Characteristics 3.1.3 Space Charge Considerations 3.1.4 Conclusions 3.2 Influence of the I/A Ratio and Ion Kinetic Energy 3.2.1 Determination of the GaN Phase Composition 3.2.2 Film Topography and Growth Mode 3.2.3 Crystal Structure and Orientation 3.2.4 Microstructure at the Interface 3.2.5 Conclusions 3.3 Impact of the Ion Species on Growth Instabilities 3.3.1 Growth Rates and Thin Film Topography 3.3.2 Crystal Structure 3.3.3 Growth Mode and RHEED pattern evolution 3.3.4 Conclusions 4 Summary and Conclusions Bibliography Complete Publication List of the Author Acknowledgments Declaration of Authorship

Unmanned aerial vehicles (UAVs) have emerged as a promising technology in search and rescue operations (SAR). UAVs have the ability to provide more timely localization, thus decreasing the crucial duration of SAR operations. Previous work have demonstrated proof-of-concept in regard to localizing missing people by utilizing received signal strength (RSS) and UAVs. The localization system is based on the assumption that the missing person wears an enabled smartphone whose Wi-Fi signal can be intercepted. This thesis proposes a two-staged path planner for UAVs, utilizing RSS-signals and an initial belief regarding the missing person's location. The objective of the first stage is to locate an RSS-signal. By dividing the search area into grids, a hierarchical solution based on several Markov decision processes (MDPs) can be formulated which takes different areas probabilities into consideration. The objective of the second stage is to isolate the RSS-signal and provide a location estimate. The environment is deemed to be partially observable, and the problem is formulated as a partially observable Markov decision process (POMDP). Two different filters, a point mass filter (PMF) and a particle filter (PF), are evaluated in regard to their ability to correctly estimate the state of the environment. The state of the environment then acts as input to a deep Q-network (DQN) which selects appropriate actions for the UAV. Thus, the DQN becomes a path planner for the UAV and the trajectory it generates is compared to trajectories generated by, among others, a greedy-policy.  Results for Stage 1 demonstrate that the path generated by the MDPs prioritizes areas with higher probability, and intuitively seems very reasonable. The results also illustrate potential drawbacks with a hierarchical solution, which potentially can be addressed by considering more factors into the problem. Simulation results for Stage 2 show that both a PMF and a PF can successfully be used to estimate the state of the environment and provide an accurate localization estimate. The PMF generated slightly more accurate estimations compared to the PF. The DQN is successful in isolating the missing person's probable location, by relatively few actions. However, it only performs marginally better than the greedy policy, indicating that it may be a complicated solution to a simpler problem.