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快速测量具有连续大角度范围的单个悬浮粒子的散射偏振参数。

Rapidly Measuring Scattered Polarization Parameters of the Individual Suspended Particle with Continuously Large Angular Range.

机构信息

School of Physics and Optoelectronic Engineering, Yangtze University, Jingzhou 434023, China.

Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.

出版信息

Biosensors (Basel). 2022 May 10;12(5):321. doi: 10.3390/bios12050321.

Abstract

Suspended particles play a vital role in aquatic environments. We propose a method to rapidly measure the scattered polarization parameters of individual suspended particles with continuously large angular range (PCLAR), from 60° to 120° in one shot. A conceptual setup is built to measure PCLAR with 20 kHz; to verify the setup, 10 μm-diameter silica microspheres suspended in water, whose PCLAR are consistent with those simulated by Mie theory, are measured. PCLAR of 6 categories of particles are measured, which enables high-accuracy classification with the help of a convolutional neural network algorithm. PCLAR of different mixtures of and silica microspheres are measured to successfully identify particulate components. Furthermore, classification ability comparisons of different angular-selection strategies show that PCLAR enables the best classification beyond the single angle, discrete angles and small-ranged angles. Simulated PCLAR of particles with different size, refractive index, and structure show explicit discriminations between them. Inversely, the measured PCLAR are able to estimate the effective size and refractive index of individual cells. Results demonstrate the method's power, which intrinsically takes the advantage of the optical polarization and the angular coverage. Future prototypes based on this concept would be a promising biosensor for particles in environmental monitoring.

摘要

悬浮颗粒在水生环境中起着至关重要的作用。我们提出了一种方法,可以快速测量单个悬浮颗粒的散射偏振参数,具有连续大角度范围(PCLAR),一次可测量 60°至 120°。建立了一个概念性设置来以 20 kHz 测量 PCLAR;为了验证该设置,测量了悬浮在水中的 10 μm 直径的二氧化硅微球,其 PCLAR 与米氏理论模拟的一致。测量了 6 类颗粒的 PCLAR,借助卷积神经网络算法可以实现高精度分类。测量了 和二氧化硅微球的不同混合物的 PCLAR,成功识别了颗粒成分。此外,不同角度选择策略的分类能力比较表明,PCLAR 能够实现最佳分类,超越了单一角度、离散角度和小角度范围。不同大小、折射率和结构的颗粒的模拟 PCLAR 之间表现出明显的区别。相反,测量的 PCLAR 能够估计单个 细胞的有效大小和折射率。结果证明了该方法的有效性,该方法本质上利用了光学偏振和角度覆盖范围。基于该概念的未来原型将成为环境监测中颗粒的有前途的生物传感器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb5/9138884/5a5ba9a41bae/biosensors-12-00321-g001.jpg

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