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Papers
20 resultsShowing papers similar to Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy
ClearMicroplastic 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.
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.
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.
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.
Rapid identification of micro and nanoplastics by line scan Raman micro-spectroscopy
Researchers developed a faster Raman spectroscopy tool for identifying microplastic particles by scanning a line rather than a single point at a time, improving imaging speed by 10 to 100 times over conventional methods. This allows the same chemical identification and size characterization of microplastics across large sample areas in a fraction of the time. Faster analysis methods are critical for processing the large numbers of samples needed in environmental monitoring programs.
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.
A critical assessment of visual identification of marine microplastic using Raman spectroscopy for analysis improvement
Researchers critically evaluated the accuracy of visual identification versus Raman spectroscopy for identifying marine microplastics, finding that visual identification alone has significant error rates and that spectroscopic confirmation is necessary for reliable results.
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.
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.
Raman Spectroscopy and Machine Learning for Microplastics Identification and Classification in Water Environments
Researchers combined Raman spectroscopy with machine learning algorithms for automated identification and classification of microplastics in water environments, achieving high accuracy in distinguishing different polymer types based on spectral fingerprints.
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 of Marine Microplastics - A short comprehensive compendium for the environmental scientists
Researchers produced a practical primer on Raman spectroscopy for non-specialist environmental scientists working with marine microplastics, covering instrument principles, sample preparation, spectral interpretation, and common challenges, aimed at improving the reliability and comparability of Raman-based MP identification.
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.
Visualization and characterisation of microplastics in aquatic environment using a home-built micro-Raman spectroscopic set up
Researchers built an affordable micro-Raman spectroscopy system capable of identifying microplastics in water samples, offering a low-cost alternative to expensive commercial equipment. The system could visualize, measure, and chemically identify different types of microplastic particles. This kind of accessible detection technology is important, especially for developing countries, because widespread monitoring of microplastic pollution in water sources is essential for protecting public health.
Fast 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 identification of microplastic using portable Raman system and extra trees algorithm
Researchers developed a portable Raman spectroscopy system combined with a machine learning algorithm to rapidly identify and classify different types of microplastics in the field. Portable real-time identification tools are important for environmental monitoring programs that need to quickly characterize microplastics without sending samples to a laboratory.
A Raman spectral reference library of potential anthropogenic and biological ocean polymers
Researchers created an open-access Raman spectral reference library covering major polymer types found in marine environments, providing a freely available tool to improve the accuracy and accessibility of microplastic identification in ocean research.
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.
Development of automated microplastic identification workflow for Raman micro-imaging and evaluation of the uncertainties during micro-imaging
Researchers developed an automated identification workflow for Raman micro-imaging of microplastics, validating it with artificial samples of known polymer microspheres and showing that the workflow reliably identifies plastic type and estimates particle size across a range of sizes.
Flow Raman Spectroscopy for the Detection and Identification of Small Microplastics
Researchers developed a new method using flow Raman spectroscopy to detect and identify individual microplastic particles as small as 4 micrometers while they move through water. Unlike current methods that require complex sample preparation, this technique could work in real time for monitoring food and drinking water quality. The method can distinguish between different plastic types even after they have been weathered by the environment.