Terahertz Optoelectronics Research Group

Some of the example projects include:

• Machine learning for 3D nanopatterning (Menon): To obtain high precision 3D nanostructures, we need to clearly and rigorously understand the manufacturing process, which in turn requires very careful metrology. This research project aims to enhance the precision of 2.5D and 3D structures produced by grayscale lithography. Utilizing the advanced instruments at the University of Utah’s nanofabrication facility, such as the confocal microscope, atomic force microscope (AFM), and scanning electron microscope (SEM), we plan to gather comprehensive measurement data. As part of the research project, the student will conduct detailed measurements of 2.5D and 3D structures’ characteristics using the aforementioned instruments. Data analysis will explore correlations between these measurements and various process parameters, including laser power and environmental factors, utilizing rigorous statistical methods. Leveraging machine learning techniques, predictive models will be developed to forecast metrology data based on input parameters, aiding in process optimization. The anticipated outcome is a comprehensive dataset linking process parameters to structural measurements, enabling the refinement of lithographic techniques and the potential for automated protocol optimization. This interdisciplinary approach, integrating metrology, statistical analysis, and machine learning, holds promise for advancing grayscale lithography, benefiting microelectronics manufacturing.

• Computational proximity-effect correction in 3D nanopatterning (Menon): In this project, we are building upon previous findings that the finite dimensions of a laser’s focal point significantly influence the quality of nanostructures produced by grayscale lithography. As part of the research, the student will create algorithms inspired by inverse design methods to adjust the energy distribution of the laser on the photoresist layer in 3D to minimize deviation of the final developed pattern from the designed geometry. This will include measurements of 3D structures in our nanofab, performing test lithography, creating correction algorithms and finally, testing the efficacy of these algorithms. By the conclusion of this project, we anticipate that the developed algorithms will significantly improve the fidelity of 3D printed nanostructures to their designed geometries. The contributions of this research could have far-reaching implications for the field of nanofabrication, potentially setting new standards for precision in grayscale lithography.

• Enhancing Accuracy and Efficiency in Optical Forward Modelling (Menon): This project aims to improve the accuracy and efficiency of forward models used in optical simulations, addressing key challenges and implementing innovative strategies. While scalar diffraction methods like Angular Plane-Wave Spectrum (APWS) offer simplicity, fully rigorous methods such as Finite-Difference Time-Domain (FDTD) provide higher accuracy but demand substantial computational resources. To reduce computational costs, the project proposes parallelization techniques and leveraging cloud computing platforms like AWS and Google Cloud. Additionally, algorithmic optimizations and resource management strategies will be explored to strike a balance between simulation accuracy and computational overhead. The anticipated outcomes include a highly scalable forward model capable of running high-fidelity simulations and paving the way for future directions such as integrating machine learning techniques and hybrid approaches. Ultimately, this project aims to provide researchers and engineers with powerful tools to design and analyze next-generation optical systems with unprecedented precision and efficiency.

• Advancing Gallium Oxide Schottky diodes through grayscale lithography for field plate engineering (Jia): This research project aims to innovate Gallium Oxide Schottky diode technology through the application of grayscale lithography techniques for optimized field plate engineering. Schottky diodes are pivotal components in various electronic devices, including microwave amplifiers, power rectifiers, and high-frequency mixers. The efficiency and performance of Schottky diodes heavily depend on the control and distribution of electric fields within the device structure. Field plate engineering offers a promising avenue to enhance the breakdown voltage, reduce on-state resistance, and mitigate the effects of electric field crowding in Schottky diodes. Herein, grayscale lithography provides precise control over feature height, enabling the fabrication of complex and tailored field plate structures with submicron resolution. As part of the proposed project, students will first simulate using commercial device simulation software diode structures to enhance breakdown voltage, the structures to be analyzed consist of diode step dielectric structures with variable step heights. The students will fabricate these through grayscale lithography following the processes being developed in previous projects. Finally, these devices will be tested, and performance compared with traditional geometries. 

• Optically defined digital metamaterials for reconfigurable microwave components (Jia): Recent trends in photonics have shown that optimized pixelated surfaces can outperform classical designs in reducing design area and improving the frequency response. Such pixelated surfaces, on a microstrip implementation, can also be used to realize “random” engineered RF components (e.g., filters, matching networks, power splitters/combiners, etc.). Since there are no closed-form solutions to describe the design of these surfaces, computational design is key. We have recently proposed a method for synthesizing a pixelated surface to act as a filter using a direct binary search and realized based on it a dual-band RF filter.  The method can be used to reliably create designs for generalizable RF functions, many of which are yet to be explored. For this project, the student will optimize device geometries to realize RF surfaces with various additional electromagnetic responses, in particular, power splitters and combiners with tailored frequency responses. An important question is whether inverse-designed structures can attain similar performances as traditional structures, such as a Wilkinson power divider, while simultaneously having smaller area. Furthermore, a second aspect of the project will be to provide active reconfiguration by means of using light.

• Development of extended depth of focus lens for enhanced precision in PCB via manufacturing (Sensale-Rodriguez): The goal of this research project is to design and implement an extended depth of focus (EDOF) lens system tailored specifically for printed circuit board (PCB) via manufacturing processes. PCB vias, which serve as conductive pathways between different layers of a PCB, require precise drilling and inspection to ensure optimal electrical connectivity and reliability. Conventional lens systems used in PCB via manufacturing are limited by their shallow depth of focus, leading to challenges in achieving uniform drilling depth and accurate inspection across the entire PCB surface. Building on the research being carried out in our PFI project of EDOF lens for laser manufacturing, the proposed EDOF lens system seeks to overcome these limitations by extending the focal depth while maintaining high resolution and optical clarity, thereby enhancing the precision and efficiency of PCB via manufacturing processes. As part of the proposed research, students will design a customized EDOF lens system tailored to the specific requirements of PCB via manufacturing processes. Employ optical design algorithms developed in our PFI grant to optimize lens parameters, including aperture size, focal length, and aberration correction, to achieve extended depth of focus while preserving beam quality and resolution. Then they will fabricate prototype EDOF lenses using grayscale lithography and etch on gallium oxide. This EDOF lens system will finally be integrated and tested into existing PCB manufacturing equipment, ensuring compatibility and seamless operation within the manufacturing workflow. The system will then be characterized and its performance evaluated.

• Inverse design of fiber-to-waveguide couplers (Sensale-Rodriguez): This research project aims to leverage the principles of inverse design and digital metamaterials to develop advanced fiber-to-waveguide couplers with unprecedented performance and versatility. Fiber-to-waveguide couplers are essential components in optical communication systems, facilitating efficient and low-loss coupling of light between optical fibers and integrated photonic devices. Traditional design approaches for couplers often rely on iterative optimization methods and conventional materials, limiting the achievable performance and adaptability. By harnessing the power of inverse design algorithms and digital metamaterials through machine learning, this project seeks to enable the design and fabrication of fiber-to-waveguide couplers with tailored functionalities and enhanced performance metrics. As part of the proposed research, the students will take existing inverse design algorithms capable of optimizing the electromagnetic properties of digital metamaterial structures and tailor these to efficient fiber-to-waveguide coupling, defining properly the problem to be optimized and figures of merit. Then they will prototype digital metamaterial couplers using state-of-the-art nanofabrication techniques such as focused ion beam milling available at the University of Utah Nanofab. Finally, they will characterize the optical performance of the fabricated couplers through experimental testing and analysis, including insertion loss, polarization dependence, and spectral response measurements.

• Design of diffractive optical elements for parallel STED Direct Laser Writing (Majumder): This project focuses on enhancing multi-photon 3D laser micro- and nanoprinting by developing a novel optical element that simultaneously generates writing and depletion beams, eliminating the need for separate optical components and enabling parallel processing. By combining Finite Difference Time Domain (FDTD) analysis with machine-learning optimization, a high Numerical Aperture (NA) element capable of producing multiple self-aligned beams will be designed. This approach aims to increase print speed and spatial resolution while simplifying the system and reducing costs. The project involves designing and optimizing the optical elements, fabricating them using grayscale lithography, and conducting metrology and optical characterization. Through this interdisciplinary approach, the student will gain expertise in wave optics, computational design optimization, microfabrication, and optical characterization techniques. Key questions include addressing focusing efficiency, optical null darkness, maximum achievable NA, and fabrication error effects. The project’s ultimate goal is to develop a highly parallelized super-resolution 3D nanofabrication system.

• Design of diffractive optical elements for snapshot hyperspectral imaging in the long-wave infrared (Majumder): This project focuses on advancing Hyperspectral Imaging (HSI) technology in the long wave infrared (LWIR) spectrum, particularly for quality monitoring of microelectronics. Traditional HSI methods involve complex scan-and-stitch techniques, which are time-consuming and lack real-time capabilities. The innovation in this research project lies in the development of a snapshot HSI approach using diffractive optical elements and computational reconstruction. The project aims to design and fabricate a nanostructured diffractive filter array (DFA) optimized for LWIR imaging, assemble a snapshot LWIR HSI camera, and test its capabilities in identifying organic contaminants in electronic chips. The student involved will gain expertise in wave optics, inverse design optimization, fabrication techniques, imaging metrics, and machine learning. Key parameters to investigate include DFA feature size requirements, achievable spectral resolution, and the impact of fabrication errors. The desired outcome is a snapshot LWIR HSI camera for efficient quality inspection in the electronics industry.