Applied Physics

From first-principles modeling to device designs.

Our research in this area uses physics to develop new technologies or solve an engineering problem, including optimal design of freeform optics, metamaterials, photonic and solid-state semiconductor devices; the modeling and analysis of electro-magnetic systems and studies on superconductivity and magnets.

  • Researchers

  • News & Events

    •  EVENT   Prof. Melanie Zeilinger of ETH to give keynote at MERL's Virtual Open House
      Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
      Speaker: Prof. Melanie Zeilinger, ETH
      Location: Virtual Event
      Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
      Brief
      • MERL is excited to announce the second keynote speaker for our Virtual Open House 2021:
        Prof. Melanie Zeilinger from ETH .

        Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

        Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Zeilinger's talk is scheduled for 3:15pm - 3:45pm (EST).

        Registration: https://mailchi.mp/merl/merlvoh2021

        Keynote Title: Control Meets Learning - On Performance, Safety and User Interaction

        Abstract: With increasing sensing and communication capabilities, physical systems today are becoming one of the largest generators of data, making learning a central component of autonomous control systems. While this paradigm shift offers tremendous opportunities to address new levels of system complexity, variability and user interaction, it also raises fundamental questions of learning in a closed-loop dynamical control system. In this talk, I will present some of our recent results showing how even safety-critical systems can leverage the potential of data. I will first briefly present concepts for using learning for automatic controller design and for a new safety framework that can equip any learning-based controller with safety guarantees. The second part will then discuss how expert and user information can be utilized to optimize system performance, where I will particularly highlight an approach developed together with MERL for personalizing the motion planning in autonomous driving to the individual driving style of a passenger.
    •  
    •  EVENT   Prof. Ashok Veeraraghavan of Rice University to give keynote at MERL's Virtual Open House
      Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
      Speaker: Prof. Ashok Veeraraghavan, Rice University
      Location: Virtual Event
      Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
      Brief
      • MERL is excited to announce the first keynote speaker for our Virtual Open House 2021:
        Prof. Ashok Veeraraghavan from Rice University.

        Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

        Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Veeraraghavan's talk is scheduled for 1:15pm - 1:45pm (EST).

        Registration: https://mailchi.mp/merl/merlvoh2021

        Keynote Title: Computational Imaging: Beyond the limits imposed by lenses.

        Abstract: The lens has long been a central element of cameras, since its early use in the mid-nineteenth century by Niepce, Talbot, and Daguerre. The role of the lens, from the Daguerrotype to modern digital cameras, is to refract light to achieve a one-to-one mapping between a point in the scene and a point on the sensor. This effect enables the sensor to compute a particular two-dimensional (2D) integral of the incident 4D light-field. We propose a radical departure from this practice and the many limitations it imposes. In the talk we focus on two inter-related research projects that attempt to go beyond lens-based imaging.

        First, we discuss our lab’s recent efforts to build flat, extremely thin imaging devices by replacing the lens in a conventional camera with an amplitude mask and computational reconstruction algorithms. These lensless cameras, called FlatCams can be less than a millimeter in thickness and enable applications where size, weight, thickness or cost are the driving factors. Second, we discuss high-resolution, long-distance imaging using Fourier Ptychography, where the need for a large aperture aberration corrected lens is replaced by a camera array and associated phase retrieval algorithms resulting again in order of magnitude reductions in size, weight and cost. Finally, I will spend a few minutes discussing how the wholistic computational imaging approach can be used to create ultra-high-resolution wavefront sensors.
    •  

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  • Internships

    • SP1747: Learning for Inverse Problems

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that solve inverse problems in computational sensing that incorporate deep learning architectures for a variety of sensing applications. The project goal is to improve the performance and develop an analysis of algorithms used for inverse problems by incorporating new tools from machine learning and artificial intelligence. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, large-scale optimization, plug-and-play priors, learning-based modeling for imaging, learning theory for computational imaging. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible.

    • MD1715: Electric Motor Fault Analysis

      MERL is seeing a motivated and qualified individual to conduct research on electric machine fault analysis and detection. The ideal candidate should have solid background in electric machine theory, modeling, numerical analysis, operation, and fault detection techniques, including machine learning. Research experiences on modeling and analysis of electric machines and fault detection are required. Hands-on experience with permanent magnet motor design and analysis, and knowledge on machine learning are desirable. Senior Ph.D. students in related expertise are encouraged to apply. Start date for this internship is flexible.

    • SA1778: Metasurface optics design & optimization

      We are seeking a talented graduate student for a research project in metalens design optimization. Ideal applicants will have a strong mathematics/optimization background, experience with metasurface optics, and fluency in scientific programming. Background knowledge in machine learning, freeform metasurfaces, or polarometry is a plus, as is a working knowledge of any of the following tools: Lumerical, RWCA, ComSol, Matlab, pyTorch/scipy. Creativity and execution are more important than expertise.


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  • Recent Publications

    •  Teo, K.H., Zhang, Y., Chowdhury, N., Rakheja, S., Ma, R., Xie, Q., Yagyu, E., Yamanaka, K., Li, K., Palacios, T., "Emerging GaN technologies for power, RF, digital and quantum computing applications: recent advances and prospects", Journal of Applied Physics, DOI: 10.1063/​5.0061555, December 2021.
      BibTeX TR2022-002 PDF
      • @article{Teo2021dec,
      • author = {Teo, Koon Hoo and Zhang, Yuhao and Chowdhury, Nadim and Rakheja, Shaloo and Ma, Rui and Xie, Qingyun and Yagyu, Eiji and Yamanaka, Koji and Li, Kexin and Palacios, Tomas},
      • title = {Emerging GaN technologies for power, RF, digital and quantum computing applications: recent advances and prospects},
      • journal = {Journal of Applied Physics},
      • year = 2021,
      • month = dec,
      • doi = {10.1063/5.0061555},
      • url = {https://www.merl.com/publications/TR2022-002}
      • }
    •  Li, X., Kojima, K., Brand, M.E., "Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics", IEEE Photonics Conference (IPC), DOI: 10.1109/​IPC48725.2021.9593086, October 2021, pp. 1-2.
      BibTeX TR2021-140 PDF
      • @inproceedings{Li2021oct,
      • author = {Li, Xinhao and Kojima, Keisuke and Brand, Matthew E.},
      • title = {Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics},
      • booktitle = {IEEE Photonics Conference (IPC)},
      • year = 2021,
      • pages = {1--2},
      • month = oct,
      • doi = {10.1109/IPC48725.2021.9593086},
      • url = {https://www.merl.com/publications/TR2021-140}
      • }
    •  Wang, B., Shin, K.-H., Hidaka, Y., Kondo, S., Arita, H., Ito, K., "Analytical Magnetic Model for Variable-Flux Interior Permanent Magnet Synchronous Motors", IEEE Energy Conversion Congress and Exposition (ECCE), DOI: 10.1109/​ECCE47101.2021.9595341, October 2021, pp. 4142-4148.
      BibTeX TR2021-123 PDF
      • @inproceedings{Wang2021oct2,
      • author = {Wang, Bingnan and Shin, Kyung-Hun and Hidaka, Yuki and Kondo, Shota and Arita, Hideaki and Ito, Kazumasa},
      • title = {Analytical Magnetic Model for Variable-Flux Interior Permanent Magnet Synchronous Motors},
      • booktitle = {2021 IEEE Energy Conversion Congress and Exposition (ECCE)},
      • year = 2021,
      • pages = {4142--4148},
      • month = oct,
      • publisher = {IEEE},
      • doi = {10.1109/ECCE47101.2021.9595341},
      • url = {https://www.merl.com/publications/TR2021-123}
      • }
    •  Wang, B., Zhou, L., Wang, H., Lin, C., "Analytical Modeling and Design Optimization of a Vernier Permanent Magnet Motor", IEEE Energy Conversion Congress and Exposition (ECCE), DOI: 10.1109/​ECCE47101.2021.9595230, October 2021, pp. 4480-4485.
      BibTeX TR2021-124 PDF
      • @inproceedings{Wang2021oct3,
      • author = {Wang, Bingnan and Zhou, Lei and Wang, Hongyu and Lin, Chungwei},
      • title = {Analytical Modeling and Design Optimization of a Vernier Permanent Magnet Motor},
      • booktitle = {2021 IEEE Energy Conversion Congress and Exposition (ECCE)},
      • year = 2021,
      • pages = {4480--4485},
      • month = oct,
      • publisher = {IEEE},
      • doi = {10.1109/ECCE47101.2021.9595230},
      • url = {https://www.merl.com/publications/TR2021-124}
      • }
    •  Tanaka, R., Nabi, S., Nonaka, M., "Airflow Optimization for Room Air Conditioners", Building Simulation 2021 Conference, September 2021.
      BibTeX TR2021-106 PDF
      • @inproceedings{Tanaka2021sep,
      • author = {Tanaka, Ryuta and Nabi, Saleh and Nonaka, Mio},
      • title = {Airflow Optimization for Room Air Conditioners},
      • booktitle = {Building Simulation 2021 Conference},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-106}
      • }
    •  Li, K., Yagyu, E., Sato, H., Teo, K.H., Rakheja, S., "Compact modeling of gate leakage phenomenon in GaN HEMTs", IEEE Transactions on Electron Devices, DOI: 10.23919/​SISPAD49475.2020.9241666, June 2021.
      BibTeX TR2021-079 PDF
      • @article{Li2021jun,
      • author = {Li, Kexin and Yagyu, Eiji and Sato, Hisashi and Teo, Koon Hoo and Rakheja, Shaloo},
      • title = {Compact modeling of gate leakage phenomenon in GaN HEMTs},
      • journal = {IEEE Transactions on Electron Devices},
      • year = 2021,
      • month = jun,
      • doi = {10.23919/SISPAD49475.2020.9241666},
      • url = {https://www.merl.com/publications/TR2021-079}
      • }
    •  Zhou, L., Guo, F., Wang, H., Wang, B., "High-Torque Direct-Drive Machine with Combined Axial- and Radial-flux Out-runner Vernier Permanent Magnet Motor", International Electric Machine & Drives Conference (IEMDC), DOI: 10.1109/​IEMDC47953.2021.9449499, May 2021, pp. 1-8.
      BibTeX TR2021-050 PDF
      • @inproceedings{Zhou2021may,
      • author = {Zhou, Lei and Guo, Feng and Wang, Hongyu and Wang, Bingnan},
      • title = {High-Torque Direct-Drive Machine with Combined Axial- and Radial-flux Out-runner Vernier Permanent Magnet Motor},
      • booktitle = {2021 IEEE International Electric Machines Drives Conference (IEMDC)},
      • year = 2021,
      • pages = {1--8},
      • month = may,
      • publisher = {IEEE},
      • doi = {10.1109/IEMDC47953.2021.9449499},
      • url = {https://www.merl.com/publications/TR2021-050}
      • }
    •  Zhou, L., Wang, B., Lin, C., Miyoshi, M., Inoue, H., "Static Eccentricity Fault Detection for PSH-type Induction Motors Considering High-order Air Gap Permeance Harmonics", International Electric Machine & Drives Conference (IEMDC), DOI: 10.1109/​IEMDC47953.2021.9449496, May 2021, pp. 1-7.
      BibTeX TR2021-051 PDF
      • @inproceedings{Zhou2021may2,
      • author = {Zhou, Lei and Wang, Bingnan and Lin, Chungwei and Miyoshi, Masahito and Inoue, hiroshi},
      • title = {Static Eccentricity Fault Detection for PSH-type Induction Motors Considering High-order Air Gap Permeance Harmonics},
      • booktitle = {2021 IEEE International Electric Machines Drives Conference (IEMDC)},
      • year = 2021,
      • pages = {1--7},
      • month = may,
      • publisher = {IEEE},
      • doi = {10.1109/IEMDC47953.2021.9449496},
      • url = {https://www.merl.com/publications/TR2021-051}
      • }
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  • Videos