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Publications
Skyler P Selvin; Majid Esfandyarpour; Anqi Ji; Yan Joe Lee; Colin Yule; Jung-Hwan Song; Mohammad Taghinejad; Mark L Brongersma
Acoustic wave modulation of gap plasmon cavities Journal Article
In: Science, vol. 389, iss. 6759, pp. 516-520, 2025.
@article{selvin2025acoustic,
title = {Acoustic wave modulation of gap plasmon cavities},
author = {Skyler P Selvin and Majid Esfandyarpour and Anqi Ji and Yan Joe Lee and Colin Yule and Jung-Hwan Song and Mohammad Taghinejad and Mark L Brongersma},
url = {https://brongersma.stanford.edu/wp-content/uploads/2025/08/science.adv1728-2.pdf
https://www.science.org/stoken/author-tokens/ST-2800/full},
doi = {10.1126/science.adv1728},
year = {2025},
date = {2025-07-31},
urldate = {2025-07-31},
journal = {Science},
volume = {389},
issue = {6759},
pages = {516-520},
abstract = {The important role of metallic nanostructures in nanophotonics will expand if ways to electrically manipulate their optical resonances at high speed can be identified. We capitalized on electrically driven surface acoustic waves and the extreme light concentration afforded by gap plasmons to achieve this goal. We placed gold nanoparticles in a particle-on-mirror configuration with a few-nanometer-thick, compressible polymer spacer. Surface acoustic waves were then used to tune light scattering at speeds approaching the gigahertz regime. We observed evidence that the surface acoustic waves produced mechanical deformations in the polymer and that ensuing nonlinear mechanical dynamics led to unexpectedly large levels of strain and spectral tuning. Our approach provides a design strategy for electrically driven dynamic metasurfaces and fundamental explorations of high-frequency, polymer dynamics in ultraconfined geometries.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The important role of metallic nanostructures in nanophotonics will expand if ways to electrically manipulate their optical resonances at high speed can be identified. We capitalized on electrically driven surface acoustic waves and the extreme light concentration afforded by gap plasmons to achieve this goal. We placed gold nanoparticles in a particle-on-mirror configuration with a few-nanometer-thick, compressible polymer spacer. Surface acoustic waves were then used to tune light scattering at speeds approaching the gigahertz regime. We observed evidence that the surface acoustic waves produced mechanical deformations in the polymer and that ensuing nonlinear mechanical dynamics led to unexpectedly large levels of strain and spectral tuning. Our approach provides a design strategy for electrically driven dynamic metasurfaces and fundamental explorations of high-frequency, polymer dynamics in ultraconfined geometries.
Siddharth Doshi; Anqi Ji; Ali I Mahdi; Scott T Keene; Skyler P Selvin; Philippe Lalanne; Eric A Appel; Nicholas A Melosh; Mark L Brongersma
Electrochemically mutable soft metasurfaces Journal Article
In: Nature Materials, vol. 24, iss. 2, pp. 205-211, 2024.
@article{doshi2024electrochemically,
title = {Electrochemically mutable soft metasurfaces},
author = {Siddharth Doshi and Anqi Ji and Ali I Mahdi and Scott T Keene and Skyler P Selvin and Philippe Lalanne and Eric A Appel and Nicholas A Melosh and Mark L Brongersma},
doi = {10.1038/s41563-024-02042-4},
year = {2024},
date = {2024-11-13},
journal = {Nature Materials},
volume = {24},
issue = {2},
pages = {205-211},
abstract = {Active optical metasurfaces, capable of dynamically manipulating light in ultrathin form factors, enable novel interfaces between humans and technology. In such interfaces, soft materials bring many advantages based on their flexibility, compliance and large stimulus-driven responses. Here, we create electrochemically mutable, soft metasurfaces that capitalize on the swelling of soft conducting polymers to alter the shape and associated resonant response of metasurface elements. Such geometric tuning overcomes the typical trade-off between achieving substantial tuning and low optical loss that is intrinsic to dynamic metasurfaces relying on index tuning of materials. Using the commercial polymer PEDOT:PSS, we demonstrate dynamic, high-resolution colour tuning and high-diffraction-efficiency (\>19%) beam-steering devices that operate at CMOS-compatible voltages (~1.5 V). These results highlight how the deformability of soft materials can enable a class of high-performance metasurfaces that are suitable for body-worn technologies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Active optical metasurfaces, capable of dynamically manipulating light in ultrathin form factors, enable novel interfaces between humans and technology. In such interfaces, soft materials bring many advantages based on their flexibility, compliance and large stimulus-driven responses. Here, we create electrochemically mutable, soft metasurfaces that capitalize on the swelling of soft conducting polymers to alter the shape and associated resonant response of metasurface elements. Such geometric tuning overcomes the typical trade-off between achieving substantial tuning and low optical loss that is intrinsic to dynamic metasurfaces relying on index tuning of materials. Using the commercial polymer PEDOT:PSS, we demonstrate dynamic, high-resolution colour tuning and high-diffraction-efficiency (>19%) beam-steering devices that operate at CMOS-compatible voltages (~1.5 V). These results highlight how the deformability of soft materials can enable a class of high-performance metasurfaces that are suitable for body-worn technologies.
Sulagna Sarkar; Anqi Ji; Zachary Jermain; Robert Lipton; Mark L Brongersma; Kaushik Dayal; Hae Young Noh
Physics‐Informed Machine Learning for Inverse Design of Optical Metamaterials Journal Article
In: Advanced Photonics Research, pp. 2300158, 2023.
@article{sarkar2023physics,
title = {Physics‐Informed Machine Learning for Inverse Design of Optical Metamaterials},
author = {Sulagna Sarkar and Anqi Ji and Zachary Jermain and Robert Lipton and Mark L Brongersma and Kaushik Dayal and Hae Young Noh},
doi = {10.1002/adpr.202300158},
year = {2023},
date = {2023-10-11},
urldate = {2023-10-11},
journal = {Advanced Photonics Research},
pages = {2300158},
abstract = {Optical metamaterials manipulate light through various confinement and scattering processes, offering unique advantages like high performance, small form factor and easy integration with semiconductor devices. However, designing metasurfaces with suitable optical responses for complex metamaterial systems remains challenging due to the exponentially growing computation cost and the ill-posed nature of inverse problems. To expedite the computation for the inverse design of metasurfaces, a physics-informed deep learning (DL) framework is used. A tandem DL architecture with physics-based learning is used to select designs that are scientifically consistent, have low error in design prediction, and accurate reconstruction of optical responses. The authors focus on the inverse design of a representative plasmonic device and consider the prediction of design for the optical response of a single wavelength incident or a spectrum of wavelength in the visible light range. The physics-based constraint is derived from solving the electromagnetic wave equations for a simplified homogenized model. The model converges with an accuracy up to 97% for inverse design prediction with the optical response for the visible light spectrum as input, and up to 96% for optical response of single wavelength of light as input, with optical response reconstruction accuracy of 99%.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Optical metamaterials manipulate light through various confinement and scattering processes, offering unique advantages like high performance, small form factor and easy integration with semiconductor devices. However, designing metasurfaces with suitable optical responses for complex metamaterial systems remains challenging due to the exponentially growing computation cost and the ill-posed nature of inverse problems. To expedite the computation for the inverse design of metasurfaces, a physics-informed deep learning (DL) framework is used. A tandem DL architecture with physics-based learning is used to select designs that are scientifically consistent, have low error in design prediction, and accurate reconstruction of optical responses. The authors focus on the inverse design of a representative plasmonic device and consider the prediction of design for the optical response of a single wavelength incident or a spectrum of wavelength in the visible light range. The physics-based constraint is derived from solving the electromagnetic wave equations for a simplified homogenized model. The model converges with an accuracy up to 97% for inverse design prediction with the optical response for the visible light spectrum as input, and up to 96% for optical response of single wavelength of light as input, with optical response reconstruction accuracy of 99%.
Anqi Ji; Jung-Hwan Song; Qitong Li; Fenghao Xu; Ching-Ting Tsai; Richard C Tiberio; Bianxiao Cui; Philippe Lalanne; Pieter G Kik; David AB Miller; Mark L Brongersma
Quantitative phase contrast imaging with a nonlocal angle-selective metasurface Journal Article
In: Nature Communications, vol. 13, iss. 1, pp. 1-7, 2022.
@article{ji2022quantitative,
title = {Quantitative phase contrast imaging with a nonlocal angle-selective metasurface},
author = {Anqi Ji and Jung-Hwan Song and Qitong Li and Fenghao Xu and Ching-Ting Tsai and Richard C Tiberio and Bianxiao Cui and Philippe Lalanne and Pieter G Kik and David AB Miller and Mark L Brongersma},
year = {2022},
date = {2022-12-21},
urldate = {2022-12-21},
journal = {Nature Communications},
volume = {13},
issue = {1},
pages = {1-7},
abstract = {Phase contrast microscopy has played a central role in the development of modern biology, geology, and nanotechnology. It can visualize the structure of translucent objects that remains hidden in regular optical microscopes. The optical layout of a phase contrast microscope is based on a 4 f image processing setup and has essentially remained unchanged since its invention by Zernike in the early 1930s. Here, we propose a conceptually new approach to phase contrast imaging that harnesses the non-local optical response of a guided-mode-resonator metasurface. We highlight its benefits and demonstrate the imaging of various phase objects, including biological cells, polymeric nanostructures, and transparent metasurfaces. Our results showcase that the addition of this non-local metasurface to a conventional microscope enables quantitative phase contrast imaging with a 0.02π phase accuracy. At a high level, this work adds to the growing body of research aimed at the use of metasurfaces for analog optical computing.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Phase contrast microscopy has played a central role in the development of modern biology, geology, and nanotechnology. It can visualize the structure of translucent objects that remains hidden in regular optical microscopes. The optical layout of a phase contrast microscope is based on a 4 f image processing setup and has essentially remained unchanged since its invention by Zernike in the early 1930s. Here, we propose a conceptually new approach to phase contrast imaging that harnesses the non-local optical response of a guided-mode-resonator metasurface. We highlight its benefits and demonstrate the imaging of various phase objects, including biological cells, polymeric nanostructures, and transparent metasurfaces. Our results showcase that the addition of this non-local metasurface to a conventional microscope enables quantitative phase contrast imaging with a 0.02π phase accuracy. At a high level, this work adds to the growing body of research aimed at the use of metasurfaces for analog optical computing.
Anqi Ji
Quantitative Phase Contrast Imaging with A Nonlocal Angle-Selective Metasurface PhD Thesis
Stanford University, 2022.
@phdthesis{anqijithesis,
title = {Quantitative Phase Contrast Imaging with A Nonlocal Angle-Selective Metasurface},
author = {Anqi Ji},
url = {http://purl.stanford.edu/rk000mv7920},
year = {2022},
date = {2022-08-28},
urldate = {2022-08-28},
address = {Stanford, CA, US},
school = {Stanford University},
abstract = {Phase contrast microscopy has played a central role in the development of modern biology, geology, and nanotechnology. It can visualize the structure of translucent objects that remains hidden in regular optical microscopes. The optical layout of a phase contrast microscope is based on a 4f image processing setup and has essentially remained unchanged since its invention by Zernike in the early 1930s. Here, we propose a conceptually new approach to phase contrast imaging that harnesses the non-local optical response of a guided-mode-resonator metasurface. We highlight its benefits and demonstrate the imaging of various phase objects, including biological cells, polymeric nanostructures, and transparent metasurfaces. Our results showcase that the addition of this non-local metasurface to a conventional microscope enables quantitative phase contrast imaging with a 0.02π phase accuracy. At a high level, this work adds to the growing body of research aimed at the use of metasurfaces for analog optical computing.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Phase contrast microscopy has played a central role in the development of modern biology, geology, and nanotechnology. It can visualize the structure of translucent objects that remains hidden in regular optical microscopes. The optical layout of a phase contrast microscope is based on a 4f image processing setup and has essentially remained unchanged since its invention by Zernike in the early 1930s. Here, we propose a conceptually new approach to phase contrast imaging that harnesses the non-local optical response of a guided-mode-resonator metasurface. We highlight its benefits and demonstrate the imaging of various phase objects, including biological cells, polymeric nanostructures, and transparent metasurfaces. Our results showcase that the addition of this non-local metasurface to a conventional microscope enables quantitative phase contrast imaging with a 0.02π phase accuracy. At a high level, this work adds to the growing body of research aimed at the use of metasurfaces for analog optical computing.
