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In-Situ and Ultrasensitive Detection of Mercury (Ii) Ions (Hg2+) Using the Localized Surface Plasmon Resonance (Lspr) Nanosensor and the Microfluidic Chip

SSRN

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SSRN 2022年

作者： Zhang, Wenjia Liu, Guohua Bi, Jinqiang Bao, Kexin Wang, Peiren Tianjin Research Institute of Water Transport Engineering M.O.T. Tianjin300456 China National Engineering Research Center of Port Hydraulic Construction Technoloy Tianjin300456 China College of Microelectronics Nankai University Tianjin300350 China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin300350 China Engineering Research Center of thin film optoelectronics technology Ministry of Education Nankai University Tianjin300350 China School of Marine Science and Technology Tianjin University Tianjin300192 China

Mercury is one of the most dangerous heavy metals due to its extreme toxicity to both humans and the biosphere. In this work, an in-situ and ultrasensitive method for the detection of mercury (II) ions (Hg 2+ ) using the dark-field microspectroscopy-based localized surface plasmon resonance (LSPR) nanosensor is demonstrated. In our homemade high-throughput microfluidic chip, the fixed nanorods and the free small gold nanospheres combine to form the core-satellite structures with the help of T- Hg 2+ -T chemical coordination. Such a process results in a spectral red shift due to plasmonic coupling, which allows us to reach a picomolar detection limit and a linear response range from 10 pM to 10 µM. In addition, our LSPR nanosensor has excellent selectivity and no interference for the detection of Hg 2+ , which was evaluated by monitoring responses to different heavy metal ions (Pb 2+ , Cd 2+ , Cr 2+ , Ni 2+ , and Cu 2+ ) and their mixed samples. Our sensor platform's effectiveness offers a practical method for detecting traces of Hg 2+ in real-life water samples. © 2022, The Authors. All rights reserved.

关键词： Microfluidic chips

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Highly Directional Aerosol Fluorescence Emission Excited by Femtosecond Laser Filament

SSRN

引用

SSRN 2022年

作者： Xue, Jiayun Zeng, Xi Guo, Lanjun Guo, Rui Zhang, Zhi Chu, Chunyue Cheng, Zhenzhou Zhang, Nan Lin, Lie Liu, Weiwei Institute of Modern Optics Eye Institute Nankai University Tianjin300350 China School of Medical Devices Shanghai University of Medicine and Health Sciences Shanghai201318 China Shanghai University of Medicine and Health Sciences China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin300350 China School of Economics and Management Qilu Normal University Shandong Jinan250013 China

Backward angular distributions of the sodium fluorescence in NaCl aerosols induced by femtosecond laser filamentation in air with a distance of 10 m are measured. The recorded signals appear as strong angular dependence. Further study indicates that it could be associated with the Mie scattering of the filamentation-induced "aerosol lasing" in the forward direction. These results will benefit the remote-sensing of air pollutants by femtosecond laser filamentation-based LIDAR (light detection and ranging). © 2022, The Authors. All rights reserved.

关键词： Remote sensing

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Automated Segmentation of Brain Gray Matter Nuclei on Quantitative Susceptibility Mapping Using Deep Convolutional Neural network

arXiv

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arXiv 2020年

作者： Chai, Chao Qiao, Pengchong Zhao, Bin Wang, Huiying Liu, Guohua Wu, Hong Haacke, E. Mark Shen, Wen Cao, Chen Ye, Xinchen Liu, Zhiyang Xia, Shuang Department of Medical Imaging Tianjin First Central Hospital Tianjin300192 China Tianjin Medical Imaging Institute Tianjin300192 China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology College of Electronic Information and Optical Engineering Nankai University Tianjin300350 China Department of Radiology Wayne State University DetroitMI48202 United States Department of Medical Imaging Tianjin Huanhu Hospital Tianjin300350 China DUT-RU International School of Information Science and Engineering Dalian University of Technology Dalian116620 China

Abnormal iron accumulation in the brain subcortical nuclei has been reported to be correlated to various neurodegenerative diseases, which can be measured through the magnetic susceptibility from the quantitative susceptibility mapping (QSM). To quantitively measure the magnetic susceptibility, the nuclei should be accurately segmented, which is a tedious task for clinicians. In this paper, we proposed a double-branch residual-structured U-Net (DB-ResUNet) based on 3D convolutional neural network (CNN) to automatically segment such brain gray matter nuclei. To better tradeoff between segmentation accuracy and the memory efficiency, the proposed DB-ResUNet fed image patches with high resolution and the patches with low resolution but larger field of view into the local and global branches, respectively. Experimental results revealed that by jointly using QSM and T1 weighted imaging (T1WI) as inputs, the proposed method was able to achieve better segmentation accuracy over its single-branch counterpart, as well as the conventional atlas-based method and the classical 3D-UNet structure. The susceptibility values and the volumes were also measured, which indicated that the measurements from the proposed DB-ResUNet are able to present high correlation with values from the manually annotated regions of interest. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic susceptibility

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Corrections to “Label-Free Detection of DNA Hybridization Utilizing Dual S-Tapered Thin-Core Fiber Interferometer”

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Journal of Lightwave technology 2019年第19期37卷 5158-5158页

作者： Xu Zhang Bo Liu Hao Zhang Binbin Song Jixuan Wu Shaoxiang Duan Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology College of Electronic Information and Optical Engineering Nankai University Tianjin China Key Laboratory of Computer Vision and Systems Ministry of Education School of Computer Science and Engineering Tianjin University of Technology Tianjin China College of Electronic and Information Engineering Tianjin Polytechnic University Tianjin China

Presents corrections to above named paper.

关键词： Biosensors DNA Optical fiber sensors Molecular biophysics Microsensors

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Quasinormal mode solvers for resonators with dispersive materials

arXiv

引用

arXiv 2018年

作者： Lalanne, P. Yan, W. Gras, A. Sauvan, C. Hugonin, J.-P. Besbes, M. Demésy, G. Truong, M.D. Gralak, B. Zolla, F. Nicolet, A. Binkowski, F. Zschiedrich, L. Burger, S. Zimmerling, J. Remis, R. Urbach, P. Liu, H.T. Weiss, T. LP2N Institut d’Optique Graduate School CNRS Univ. Bordeaux Talence33400 France Laboratoire Charles Fabry Institut d’Optique Graduate School CNRS Université Paris-Saclay Palaiseau Cedex91127 France Aix Marseille Univ CNRS Centrale Marseille Institut Fresnel Marseille France Zuse Institute Berlin Berlin14195 Germany JCMwave GmbH Berlin14050 Germany Circuits and Systems Delft University of Technology Mekelweg 2 Delft2628 CD Netherlands Optics Research Group Delft University of Technology Mekelweg 2 Delft2628 CD Netherlands Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Institute of Modern Optics College of Electronic Information and Optical Engineering Nankai University Tianjin300350 China Physics Institute and Research Center SCoPE University of Stuttgart Pfaffenwaldring 57 Stuttgart70550 Germany

Optical resonators are widely used in modern photonics. Their spectral response and temporal dynamics are fundamentally driven by their natural resonances, the so-called quasinormal modes (QNMs), with complex frequencies. For optical resonators made of dispersive materials, the QNM computation requires solving a nonlinear eigenvalue problem. This rises a difficulty that is only scarcely documented in the literature. We review our recent efforts for implementing efficient and accurate QNM-solvers for computing and normalizing the QNMs of micro- and nanoresonators made of highly-dispersive materials. We benchmark several methods for three geometries, a two-dimensional plasmonic crystal, a two-dimensional metal grating, and a three-dimensional nanopatch antenna on a metal substrate, in the perspective to elaborate standards for the computation of resonance modes. Copyright © 2018, The Authors. All rights reserved.

关键词： Nanoantennas

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