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Papers
61,005 resultsShowing papers similar to Recognition of microplastics suspended in seawater via refractive index by Mueller matrix polarimetry
ClearUnderwater Particle Classification Detector using Mueller Matrix and Fluorescence Signal
A new underwater particle classification detector using Mueller matrix polarimetry was developed to distinguish microplastics from natural particles like sediment and organic matter in situ. The instrument advances real-time, in-water monitoring of microplastics without requiring sample collection and laboratory analysis.
Statistical Mueller matrix driven discrimination of suspended particles
Researchers developed a statistical method using polarized light scattering to distinguish between different types of suspended particles. This technique has potential applications for identifying and characterizing microplastic particles in water samples.
Optimized Classification of Suspended Particles in Seawater by Dense Sampling of Polarized Light Pulses
Researchers developed an optical method using polarized light pulses to classify suspended particles in seawater, aiming to distinguish microplastics from natural particles like algae in situ. A reliable in-water optical sensor for microplastics would greatly improve environmental monitoring capability.
Classification of Microplastic Particles in Water using Polarized Light Scattering and Machine Learning Methods
Researchers developed a reflection-based, in-situ classification method for microplastic particles in water using polarized light scattering combined with machine learning, successfully identifying colorless particles in the 50-300 micrometer range. The approach circumvents transmission-based interference problems and offers a pathway toward continuous, large-scale microplastic monitoring in aquatic environments.
In-situ Detection Method for Microplastics in Water by Polarized Light Scattering
Researchers developed an in-situ detection method for microplastics in water using polarized light scattering at 120 degrees, enabling real-time measurement of individual particles without sample collection or laboratory processing.
Differentiation of suspended particles by polarized light scattering at 120°
A polarized light scattering method was developed to rapidly distinguish different types of suspended particles in seawater, including microplastics, microalgae, and sediment. This optical approach could enable faster, real-time monitoring of microplastic concentrations in ocean water.
Identification of microplastics in wastewater samples by means of polarized light optical microscopy
Scientists tested polarized light optical microscopy as a rapid method for identifying microplastics in wastewater samples, finding it could distinguish synthetic polymer particles from natural debris based on their optical properties without requiring expensive spectroscopy equipment.
Probing Individual Particles in Aquatic Suspensions by Simultaneously Measuring Polarized Light Scattering and Fluorescence
Researchers developed a portable optical sensor that simultaneously measures polarized light scattering and fluorescence from individual particles in water, enabling classification of microplastics versus microalgae in situ. This dual-measurement approach improves particle identification accuracy compared to single-measurement methods.
Detection of Microplastics in Water and Ice
Researchers explored optical detection methods for identifying microplastics floating on water surfaces or trapped in ice, taking advantage of the unique light-reflecting properties of different plastic types. Advances in optical detection are important for developing faster, non-destructive tools for monitoring microplastic pollution.
Holographic and polarization features analysis for microplastics characterization and water monitoring
Researchers explored digital holography and polarization imaging as a combined technique for characterizing and classifying microplastics in water, computing features including angle of polarization (AoP) and degree of linear polarization (DoLP) to distinguish microplastics from biological and natural particles. The method demonstrated potential for real-time, non-contact, in situ microplastic detection and water quality monitoring.
Classification of suspended particles in seawater using an in situ polarized light scattering prototype
This study developed and field-tested an underwater sensor that uses polarized light scattering to distinguish between microplastics, sediment particles, and phytoplankton in seawater in real time. Lab tests showed classification accuracy above 85%, and the device was successfully deployed in a Chinese coastal bay across two seasons. Such in-situ monitoring tools could greatly improve our ability to track microplastic concentrations in the ocean without the labor-intensive sample collection and lab analysis currently required.
Characterization of common plastic microspheres through holographic Mueller matrix imaging
Researchers used polarimetric in-line holographic imaging to measure Mueller matrices from common plastic microspheres, demonstrating that different plastic types exhibit distinctive polarimetric signatures. The study presents this holographic Mueller matrix approach as a deterministic tool for automated microplastic detection and characterization.
Polarization digital holography for advanced classification of microplastic particles
Researchers developed a polarization digital holography approach for classifying microplastic particles based on their optical birefringence properties, requiring minimal sample preparation. The non-destructive method can distinguish microplastics from biological material by detecting how particles alter light polarization states.
Snapshot Polarization-Sensitive Holography for Detecting Microplastics in Turbid Water
Researchers developed a new imaging technique combining holography and polarimetry to detect microplastic particles in turbid water, a setting where traditional detection methods struggle. The approach uses differences in how light polarizes when passing through plastic versus natural particles to distinguish microplastics even in murky conditions. The study demonstrates a promising tool for faster, more practical monitoring of microplastic pollution in real-world water environments.
Fluorescence polarimetry for microplastics identification
Researchers developed a novel fluorescence polarimetry approach using anisotropy measurements to identify and characterize microplastics, offering a faster and simpler alternative to conventional spectroscopy and chromatography methods that require complex sample preparation.
Imaging-based lensless polarisation-resolving fluid stream analyser for automated, label-free and cost-effective microplastic classification
Researchers developed an imaging-based, lensless, polarisation-resolving fluid stream analyser for automated, label-free, and cost-effective microplastic classification in liquid samples, addressing the lack of in-situ monitoring solutions for ocean environments. The device operates at high flow rates using a custom illumination circuit to reduce motion blur, providing quantitative classification of microplastics without the labour intensity and cost of traditional sampling methods.
Sorting microplastics from other materials in water samples by ultra-high-definition imaging
Researchers used a commercial particle analyzer with ultra-high-definition imaging to sort and identify microplastic particles in water samples. The device successfully distinguished between different plastic types based on how light scatters through or off their surfaces, and could separate microplastics from air bubbles and other non-plastic particles. The study demonstrates a relatively fast and accessible method for characterizing microplastic contamination in water.
Smart polarization and spectroscopic holography for real-time microplastics identification
Researchers developed a new optical imaging system called SPLASH that simultaneously captures polarization, holographic, and texture data from tiny particles — without needing a traditional spectrometer — and used machine learning to identify different types of microplastics with high accuracy. This approach could enable faster, more practical real-time monitoring of microplastic pollution in water.
On optical sensing of surface roughness of flat and curved microplastics in water
Researchers developed and tested an optical sensor prototype capable of detecting microplastic particles of different shapes and surface textures in water by measuring light reflection patterns. The sensor offers a potential path to faster, in-situ microplastic detection without requiring chemical analysis.
Detecting Microplastics in Seawater with a Novel Optical Sensor Based on Artificial Intelligence Models
Detecting microplastics in seawater quickly and accurately is a major technical challenge, and this study developed a novel optical sensor that uses artificial intelligence to identify plastic particles from light-scattering data in real time. The AI-powered system was tested on seawater samples and showed promising accuracy for classifying microplastic types without the need for time-consuming laboratory processing. Automated in-situ sensors like this could enable continuous, large-scale ocean monitoring for microplastic pollution.
Quantification of Very Low Concentrations of Colloids with Light Scattering Applied to Micro(Nano)Plastics in Seawater
Researchers evaluated static and dynamic light scattering techniques for detecting and quantifying colloidal microplastic and nanoplastic particles (0.1-0.8 micron diameter) at very low concentrations in marine water, demonstrating their potential as rapid, non-destructive monitoring tools.
Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy
Researchers developed a rapid identification system for marine microplastics using Raman spectroscopy, enabling quick determination of plastic type and size. Fast, accurate identification tools are critical for monitoring the growing problem of microplastic pollution in ocean environments.
Real-time microplastic detection using polarization digital holographic microscope
Researchers developed a real-time microplastic detection system using a polarization digital holographic microscope, enabling identification and characterization of MP particles in water based on their optical properties without the need for chemical staining or extensive sample preparation.
Effect of medium refractive index on microparticle characterization by optical scattering
Researchers investigated how the refractive index of the medium affects optical scattering measurements used to characterize microplastic particles, finding that medium choice significantly influences size estimation accuracy. Machine learning was applied to improve classification of particles under varying optical conditions.