纳米工程石墨烯金属表面表面等离子体共振传感器与人工智能辅助性能预测用于精确检测血红蛋白

IF 3.3 4区 物理与天体物理 Q2 CHEMISTRY, PHYSICAL
Jacob Wekalao, Ngaira Mandela, Obed Apochi, Costable Lefu, Tobias Topisia
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引用次数: 0

摘要

开发高灵敏度和可靠的血红蛋白检测生物传感器对于各种医疗和诊断应用至关重要。血红蛋白是红细胞中负责氧气运输的重要蛋白质,是许多健康状况的重要生物标志物。准确、快速地测量血红蛋白水平有助于及早发现和监测贫血、血液疾病和其他病症。本研究介绍了一种用于检测血红蛋白的生物传感器设计,它将基于石墨烯的元表面与由银和金纳米结构构建的圆形和方形环形谐振器集成在一起。拟议的传感器利用了等离子纳米结构的独特等离子特性和石墨烯的显著光学特性来提高其性能。为了提高检测精度和其他性能参数,进行了广泛的参数分析和优化。检测分析表明,传感器能够通过透射和反射光谱的明显变化来分辨血红蛋白浓度的变化。由此产生的传感器对红外能量的灵敏度提高到 3500nmRIU-1,最大 FOM 为 17.6,除其他性能参数外,检测限为 0.05。此外,利用一维卷积神经网络回归的机器学习优化技术来预测传感器的行为,实现了较高的准确度,最大 R2 分数可达 1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Nanoengineered Graphene Metasurface Surface Plasmon Resonance Sensor for Precise Hemoglobin Detection with AI-Assisted Performance Prediction

Nanoengineered Graphene Metasurface Surface Plasmon Resonance Sensor for Precise Hemoglobin Detection with AI-Assisted Performance Prediction

The development of highly sensitive and reliable biosensors for hemoglobin detection is crucial for various medical and diagnostic applications. Hemoglobin, a vital protein in red blood cells responsible for oxygen transport, serves as an important biomarker for numerous health conditions. Accurate and rapid measurement of hemoglobin levels can aid in the early detection and monitoring of anemia, blood disorders, and other medical conditions. This study presents a biosensor design for hemoglobin detection, integrating a graphene-based metasurface with circular and square ring resonators constructed from silver and gold nanostructures. The proposed sensor leverages the unique plasmonic properties of plasmonic nanostructures and the remarkable optical characteristics of graphene to enhance its performance. Extensive parametric analysis and optimization are conducted to enhance detection accuracy among other performance parameters. Detection analysis demonstrated the sensor’s ability to resolve changes in hemoglobin concentration through distinct shifts in transmittance and reflectance spectra. The resulting sensor exhibits enhanced sensitivity of 3500nmRIU−1 to infrared energy, maximum FOM of 17.6, and detection limits of 0.05 among other performance parameters. Furthermore, machine learning optimization using 1D convolutional neural network regression is employed to predict the sensor’s behavior achieving high accuracy with maximum R2 scores ranging up to 1. The sensor design exhibits remarkable potential for applications requiring highly sensitive and precise hemoglobin monitoring in medical diagnostics and healthcare.

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来源期刊
Plasmonics
Plasmonics 工程技术-材料科学:综合
CiteScore
5.90
自引率
6.70%
发文量
164
审稿时长
2.1 months
期刊介绍: Plasmonics is an international forum for the publication of peer-reviewed leading-edge original articles that both advance and report our knowledge base and practice of the interactions of free-metal electrons, Plasmons. Topics covered include notable advances in the theory, Physics, and applications of surface plasmons in metals, to the rapidly emerging areas of nanotechnology, biophotonics, sensing, biochemistry and medicine. Topics, including the theory, synthesis and optical properties of noble metal nanostructures, patterned surfaces or materials, continuous or grated surfaces, devices, or wires for their multifarious applications are particularly welcome. Typical applications might include but are not limited to, surface enhanced spectroscopic properties, such as Raman scattering or fluorescence, as well developments in techniques such as surface plasmon resonance and near-field scanning optical microscopy.
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