Contact

  • Academic
    sdong15@stanford.edu
    University - Student Department: Electrical Engineering Position: Graduate
    University - Student Department: Management Science and Engineering Position: Graduate

Additional Info

  • Mail Code: 9505

All Publications

  • An Information-Theoretic Analysis for Thompson Sampling with Many Actions Dong, S., Van Roy, B., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018

    View details for Web of Science ID 000461823304019

  • Electrochemically Programmable Plasmonic Antennas. ACS nano Dong, S., Zhang, K., Yu, Z., Fan, J. A. 2016; 10 (7): 6716-6724

    Abstract

    Plasmonic antennas are building blocks in advanced nano-optical systems due to their ability to tailor optical response based on their geometry. We propose an electrochemical approach to program the optical properties of dipole antennas in a scalable, fast, and energy-efficient manner. These antennas comprise two arms, one serving as an anode and the other a cathode, separated by a solid electrolyte. As a voltage is applied between the antenna arms, a conductive filament either grows or dissolves within the electrolyte, modifying the antenna load. We probe the dynamics of stochastic filament formation and their effects on plasmonic mode programming using a combination of three-dimensional optical and electronic simulations. In particular, we identify device operation regimes in which the charge-transfer plasmon mode can be programmed to be "on" or "off." We also identify, unexpectedly, a strong correlation between DC filament resistance and charge-transfer plasmon mode frequency that is insensitive to the detailed filament morphology. We envision that the scalability of our electrochemical platform can generalize to large-area reconfigurable metamaterials and metasurfaces for on-chip and free-space applications.

    View details for DOI 10.1021/acsnano.6b02031

    View details for PubMedID 27328022