Electronic and Photonic Devices

Pursuing theoretical and experimental research for next generation devices.

We explore various device technologies, material science and device architectures to dramatically improve power and RF device performance to achieve higher efficiency, high linearity and much wider frequency band. We develop novel photonic integrated circuits to improve performance and reduce cost in optical communications applications.

  • Researchers

  • Awards


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  • News & Events

    •  NEWS   Rui Ma gives invited IEEE course on the latest insights in advanced radio frequency amplifiers
      Date: October 13, 2020
      Where: online
      MERL Contact: Rui Ma
      Research Areas: Communications, Electronic and Photonic Devices
      Brief
      • MERL researcher Dr. Rui Ma is invited to give a talk on the latest insights on RF power Amplifier design, which is one of series invited courses organized by IEEE Boston Section.

        Dr. Ma is addressing the advancement of digital radio transmitter based on enabling technology of GaN for next generation wireless communications.

        This six week lecture series is intended to give a broad overview of state-of-the-art RF PA techniques with practical aspects for working professionals together with students for future RF PA designers, from fundamentals to applications. It begins with a review of RF power amplifier concepts then teaches handset PA design techniques, issues and solutions faced with designing RF PAs for mobile applications. It also discusses high efficiency amplifier structures with different classes of operation, and other architectures. A high linearity techniques lecture with behavioral modelling will follow. GaAs/GaN MMIC level millimeter-wave amplifier design tutorials and techniques will be lectured including foundry/technology selection, loadpull, loadline analysis and simulations with EDA tools. Lastly, digital perspective transmitters will be presented using GaN technology together with FPGA and ASICs.
    •  
    •  TALK   Microwaving a Biological Cell Alive ‒ Broadband Label-Free Noninvasive Electrical Characterization of a Live Cell
      Date & Time: Tuesday, August 25, 2020; 11:00 AM
      Speaker: Prof. James Hwang, Cornell University
      MERL Host: Rui Ma
      Research Areas: Applied Physics, Electronic and Photonic Devices
      Brief
      • Microwave is not just for cooking, smart cars, or mobile phones. We can take advantage of the wide electromagnetic spectrum to do wonderful things that are more vital to our lives. For example, microwave ablation of cancer tumor is already in wide use, and microwave remote monitoring of vital signs is becoming more important as the population ages. This talk will focus on a biomedical use of microwave at the single-cell level. At low power, microwave can readily penetrate a cell membrane to interrogate what is inside a cell, without cooking it or otherwise hurting it. It is currently the fastest, most compact, and least costly way to tell whether a cell is alive or dead. On the other hand, at higher power but lower frequency, the electromagnetic signal can interact strongly with the cell membrane to drill temporary holes of nanometer size. The nanopores allow drugs to diffuse into the cell and, based on the reaction of the cell, individualized medicine can be developed and drug development can be sped up in general. Conversely, the nanopores allow strands of DNA molecules to be pulled out of the cell without killing it, which can speed up genetic engineering. Lastly, by changing both the power and frequency of the signal, we can have either positive or negative dielectrophoresis effects, which we have used to coerce a live cell to the examination table of Dr. Microwave, then usher it out after examination. These interesting uses of microwave and the resulted fundamental knowledge about biological cells will be explored in the talk.
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  • Internships

    • MD1370: Machine Learning based DPD for Power Amplifier

      MERL is looking for a talented intern to work on the next generation Digital-predistortion algorithms for power amplifier linearization such as 5G. The development of a DPD system involves aspects of signal processing and statistical algorithm design, RF components and instrumentation, digital hardware and software. It is therefore both a challenging and intellectually rewarding experience. This will involve MATLAB coding, interfacing to test equipment such as power sources, signal generators and analyzers and construction and calibration of RF component assemblies. The ideal candidate should have knowledge and experience in adaptive signal processing, machine learning, and radio communication. Good practical laboratory skills are needed. RF semiconductor devices and circuit knowledge is a plus. Duration is 3 to 6 months.


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  • Recent Publications

    •  Kojima, K., Tang, Y., Koike-Akino, T., Wang, Y., Jha, D., Parsons, K., TaherSima, M., Sang, F., Klamkin, J., Qi, M., "Inverse Design of Nanophotonic Devices using Deep Neural Networks", Asia Communications and Photonics Conference (ACP), September 2020.
      BibTeX TR2020-130 PDF
      • @inproceedings{Kojima2020sep,
      • author = {Kojima, Keisuke and Tang, Yingheng and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh and Parsons, Kieran and TaherSima, Mohammad and Sang, Fengqiao and Klamkin, Jonathan and Qi, Minghao},
      • title = {Inverse Design of Nanophotonic Devices using Deep Neural Networks},
      • booktitle = {Asia Communications and Photonics Conference (ACP)},
      • year = 2020,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2020-130}
      • }
    •  Skvortcov, P., Phillips, I., Forysiak, W., Koike-Akino, T., Kojima, K., Parsons, K., Millar, D.S., "Nonlinearity Tolerant LUT-based Probabilistic Shaping for Extended-Reach Single-Span Links", IEEE Photonics Technology Letters, DOI: 10.1109/LPT.2020.3006737, Vol. 32, No. 16, pp. 967-970, July 2020.
      BibTeX TR2020-107 PDF
      • @article{Skvortcov2020jul,
      • author = {Skvortcov, Pavel and Phillips, Ian and Forysiak, Wladek and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran and Millar, David S.},
      • title = {Nonlinearity Tolerant LUT-based Probabilistic Shaping for Extended-Reach Single-Span Links},
      • journal = {IEEE Photonics Technology Letters},
      • year = 2020,
      • volume = 32,
      • number = 16,
      • pages = {967--970},
      • month = jul,
      • doi = {10.1109/LPT.2020.3006737},
      • issn = {1941-0174},
      • url = {https://www.merl.com/publications/TR2020-107}
      • }
    •  Komatsuszaki, Y., Ma, R., Sakata, S., Nakatani, K., Shinjo, S., "A Dual-Mode Bias Circuit Enabled GaN Doherty Amplifier Operating in 0.85-2.05GHz and 2.4-4.2GHz", IEEE International Microwave Symposium (IMS), June 2020.
      BibTeX TR2020-080 PDF
      • @inproceedings{Komatsuszaki2020jun,
      • author = {Komatsuszaki, Yuji and Ma, Rui and Sakata, Shuichi and Nakatani, Keigo and Shinjo, Shintaro},
      • title = {A Dual-Mode Bias Circuit Enabled GaN Doherty Amplifier Operating in 0.85-2.05GHz and 2.4-4.2GHz},
      • booktitle = {IEEE International Microwave Symposium (IMS)},
      • year = 2020,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2020-080}
      • }
    •  Sakata, S., Kato, K., Teranishi, E., Sugitani, T., Ma, R., Chuang, K., Wu, Y., Fukunaga, K., Komatsuszaki, Y., Kenichi, H., Yamanaka, K., Shinjo, S., "A Fully-Integrated GaN Doherty Power Amplifier Module with a Compact Frequency-Dependent Compensation Circuit for 5G massive MIMO Base Stations", IEEE International Microwave Symposium (IMS), June 2020.
      BibTeX TR2020-077 PDF
      • @inproceedings{Sakata2020jun,
      • author = {Sakata, Shuichi and Kato, Katsuya and Teranishi, Eri and Sugitani, Takumi and Ma, Rui and Chuang, Kevin and Wu, Yuchen and Fukunaga, Kei and Komatsuszaki, Yuji and Kenichi, Horiguchi and Yamanaka, Koji and Shinjo, Shintaro},
      • title = {A Fully-Integrated GaN Doherty Power Amplifier Module with a Compact Frequency-Dependent Compensation Circuit for 5G massive MIMO Base Stations},
      • booktitle = {IEEE International Microwave Symposium (IMS)},
      • year = 2020,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2020-077}
      • }
    •  Sravan Kumar, P., Ma, R., "Design Considerations and FPGA Implementation of a Wideband All-Digital Transmit Beamformer with 50% Fractional Bandwidth", IEEE International Microwave Symposium (IMS), June 2020.
      BibTeX TR2020-078 PDF
      • @inproceedings{SravanKumar2020jun,
      • author = {Sravan Kumar, Pulipati and Ma, Rui},
      • title = {Design Considerations and FPGA Implementation of a Wideband All-Digital Transmit Beamformer with 50% Fractional Bandwidth},
      • booktitle = {IEEE International Microwave Symposium (IMS)},
      • year = 2020,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2020-078}
      • }
    •  Fehenberger, T., Millar, D.S., Koike-Akino, T., Kojima, K., Parsons, K., Griesser, H., "Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables", IEEE Journal of Lightwave Technology, DOI: 10.1109/JLT.2020.2987210, Vol. 38, No. 10, pp. 2825-2833, April 2020.
      BibTeX TR2020-051 PDF
      • @article{Fehenberger2020apr2,
      • author = {Fehenberger, Tobias and Millar, David S. and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran and Griesser, Helmut},
      • title = {Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables},
      • journal = {IEEE Journal of Lightwave Technology},
      • year = 2020,
      • volume = 38,
      • number = 10,
      • pages = {2825--2833},
      • month = apr,
      • doi = {10.1109/JLT.2020.2987210},
      • issn = {1558-2213},
      • url = {https://www.merl.com/publications/TR2020-051}
      • }
    •  Zhang, S., Zhang, S., Wang, B., Habetler, T., "Deep Learning Algorithms for Bearing Fault Diagnostics – A Comprehensive Review", IEEE Access, DOI: 10.1109/ACCESS.2020.2972859, Vol. 8, pp. 29857-29881, March 2020.
      BibTeX TR2020-034 PDF
      • @article{Zhang2020mar,
      • author = {Zhang, Shen and Zhang, Shibo and Wang, Bingnan and Habetler, Thomas},
      • title = {Deep Learning Algorithms for Bearing Fault Diagnostics – A Comprehensive Review},
      • journal = {IEEE Access},
      • year = 2020,
      • volume = 8,
      • pages = {29857--29881},
      • month = mar,
      • doi = {10.1109/ACCESS.2020.2972859},
      • issn = {2169-3536},
      • url = {https://www.merl.com/publications/TR2020-034}
      • }
    •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D., Tang, Y., Parsons, K., Sang, F., Klamkin, J., "Deep Neural Networks for Designing Integrated Photonics", Optical Fiber Communication Conference and Exposition (OFC), DOI: 10.1364/OFC.2020.Th1A.6, March 2020.
      BibTeX TR2020-057 PDF
      • @inproceedings{Kojima2020mar,
      • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh and Tang, Yingheng and Parsons, Kieran and Sang, Fengqiao and Klamkin, Jonathan},
      • title = {Deep Neural Networks for Designing Integrated Photonics},
      • booktitle = {Optical Fiber Communication Conference and Exposition (OFC)},
      • year = 2020,
      • month = mar,
      • publisher = {OSA},
      • doi = {10.1364/OFC.2020.Th1A.6},
      • isbn = {978-1-943580-71-2},
      • url = {https://www.merl.com/publications/TR2020-057}
      • }
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