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2024-11-18
PIER
Vol. 180, 79-87, 2024
download: 278
Some Selected Unsolved Problems in Classical and Quantum Electromagnetics
Weng Cho Chew , Boyuan Zhang and Jie Zhu
In this paper, we propose some suggestions for unsolved problems in classical and quantum electromagnetics. We aim to explain these problems in the simplest way possible. Some issues like the quantum computer may need a lot more work. The subject matter is interdisciplinary needing international collaboration in many different areas such as physics, math, engineering, and material science.
Some Selected Unsolved Problems in Classical and Quantum Electromagnetics
2024-11-15
PIER
Vol. 180, 61-78, 2024
download: 293
New Bounds on Spherical Antenna Bandwidth and Directivity: Updates to the Chu-Harrington Limits
Carl Pfeiffer and Bae-Ian Wu
The Chu circuit model provides the basis for analyzing the minimum radiation quality factor, Q, of a given spherical mode. However, examples of electrically large spherical radiators readily demonstrate that this Q limit has limitations in predicting bandwidth. Spherical mode radiation is reexamined, and an equivalent 1D transmission line model is derived that exactly models the fields. This model leads to a precise cutoff frequency of the spherical waveguide, which provides a clear boundary between propagating and evanescent fields. A new delineation of `stored' and `radiated' electromagnetic energy is postulated, which leads to a new definition of spherical mode Q. Next, attention is turned to the Harrington bound on the directivity-bandwidth tradeoff of an antenna with an arbitrary size. Harrington derived the maximum directivity for a specified number of spherical harmonics such that the Q is not `large'. Here, the method of Lagrange multipliers is used to quantify the maximum directivity for a given bandwidth. It is shown that optimally exciting all spherical harmonics (including n>ka) enables both larger directivity and bandwidth than Harrington's previous limit. While Chu and Harrington's analyses are generally good approximations for most situations, the new self-consistent theory that defines fundamental antenna limits leads to updated results.
New Bounds on Spherical Antenna Bandwidth and Directivity: Updates to the Chu-Harrington Limits
2024-09-23
PIER
Vol. 180, 55-60, 2024
download: 723
Topology-Optimized Plasmonic Nanoantenna for Efficient Single-Photon Extraction
Min Chen , Lian Shen , Yifei Hua , Zijian Qin and Huaping Wang
Quantum emitters coupled to plasmonic nanostructures can act as extremely bright single-photon sources. Interestingly, the mode volumes supported by the plasmonic nanostructures can be several orders of magnitude smaller than the cubic wavelength, which leads to dramatically enhanced light-matter interactions and drastically increased photon emission. However, the requirements of a small mode volume for emission speed-up are always contradictory with a sufficiently large mode volume for efficient extraction, especially in a single architecture. Here, we report the design of a topology-optimized plasmonic nanoantenna to alleviate the above limitation which could greatly enhance far-field photon extraction. The plasmonic nanoantenna is composed of an optimized gold pattern and a silicon nitride substrate, with a nanohole in the center of the gold pattern. Our design is based on density-based topology optimization and is inherently robust to dimensions and fabrication errors. As a result, the normalized extraction decay rate (γe⁄γ0) can reach 5.48 at a wavelength of 517 nm if an objective lens with a numerical aperture of 0.45 is utilized. Plasmonic nanostructures can be obtained with a small mode volume of about 5 × 10-21 m3, while emission speed-up could still be achieved. The proposed method to alleviate the contradiction of plasmonic mode volume could brighten the prospects for future integration of single-photon sources into photonic quantum networks and applications in quantum information science.
Topology-optimized Plasmonic Nanoantenna for Efficient Single-photon Extraction
2024-09-18
PIER
Vol. 180, 25-53, 2024
download: 868
Alternative Plasmonic Materials for Biochemical Sensing: a Review (Invited Review)
Leonid Yu. Beliaev , Andrei V. Lavrinenko and Osamu Takayama
Optical materials whose permittivity becomes negative for certain wavelength ranges, so-called plasmonic materials, have been widely used for biochemical sensing applications to detect a wide variety of analytes from chemical agents to protein biomarkers. Since many analytes are or contain nanoscale objects, they interact very weakly with light. Thus, light confinement is a key to improving sensitivity. Using metal or plasmonic nanostructures is a natural solution to confine light and boost light-matter interactions. As there are several different optical sensing schemes, such as refractometric sensing, fluorescence-labeled sensing, and vibrational spectroscopy, whose operating wavelength spans from ultraviolet to mid-infrared wavelength regions, some plasmonic materials are superior to others for certain wavelength regions. In this article, we review current progress on alternative plasmonic materials, other than gold, silver, and aluminum, used in biochemical sensing applications. We cover a wide variety of plasmonic material platforms, such as transparent conductive oxides, nitrides, doped semiconductors, polar materials, two-dimensional, van der Waals materials, transition metal dichalcogenides, and plasmonic materials for ultraviolet wavelengths.
Alternative Plasmonic Materials for Biochemical Sensing: A Review (Invited Review)
2024-09-04
PIER
Vol. 180, 13-24, 2024
download: 879
Measurement of Time-Range-Angle-Dependent Beam Patterns of Frequency Diverse Arrays (Invited)
Haochi Zhang , Lepeng Zhang , Shengheng Liu , Zihuan Mao , Yahui Ma , Pei Hang He , Wen Yi Cui , Yi Fei Huang , Qi Yang and Tie-Jun Cui
Frequency diverse arrays (FDAs) have drawn great attention because they can provide a time-range-angle-dependent beam pattern that has many promising potential applications in navigation and radar systems. However, due to the limitations of measurement systems, this attractive beam pattern has not been experimentally observed. Here, a far-field measurement system for the time-range-angle beam pattern of FDA is proposed by improving the existing near-field mapping system. Without loss of generality, two types of time-range-angle-dependent beam patterns for FDA systems with different frequency sets are observed using the proposed far-field measurement system. The high efficiency and accuracy of the proposed system is verified by good agreement between the measured and simulated results. This work marks significant progress toward the practical implementation and application of FDAs.
Measurement of Time-Range-Angle-Dependent Beam Patterns of Frequency Diverse Arrays (Invited)
2024-09-01
PIER
Vol. 180, 1-11, 2024
download: 881
Highly Accurate and Efficient 3D Implementations Empowered by Deep Neural Network for 2DLMs -Based Metamaterials
Naixing Feng , Huan Wang , Xuan Wang , Yuxian Zhang , Chao Qian , Zhixiang Huang and Hongsheng Chen
Streamlining the on-demand design of metamaterials, both forward and inverse, is highly demanded for unearthing complex light-matter interaction. Deep learning, as a popular data-driven method, has recently found to largely alleviate the time-consuming and experience-orientated features in widely-used numerical simulations. In this work, we propose a convolution-based deep neural network to implement the inverse design and spectral prediction of a broadband absorber, and deep neural network (DNN) not only achieves highly-accurate results based on small data samples, but also converts the one-dimensional (1D) spectral sequence into a 2D picture by employing the Markov transition field method so as to enhance the variability between spectra. From the perspective of a single spectral sample, spectral samples carry not enough information for neural network due to the constraints of the number of sampling points; from the perspective of multiple spectral samples, the gap between different spectral samples is very small, which can hinder the performance of the reverse design framework. Markov transition field method can enhance the performance of the model from those two aspects. The experimental results show that the final value of the soft required accuracy of the one-dimensional fully connected neural network model and the two-dimensional residual neural network model differ by nearly 1%, the final value of the soft accuracy of the one-dimensional residual neural network model is 97.6%. The final value of the two-dimensional residual neural network model model is 98.5%. The model utilises a data enhancement approach to improve model accuracy and also provides a key reference for designing two-dimensional layered materials (2DLMs) based metamaterials with on-demand properties before they are put into manufacturing.
Highly Accurate and Efficient 3D Implementations Empowered by Deep Neural Network for 2DLMs-based Metamaterials