PRIMALIGHT Research Group

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  • Presentation

    Metasurface Light Encoders Enable Real-Time Hyperspectral Imaging and Video Understanding

    (IEEE, 2023-06-26) Makarenko, Maksim; Burguete-Lopez, A.; Wang, Qizhou; Getman, Fedor; Giancola, Silvio; Ghanem, Bernard; Fratalocchi, Andrea; King Abdullah University of Science and Technology,Faculty of Electrical Engineering; Applied Mathematics and Computational Science,Thuwal,Saudi Arabia,23955-6900; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Visual Computing Center (VCC); Applied Mathematics and Computational Science Program

    Hyperspectral imaging has emerged as a powerful tool for identifying and remotely sensing complex materials in a wide range of applications, including medical diagnostics, security, food safety, and precision agriculture [1], [2]. Despite significant advances in this field, there remain a number of challenges that must be addressed in order to fully realize the potential of hyperspectral imaging in real-world applications. One major challenge is the high cost and slow acquisition time of current state-of-the-art hyperspectral imaging systems, which can exceed 20.000 USD for a single camera and take up to a minute to acquire a single image[3]. Additionally, existing systems are often limited by low spatial resolution and require large amounts of memory storage.

  • Presentation

    Machine Learning Empowers Large-Scale Optical Sensors for Ultrasensitive Detection

    (IEEE, 2023-06-26) Li, Ning; Wang, Qizhou; He, Zhao; Burguete-Lopez, A.; Xiang, Fei; Fratalocchi, Andrea; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Electrical and Computer Engineering Program

    Optical sensors are stirring broad interests in disease diagnostics, food safety, and environment monitoring [1]––[3]. Several criteria assess the performance of a sensor, including the analytical detection speed, cost, sensitivity, and reproducibility [4], [5]. Traditionally, optical sensing leverages localized spectral features such as e.g., resonance peaks shift, intensity variations, and widths. This approach, while straightforward in implementation, results in a weak detection limit for analytes, and needs improvement for enabling practical applications. Recent pioneering work focuses on artificial intelligence (AI) to address this issue, leveraging sparse features in broad amounts of data to enhance the sensor detection sensitivity [6]. However, most of these approaches rely on post-processing data collected with complex equipment, such as spectrum analyzers. These systems are significantly expensive, not integrated, and compete poorly with traditional sensing based on localized features.

  • Presentation

    Record Efficient and Stable Si-Based Photoanodes Enabled by Ultrathin Transition-Metal Alloy Film for Solar-Assisted Water Splitting

    (IEEE, 2023-06-26) Xiang, Fei; Li, Ning; Burguete-Lopez, A.; He, Zhao; Elizarov, Maxim; Fratalocchi, Andrea; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Material Science and Engineering Program; Physical Science and Engineering (PSE) Division

    Photoelectrochemical (PEC) water splitting is attracting tremendous research interest as a promising energy conversion and storage route to ease the reliance on fossil fuels and contribute to sustainable development [1]–[3]. It produces clean hydrogen fuels from solar energy and water with zero carbon emissions and requires much less external bias input than the traditional pure electrolyzing system [4], [5]. Since the sluggish kinetics of water oxidation reaction at the anode side bottleneck the overall performance of the entire device, current research focuses on enhancing the catalytic performance at the photoanodes [4], [6].

  • Presentation

    Metrology System Based on Metasurface Implementation of Artificial Inteligence

    (IEEE, 2023-06-26) Burguete-Lopez, A.; Makarenko, Maksim; Wang, Qizhou; Getman, Fedor; Fratalocchi, Andrea; King Abdullah University of Science and Technology,PRIMALIGHT, Faculty of Electrical Engineering; Applied Mathematics and Computational Science,Thuwal,Saudi Arabia,23955-6900; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Applied Mathematics and Computational Science Program

    Optical instrumentation is ubiquitous across scientific disciplines and industrial settings for its ability to deliver non-destructive and high accuracy mesurements [1]. However, as global manufacturing transitions an automated industry paradigm, the need for highly integrated metrology systems for autonomous machines cannot be addressed traditional bulk optics based equipment [2]. Metasurfaces provide a possible solution to this challenge, enabling near-arbitrary light control functionality in a compact form factor [3]–[5].

  • Presentation

    Laser-Induced Engineering of Nanomaterial Phase and Shape for 3D Light Control at the Nanoscale

    (IEEE, 2023-06-26) Elizarov, Maxim; Li, Ning; Fratalocchi, Andrea; PRIMALIGHT, Applied Mathematics and Computational Science King Abdullah University of Science and Technology,Faculty of Electrical Engineering,Thuwal,Saudi Arabia,23955-6900; Material Science and Engineering Program; Physical Science and Engineering (PSE) Division; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Electrical and Computer Engineering Program; Applied Mathematics and Computational Science Program

    The control of light at the nanoscale through new nanofabrication techniques has garnered significant attention in research [1]. Recent advancements in fabrication methodologies have focused on processing specific geometrical patterns in a given material. However, a technique that allows point-to-point control over both material phase and geometrical shape is currently unavailable. Addressing this problem can open new pathways for controlling materials' optical response, leading to new levels of performance of photonic devices.