Session Index

The contrast or signal-to-noise ratio (SNR) the most crucial and fundamental parameter in an optical sensing system. It’s immediately related with the quality of sensing. In an imaging system, with
a better image contrast/SNR, the imaging system can be performed at a faster frame rate or
deeper tissue locations without compromising image quality.
In this talk, the recent studies of our group on the contrast enhancement in femtosecond laser
based optical sensing/imaging systems will be presented by the higher-order-modulations or the
carrier pulse-stretching. These optical or electrical-optical methods will largely enhance the contrast in the coherent and in-coherent nonlinear laser scanning microscopes. Significant background reduction together with the SNR enhancement will presented in the second-harmonic generation microscopy on collagen fibrils or the two-photon fluorescence microscopy on whole drosophila brains.The fundamental working principles, experimental design, various results on the
femtosecond sensing with enhanced contrast, and the future perspective/possibility for these
technique will be also presented.

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An aluminum-doped gallium oxide (Ga2O3:Al) active layer of metal-semiconductor-metal ultraviolet C photodetectors (MSM UVC-PDs) was deposited by a plasma-enhanced atomic layer deposition (PE-ALD) system. Compared with the Ga–O bond, the Al–O bond was more easily formed, which suppressed the generation of oxygen vacancies in the Ga2O3:Al films. Accordingly, under bias of 10 V, the optimal performance of the resulting UVC-PDs with Al content of 1.88 at.% could be achieved to photocurrent/dark current ratio of 7.8×10^4, responsivity of 0.5 A/W, UV-VIS rejection ratio of 3.6×10^5, and the detectivity of 8.3×10^13 Jones.

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In this work, we present an effect of polarization on the machine-learned, speckle pattern-based Laguerre Gaussian (LG) beam classification. Specifically, four different polarization states are explored namely, linear +45, linear +135, right circular, and left circular; and their effect on the classification performance of a simple machine learning model. The classification accuracies >80% are achieved for each polarization state corresponding to different LG modes. This proves the efficacy of machine learning models for recognizing the speckle patterns of LG modes which are polarization encoded and might be useful in real-world applications for efficient OAM beam multiplexing in free space communication.

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This work developed the colorimetric change optical CO2 sensor using the pH indicator phenol red and
CdSe/ZnS quantum dots embedded in polymer matrix. All of the sensing film materials are coated on the surface
of filter paper. Meanwhile, from the investigation of emission spectra exposed of CdSe/ZnS quantum dots will
increase as the CO2 concentration increased. The experiment results show the optical CO2 sensor has a
sensitivity of 1.8 and it can be applied to environmental applications.

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This study introduces a quasi-optical system developed for material characterization. The system, based on the quasi-optical principle, is operated using a Vector Network Analyzer (VNA). We successfully measured the optical properties of various plastic plates in the millimeter-wave region, specifically from 8 GHz to 12 GHz. The experimental results have been compared with existing data to validate the accuracy and efficacy of the proposed quasi-optical system.

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This work demonstrates a simple approach for the direct synthesis of gold nanoparticles (AuNPs) through photoreduction and the self-assembly of AuNPs on APTES-functionalized surfaces as the substrates for surface-enhanced Raman spectroscopy. We investigated the impact of various reduction parameters, as well as different sizes of AuNPs, on the optical behavior of the Raman intensity. Finally, we applied the SERS substrates to detect MG and biomolecular. Our approach not only involves simple processing steps but is also cost-effective, allowing for the production of more than tens of samples at once.

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This study demonstrates a simple approach for the detection of polystyrene microplastics using Raman spectroscopy. This method involves utilizing compact monolayer polystyrene nanospheres to create an inverted pyramid structure. The SERS (surface-enhanced Raman spectroscopy) substrates were fabricated through nanoimprint and deposition of a gold film using electron beam evaporation. Various SERS sensing approaches to enhance the Raman signal were explored. This study offers a simple and mass-produced method for the detection of microplastics.

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