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Li J, Liu H, Liao R, Wang H, Chen Y, Xiang J, Xu X, Ma H. Recognition of microplastics suspended in seawater via refractive index by Mueller matrix polarimetry. MARINE POLLUTION BULLETIN 2023; 188:114706. [PMID: 36764147 DOI: 10.1016/j.marpolbul.2023.114706] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Microplastics have become the marine pollution posing a human health risk, but they are difficult to be detected and recognized for different materials, irregular shapes, and broad size distributions. Microplastics' refractive index (RI) is related to the materials and can be characterized by the Mueller matrix. In this work, the particles are suspended in water and their Mueller matrices are measured by a particulate Mueller matrix polarimetry setup. Four kinds of spherical particles including microplastics are effectively classified by their Mueller matrices. Moreover, two kinds of common microplastics with broad size distributions, irregular shapes, and random orientations are also well recognized by the Mueller matrix. These results imply that RI plays a vital role in the recognition of microplastics suspended in water. By using the Mie theory and discrete dipole approximation simulation, the discussions explain in physics origin how RI affects Mueller matrix coupling with size and structure, and give some decoupling methods. Results in this work help advance future tools to in situ recognize the microplastics in seawater.
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Affiliation(s)
- Jiajin Li
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; Guangdong Research Center of Polarization Imaging and Measurement Engineering Technology, Institute of Biopharmaceutical and Health Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Hongyuan Liu
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Ran Liao
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
| | - Hongjian Wang
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Yan Chen
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Jing Xiang
- College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434020, China
| | - Xiangrong Xu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
| | - Hui Ma
- Shenzhen Key Laboratory of Marine IntelliSensing and Computation, Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; Guangdong Research Center of Polarization Imaging and Measurement Engineering Technology, Institute of Biopharmaceutical and Health Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
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Sensors for Environmental Monitoring and Food Safety. BIOSENSORS 2022; 12:bios12060366. [PMID: 35735513 PMCID: PMC9220911 DOI: 10.3390/bios12060366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 05/25/2022] [Indexed: 12/03/2022]
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Chen Y, Wang H, Liao R, Li H, Wang Y, Zhou H, Li J, Huang T, Zhang X, Ma H. Rapidly Measuring Scattered Polarization Parameters of the Individual Suspended Particle with Continuously Large Angular Range. BIOSENSORS 2022; 12:bios12050321. [PMID: 35624622 PMCID: PMC9138884 DOI: 10.3390/bios12050321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 05/05/2022] [Accepted: 05/09/2022] [Indexed: 11/16/2022]
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 Cyclotella stelligera 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 Cyclotella 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.
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Affiliation(s)
- Yan Chen
- School of Physics and Optoelectronic Engineering, Yangtze University, Jingzhou 434023, China; (Y.C.); (H.Z.)
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Hongjian Wang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Ran Liao
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
- Correspondence:
| | - Hening Li
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Yihao Wang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Hu Zhou
- School of Physics and Optoelectronic Engineering, Yangtze University, Jingzhou 434023, China; (Y.C.); (H.Z.)
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Jiajin Li
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Tongyu Huang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
| | - Xu Zhang
- College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434020, China;
| | - Hui Ma
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; (H.W.); (H.L.); (Y.W.); (J.L.); (T.H.); (H.M.)
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Zhou H, Li J, Liao R, Chen Y, Liu T, Wang Y, Zhang X, Ma H. Profile probing of suspended particles in water by Stokes vector polarimetry. OPTICS EXPRESS 2022; 30:14924-14937. [PMID: 35473225 DOI: 10.1364/oe.455288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/02/2022] [Indexed: 06/14/2023]
Abstract
Suspended particles are the important components of natural water. In this paper, a method based on polarized light scattering is proposed for profile probing of the particulate components in water. The profile probing is achieved by a polarized light sheet illuminating the suspension and the Stokes vector imaging system at a 120° backscattering angle, receiving the scattered light of the particles in the scattering volume. Each Stokes vector image (SVI) includes hundreds of star-studded particles whose Stokes vectors are used to retrieve the numbers of each particulate component in water. Experiments of typical particles are conducted. The classifications of these particles powered by the convolutional neural network (CNN) are demonstrated. The particulate components in mixed samples are successfully recognized and quantitatively compared. Considering at least 10 SVIs every second, the concentrations of each particulate component in water are effectively evaluated. The concept of profile probing the particulate components in water is proved to be powerful, by which we can measure up to almost 8000 particles per second. These results encourage the development of in-situ tools with this concept for particle profiling in future field surveying.
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