Research Topics

Scholars are encouraged to contact any mentors whose projects they find of interest. To contact the mentor, use the link included at the conclusion of each project description.

Design, develop, and operate systems that generate and use electrical waveforms. This includes
power generation and distribution systems for aircraft and spacecraft, data processing and
control, and instrumentation systems. Computers and digital circuits have become an integral
part of these systems. Electrical engineers are also concerned with the devices that make up such
systems: transistors, integrated circuits, antennas, computer memory devices, and fusion plasma
confinement devices.

Successful integration of dielectrics into a transistor process flow with negligible defect density has historically been the key for wide scale application of electronic devices in aerospace applications. Dielectrics are needed not only as gate insulators, they are also needed for passivation. The presence of defects either in the bulk or in the interface of these dielectrics critically affects the performance of transistors. Additional defects are formed either during operation of the device and/or due to exposure to radiation.

The semiconducting channel in transistors studied for aerospace applications are generally made with III-V (like GaAs, GaN, AlGaN) or III-O (like Ga2O3, AlGaO) materials. These materials do not have a native dielectric as Si has in the form of SiO2; and therefore, have an unoptimized dielectric/semiconductor interface even after 40 years of their introduction into RF electronics. In addition, formation of novel dielectrics on these materials poses additional challenges in terms of bulk and interface defects, radiation damage, and carrier injection into dielectric, which leads to instability in device operation. Significant research opportunities therefore exist in integrating classical and novel dielectric in III-V and III-O based semiconductors.

This research topic targets integration of dielectrics in high-power III-N and III-O based transistors. This will require optimization of a wide range of process parameters during device fabrication in AFRL/RY’s class 100 (ISO-5) cleanroom. Resultant devices will go through extensive electrical (impedance spectroscopy, DC/RF testing, transient, noise analysis), optical (different forms of spectroscopy and microscopy) and materials characterization for confirming the effect of different process parameters on device performance. AFRL has excellent characterization capability that will be useful for such characterization. The goal of this project is to generate critical and novel knowledge that will enable application of III-N and III-O materials by satisfying the unique requirements of the United States Air Force and Space Force.

Our research interests include development of Infrared (IR) Materials, Detectors, and Focal Plane Arrays (FPAs) utilizing group III‐V materials, mainly Sb-based type II strained layer superlattices (SLSs), and novel detector architectures such as unipolar barrier detectors. Through design, material growth, and device fabrication, we are developing FPAs to cover the mid wave infrared (MWIR) and long wave infrared (LWIR) spectral bands for passive imaging. There has been significant progress recently in MBE growth of these SLS materials, opening up the possibility of new device architectures that were not possible before. However, the device performance could still be limited by the surface current if the detector pixels are fully reticulated. In this project, the focus will be on new fabrication processes, including mesa geometries and surface passivation techniques as a way to produce devices with improved performance and mitigate surface leakage current. Novel concepts and solutions amenable to commercial‐scale FPA manufacturing are encouraged.

Objectives: Research and develop planning, guidance, and control methodologies and accompanying verification approaches for aerospace systems such as fixed-wing aircraft, rotary-wing aircraft, or spacecraft operating collaboratively, with a particular emphasis on space dynamics. Verification approaches can include offline verification such as formal methods, neural network verification, reachability, and mathematical analysis or novel test case generation techniques, as well as online verification approaches such as run time assurance. Also interested in hazard analysis techniques such as Systems Theoretic Process Analysis, as well as assurance case generation.

Description: Autonomous systems that utilize novel control techniques, including those based on reinforcement learning, promise to improve the speed with which systems can react in real time to changing mission needs and reduce the number of humans required to operate large numbers of unmanned aircraft or a constellation of satellites. However, hard-to-detect design flaws in advanced controllers could have catastrophic consequences, especially in safety-critical applications. The controller designs should address issues such as simultaneous satisfaction of multiple design and safety constraints, real-time task assignment and prioritization, effects of uncertainty with information and game theory considerations, operation on processing and memory-constrained computing hardware, interactions with human operators, and scalability of the design. Verification of these controller designs should include provably correct algorithms and architectures, formal verification, reachability analysis, fuzzing, novel test case generation approaches, and/or offline verification techniques such as monitoring and bounding of system behavior. Development of verification evidence should be conducted in concert with hazard analysis approaches that consider software failures and human interaction as well as novel approaches to certification based on structured assurance case arguments are of interest. Verification approaches should complement traditional approaches such as failure modes and effects testing/analysis, Monte Carlo simulation, hardware in the loop simulation, flight test, etc.

The Mission of the Warfighter’s Division is to develop technologies to aid the Warfighter in their mission. In particular, we focus on the Warfighters wellbeing and ensuring the Warfighters’ trust in any technologies we develop. Building trust between human and machine is no easy task. Often times the solution is to develop an elaborate user interface to model each mechanism of the machine or the solution is to have the human repeatedly train with the machine to eventually gain trust in its accuracy. Both of these solutions take time. We propose a strategy based on how humans quickly build trust with other humans—communication.
We can use Large Language Models(LMM) in a text-to-text dialogue agent to not only build trust between human and machine, but also help personnel recognize and address moments of stress and burnout within themselves. To achieve this goal requires capabilities that have not yet been developed. Such capabilities are the ability to identify stress from conversational text in a work place setting, the ability to identify the best remedy for different types of stress, and the ability to identify and adapt written communication style to the style best received and understood by the user.