Biosensors are needed for today’s health monitoring system for detecting different biomolecules. Graphene is a monolayer material that can be utilized to sense biomolecules and design biosensors. We have proposed a Graphene-Gold-Silver hybrid structure design based on Zinc Oxide which gives sensitive performance to detect hemoglobin biomolecules. The advanced biosensor designed based on this hybrid structure shows the highest sensitivity of 1000 nm/RIU which is far better concerning similar structure previously analyzed. The graphene-gold-silver hybrid structure is presented for its possible reflectance results and electric field results. The E-field results match well with the reflectance results given by the sensitive hybrid structure. The sensing biomolecules are presented above the structure where a combination of graphene-gold-silver hybrid structure improves the sensitivity to a great extent. The optimized parameters are obtained by applying variations in the physical parameters of the design. The machine learning algorithm employed for reflectance prediction shows a high prediction accuracy and can be utilized for simulation resource reduction. The proposed biosensor can be used in real-time hemoglobin monitoring.

中文翻译：

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利用机器学习优化基于新型 2D 材料的 SPR 生物传感器

当今的健康监测系统需要生物传感器来检测不同的生物分子。石墨烯是一种单层材料，可用于传感生物分子和设计生物传感器。我们提出了一种基于氧化锌的石墨烯-金-银混合结构设计，它具有检测血红蛋白生物分子的灵敏性能。基于这种混合结构设计的先进生物传感器显示出 1000 nm/RIU 的最高灵敏度，这比之前分析的类似结构要好得多。提出了石墨烯-金-银混合结构的可能的反射率结果和电场结果。电场结果与敏感混合结构给出的反射率结果非常吻合。传感生物分子呈现在结构上方，其中石墨烯-金-银杂化结构的组合在很大程度上提高了灵敏度。通过应用设计的物理参数的变化来获得优化的参数。用于反射率预测的机器学习算法显示出较高的预测精度，并且可用于减少模拟资源。所提出的生物传感器可用于实时血红蛋白监测。