CLAWS Research Experience for Undergraduates (REU) Projects

Please review the following sample projects for our Summer 2025 REU program at NC State. Priority applications are due by March 14, 2025, but please apply as soon as possible if you can’t meet this deadline. If you are having issues getting professional references in time, please go ahead and submit your application. We will reach back out if we need them. If you wish to apply, please do so using the button below. Any questions can be directed to Phillip Strader (phillip_strader@ncsu.edu)

1. Building a cryogenic optical characterization setup for nanoscale semiconductor light sources and metasurfaces (Qing Gu, NC State, Electrical and Computer Engineering)

The goals of this projects are: (1) participating in the building and testing of an optical characterization setup that is used to measure transmission, reflection, and emission of nano- and micro-scale light sources and metasurfaces. (2) build and configure a cyrogenic system from existing components and integrate it into the optical characterization setup.

2. Waferbonding of GaN to SiN waveguides (Stanley Cheung, NC State, Electrical and Computer Engineering)

This REU project focuses on the integration of III-N (GaN) compound semiconductors with silicon nitride (SiN) through wafer bonding techniques. Wide bandgap III-N materials exhibit superior electronic and optoelectronic properties, making them highly desirable for applications in high-speed electronics, photonics, and energy-efficient devices. However, the direct growth of III-N materials on SiN presents challenges due to lattice mismatch and thermal expansion coefficient differences. Wafer bonding offers an alternative pathway to monolithic integration, enabling the combination of III-N and SiN technologies for next-generation electronic and photonic devices.

Project Objectives:

• Investigate different wafer bonding techniques, including direct bonding, plasma-assisted bonding, and adhesive bonding.
• Characterize the interface quality, bonding strength, and electrical/optical performance of bonded III-V/Si structures.
• Optimize processing conditions to achieve high-quality bonded interfaces with minimal defect formation.
• Explore post-bonding treatments such as annealing and surface passivation to enhance device performance.

3. High Speed Testing of Hybrid III-V/Si Micro-Ring Lasers (Stanley Cheung, NC State, Electrical and Computer Engineering)

This REU project focuses on the high-speed characterization of III-V/Si hybrid micro-ring lasers, which combine the superior optoelectronic properties of III-V materials with the scalability and manufacturability of silicon photonics. These lasers are essential for next-generation high-speed optical communication systems, offering improved efficiency, compact integration, and potential compatibility with CMOS technology. The project’s goal is to evaluate the performance of these lasers under high-speed modulation to optimize their application in datacenters, telecommunications, and photonic computing.

Project Objectives:

• Write lab automation software for basic semiconductor laser testing.
• Conduct high-speed testing of III-V/Si hybrid lasers, including small-signal and large-signal modulation analysis.
• Measure key laser parameters such as threshold current, output power, linewidth, and modulation bandwidth.
• Utilize advanced radio-frequency (RF) and optical characterization techniques, including vector network analysis and high-speed photodetection.
• Analyze the impact of temperature, bias conditions, and yield.
• Compare experimental results with theoretical models to improve device design.

4. Optical Hyper Dimensional Computing (Stanley Cheung, NC State, Electrical and Computer Engineering)

This REU project explores the development of optical hyperdimensional computing (HDC), an emerging paradigm that mimics brain-like computing by encoding and processing information in high-dimensional space. HDC offers advantages in energy efficiency, noise resilience, and rapid learning, making it a promising approach for artificial intelligence (AI), signal processing, and edge computing applications. By leveraging integrated photonics and optical signal processing, this project aims to develop novel high-speed, low-power HDC frameworks for artificial intelligence (AI), neuromorphic computing, and edge applications.

Project Objectives:

• Develop photonic-based encoding schemes to map real-world data (e.g., images, text, sensor inputs) into high-dimensional vectors using spatial, spectral, and temporal encoding techniques.
• Design and simulate optical vector manipulation architectures using silicon photonics, spatial light modulators, or free-space optics to perform ML operations such as similarity search and classification.
• Implement an end-to-end machine learning framework that integrates optical computation with digital post-processing for benchmarking against conventional electronic ML models.
• Evaluate system performance in terms of accuracy, speed, power consumption, and noise robustness compared to conventional digital HDC approaches.

Machine Learning Framework & Design:

This project will integrate machine learning algorithms with optical HDC hardware, allowing students to:

• Train and test ML models using software-based HDC implementations (e.g., in Python using TensorFlow, PyTorch, or Scikit-learn).
• Develop hybrid electronic-photonic architectures, where optical systems accelerate high-dimensional vector operations while digital systems handle preprocessing and control.
• Optimize feature encoding and hypervector design to improve classification accuracy for applications such as image recognition, natural language processing, and biosignal analysis.
• Compare optical HDC against traditional ML models such as deep neural networks (DNNs) and support vector machines (SVMs) in terms of computational complexity and energy efficiency.

5. Co-Design of Electronic Packaging via AI/ML-Based Optimization (Jong Ryu, NC State, Mechanical and Aerospace Engineering)

Electronic packaging refers to the design and assembly of electronic components and systems into a physical structure that protects them from environmental and mechanical damage while ensuring electrical connectivity and thermal management. It plays a crucial role in maintaining the performance, reliability, and manufacturability of electronic devices, especially in power electronics applications such as silicon carbide (SiC) power modules.

Traditional packaging design relies on iterative simulations and empirical testing, which can be time-consuming and cost-intensive. This project aims to leverage artificial intelligence (AI) and machine learning (ML) techniques to optimize the co-design of electronic packaging, integrating multiphysics considerations such as thermal management, mechanical reliability, and electrical performance. AI/ML-driven models will be developed using high-fidelity simulation and experimental data to accelerate design space exploration and predictive analysis. A digital twin framework will be incorporated to continuously refine predictions using real-time data, improving the adaptability of the design process.

To validate the AI/ML-based optimization framework, experimental studies will be conducted. These include power cycling tests to assess thermal and mechanical fatigue in interconnects and solder joints, as well as reliability tests to evaluate long-term performance under thermal, electrical, and mechanical stress conditions. The experimental results will be used to further refine and validate the predictive models, ensuring robust and manufacturable packaging solutions.

By integrating AI/ML with physics-based simulations and experimental validation, this research aims to reduce design iteration cycles, enhance operational efficiency, and extend the lifetime of power electronic modules. The outcomes will benefit industries focused on power electronics, automotive applications, and semiconductor manufacturing by providing a data-driven, automated approach to electronic packaging co-design.

6. LED fabrication and testing (Jonathan Wierer, NC State, Electrical and Computer Engineering)

The student will be exposed to and contribute to active research on state-of-the-art III-nitride semiconductor LEDs and laser diodes (LDs). They will learn semiconductor fabrication, testing, and characterization techniques that allow the research team to make informed and timely decisions on growth improvements.  

Specific duties include:

• Learn and perform LED device fabrication and testing.
• Convert epitaxial run data into layered structures in a spreadsheet.
• Learn and perform semiconductor characterization measurements such as Hall effect, photoluminescence, X-ray diffraction, and atomic force microscopy.

Applicants should have some basic semiconductor knowledge (taken ECE 302 and preferably 404) and the ability to code with Matlab. Electrical Engineering students are preferred. A regular LED fabrication and testing schedule is required so the team can plan for growth runs.  Prof Wierer will advise the applicant and work closely with senior researchers and graduate students.  These research tools are in the Monteith Research Center (MRC). High-performing students could lead to expanded duties.

7. Investigating the Interaction of Microwave Fields with Materials (Daryoosh Vashae, NC State, Electrical and Computer Engineering)

This project aims to explore how electromagnetic fields, particularly microwave frequencies, interact with different materials and potentially influence chemical reactions. The primary goal is to understand how microwave energy can initiate, accelerate, or control both gaseous and solid-state reactions. A variety of experimental techniques will be employed to characterize these interactions, including:

• RGA (Residual Gas Analysis) for studying reaction products and gas-phase dynamics.
• XRD (X-ray Diffraction) to analyze the lattice structure of materials before and after exposure.
• Raman Spectroscopy to monitor vibrational modes and molecular changes.
• UV-Vis Spectroscopy for probing optical properties and reaction kinetics.
• Transmission Electron Microscopy (TEM) to observe material morphology and microstructure at the nanoscale.
• Vibrating Sample Magnetometry (VSM) and AC Magnetic Susceptibility (ACMS) for examining magnetic properties.
• Electrical conductivity measurements to assess changes in electrical behavior due to EMF exposure.

By combining these techniques, the project will provide detailed insights into the role of microwave fields in material transformation and chemical reactions.

8. Synthesis and Characterization of Spin-Driven Thermoelectric Materials (Daryoosh Vashae, NC State, Electrical and Computer Engineering)

This project focuses on the synthesis of novel thermoelectric materials with spin-driven properties. The goal is to design and produce materials that exhibit enhanced thermoelectric performance for energy conversion applications. Key synthesis techniques will include nanopowder preparation, spark plasma sintering, and wafer slicing and dicing to fabricate the thermoelectric materials.

The materials will be extensively characterized to investigate their thermal, electrical, magnetic, and thermoelectric properties. The following experimental methods will be employed:

• X-ray Diffraction (XRD) to analyze the lattice structure and phase composition of the materials.
• Raman Spectroscopy to monitor vibrational modes and molecular changes that may affect thermoelectric performance.
• UV-Vis Spectroscopy to probe optical properties and study reaction kinetics during material processing.
• Transmission Electron Microscopy (TEM) to examine material morphology and microstructure at the nanoscale.
• Vibrating Sample Magnetometry (VSM) and AC Magnetic Susceptibility (ACMS) to study magnetic behaviors that may influence thermoelectric efficiency.
• Electrical conductivity, Hall coefficient, Nernst coefficient, thermal conductivity, and thermopower measurements to evaluate the materials’ thermoelectric performance and determine their suitability for practical applications.

Through these techniques, the project aims to develop efficient thermoelectric materials for energy harvesting applications.  

9. “Special Topics in Wide Bandgap Materials and Devices” (Spyridon Pavlidis, NC State) 

Students will work on research projects focused on Wide-bandgap (WBG) semiconductors. WBG Semiconductors like Silicon Carbide,and Gallium Nitride enable electronic devices to operate at much higher voltages, frequencies, and temperatures more efficiently than silicon. These technologies are great for defense and civilian applications where Size, Weight, and Power (SWaP) matter, allowing more electronics on airplanes and satellites, electric vehicles that go further on a battery charge, more powerful and accurate Radars, and faster communication systems. Emerging ultra-wide bandgap semiconductors like Diamond and Gallium Oxide can operate at even higher voltages and may be part of shipboard systems and future electric power grids. Students that participate in this program will work on a variety of materials fabrication and/or characterization techniques with these materials as well as receive professional development and networking opportunities.

10. “Special Topics in Wide Bandgap Materials and Devices” (John Muth, NC State)

Students will work on research projects focused on Wide-bandgap (WBG) semiconductors. WBG Semiconductors like Silicon Carbide,and Gallium Nitride enable electronic devices to operate at much higher voltages, frequencies, and temperatures more efficiently than silicon. These technologies are great for defense and civilian applications where Size, Weight, and Power (SWaP) matter, allowing more electronics on airplanes and satellites, electric vehicles that go further on a battery charge, more powerful and accurate Radars, and faster communication systems. Emerging ultra-wide bandgap semiconductors like Diamond and Gallium Oxide can operate at even higher voltages and may be part of shipboard systems and future electric power grids. Students that participate in this program will work on a variety of materials fabrication and/or characterization techniques with these materials as well as receive professional development and networking opportunities.