谐振器
计算机科学
人工神经网络
组分(热力学)
戒指(化学)
测距
主成分分析
模式识别(心理学)
生物系统
材料科学
人工智能
电信
光电子学
物理
化学
生物
热力学
有机化学
作者
Zhenyu Li,Hui Zhang,Bình Thị Thanh Nguyễn,Shaobo Luo,Patricia Yang Liu,Jun Zou,Yuzhi Shi,Hong Cai,Zhenchuan Yang,Yufeng Jin,Yilong Hao,Yi Zhang,A. Q. Liu
出处
期刊:Photonics Research
[Optica Publishing Group]
日期:2020-11-20
卷期号:9 (2): B38-B38
被引量:40
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI