High-temperature ferromagnetism in transition metal implanted wide-bandgap semiconductors

Raley, Jeremy A Air Force Institute of Technology 2005 해외박사(DDOD)

The field of spin transport electronics (spintronics) is a viable candidate for advancing computing and communication technologies. Material with both semiconductor and magnetic properties, which is commonly called a dilute magnetic semiconductor (DMS), will prove most useful in the fabrication of spintronic devices. In order to produce a DMS at above room temperature, transition metals (TMs) were implanted into host semiconductors of p-GaN, Al0.35Ga0.65N, or ZnO. Magnetic hysteresis measurements using a superconducting quantum interference device (SQUID) magnetometer show that some of the material combinations clearly exhibit ferromagnetism above room temperature. The most promising materials for creating spintronic devices using ion implantation are p-GaN:Mn, Al0.35Ga0.65N:Cr, and Fe-implanted ZnO nanotips on Al2O3. Temperature-dependent magnetization measurements confirm that indications of ferromagnetism are due to DMS behavior. Photo- and cathodoluminescence measurements show that implantation damage is recovered and the implanted TMs are incorporated into the semiconductor. As progress is made toward realizing practical spintronic devices, the work reported here will be useful for determining material combinations and implantation conditions that will yield the needed materials.

A flash vaporization system for detonation of hydrocarbon fuels in a pulse detonation engine

Tucker, Kelly Colin Air Force Institute of Technology 2005 해외박사(DDOD)

Current research by both the US Air Force and Navy is concentrating on obtaining detonations in a pulse detonation engine (PDE) with low vapor pressure, kerosene based jet fuels. These fuels, however, have a low vapor pressure and the performance of a liquid hydrocarbon fueled PDE is significantly hindered by the presence of fuel droplets. A high pressure, fuel flash vaporization system (FVS) has been designed and built to reduce and eliminate the time required to evaporate the fuel droplets. Four fuels are tested: n-heptane, isooctane, aviation gasoline, and JP-8. The fuels vary in volatility and octane number and present a clear picture on the benefits of flash vaporization. Results show the FVS quickly provided a detonable mixture for all of the fuels tested without coking or clogging the fuel lines. Combustion results validated the model used to predict the fuel and air temperatures required to achieve gaseous mixtures with each fuel. The most significant achievement of the research was the detonation of flash vaporized JP-8 and air. The results show that the flash vaporized JP-8 used 20 percent less fuel to ignite the fuel air mixture twice as fast (8 ms from 16 ms) when compared to the unheated JP-8 combustion data. Likewise, the FVS has been validated as a reliable method to create the droplet free mixtures required for liquid hydrocarbon fueled PDEs.

Operator state estimation for adaptive aiding in uninhabited combat air vehicles

Russell, Christopher A Air Force Institute of Technology 2005 해외박사(DDOD)

Chris Russell's research, sponsored by the Air Force Research Laboratory Human Effectiveness Directorate, demonstrated significant improvement of mission effectiveness using adaptive automation and the operator's mental workload in Uninhabited Combat Air Vehicle (UCAV) missions. His work is the first example of closing the loop between the human and the machine by using mental workload based on physiological signals from the operator to adapt the system. Implementation of his research is being demonstrated in a variety of applications, including the Uninhabited Combat Air Vehicle control workstation, Tactical Tomahawk Weapons Control System, and the Objective Force Warrior Program.

MANUAL TRACKING FLIGHT CONTROL WITH AMPLITUDE AND RATE CONSTRAINED DYNAMIC ACTUATORS

MILLER, RUSSEL B AIR FORCE INSTITUTE OF TECHNOLOGY 1997 국내박사

Engineering tools for variable stiffness vibration suppression and isolation

Winthrop, Michael F Air Force Institute of Technology 2005 해외박사(DDOD)

With the advent of smart materials, the concept of semi-active control or dynamic control of stiffness and/or damping for vibration control of structures has become practical and has seen limited use. Semi-active control has advantages over active and passive control methods, since it provides almost as much capability as active control while requiring much less power. Its main disadvantage is its inherent nonlinearity, greatly complicating engineering design. The purpose of this research is to extend semi-active control vibration isolation tools and methods, considering applications for space launch and on-orbit systems. After surveying the literature, variable stiffness using a general on-off control law with constant damping is examined in several contexts. First, the single degree of freedom problem is solved in exact form and approximated for the initial value problem. Results include development of an optimal control policy for all possible variable stiffness settings and a large range of viscous damping settings, guaranteed stability regions, and new possibilities for fast settling time even with an overdamped system. Second, the sinusoidally forced problem was approximated and a near optimal control policy was formulated. Third, the results of the initial value problem were extended to two multi-degree of freedom problems. The problems examined are representative of a cross section of a simple space telescope structure and of a variable stiffness beam. Besides providing new engineering design tools and insight into the nonlinear behavior of variable stiffness concepts, the results open several future research possibilities.

Optimization of automatic target recognition with a reject option using fusion and correlated sensor data

Laine, Trevor I Air Force Institute of Technology 2005 해외박사(DDOD)

In many pattern recognition applications, significant costs can be associated with various decision options. Often, a minimum acceptable level of confidence is required prior to making an actionable decision. Combat target identification (CID) is one example where the incorrect labeling of Targets and Non-targets has substantial costs; yet, these costs may be difficult to quantify. One way to increase decision confidence is through fusion of data from multiple sources or from multiple looks through time. Numerous methods have been published to determine optimal rules for the fusion of decision labels or to determine the Bayes' optimal decision if prior probabilities along with decision costs can be accurately estimated. This research introduces a mathematical framework to optimize multiple decision thresholds subject to a decision maker's preferences. The decision variables may include rejection thresholds to specify Non-declaration regions and ROC thresholds to explore viable true positive and false positive Target classification rates. This methodology yields an optimal class declaration rule subject to decision maker preferences without using explicit costs associated with each type of decision. This optimization framework is demonstrated using various generated and collected sensor data. The experiments using generated data were performed to gain insight of the potential effects of fusing data with various degrees of correlation. The optimization framework is then applied to assess two competing fusion systems across four test sets of radar data. The fusion methods include Boolean logic and probabilistic neural networks for the fusion of collected 2-D SAR data processed via 1-D HRR moving target algorithms. Excursions are performed by varying the prior probabilities of Targets and Non-targets and varying the correlation between multiple sensor looks. In addition to optimizing thresholds according to decision maker preferences, an objective function is presented to facilitate comparison between CID systems, where the time associated with each look is incorporated.

Classification of battlespace detonations from temporally resolved multi-band imagery and mid-infrared spectra

Dills, Anthony N Air Force Institute of Technology 2005 해외박사(DDOD)

The classification of battlespace detonations, specifically the determination of munitions type and size using temporal and spectral features, has been studied using near-infrared (NIR) and multi-color visible wavelength imagers. Key features from the time dependence of fireball size are identified for discriminating various types and sizes of detonation flashes. The five classes include three weights of trinitrotoluene (TNT) and two weights of an enhanced mixture, all of which are uncased and detonated with 10% C4. Using Fisher linear discriminant techniques, features are projected onto a line such that the projected points are maximally clustered for the different classes of detonations. Bayesian decision boundaries are then established on class-conditional probability densities. Feature saliency and stability are determined by selecting features that best discriminate while requiring low variations in class-conditional probability densities and high performance in independent testing. The most important and stable feature is the time to the maximum fireball area in the near-infrared wavelength band. Overall, the features related to the time to peak (tmp) of the fireball provide the best classification for each of three a priori conditions. This feature correctly discriminates between TNT and ENE about 90% of the time, whether weight is known or not. The associated class-conditional probability densities separate the two classes with a Fisher ratio of 2.9 and an area under the receiver operating characteristic, AROC, of 0.992. Also, tmp achieves approximately 60% success rate at discerning both weight and type.

Combat identification with sequential observations, rejection option, and out-of-library targets

Albrecht, Timothy W Air Force Institute of Technology 2005 해외박사(DDOD)

Combat target identification (CID) is the process by which detected objects are characterized pursuant to military action. Errors in CID such as mis-labeling targets and non-targets carry significant costs. Fusing data from multiple sources and allowing a rejection, or non-declare, option can improve CID error rates. This research extends a mathematical framework that selects the optimal sensor ensemble and fusion method across multiple decision thresholds subject to warfighter constraints. The formulation includes treatment of exemplars from target classes on which the CID system classifiers are not trained (out-of-library classes), and it enables the warfighter to optimize a CID system without explicit enumeration of classifier error costs. A time-series classifier design methodology is developed and applied, resulting in a multi-variate Gaussian hidden Markov model (HMM) with a specially constructed hidden state space. The extended CID framework is used to compete the HMM-based CID system against a template-based CID system. The assessment uses a real world synthetic aperture radar (SAR) data collection comprised of ten in-library target classes and five out-of-library target classes. The framework evaluates competing classifier systems that use multiple fusion methods, including neural network fusion and label fusion, varied prior probabilities of targets and non-targets, varied correlation between multiple sensor looks, and varied levels of target pose estimation error. Also, an on-line target pose estimator is developed using principal component analysis of masked target SAR images. This estimator validates experimental assumptions on target pose prior to classification. The CID system assessment using the extended framework reveals larger feasible operating regions for the HMM-based classifier across experimental settings. In some cases the HMM-based classifier yields a feasible region that is 25% of the threshold operating space versus 1% for the template-based classifier. Similar performance results are obtained for rule-based label fusion and the more complex neural network fusion and are explained by the new ability to independently set classifier thresholds with the label fusion method.

Wide-angle multistatic synthetic aperture radar: Focused image formation and aliasing artifact mitigation

Luminati, Jonathan E Air Force Institute of Technology 2005 해외박사(DDOD)

Traditional Synthetic Aperture Radar (SAR) platforms use narrow radar beams, forcing the user to choose between two image types: larger, low resolution images or smaller, high resolution images. SAR platforms also usually operate in a monostatic configuration, transmitting and receiving radar echoes from the same antenna. Switching to a wide-angle multistatic approach dramatically improves SAR performance. The wide beam enables simultaneous high resolution image production over large ground swaths. The multistatic configuration provides additional data diversity and promotes platform survivability. Combining these two attributes results in an approach termed Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR). Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. This routine consists of a variable bistatic tomographic imaging algorithm with near-field and warped ground plane corrections. Inverse Synthetic Aperture Radar (ISAR) imagery produced using Radar Cross Section (RCS) chamber data validates this approach. The second implementation problem stems from the large Doppler spread in the wide-angle scene, leading to severe aliasing problems. This research effort develops a new anti-aliasing technique using randomized Stepped-Frequency (SF) waveforms. The SAR imaging process coherently combines the individual waveform ambiguity functions, resulting in a |sinc|2 structure which places Doppler nulls at aliasing artifact locations. This approach does not increase the image formation algorithm's computational complexity. Both simulation and laboratory results demonstrate effective aliasing artifact mitigation, eliminating more than 99% of the aliased energy.

Deep level defects in electron-irradiated aluminum gallium nitride grown by molecular beam epitaxy

Hogsed, Michael R Air Force Institute of Technology 2005 해외박사(DDOD)

Aluminum gallium nitride (AlGaN)-based devices are attractive candidates for integration into future Air Force communication and sensor platforms, including those that must operate in harsh radiation environments. Radiation-induced performance degradation in GaN and AlGaN devices has been observed, and this has been attributed to the creation of microscopic point defects such as vacancies, interstitials, and related defect complexes, which have been associated with energy levels deep in the semiconductor band gap. In recent years, several of these defect energy levels in GaN have been experimentally observed and characterized, but very few studies have been performed on radiation-induced defect energy levels in AlGaN. In this study, the electrical and optical properties of 1.0 MeV electron irradiated n-AlxGa1-xN are characterized for aluminum mole fraction x = 0.0 to 0.3 using deep level transient spectroscopy (DLTS), temperature-dependent Hall, and cathodoluminescence (CL) measurements. The DLTS measurements reveal the presence of electron traps in as-grown GaN that are characteristic of those previously reported in the literature. Also, three electron traps, labeled D, P1, and P2 are observed in the as-grown AlGaN. Following 1.0 MeV electron irradiation of the AlGaN, it has been found that four additional electron traps labeled R1, R2, R3, and R4 are created and their properties are characterized for the first time, to the best of our knowledge. Three of these traps, R1--R3, correspond to radiation-induced traps reported in GaN. The newly discovered fourth trap, R4, appears to be unique to AlGaN, and may thus be related to aluminum displacement. It has also been found that trap levels deepen significantly in the energy band gap with increase in aluminum mole fraction. The room temperature carrier concentration decreases following irradiation, and the carrier removal rate is found to depend foremost on the initial carrier concentration, regardless of the aluminum mole fraction. Also, following 1.0 MeV electron irradiation at a fluence of 1 x 1017 cm -2, the peak CL intensities of the samples are reduced, on average, by 50%. In spite of these findings, it is concluded that n-AlxGa 1-xN is intrinsically more tolerant to radiation than conventional semiconductor materials such as GaAs and Si.