We demonstrate a smart sensor for label-free multicomponent chemical analysis using a single label-free ring resonator to acquire the entire resonant spectrum of the mixture and a neural network model to predict the composition for multicomponent analysis. The smart sensor shows a high prediction accuracy with a low root-mean-squared error ranging only from 0.13 to 2.28 mg/mL. The predicted concentrations of each component in the testing dataset almost all fall within the 95% prediction bands. With its simple label-free detection strategy and high accuracy, the smart sensor promises great potential for multicomponent analysis applications in many fields.

中文翻译：

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基于智能环形共振器的传感器，用于通过机器学习进行多组分化学分析

我们演示了一种用于无标签多组分化学分析的智能传感器，该传感器使用单个无标签的环形共振器来获取混合物的整个共振谱，并通过神经网络模型来预测用于多组分分析的成分。智能传感器显示出很高的预测精度，且均方根误差低，仅为0.13至2.28 mg / mL。测试数据集中每种成分的预测浓度几乎都在95％的预测范围内。凭借其简单的无标签检测策略和高精度，该智能传感器有望在许多领域中为多组分分析应用提供巨大潜力。