47,810 research outputs found
Dataset for the journal article 'Photonic Metamaterial Analogue of a Continuous Time Crystal'
No full textExperimental data presented in the paper published in Nature Physics:
Photonic metamaterial analogue of a continuous time crystal, Tongjun Liu, Jun-Yu. Ou, Kevin F. MacDonald, Nikolay I. Zheludev, Nat. Phys.
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Random access actuation of nanowire grid metamaterial
Get PDFDataset supporting:
Cencillo Abad, Pablo, Ou, Jun-Yu, Plum, Eric, Valente, João and Zheludev, Nikolay (2016) Random access actuation of nanowire grid metamaterial. Nanotechnology, 27, 485206</span
Dataset for Visualization of Sub-atomic Movements in Nanostructures
No full textExperimental data presented in the paper published in Nano Letters:
Tongjun Liu, Jun-Yu Ou, Eric Plum, Kevin F. MacDonald, and Nikolay I. Zheludev (2021), 'Visualization of Subatomic Movements in Nanostructures', NANO Letters,
https://doi.org/10.1021/acs.nanolett.1c02644</span
Coherent selection of invisible high-order electromagnetic excitations
Get PDFResearch data for Coherent selection of invisible high-order electromagnetic excitations, Ming Lun Tseng, Xu Fang, Vassili Savinov, Pin Chieh Wu, Jun-Yu Ou, Nikolay I. Zheludev, and Din Ping Tsai, Scientific Reports 7, 44488(2017)</span
Dataset for Optical addressing of nanomechanical metamaterials with subwavelength resolution
No full textDataset supports:
Ou, J., Plum, E., Zheludev, N. (2018). Optical addressing of nanomechanical metamaterials with subwavelength resolution. Applied Physics Letters.</span
Reconfigurable photonic metamaterials
No full textThis thesis reports on the development of a new class of switchable nanostructured photonic metamaterials, Reconfigurable Photonic Metamaterials (RPMs). Over the last decade, fascinating material properties including negative refraction, optical magnetism, invisibility, asymmetric transmission, perfect lenses and many more were demonstrated in metamaterials. Inspired by pioneering work on micro-electro mechanical metamaterials for the terahertz and microwave spectral regions with feature sizes from millimeters to tens and hundreds microns, I develop reconfigurable photonic metamaterials for the optical spectral range that have sub-micron meta molecules and nanoscale design features.In particular, for the first time I developed: Novel fabrication processes for manufacturing reconfigurable photonic metamaterials based on the platform of elastic silicon nitride membranes using focused ion beam lithography, film deposition, precise alignment, etching and annealing techniques. These fabrication techniques have allowed the manufacturing of a wide range of reconfigurable metamaterials consisting of bi-layer (gold/silicon nitride) or tri-layer (gold/silicon nitride/gold) structured membranes suitable for applications as plasmonic RPMs.Novel RPMs tunable by ambient temperature that operate in the optical and near infrared parts of the spectrum. With such metamaterials exploiting the change in plasmonic response due to differential thermal expansion in bimorph nanostructures I have demonstrated 50% changes in optical transmission at the wavelength of 1735 nm when the temperature is ramped from 76 K to 270 K.Novel RPMs operating in the near-infrared part of the spectrum that can be controlled by electric signals. These types of metamaterials harness electrostatic forces on the nanoscale and offer up to 20 MHz modulation bandwidth. At a threshold level of stimulation these metamaterials exhibit non-volatile switching with up to 250% transmission change. As a part of this research I developed a characterization technique that allows imaging and recording of the electrostatic switching under a scanning electron microscope.Novel optically controlled RPMs exploiting near-field optical forces induced by light and optical heating for reconfiguration. Such metamaterials show a new type of optomechanical nonlinearity leading to intensity-dependent transmission that exceeds the cubic nonlinearity of GaAs by seven orders of magnitude. Using CW diode lasers operating at telecommunication wavelengths of 1.3 µm and 1.55 µm I have demonstrated cross-wavelength optical modulation with amplitude of about 1 % that can be achieved at only about 1 mW of average power of the control beam. I also developed the numerical analysis of thermo-opto-mechanical properties of the structures and calculated eigenmodes and cooling constants of the RPMs under modulated laser irradiation.Overall, the development of reconfigurable photonic metamaterials provides a new and flexible platform for the control of metamaterial properties "on demand". Such metamaterials can find applications in sensors, tunable spectral filters, switches, modulators, programmable transformation optics devices and any other application where tunable optical properties are required
Optimization of metamaterials and metamaterial-microcavity based on deep neural networks
No full textComputational inverse-design and forward prediction approaches provide promising pathways for on-demand nanophotonics. Here, we use a deep-learning method to optimize the design of split-ring metamaterials and metamaterial-microcavities. Once the deep neural network is trained, it can predict the optical response of the split-ring metamaterial in a second which is much faster than conventional simulation methods. The pretrained neural network can also be used for the inverse design of split-ring metamaterials and metamaterial-microcavities. We use this method for the design of the metamaterial-microcavity with the absorptance peak at 1310 nm. Experimental results verified that the deep-learning method is a fast, robust, and accurate method for designing metamaterials with complex nanostructures.</p
Dataset to support the journal article 'Optimization of metamaterials and metamaterial-microcavity based on deep neural networks'
No full textThis dataset contains: Data supporting the figures in the article in Excel format</span
Method for optimising the performance of PML in anchor-loss limited model via COMSOL
No full textPerfectly matched layer has been used for solving anchor-loss limited quality factor in the Micro electromechanical systems. However, setting up a well-behaved perfectly matched layer requires users to change the parameters of a perfectly matched layer to give correct results, while the current existing methods for choosing the right parameters are vague and lack theoretical support. Based on the mathematical theory of perfectly matched layer and simulation results of a beam structure's quality factor, this paper proposes a method for choosing the parameter to optimise the performance of perfectly matched layer in COMSOL. The accuracy of the proposed method is proved by matching the effect of substrate height on beam's quality factor with theory prediction. The author also studies the effect of beam height and beam width on the quality factor of the beam. The results demonstrate that simulated quality factors are in agreement with analytical values when the ratio of height over length is small but will show great divergence when height equals the length. This trend can be observed for the beam width as well. Especially for larger ratio of beam width over beam length, instead of decreasing monotonously as analytical equitation would expect, the simulated quality factor will converge into a stable value of 1700, which matches the result of two-dimensional model for the same beam structure. This means that a three-dimensional model has to be used for estimating the quality factor of a beam structure
Dataset to support the journal article '2D super-resolution metrology based on superoscillatory light'
No full textThis dataset is supporting the publication by Yu Wang et al, (2024)
"2D Super-resolution Metrology Based on Superoscillatory Light" in Advanced Science.
This dataset contains data supporting the figures in the article in Excel format:
Fig. 2 data.xlsx
Fig. 3 data.xlsx
Fig. 4 data.xlsx
This work is supported by the UK Engineering and Physical Science Research Council (grants EP/T02643X/1, EP/X03495X/1, EP/X041166/1), the Royal Society (project number RG\R2\232531), the Singapore National Research Foundation (grant No. NRF-CRP23-2019-0006), the Singapore Ministry of Education (grant MOE2016-T3-1-006), and the China Scholarship Council (202006150050; Y. Wang).</span
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