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A Differential Detection Method Based on a Linear Weak Measurement System

Self-reference detection is necessary and important to a biosensor. The linear weak measurement system based on total internal reflection has attracted widespread attention due to its high stability, label-free detection, and easy integration. In this paper, we propose a differential detection metho...

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Autores principales: Xiong, Nian, Guan, Tian, Xu, Yang, Shi, Lixuan, Zhong, Suyi, Zhou, Xuesi, He, Yonghong, Li, Dongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603576/
https://www.ncbi.nlm.nih.gov/pubmed/31151193
http://dx.doi.org/10.3390/s19112473
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author Xiong, Nian
Guan, Tian
Xu, Yang
Shi, Lixuan
Zhong, Suyi
Zhou, Xuesi
He, Yonghong
Li, Dongmei
author_facet Xiong, Nian
Guan, Tian
Xu, Yang
Shi, Lixuan
Zhong, Suyi
Zhou, Xuesi
He, Yonghong
Li, Dongmei
author_sort Xiong, Nian
collection PubMed
description Self-reference detection is necessary and important to a biosensor. The linear weak measurement system based on total internal reflection has attracted widespread attention due to its high stability, label-free detection, and easy integration. In this paper, we propose a differential detection method based on the linear total internal reflection weak measurement system. We introduce the half-wave plate (HWP) to convert the H light and the V light to each other, thereby obtaining the difference in phase change of the optical path before and after the HWP. Experiments show that the system can not only achieve differential detection, but also has high stability. The linear differential weak measurement system proposed in this paper not only provides a new differential measurement method for real-time biosensors, but also enriches the types of weak measurement sensors.
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spelling pubmed-66035762019-07-17 A Differential Detection Method Based on a Linear Weak Measurement System Xiong, Nian Guan, Tian Xu, Yang Shi, Lixuan Zhong, Suyi Zhou, Xuesi He, Yonghong Li, Dongmei Sensors (Basel) Article Self-reference detection is necessary and important to a biosensor. The linear weak measurement system based on total internal reflection has attracted widespread attention due to its high stability, label-free detection, and easy integration. In this paper, we propose a differential detection method based on the linear total internal reflection weak measurement system. We introduce the half-wave plate (HWP) to convert the H light and the V light to each other, thereby obtaining the difference in phase change of the optical path before and after the HWP. Experiments show that the system can not only achieve differential detection, but also has high stability. The linear differential weak measurement system proposed in this paper not only provides a new differential measurement method for real-time biosensors, but also enriches the types of weak measurement sensors. MDPI 2019-05-30 /pmc/articles/PMC6603576/ /pubmed/31151193 http://dx.doi.org/10.3390/s19112473 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiong, Nian
Guan, Tian
Xu, Yang
Shi, Lixuan
Zhong, Suyi
Zhou, Xuesi
He, Yonghong
Li, Dongmei
A Differential Detection Method Based on a Linear Weak Measurement System
title A Differential Detection Method Based on a Linear Weak Measurement System
title_full A Differential Detection Method Based on a Linear Weak Measurement System
title_fullStr A Differential Detection Method Based on a Linear Weak Measurement System
title_full_unstemmed A Differential Detection Method Based on a Linear Weak Measurement System
title_short A Differential Detection Method Based on a Linear Weak Measurement System
title_sort differential detection method based on a linear weak measurement system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603576/
https://www.ncbi.nlm.nih.gov/pubmed/31151193
http://dx.doi.org/10.3390/s19112473
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