Electrical and Electronic Engineering - Research Publications

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    Mid-infrared spectral reconstruction with dielectric metasurfaces and dictionary learning
    Russell, BJ ; Cadusch, JJ ; Meng, J ; Wen, D ; Crozier, KB (Optica Publishing Group, 2022-05-15)
    Mid-infrared (MIR) spectroscopy has numerous industrial applications and is usually performed with Fourier-transform infrared (FTIR) spectrometers. While these work well for many purposes, there is currently much interest in alternative approaches that are smaller and lighter, i.e., MIR microspectrometers. Here we investigate all-dielectric metasurfaces as spectral filters for MIR microspectrometers. Two metasurface types are studied. For the first, we design, fabricate, and test a metasurface with a narrow and angularly tunable transmission stop band. We use it to reconstruct the transmission spectra of various materials. The second metasurface, investigated theoretically, possesses narrow passband features via symmetry-protected bound states in the continuum.
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    Compact Chemical Identifier Based on Plasmonic Metasurface Integrated with Microbolometer Array
    Meng, J ; Weston, L ; Balendhran, S ; Wen, D ; Cadusch, JJ ; Unnithan, RR ; Crozier, KB (WILEY-V C H VERLAG GMBH, 2022-04)
    Abstract The identification of chemicals from their mid‐infrared spectra has applications that include industrial production of chemicals, food production, pharmaceutical manufacturing, and environmental monitoring. This is generally done using laboratory benchtop tools, such as the Fourier transform infrared spectrometer. Although such systems offer high performance, alternative platforms offering reduced size, weight, and cost can enable a host of new applications, e.g. in consumer personal electronics. Here a compact microspectrometer platform for chemical identification, comprising a mid‐infrared metasurface integrated with a lightweight (≈1 g) and very small (≈1 cm3) microbolometer‐based thermal camera is experimentally demonstrated. A machine learning algorithm is trained to analyze the microspectrometer output and classify chemicals based on their mid‐infrared fingerprints. High accuracy identification of four liquid chemicals, concentration quantification of ethyl lactate in cyclohexane down to subpercentage levels, and the classification of food and drug samples is demonstrated.
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    Genetic optimization of mid-infrared filters for a machine learning chemical classifier.
    Tan, H ; Cadusch, JJ ; Meng, J ; Crozier, KB (Optica Publishing Group, 2022-05-23)
    Miniaturized mid-infrared spectrometers present opportunities for applications that range from health monitoring to agriculture. One approach combines arrays of spectral filters with infrared photodetectors, called filter-array detector-array (FADA) microspectrometers. A paper recently reported a FADA microspectrometer in tandem with machine learning for chemical identification. In that work, a FADA microspectrometer with 20 filters was assembled and tested. The filters were band-pass, or band-stop designs that evenly spanned the microspectrometer's operating wavelength range. However, given that a machine learning classifier can be trained on an arbitrary filter basis, it is not apparent that evenly spaced filters are optimal. Here, through simulations with noise, we use a genetic algorithm to optimize six bandpass filters to best identify liquid and gaseous chemicals. We report that the classifiers trained with the optimized filter sets outperform those trained with evenly spaced filter sets and those handpicked to target the absorption bands of the chemicals investigated.
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    Algorithmic Spectral Reconstruction Using Angularly Tuned Zero-Contrast Gratings
    Russell, B ; Meng, J ; Wen, D ; Cadusch, J ; Ye, M ; Crozier, K (IEEE, 2020)
    We experimentally demonstrate the algorithmic reconstruction of the infrared transmission spectrum of a polymer using a zero-contrast waveguide-grating metasurface as a filter. By changing the metasurface angle, a variety of filter functions are obtained.
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    Geometric Phase Metasurface Hologram for Optical Tractor Beam Generation
    Cadusch, J ; Wen, D ; Meng, J ; Crozier, KB (OSA & IEEE, 2020-01-01)
    We present a geometric phase silicon metasurface hologram design intended to produce a non-diffracting solenoid beam. Such optical beams have been shown to exert long range retrograde (i.e. toward source) optical forces on light-scattering particles.
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    Polarization State Generation and Detection by VCSELs with Integrated Metasurfaces
    Wen, D ; Meng, J ; Cadusch, J ; Crozier, KB (OSA & IEEE, 2020-01-01)
    We experimentally demonstrate vertical-cavity surface-emitting lasers (VCSEL) with integrated plasmonic and dielectric metasurfaces. The metasurfaces shape the polarization of the laser emission from the VCSELs and also enable them to serve as polarization-dependent photodetectors.
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    Material identification with a filter array-detector array infrared microspectrometer: Numerical study
    Meng, J ; Cadusch, JJ ; Crozier, KB (Optica Publishing Group, 2020-09-14)
    We design a plasmonic filter array for a filter array-detector array microspectrometer. We perform numerical experiments, including noise, that predict that this configuration would enable the identification of various materials via their infrared fingerprints.
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    All-silicon, optics-free microspectromer chip based on vertical waveguide array pixels
    Cadusch, JJ ; Meng, J ; Wen, D ; Crozier, KB (OSA & IEEE, 2021-01-01)
    We experimentally demonstrate a nanostructured silicon microspectrometer chip that consists of 144 pixels, each comprising an array of vertical waveguides of subwavelength period. We show that both broad- and narrow-band visible spectra can be reconstructed.
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    Material identification by plasmonic infrared microspectrometer employing machine learning
    Meng, J ; Weston, L ; Balendhran, S ; Wen, D ; Cadusch, JJ ; Unnithan, RR ; Crozier, KB (Optica Publishing Group, 2021-01-01)
    We demonstrate a microspectrometer comprising plasmonic filters integrated with an infrared camera. Blackbody light illuminates the material being studied, with transmitted light collected by the microspectrometer. The latter uses machine learning to identify the material.
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    Triple-helix tractor beam generation with a dielectric metasurface pancharatnam-berry phase hologram
    Cadusch, J ; Wen, D ; Meng, J ; Crozier, KB (Optica Publishing Group, 2021-01-01)
    We present a silicon-based Pancharatnam-Berry (PB) phase metasurface hologram that produces a triple-helix solenoid tractor beam from a Gaussian input beam. Our metasurface has a >90% diffraction efficiency and >75% transmission.