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2019 SURE/SROP Research Projects in ECE

Directions: Below are listed the most recent descriptions of 2019 SURE and SROP projects available in Electrical and Computer Engineering (ECE). Please consider this list carefully before applying to the SURE or SROP program. You are welcome to contact faculty if you have additional, specific questions regarding these projects.

*IMPORTANT*: In addition to their online application, SURE applicants for ECE projects must also submit a resume and statement explaining their interest in and qualifications for the project that most interests them, including why they want to work on the project, the relevant skills they bring, and what they expect from their experience. The statement should be no longer than one page (12 point font and 1” margins) and must be uploaded in “other” at the bottom of the online application. Applications without this information may not be considered. Please include your name and UMID on all documents submitted.

SROP applicants for ECE projects should follow the specific directions outlined in the online application.

Research Area	Project Number
Applied Electromagnetics & RF Circuits	1, 2, 3
Control Systems	4, 5
Embedded Systems	6, 7, 8, 9, 10
Integrated Circuits & VLSI	11, 12, 13
MEMS & Microsystems	14, 15, 16, 17, 18
Network, Communication & Information Systems	19, 20, 21, 22
Optics & Photonics	23, 24, 25, 26
Power & Energy	27, 28
Robotics	29, 30
Solid State & Nanotechnology	24, 25, 26, 31, 32, 33, 34, 35, 36

ECE Project 1: Antenna beam steering with ultra-thin programmable surfaces (metasurfaces).

Faculty Mentor: Anthony Grbic ([email protected])

Prerequisites: EECS 230 required. EECS 330 or EECS 334 preferred. Student should have knowledge of time-harmonic electromagnetic fields (plane waves).

Description: The student will develop a versatile platform for the characterization and control of ultra-thin, programmable electromagnetic surfaces (metasurfaces) with various wireless applications in mind, including 5G, satellite, full duplex communications, and radar. The programmable transparent metasurface can modify the phase of a wave transmitted through it. By sending time-varying control signals to modulate the individual metasurface elements, the student researcher will demonstrate and experimentally characterize capabilities such as real-time beam steering, beam shaping, and Doppler spoofing. The student will help develop a computer control system and investigate various beamforming and modulation techniques. Knowledge of time harmonic electromagnetic fields is required, and LabVIEW programming experience is an asset. The student will gain a working knowledge of antennas and radiation, beam steering, and microwave measurement techniques, as well as learn about the emerging area of metamaterials/metasurfaces.

ECE Project 2: Flat quasi-optical devices fabricated using additive manufacturing

Faculty Mentor: Anthony Grbic ([email protected])

Prerequisites: EECS 230 required. EECS 330 or EECS 334 preferred. Student should have knowledge of time-harmonic electromagnetic fields (plane waves).

Description: Metasurfaces are subwavelength-textured surfaces designed to exhibit tailored electromagnetic/optical properties. Metasurfaces allow extreme control of electromagnetic wavefronts across electrically-thin layers, and therefore are ideally suited for the development of flat optical elements: low profile refracting, beam shaping, and focusing and polarization elements.

The student researcher will begin by experimentally characterizing existing all-dielectric metasurfaces, and then move on to analyze, design and test their own prototypes at millimeter-wave frequencies. These prototypes will be fabricated using additive manufacturing techniques. The student will become well versed in industry-standard microwave/electromagnetic CAD packages. He/she will use these packages to simulate metasurface designs, and develop their own metasurfaces. The metasurfaces will be characterized in the laboratory using a Gaussian beam measurement system. The student will learn about wave propagation and develop analytical/circuit models for complex 2D structures. He/she will employ modern techniques for the synthesis of microwave and photonic devices.

ECE Project 3: Resonant Cavity Enabled Wireless Power Transfer

Faculty Mentor: Alanson Sample ([email protected])

Prerequisites: Understanding of RF and Analog Circuits and/or experience with embedded systems.

Description: Wireless power technology is typically limited to 1-D charging cradles and 2-D charging pads. In this work we explore means of providing power to large 3-D volumes of space using the natural electromagnetic modes of hollow metallic structures to produce uniform magnetic fields, which can simultaneously power multiple receivers contained nearly anywhere inside.

ECE Project 4: Privacy and Security of Cyber and Cyber-Physical Control Systems

Faculty Mentor: Stephane Lafortune ([email protected])

Prerequisites: Programming experience in C, C++ and/or Java required.

Description: We are developing methodologies for (i) privacy enforcement in cyber systems and (ii) detection and mitigation of sensor and actuator attacks in cyber-physical control systems. The student intern will work on implementing and testing the algorithmic procedures of these methodologies, either as stand-alone procedures or as part of our existing M-DES software tools (see: https://gitlab.eecs.umich.edu/M-DES-tools). The student will also work on the development of case studies to test these algorithms, as well as on visualization tools for illustrating these case studies. The student will work in close collaboration with graduate students and postdoctoral researchers.

ECE Project 5: Theory and algorithms for finding corner-cases and bugs in autonomous vehicle controllers

Faculty Mentor: Necmiye Ozay ([email protected])

Prerequisites: Strong analytical skills and knowledge of linear algebra. Experience with MATLAB, Python, C++, or otherwise enough software engineering knowledge that suggests learning other languages, environments, etc. will not be difficult. Familiarity with git is not required but considered useful.

Description: One of the greatest hurdles to putting autonomous vehicles (as well as other complex autonomous systems) into the market is the difficulty in evaluating their performance/safety across a wide variety of conditions. To tackle this problem, our group has recently developed a method for verifying safety of autonomous driving software [1] based on the concept of the controlled invariant set in control theory and two-player game solutions for reachability and safety games. Participants in this project will extend our previous work by testing several real world autonomous driving softwares by generating hard test cases according to the theory developed in [1]. As an extension, we will study the impacts of varying sensor noise levels on the safety guarantees and how the effects of sensor/perception imperfections can be incorporated in the existing theory and algorithms.

[1] G. Chou, Y. E. Sahin, L. Yang, K. J. Rutledge, P. Nilsson and N. Ozay, “Using Control Synthesis to Generate Corner Cases: A Case Study on Autonomous Driving,” in IEEE Transactions on Computer-Aided Design (special issue for ESWEEK), vol. 37, no. 11, pp. 2906-2917, Nov. 2018. (https://arxiv.org/abs/1807.09537) (code repository: https://bitbucket.org/ozay_group/falsification_by_synthesis_emsoft_results/)”

ECE Project 6: Crowd-sourced photo-based air quality estimation

Faculty Mentor: Robert Dick ([email protected])

Prerequisites: Programming for data analysis. Algorithm design. Basic understanding of optical scattering and absorption.

Description: Develop methods of estimating air quality based on crowd-sourced data, potentially gathered for unrelated reasons. We are currently developing techniques allowing outdoor photographs posted on social media sites for any reason to be analyzed in order to estimate concentrations of different types of air pollution, including particulates and NO2. This work requires an understanding of pollutant optical properties, computer graphics, machine vision, and machine learning. It also provides a smooth path from (relatively straight-forward) data gathering and analysis to the development of original ideas.

ECE Project 7: Sensing and Understanding Natural Environments

Faculty Mentor: Robert Dick ([email protected])

Prerequisites: Comfort with using mathematical algorithms and data analysis. Python knowledge a plus.

Description: Help design a wireless ultra long battery life system for automatically sensing and understanding natural audio environments. The focus is on classifying and counting pollinators. Help figure out why so many bee colonies have died that there has been a 20% increase in the cost of pollination services, which accounts for billions of dollars per year, and why there has been a 75% reduction in the mass of flying insects in nature reserves in the base 25 years. Initially, participants will collect and analyze audio data on bee activity. The goal is to identify the presence and classify bee genus and activity to support entomological research. Ultimately, low-power IoT devices will be designed for deployment in agricultural environments.

ECE Project 8: Infrastructureless Communication Smartphone App

Faculty Mentor: Robert Dick ([email protected])

Prerequisites: Smartphone programming or marketing experience.

Description: How would you like to be put back in control of what you see and share via social media, even as others attempt to use it as a tool of censorship and surveillance? Develop Android/iOS microblogging applications supporting direct and transitive phone-to-phone communication that is resistant to outages, blocking, censorship, and surveillance. Create local community-oriented networks that would keep working even if the plug were pulled on the internet. Development team members will need iOS or Android programming experience. Marketing team members will need website design, video production, or social media marketing experience.

ECE Project 9: IoT Communication Design and Modeling

Faculty Mentor: Robert Dick ([email protected])

Prerequisites:
1) High-level understanding of wireless transceiver power consumption characteristics and ability to learn.
2) Ability to measure circuit power consumption.
3) Ability to interface various transceivers with development boards, e.g., Arduinos, using serial communication protocols.

Description: The personal computer, internet, and mobile computing changed mankind. The Internet of Things (IoT) is next. This network of ubiquitous, often low-power and wireless, devices will sense, analyze, and control the world. To create it, system designers must see the implications of their design decisions, and to do that they need system-level models of the wireless communication transceivers they are considering. There are many competitors (LoRa, NB-IoT, Weightless W, N, and P, Sigfox, and others), most of which are new, and nobody knows which will succeed.

Our goals are to experimentally characterize several potential IoT wireless communication technologies in order to build models for use in research and design. Real-world prototypes will be used, and their firmware modified, to evaluate the performance, reliability, and energy consumption implications of design decisions. A literature survey will also be required.

ECE Project 10: Smart IoT Sensor Interface Design

Faculty Mentor: Robert Dick ([email protected])

Prerequisites: One or more of the following.
1) PCB design.
2) PCB assembly, including surface mount soldering.
3) Electrical system testing and characterization.
4) Analog circuit design.

Description: Implement and test a smart sensor interface that turns dumb, manual sensors into accurate, automatic, wireless remote sensing systems. Water quality, air quality, audio… almost anything. Make the IoT real, today. Academic users/customers already enthusiastically waiting for the product.

ECE Project 11: Evaluation and Development of Analog and Wireless Systems

Faculty Mentor: Michael P. Flynn ([email protected])

Prerequisites: Matlab and some knowledge of digital and analog circuit design.

Description: This research project will evaluate analog and wireless systems, help develop demonstrations of the analog and wireless systems and design new circuits. Flynn’s research group designs analog and mixed-signal integrated circuits for applications as diverse as weather satellites and interfaces to the brain. This project will involve the design of new boards, and the writing of test software as well as software to control instruments. Some integrated circuit design will also be included in the project.

ECE Project 12: Millimeter-scale Sensor System

Faculty Mentor: David Blaauw ([email protected])

Prerequisites: Interest in embedded systems, circuit design. Responsibilities will depends on candidate background.

Description: In this project we are looking for a student to help us with embedded hardware and software development of mm-scale sensor systems for Internet of Things (IoT) applications. In the last few years we have prototyped the world’s first complete and functional mm-sized embedded systems. The system incorporated a commercial ARM Cortex M0 processor with low leakage memory, ultra-low power flash, battery, harvesting and RF communication. Early versions sensed temperature and pressure and more recent versions can also record audio and images. This work is currently featured at the Computer History Museum in California as the world’s smallest computer and also in the atrium of the EECS building. Our team is currently working actively with other researchers to deploy the sensors for butterfly tracking, down-hole oil-reservoir exploration and medical implantable applications as well as commercializing the technology. We are currently working to expand our sensor capabilities to include new sensing modalities, better interfaces and increasing radio range. The student work will depend on the background of the candidate and can include embedded software development for low power operation, GUI design, development of new sensor applications, help with digital and mixed signal circuit design, and testing and diagnosis of fabricated chips.

ECE Project 13: Accelerating Whole Genome Sequencing

Faculty Mentor: David Blaauw ([email protected])

Prerequisites: Interest in biomedical algorithm design, FPGA implementation, VLSI Verilog chips design. Responsibilities will depends on candidate background.

Description: Whole genome sequencing (WGS) determines the complete DNA sequence of an organism’s genome. While it cost nearly $3 billion to sequence the first human genome in 2001, just over the last one decade, the production cost of sequencing has plummeted from ten million dollars to thousand dollars, making it a promising tool for individualized treatment plans and precision health. In the sequencing pipeline, hundreds to thousands of CPU hours of intensive computation needs to be performed on raw data to sequence one genome, which are opportunities for software algorithm optimization and hardware acceleration. In this project, we are developing novel algorithms tailored for hardware acceleration to speed up the entire secondary analysis for a number of emerging genomics applications, such as whole genome sequencing, RNA single cell sequencing, and microbiome analysis. We aim to build a heterogeneous hardware system to speed up the current software pipeline by 1000x or more using algorithm and FPGA/ASIC implementation co-design. The work will depend on the background of the candidate and can involve both software / hardware development as well as exploring new genomics applications.

ECE Project 14: Data-driven high-throughput single-cell morphological, behavioral, and genotypic analysis

Faculty Mentor: Yu-Chih Chen ([email protected])

Prerequisites:
1. Patience and carefulness in doing experiments.
2. Good hand skill for doing experiments.
3. Basic skills in using Excel for data analysis.
4. Basic understanding in statistics such as hypothesis testing.
5. The capability to use MATLAB and write simple scripts for automatic data analysis.

Description: Cell heterogeneity is a new challenge in cancer therapy. Each cell in the heterogeneous population has its own unique property, and thus responds differently to the same drug, making cancer treatment difficult and complicated. Therefore, it is important to understand the heterogeneity characteristics of cells in drug assays. Still most assays measure the average behavior over large numbers of cells with an underline assumption that all cells are identical, which can lead to incorrect, imprecise results. To understand the behavior of each cell in heterogeneous groups, we should be able to provide high-throughput assays at single cell resolution, enlightening individual properties of each cell rather than the average behavior of the bulk tumor. Using microfluidic technologies, we can reliably monitor 10,000 single cells on-chip. In addition to cell behaviors, we are investigating the cellular heterogeneity in gene expression using Next Generation Sequencing (NGS). We also extract cell morphological features to predict its properties using random decision forest (RDF) and Convolutional neural network (CNN). Through this integrated approach, we will identify and validate novel genes and pathways, providing new therapeutic targets to eliminate cancer cells and ultimately leading to improved outcomes for patients.

ECE Project 15: The Investigation of Cancer Stem Cell Development Using Single Cell Microfluidics

Faculty Mentor: Euisik Yoon ([email protected])

Description: Cell heterogeneity is a new challenge in cancer therapy. Each cell in the heterogeneous population has its own unique property, and thus responds differently to the same drug, making cancer treatment difficult and complicated. Therefore, it is important to understand the heterogeneity characteristics of cells in drug assays. Still most assays measure the average behavior over large numbers of cells with an underline assumption that all cells are identical, which can lead to incorrect, imprecise results. To understand the behavior of each cell in heterogeneous groups, we should be able to provide high-throughput assays at single cell resolution, enlightening individual properties of each cell rather than the average behavior of the bulk tumor. In this work, we focus on studying the self-renewal and differentiation of cancer stem cells. Using microfluidic technologies, we can isolate and culture an array of 10k single cancer stem cells for several days, and observe their developments on-chip. The proliferation rate and self-renewal/differentiation can be measured using fluorescent imaging.

ECE Project 16: Data Storage for High-speed Brain Research

Faculty Mentor: Euisik Yoon ([email protected])

Prerequisites: Background in Electrical Circuits and Optics. Advanced courses in such areas as embedded controls, or electromagnetics are desired. A demonstrated interest in cross-disciplinary projects is also a plus.

Description: We are looking for a highly motivated undergraduate to advance electrical circuit technology in the context of brain research. Our current project uses optical light stimulation, high-speed electrical recordings, and custom ICs. In the neuroscience experiments, the amount of data streaming out of a rodent brain is too much to transfer real-time and hence we need to write most of the information to SRAM in a small rodent backpack assembly. This system needs to be developed using commercially available parts and protocols.

ECE Project 17: Vibration Energy Harvesting for Self-Powered Industrial Sensors

Faculty Mentor: Erkan Aktakka ([email protected])

Prerequisites: The student should enjoy hands-on lab work, show good attention to detail, and be comfortable working independently in a test lab. Familiarity with MATLAB, LabView, PCB design and assembly is not required but a plus. Basic skills in electrical system characterization and using Excel for data analysis is required.

Description: Rapid advances in solid-state devices have resulted in an increased functionality and performance in sensor systems, in addition to a continual decrease in their power consumption. Energy harvesting technology offers a further technological leap the result of which will be the development of energy-autonomous wireless sensor systems. These systems are needed in applications where using finite-lifetime batteries are not suitable. Vibration energy harvesters can capture machinery mechanical vibrations in an industrial environment into renewable electrical power, and be used to realize battery-less and maintenance-free wireless sensors and IoT nodes. This project focuses on development of miniature vibration energy harvesters with high-power density. The work will depend on the background of the candidate and can include device design, sample fabrication/assembly, electromechanical testing of fabricated devices, development of an automated test setup, circuit design for power management, or PCB-level integration of energy harvesters with sensors.

ECE Project 18: Flexible Thermoelectric Energy Harvesters for Wearable Sensors

Faculty Mentor: Erkan Aktakka ([email protected])

Description: Thermoelectric materials can convert spatial temperature differences into electricity, and be utilized to harvest ambient thermal energy into renewable electrical power for battery-less IoT (internet-of-things) nodes, such as self-powered wireless sensors or low-power wearable electronics. This project focuses on design, fabrication and characterization of a flexible and high power-density thermoelectric MEMS energy harvester for wearable wireless health-monitoring applications. The work will depend on the background of the candidate, and can include sample preparation and fabrication in a cleanroom environment, testing and diagnosis of fabricated MEMS chips, development of an automated test setup, or circuit design for power management and sensor interface.

ECE Project 19: Learning-based optimization of new caching algorithm

Faculty Mentor: Vijay Subramanian ([email protected])

Prerequisites: Strong analytical skills. Experience with TensorFlow or similar learning software. Some experience working in Unix-like environments. Knowledge of probability theory.

Description: We have developed a novel architecture and algorithm for caching content. The project goal is to determine optimal parameter settings using learning algorithms, such as Deep Learning via neural networks.

ECE Project 20: Load balancing using random graphs for cloud computing systems

Faculty Mentor: Vijay Subramanian ([email protected])

Prerequisites: Strong analytical skills. Experience with Java, Python, or enough software engineering knowledge to comfortably learn and work with other such languages. Some experience working in Unix-like environments. Knowledge of basic graph theory and probability theory.

Description: We are developing novel algorithms for load balancing in cloud computing systems that use random graphs and distributed memory. The project goal is to implement and test these algorithms by developing a web-/Java-/Python-tool that can be easily configured and can run large instances with real-world topologies.

ECE Project 21: Fast estimation of Personalized PageRank

Faculty Mentor: Vijay Subramanian ([email protected])

Description: We are developing novel algorithms for estimating Personalized PageRank using random walks and dynamic programming. The project goal is to implement and test these algorithms in two ways: first, developing a web-/Java-/Python-tool that can be easily configured and can run large instances with real network instances, and second, developing a tool to run these on the Internet.

ECE Project 22: Device-to-device sharing for real-time audio/video

Faculty Mentor: Vijay Subramanian ([email protected])

Prerequisites: Strong analytical skills. Experience with Android programming. Some experience working in Unix-like environments. Knowledge of probability theory, optimization and information theory.

Description: We are developing novel algorithms to enable easier real-time audio/video streaming on smartphone using device-to-device sharing over the WiFi interface. The project goal is to participate in the development of these algorithms, implement and test them on Android smartphones. We will use network coding and modify the kernel to implement our algorithms. We will also set up a server for generating the real-time stream. This will require two students.

ECE Project 23: Miniature Photovoltaics to Power the Internet of Things

Faculty Mentor: Jamie Phillips ([email protected])

Prerequisites: EECS 215, general knowledge of semiconductors and optics.

Description: We are working on miniature (mm-size) photovoltaic devices and arrays to harvest ambient indoor lighting for wireless sensor nodes, based on the “World’s smallest computers.” We are also using this technology to harvest infrared light through tissue to power bio-implantable devices. In this project, you would contribute to measuring the electrical and optical properties of our devices. Depending on your skillset and interests, you may also have the opportunity to contribute to the fabrication of these devices.

ECE Project 24: Thin Film GaAs Solar Cells and Solar Trackers

Faculty Mentor: Stephen Forrest ([email protected])

Prerequisites: Background in Optics and Materials Science.

Description: We are developing a method to fabricate extremely lightweight and high efficiency, thin film gallium arsenide solar cells. These flexible cells can be attached to mini (~2 cm3) solar concentrators and tracking mechanisms based on kirigami or other concepts to reduce the cost of solar power generation for mobile and even rooftop applications. The student will work with a graduate student mentor on topics ranging from optical modeling and semiconductor device fabrication, to device characterization in realistic environments (e.g., outdoor exposure to sunlight) to understand the limits of our approaches and to work on improvements.

ECE Project 25: Lifetime of Organic Light Emitting Devices

Faculty Mentor: Stephen Forrest ([email protected])

Prerequisites: Background in Electrical Circuits, Optics and Materials Science.

Description: Today, phosphorescent organic light emitting diodes (PHOLEDs) are the backbone technology supporting the OLED display industry that provides smart phones, tablets, and televisions to over 1 billion consumers worldwide. However, there are numerous challenges facing their further development; chief among them is the limited lifetime of the blue emitting PHOLED. Our project focuses on understanding and overcoming the fundamental limits to blue PHOLED lifetime. The student will work with a team of graduate students to measure the emitted light intensity from populations of blue PHOLEDs fabricated using structures testing different approaches for extending device operational lifetime. Extensive fabrication of devices and their characterization are among many of the areas to be pursued.

ECE Project 26: Roll-to-Roll Fabrication of Reliable Thin Film Organic Solar Cells

Faculty Mentor: Stephen Forrest ([email protected])

Prerequisites: Background in Materials Science.

ECE Project 27: Improving power system sustainability, reliability, and stability using flexible electric loads and energy storage

Faculty Mentor: Johanna Mathieu ([email protected])

Prerequisites: MATLAB, EECS 216, experience with optimization, controls, or simulation a plus

Description: We are developing new algorithms to use flexible electric loads like air conditioners and refrigerators and energy storage like batteries to improve power system reliability and stability, and increase the ability of the electric grid to accommodate renewable energy sources like wind and solar power. The student will learn basic load models, storage models, power system models, and control/optimization approaches; contribute to the development of these models/approaches; and run simulations to evaluate the approaches.

ECE Project 28: Using University of Michigan Buildings as Batteries

Faculty Mentor: Johanna Mathieu ([email protected])

Prerequisites: MATLAB, Excel, experience with data analysis a plus

Description: We are doing experiments on University of Michigan building to determine how well they could help the power grid accommodate more renewable energy sources like wind and solar power. More information is available here. The student will help collect and analyze data and/or develop building models to explain the experimental results.

ECE Project 29: Tracking Cloth for Deformable Object Manipulation

Faculty Mentor: Dmitry Berenson ([email protected])

Prerequisites: Significant programming experience (e.g. EECS 281). Experience with computer vision and/or 3D point-cloud processing.

Description: In order to manipulate deformable objects such as cloth we need to estimate the current configuration of the object from sensor data. This project will focus on tracking the state of a cloth as it is being manipulated using data from a Kinect sensor. A key question will be how to address occlusions, i.e. what can we infer about parts of the cloth we can’t see?

ECE Project 30: Manipulation of objects for active perception

Faculty Mentor: Dmitry Berenson ([email protected])

Prerequisites: Significant programming experience (e.g. EECS 281).

Description: We are studying how robots can interact with their environments to get more information about objects in complex arranges (e.g., in piles or stacks). For this project the student will help gather data and develop information-gathering motions for a robot arm sorting through a pile of objects such as clothes or blocks. The student may also contribute to the development of algorithms that can autonomously decide which information-gathering motion is best to do next.

ECE Project 31: Nanowire deep ultraviolet light-emitting devices

Faculty Mentor: Zetian Mi ([email protected])

Prerequisites: Background in electronics, optics and materials science. Strong experimental experience is preferred.

Description: Ultraviolet light sources are crucial for applications ranging from water purification to biochemical sensing. To date, however, the realization of high efficiency ultraviolet semiconductor optoelectronic devices including light-emitting diodes and lasers remains a challenge. This project is related to the development of nanostructures such as nanowires to achieve such solid-state light sources. The student will work with graduate student mentors on the epitaxial growth, fabrication, characterization and testing of these devices; the student is expected to deliver a detailed report on the current status of deep ultraviolet light sources and the progress that is made.

ECE Project 32: Artificial photosynthesis and solar fuels generation

Faculty Mentor: Zetian Mi ([email protected])

Prerequisites: Background in Electrical Engineering, Chemical Engineering or Materials Science.

Description: Artificial photosynthesis and solar fuels production has emerged one of the most promising approaches to address the energy and environment challenge we face today. This project involves the design of nanowire photocatalyst/photoelectrode and extensive photoelectrochemical and solar water splitting studies. This project will help develop interdisciplinary knowledge and skill sets in electrical engineering, materials science and chemistry. The student will have a graduate student mentor to prepare nanowires electrode, conduct measurement, and improve the device performance.

ECE Project 33: Full-color nanowire lasers for lighting, display and imaging applications

Faculty Mentor: Zetian Mi ([email protected])

Prerequisites: Background in Optics and Materials Science

Description: High efficiency multi-color lasers monolithically integrated on a single chip are highly desired for future smart lighting, full-color display, and imaging applications. With the use of selective area epitaxy, the emission wavelengths of InGaN/GaN nanowires can be tuned across nearly the entire visible spectrum on a single chip by varying nanowire size and compositions. This project involves the design and optical and structural characterization of nanowire photonic crystal structures and the demonstration of surface-emitting lasers. The student will work with a graduate student mentor on optical modeling and device characterization.

ECE Project 34: Electrical Characterization of GaN and Ga2O3 based transistors

Faculty Mentor: Elaheh Ahmadi ([email protected])

Prerequisites: MATLAB/Python, EECS 320 or equivalent.

Description: In this project, the SURE student will help with characterization of GaN and Ga2O3 based electronic devices via temperature dependent CV and IV measurements, as well as deep level transient spectroscopy in Ahmadi’s test lab. The student needs to be comfortable writing MATLAB/Python scripts for data analyzing. Completion of EECS 320 or an equivalent course are mandatory.

ECE Project 35: Optimization of Metal-Semiconductor Contacts to Gallium Oxide

Faculty Mentor: Becky Peterson ([email protected])

Prerequisites: Background in Electrical Engineering, Chemical Engineering, or Materials Science.

Description: Gallium oxide is an ultra-wide bandgap oxide semiconductor which is being investigated for multi-kV power devices. One of the challenges in commercializing these devices is the need for electrical contacts that are stable in light of the high current, high voltages, and high temperatures used during operation. Our group is using new approaches and materials to build ohmic and rectifying contacts and characterize their stability. In this project, the SURE student will work with a graduate student to perform in depth studies of gallium oxide contacts. Depending on the student’s expertise, the project may include materials characterization and/or electrical investigation of the interfacial properties of these contacts.

ECE Project 36: P-type oxide semiconductors

Faculty Mentor: Becky Peterson ([email protected])

Prerequisites: Background in Electrical Engineering, Chemical Engineering, or Materials Science.

Description: Oxide semiconductors offer unique properties including a wide bandgap and ease of thin film fabrication. N-type oxide semiconductors have been commercialized for flat panel display backplanes, are used in novel memories to alleviate the memory bottleneck and in high-voltage electronics. In order to build CMOS circuits, p-type oxide semiconductors are needed to complement these existing n-type materials. In this project, the SURE student will work with a graduate student or post-doc on sputtering or atomic layer deposition to make p-type metal oxide semiconductor films and characterize their properties. Depending on the student’s expertise, the studies may include materials characterization and/or electrical and optical testing.