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Development of detection system for lead ions in mixture solutions using UV-Vis measurements with peptide immobilized microbeads.

Sci Rep

January 2025

Faculty of Frontiers of Innovative Research in Science and Technology (FIRST), Konan University, Chuo-ku, Kobe, 650-0047, Hyogo, Japan.

Environmental pollution caused by heavy metals are problems worldwide. In particular, pollution and poisoning by lead ions (Pb) continue to be common and serious problems. Hence, there is a need for a widely usable method to easily detect Pb from solutions containing organic materials from environmental water such as seas, ponds, etc.

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Gold nanorod in silver tetrahedron: Cysteamine mediated synthesis of SERS probes with embedded internal markers for AFP detection.

Anal Chim Acta

February 2025

The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, No. 28 Xianning West Road, Xi'an, 710049, China. Electronic address:

Background: Plasmonic core-shell nanostructures with embedded internal markers used as Raman probes have attracted great attention in surface-enhanced Raman scattering (SERS) immunoassay for cancer biomarkers due to their excellent uniform enhancement. However, current core-shell nanostructures typically exhibit a spherical shape and are coated with a gold shell, resulting in constrained local field enhancement.

Results: In this work, we prepared a core-shell AuNR@BDT@Ag structure by depositing silver on the surface of Raman reporter-modified gold nanorods (AuNR).

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Refractive index (RI) and temperature (T) are both critical environmental parameters for environmental monitoring, food production, and medical testing. The paper develops a D-shaped photonic crystal fiber (PCF) sensor to measure RI and T simultaneously. Its cross-sectional structure encompasses a hexagonal-hole lattice, with one hole selectively filled with toluene for temperature sensing.

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Materials with Negative Permittivity or Negative Permeability-Review, Electrodynamic Modelling, and Applications.

Materials (Basel)

January 2025

Institute of Microelectronics and Optoelectronics, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland.

A review of natural materials that exhibit negative permittivity or permeability, including gaseous plasma, metals, superconductors, and ferromagnetic materials, is presented. It is shown that samples made of such materials can store large amount of the electric (magnetic) energy and create plasmonic resonators for certain values of permittivity, permeability, and dimensions. The electric and the magnetic plasmon resonances in spherical samples made of such materials are analyzed using rigorous electrodynamic methods, and the results of the analysis are compared to experimental data and to results obtained with other methods.

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With the increasing global attention to deep learning and the advancements made in applying convolutional neural networks in electromagnetics, we have recently witnessed the utilization of deep learning-based networks for predicting the spectrum and electromagnetic properties of structures instead of traditional tools like fully numerical-based methods. In this study, a Convolutional Neural Network (CNN is proposed for predicting spoof surface plasmon polaritons, enabling the examination of the absorption spectrum of metallic multilevel-grating structures (MMGS) and designing various sensor devices and absorbers in the shortest time possible. To expedite the training process of this network, a semi-analytical method of rigorous coupled-wave analysis (RCWA) enhanced with the fast Fourier factorization (FFF) technique has been employed, significantly reducing the data generation time for training.

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