EMDL: ELECTRONIC MATERIALS AND DEVICES LAB (Dr. Sushma Kotru)
The lab focuses on synthesis of micro/nanoscale devices using a wide variety of materials and their potential applications. Current research includes design and fabrication of UV sensors for wearable devices, magnetic materials for power applications, Ferroelectric, Multiferroic Materials, Piezoelectric Sensors/ Actuators, Ferroelectric Photo-voltaic. Research capabilities include Pulsed Laser Deposition and Sol-gel for film preparation, Signatone probe station, RT 6000 Ferroelectric Tester, PV and QE Tester, Piezoelectric cantilever setup, and Magneto-electric setup, for film/ device characterization. In addition, our group has access to the equipment’s available in Alabama Analytical Research Center and Micro Fabrication Facility
Our research focuses on fundamental science of light matter interactions and applications of photonic devices, metamaterials, and THz photonics in sensing, imaging, communication, and information technology. Research topics include design and simulation of metamaterial/metasurface, micro and nano fabrication, electromagnetic simulation, flat optics, Solar Sail, polarimetry, THz biomedical imaging and spectroscopy, quantum information and network, flexible THz/mm-wave devices, THz/mm-wave communication, ultrafast laser spectroscopy, and neuro-photonics. The laboratory is also heavily involved in research and development of multi-sensor LiDAR system and integration for underwater imaging, bathymetry, and remote sensing. Our application of photonics, metamaterials, THz technologies are targeted for future diagnostics platform, quantum sensing, quantum network, 6G/7G and beyond, AI aided bio-imaging, space exploration, underwater imaging, and understanding brain. Our research has been funded by DoD, DoE, NASA, NOAA, NSF.
The ONE lab focuses on solution-processed thin-film devices, including organic and perovskite solar cells, thin-film transistors (OTFTs), and large-volume manufacturing of photovoltaic cells and modules through high-speed printing on flexible substrate. The lab has expertise on rapid photonic annealing and sintering, and nanofabrication with electron-beam lithography for making nanoimprint molds and nanoimprint lithography for easy duplication of nanopatterns. The ONE lab has full set up solar cell fabrication and characterization tools, such as glove box fabrication system with built-in thermal evaporator, solar simulator, quantum efficiency testing kit, probe station, and semiconductor parameter analyzer.
NOEL: NANO OPTO-ELECTRONICS LAB (Dr. Patrick Kung)
Our research focuses on harnessing the interactions of photons, electrons, excitons, and other quantum particles in semiconductors for device application and integration. Research topics include synthesis of semiconductor materials; engineering of 0D~3D material topologies, heterostructures and interfaces; fabrication and testing of photonic and electronic devices; flexible electronics. The laboratory is also involved in the design and integration of rad-hard electronics for small satellites. The developed devices and integrated systems serve applications in nanophotonics, quantum/chem-bio sensing, quantum/optical communications, quantum information processing, neuromorphic computing, light sources, energy harvesting/conversion and others.
MMDL: MAGNETIC MATERIALS AND DEVICE LABORATORY (Dr. Yang-Ki Hong)
MMDL focuses on three areas: Electromagnetics/Electrodynamics, Electric Machines, and Computational Materials Science. Current projects in the electromagnetics and electrodynamics area are 5G/6G antennas, miniaturized AM/FM ferrite antennas, dual-polarized antennas for UAV, and EMI/EMC. Current electric machine projects are permanent magnet (PM) synchronous motor and efficiency-shifting PM motor for electric vehicles. Current projects in the computational materials science area include RE-free soft and hard magnets, wide bandgap semiconductors, and thermoelectrics. Research tools include HFSS, ANSYS Maxwell, WIEN2k, VASP, MuMax3, LLG micromagnetic simulation, ATAT, and BoltzTrap. MMDL holds 21 US patents, published 170 refereed journal papers, and presented more than 240 papers.
Our research includes wide range of topics and applications in The Energy and Power Electronic Systems and Devices area. We research and develop electric/electronic circuit topologies, controls, devices, systems, and prognosis and diagnosis methods to address/solve challenges and make improvements for several applications especially in terms of efficiency, density/size and weight, reliability, portability, interoperability, and safety. Example applications include electrified transportation, computing platforms, energy storage systems, portable electronics, and space power systems, among others. Example topics include power electronic converters, digital and adaptive controls (including prognosis and diagnosis and machine learning), renewable energy systems, wireless power, and system level power management, among others.
Our research focuses on novel solutions to enable mass integration of EVs and other distributed energy resources in the power distribution system. Developed solutions include machine learning enabled distributed controllers that can be implemented at the end-nodes within the distribution system. We design AC-DC converters (single/three-phase) used in EV chargers and other distributed energy resources. We also develop HIL testing systems to understand system level impact of power electronics integration and test the real controllers within wide-scale HIL simulation platforms. To sum up, our research overlaps design of power electronics systems and the operation of power distribution grid.
ACES: ADVANCED CONTROLS AND ENERGY SYSTEMS LABORATORY (Dr. Andy Lemmon)
Our research seeks to address the accelerating demand for high-efficiency, high-power-density power electronic applications through the use of wide band-gap semiconductors (SiC and GaN). This emerging technology enables dramatic improvement in application performance, but also introduces high-frequency artifacts which must be properly managed. The ACES lab seeks to address this challenge by (1) developing compact behavioral models of SiC and GaN devices; (2) pioneering new methods to characterize and model semiconductor packaging; (3) developing reduced-order equivalent circuit models to predict common-mode behavior and electromagnetic interference; and (4) designing, prototyping, and evaluating high-performance converters to demonstrate the concepts discovered through analysis of these models.
RESyL: RENEWABLE ENERGY SYSTEMS LABORATORY (Dr. Shuhui Li)
The research of the RESyL group focuses on 1) Renewable Energy conversion, generation and storage, 2) Electric Machines and Drives in traction, including electric vehicles, hybrid electric vehicles, and electrified railways, 3) Power Electronics in renewable energy systems, microgrids, and distributed generation, 4) Intelligent Grids and Systems, including microgrids, HVDC supergrids, artificial neural networks and their applications in power systems, 5) Smart Energy Management in buildings and homes, 6) Economics, Market and Policy of smart electric power grid, 7) High-performance computing especially for neural network training, and 7) Real-time and HIL (hardware-in-the-loop) simulation
DART’s research focuses on complex digital systems and real-time embedded systems designed to operate in extreme environments. We are closely tied to the Remote Sensing Center at the University of Alabama, which is focused on radar remote sensing of extreme environments, such as Antarctica and Greenland.
We are also focused on using FPGA and SoC technology to obtain hardware speedup for real-time and time-constrained applications for robotics and other applications.
Our research spans over the areas of artificial intelligence, machine learning, computer vision, bio-optics in biomedical engineering, computer engineering, and health informatics. Research topics include biomedical segmentation, image restoration, robust machine learning, generative deep learning, object detection, edge computing, etc. We develop computational tools to facilitate clinical treatment, medical diagnosis, biological research, behavioral study, rehabilitation, and library informatics.
Research focuses on the design and application of portable and wearable sensing systems for physiological and health monitoring. Research topics include wearable systems, sensor characterization/validation, multi-modal data analysis, and physiological feature identification; with a specific focus on muscle and joint health monitoring.
Our research focus is underwater communications and networking for mobile platforms. The aquatic environments, including the oceans, lakes, and rivers, are the basis for life. The next research frontier is to use fleets of aquatic robots, both autonomous surface vehicles and autonomous underwater vehicles, to perform adaptive sampling in aquatic environments. Underwater wireless communications and networking are the enabling technologies for distributed adaptive aquatic sampling. Collaborating with multiple institutions such as Georgia Tech, University of Houston, Michigan Tech, we are performing interdisciplinary research to advance sciences and technologies at the intersections of underwater wireless communications, sensor networking, and marine robotics.
ERSyL: EMBEDDED AND ROBOTIC SYSTEMS LABORATORY (Dr. Kenneth Ricks)
Our research focuses on all aspects of embedded devices with an emphasis on robotics. Research topics include computing architectures for embedded applications; embedded software development; computer vision; real-time computation; autonomous navigation including localization, path planning, obstacle detection and avoidance; machine learning; robotics simulation; FPGA applications; space-based robotics; and the development of robotic prototypes for various applications.
Our research focus is on the application machine learning for automatic target recognition (ATR) and the design of next-generation radar systems. This includes fundamental research in neural network architectures and training methodologies that incorporate physical sensor and target models for improved classification accuracy, robustness, and reduced computational complexity. Exploiting advances in adaptive antennas and RF electronics, we strive to incorporate biologically-inspired machine learning and artificial intelligence algorithms into radar system design for the goal of developing cognitive radars of the future. Specific applications of interest include RF-sensing for the design of human motion sensitive ambient environments, remote health monitoring, fall detection, fall risk assessment, gait analysis, as well as applications to human-computer interaction, including gesture recognition, and natural language processing, including ASL recognition and the design of smart Deaf spaces. We also work on applications of signal processing and machine learning to a variety of defense and security applications.
This lab has equipment to support advanced research in wireless networks, machine learning, cyber security, and big data. Recently, we are conducting research with NSF and DoD on big data security, UAV networks, deep learning, and virtual reality based medical rehabilitation.
Our research focuses on application of artificial intelligence, wearable and ambient sensors in bioengineering, assistive robotics and health informatics. Research topics include design of wearable device hardware, such as novel on-body sensors, microcontrollers and FPGA, flexible and conformable electronics, wireless IoT-enabled devices and body sensor networks. The laboratory is also heavily involved in signal and image processing using techniques of digital signal and image processing, machine and deep learning. The developed devices and methods are utilized internationally in human studies of health-related behaviors, including food intake, physical activity, cigarette smoking and others.
Remote Sensing Center
UA Remote Sensing Center is a multi-disciplinary research center focused on the design and development of miniaturized microwave sensors for integration on manned and unmanned aircraft and satellites. The center develops both the RF and digital hardware required for radar system design as well as the necessary signal processing and geophysical retrieval algorithms for fine resolution measurements of snow, soil and ice. Mechanical considerations of large-scale antenna structures, physical integration of sensors onto airborne platforms, piloting of drones and flight planning of airborne missions as performed in-house. The center thus offers the opportunities for students to be involved in the entire development chain of radar remote sensing systems.
Our research focuses on application of electromagnetic theory in antennas and radar remote sensing. Research topics include design of novel antennas and phased arrays, RF circuits, radar systems and the associated signal processing including physical parameters retrieval. The laboratory is affiliated with the UA Remote Sensing Center and is equipped with the state-of-the-art RF/Microwave/mmWave test equipment, including a large electromagnetic anechoic chamber with 12-m measurement range, as well as high-precision milling and laser machines for rapid PCB prototyping.
Our research focuses on the fundamental and applied research in the areas of antenna, electromagnetic devices and system, wireless power and data transfer, and biomedical engineering. Research topics includes design of high-performance millimeter-wave phased array antenna, remote sensing radar, V2X (vehicle-to-everything) communication, wireless power transfer to a deep-tissue microimplant, and human movement analysis. The electronic device and system are characterized with electromagnetic simulator, machine learning techniques, anechoic chamber, vector network analyzer, LPKF milling machine, oscilloscope, etc.
Our research focuses on statistical signal processing, radar systems and machine learning with applications in autonomous driving, digital health and industrial robotics. Research topics include radar signal processing, such as radar waveform optimization, sparse antenna array design and optimization, high resolution spectrum estimation algorithms, radar interference detection and elimination (RIDE). The laboratory also works on the design and prototyping of high-resolution imaging radar systems for environmental perception, radar machine learning and sensor fusion.