School of Physics - Research Publications
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ItemNo Preview AvailableMid-Infrared Gas Classification Using a Bound State in the Continuum Metasurface and Machine Learning(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023-10-01)
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ItemNo Preview AvailableMid-infrared spectral reconstruction with dielectric metasurfaces and dictionary learning(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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ItemNo Preview AvailableCompact, Lightweight, and Filter-Free: An AII-Si Microspectrometer Chip for Visible Light Spectroscopy(AMER CHEMICAL SOC, 2022-02-16)
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ItemCompact Chemical Identifier Based on Plasmonic Metasurface Integrated with Microbolometer Array(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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ItemBroadband Multichannel Cylindrical Vector Beam Generation by a Single Metasurface(WILEY-V C H VERLAG GMBH, 2022-10)Abstract Beams with spatially‐varying polarization states have been the topic of much interest recently due to the unusual ways in which they can interact with matter. Cylindrical vector beams (CVBs) represent the most commonly used type and feature cylindrically‐symmetric polarization distributions. The optical systems employed thus far for their generation have usually only been able to produce a single CVB. To generate and observe multiple CVBs, bulky optical systems with stringent alignment tolerances have been needed. Here, a method to generate an array of CVBs using a single optical element, namely a transmission‐mode dielectric metasurface, is demonstrated. The incident light is split into an array of left and right‐handed circularly polarized vortex beams that superpose with a controllable phase difference. An array of CVBs with 12 channels over a broad wavelength range is experimentally demonstrated. This study's method produces a significant increase in the number of polarization channels compared to previous reports and solves the long‐standing challenge of unequal intensity distributions. It furthermore improves the flexibility of the vector field control by not only generating CVBs of different orders but also controlling their polarization rotation. This method may pave the way for applications in optical communications, laser machining, and optical trapping.
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ItemInfrared modulation via near-room-temperature phase transitions of vanadium oxides & core–shell composites(Royal Society of Chemistry (RSC), 2023)Vanadium oxides (VOx) are highly promising materials for heat retardant coatings, enabled by their insulator-to-metal phase transition (IMT). Currently, this IMT typically occurs at 68 °C, well above room temperature. Here, we develop a dopant-free approach to lower the IMT temperature to ∼40 °C enabling near-room temperature infrared modulation, by simple, solution phase synthesis. This is achieved by both controlling the stoichiometry of the metal oxide and by using a SiO2 shell around the VOx particles, with the difference in thermal expansion coefficient between SiO2 and VOx inducing sufficient strain in the VOx to dramatically lower the IMT temperature. This approach enables the production of a functional solution of suspended VOx nanoparticles with near-room temperature IMT. The combination of near-room temperature IMT and solution phase nanoparticles dramatically increases the ease, scalability, and efficacy of VOx application.
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ItemNo Preview AvailableGenetic optimization of mid-infrared filters for a machine learning chemical classifier.(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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ItemExperimental Demonstration of Mid-Infrared Computational Spectroscopy with a Plasmonic Filter Array(OSA & IEEE, 2018-01-01)We demonstrate mid-infrared plasmonic filters. We experimentally determine the spectrum of a mid-infrared light source using an algorithm whose inputs are the total power transmitted by each filter and the transmission spectrum of each filter.
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ItemNanostructured Fishnet Silicon Photodetector Pixels as a Fully-Contained Microspectrometer Chip(IEEE, 2018)We experimentally demonstrate a microspectrometer comprising twenty silicon photodetector pixels, whose responsivities are engineered via nanostructured fishnet patterns. We computationally reconstruct the spectrum of light that illuminates the chip from the measured pixel photocurrents.
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