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Papers
20 resultsShowing papers similar to Rapid identification of micro and nanoplastics by line scan Raman micro-spectroscopy
ClearFast microplastics identification with stimulated Raman scattering microscopy
Stimulated Raman scattering microscopy was applied to rapidly identify and image microplastic particles in complex environmental samples at speeds dramatically faster than conventional Raman spectroscopy. The technique has potential to enable high-throughput microplastic analysis that could make large-scale environmental monitoring more feasible.
Rapid MicroplasticDetection Using High-ThroughputScreening Raman Spectroscopy
Researchers developed a high-throughput screening Raman spectroscopy system for rapid microplastic detection, overcoming the traditional tradeoff between spatial resolution, field of view, and analytical throughput to enable faster identification of plastic particles across environmental samples with low concentrations.
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.
Identification of microplastics using Raman spectroscopy: Latest developments and future prospects
This review summarizes the latest advances in using Raman spectroscopy to identify microplastics in environmental samples, highlighting improvements in speed, sensitivity, and the ability to characterize plastic type and surface chemistry.
Raman spectroscopy: Recent advances in fast and reliable microplastic analysis
This review summarized recent advances in Raman spectroscopy for fast and reliable microplastic identification, covering improvements in speed, sensitivity, and automation that are making the technique more practical for routine environmental monitoring. Raman-based methods are increasingly able to identify microplastics in complex environmental matrices including biological tissues.
An aberration-free line scan confocal Raman imager and type classification and distribution detection of microplastics
Researchers developed an advanced Raman imaging system that can identify and classify microplastics as small as 1 micrometer in diameter with 98% accuracy, working about 100 times faster than traditional methods. The system can also detect harmful chemical residues like phthalate plasticizers on microplastic surfaces. Faster and more accurate detection tools like this are essential for understanding the full scope of microplastic contamination in food and water and its potential impact on human health.
Microplastic identification using Raman microsocpy
Researchers developed and implemented a Raman spectroscopy system for rapid detection and identification of microplastic particles on substrates. The system enables efficient chemical characterization of microplastics found across diverse environmental matrices including ocean, lakes, soil, beach sediment, and human blood.
Using optimized particle imaging of micro-Raman to characterize microplastics in water samples
Researchers developed a micro-Raman automatic particle identification technique that can characterize microplastics in water samples up to 100 times faster than traditional point-by-point detection methods, while maintaining high precision for identifying polymer types, sizes, and morphologies.
Identification of Microplastics Using a Custom Built Micro-Raman Spectrometer
Researchers built a custom micro-Raman spectrometer and demonstrated its use for identifying microplastic polymer types in environmental samples, achieving sensitive and specific polymer identification at particle sizes down to a few micrometers.
Rapid Microplastic Detection Using High-Throughput Screening Raman Spectroscopy
Researchers developed a high-throughput Raman spectroscopy platform combining a 3.15 × 2.10 mm field of view with 1.4 µm spatial resolution for rapid label-free detection of microplastics. The system integrates automated particle recognition, autofocus correction, and spectral acquisition, significantly reducing analysis time compared to conventional micro-Raman approaches.
Raman Microspectroscopy: Improvement in Signal Generation and Collection to Facilitate Raman Spectroscopy
Advances in Raman microspectroscopy were reviewed for improving signal generation and analysis in microplastic identification, including new detector designs and data processing algorithms. Enhanced Raman spectroscopy capabilities enable faster and more accurate polymer identification at smaller particle sizes.
A semi-automated Raman micro-spectroscopy method for morphological and chemical characterizations of microplastic litter
Researchers developed a semi-automated Raman micro-spectroscopy method coupled with static image analysis for characterizing microplastics, achieving morphological and chemical identification of over 1,000 particles in under three hours, with polyethylene, polystyrene, and polypropylene as the dominant types in the environmental sample.
Raman spectroscopy: Recent advances in fast and reliable microplastic analysis
This review covered recent advances in Raman spectroscopy for fast and reliable microplastic analysis, with emphasis on its ability to characterize small particles that can penetrate living tissues. The authors highlight improvements in speed and sensitivity that are making Raman techniques more practical for environmental monitoring.
Fast compressive Raman micro-spectroscopy to image and classify microplastics from natural marine environment
Researchers developed a fast compressive Raman micro-spectroscopy system for imaging and classifying microplastics on filters, achieving significant speed improvements over conventional point-scanning Raman methods. The system correctly identified polymer types in heterogeneous real-world samples, offering a practical tool for routine microplastic monitoring in water and sediment samples.
Fast Detection and Classification of Microplastics by a Wide-Field Fourier Transform Raman Microscope
Researchers developed a new wide-field Raman microscope that can rapidly detect and identify microplastic particles with high spatial and chemical accuracy. The instrument can image a large sample area in about 15 minutes and identify particles down to roughly one micrometer in size. The technology was validated on microplastics from seawater and biological samples, offering a faster alternative to existing detection methods.
Fast Detection andClassification of Microplasticsby a Wide-Field Fourier Transform Raman Microscope
Researchers developed a wide-field hyperspectral Fourier transform Raman microscope for rapid detection and classification of microplastics extracted from environmental matrices. The instrument achieved high spatial resolution and chemical specificity across a large field of view, enabling faster throughput for microplastic identification compared to conventional point-scanning Raman approaches.
Characterization and identification of microplastics using Raman spectroscopy coupled with multivariate analysis
Researchers developed a new method using Raman spectroscopy combined with machine learning to identify and classify seven types of microplastics with over 98% accuracy for most polymer types. The approach was also able to correctly identify real-world microplastic samples from snack boxes, water bottles, juice bottles, and medicine vials. This technique could make microplastic detection faster and more reliable compared to manual analysis methods.
Development of a machine learning-based method for the analysis of microplastics in environmental samples using µ-Raman spectroscopy
Researchers developed a machine learning system to identify microplastics in environmental samples using Raman spectroscopy — a technique that identifies materials by how they scatter light — training it on over 64,000 spectra and achieving recall above 99% and precision above 97%. Combining the AI with human review reduced analysis time from several hours to under one hour per sample, making microplastic monitoring far more practical at scale.
High-throughput Raman platform for microplastics detection on filtration membranes
Researchers developed a high-throughput line-scan Raman imaging platform combining mosaic scanning spectroscopy and optical microscopy to detect and characterise microplastics >=10 µm on 47 mm diameter filtration membranes. By integrating deep learning segmentation algorithms for automated polymer classification and size distribution analysis, the platform completes full filter analysis within one hour, representing a substantial advance over conventional approaches for environmental and industrial microplastic monitoring.
How to Identify and Quantify Microplastics and Nanoplastics Using Raman Imaging?
This paper reviews advances in Raman imaging as a method for identifying and quantifying microplastics and nanoplastics in environmental samples, discussing current protocols, analytical challenges, and the need for standardization.