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Papers
61,005 resultsShowing papers similar to Analysis of composite microplastics in sediment using 3D Raman spectroscopy and imaging method
ClearTowards a quantitative approach for the accurate analysis of blended microplastics based on 3-D micro-Raman spectroscopy
Researchers developed a quantitative 3D micro-Raman spectroscopy approach for accurately analyzing blended microplastic particles composed of multiple polymer types, addressing the challenge that environmentally released microplastics often originate from complex multi-polymer blended materials.
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.
Misinterpretation in microplastic detection in biological tissues: When 2D imaging is not enough
Researchers demonstrated that 2D Raman imaging alone can misidentify microplastics in biological tissues, showing that 3D confocal Raman imaging is necessary to accurately distinguish microplastic particles from tissue components in mussels.
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.
Studying the concentration of polymers in blended microplastics using 2D and 3D Raman mapping
Scientists developed a 3D Raman mapping approach to measure the composition of "blended" microplastics — particles made from mixtures of different polymers rather than a single plastic type. Because blended plastics are extremely common in real-world pollution, the new technique provides a more accurate picture of what microplastic particles are actually made of, which is critical for assessing their chemical risks and environmental persistence.
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.
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.
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 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.
Detection of Microplastics in Freshwater Sediments Based on Raman Spectroscopy and Convolutional Neural Networks
Researchers developed a method combining Raman spectroscopy and convolutional neural networks to detect and classify microplastics in complex freshwater sediment samples, training the CNN on mixed spectra from extracted sediment fractions to improve detection accuracy.
Identification and visualization of environmental microplastics by Raman imaging based on hyperspectral unmixing coupled machine learning
Researchers developed a new method combining Raman imaging with machine learning to identify and visualize microplastics in environmental samples without destroying them. The technique can distinguish between different polymer types and map their distribution within a sample. The study offers a faster, more accurate approach to microplastic detection that could improve environmental monitoring efforts.
Raman Imaging Spectroscopy: History, Fundamentals and Current Scenario of the Technique
This review covers the history and principles of Raman imaging spectroscopy, a technique increasingly used to identify and map the chemical composition of microplastics in environmental samples. The review provides technical context for one of the most important tools in microplastic analysis.
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.
Detection and analysis of microplastics in offshore sediment by microscopic differential Raman spectroscopy
Researchers developed a rapid microplastic detection system combining fluorescence imaging, differential Raman spectroscopy, and confocal microscopic Raman technology using a dual 784/785 nm wavelength laser to overcome limitations of weak Raman signals and fluorescence interference, testing it on polycarbonate and high-density polyethylene particles in offshore sediments from Qingdao Shilaoren coastal waters.
Advanced microplastic monitoring using Raman spectroscopy with a combination of nanostructure-based substrates
Researchers reviewed advances in Raman spectroscopy and surface-enhanced Raman scattering (SERS) — a technique that amplifies light signals using metallic nanostructures — for detecting micro- and nanoplastics at trace concentrations in environmental samples, highlighting new plasmonic materials, 3D substrates, and microfluidic chip platforms that enable on-site monitoring.
Application of multi-step approach for comprehensive identification of microplastic particles in diverse sediment samples
Researchers developed a multi-step analytical approach to comprehensively identify and characterize microplastics in environmental samples, combining visual, spectroscopic, and thermal analysis. A systematic, multi-method approach is needed to capture the full diversity of microplastic types present in complex environmental matrices.
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.
Prevalence of small-sized microplastics in coastal sediments detected by multipoint confocal micro-Raman spectrum scanning
Researchers developed a new micro-Raman spectrum scanning method to detect small-sized microplastics in coastal sediments, revealing that particles under 50 micrometers are the most prevalent and commonly overlooked by standard techniques.
Fast detection and 3D imaging of nanoplastics and microplastics by stimulated Raman scattering microscopy
Researchers developed a fast imaging technique using stimulated Raman scattering microscopy to detect and create 3D maps of nanoplastics and microplastics at the single-particle level. The method can identify plastic particles as small as 100 nanometers and distinguish between different polymer types without the need for dyes or labels. This technology could help scientists more accurately track tiny plastic particles in environmental and biological samples.
Applications of Raman spectroscopy for microplastic detection and characterization: a comprehensive spectral reference
This review evaluates Raman spectroscopy as a tool for detecting and identifying microplastics across water, soil, air, and biological samples. The study consolidates reference spectra for common plastic polymers and discusses recent innovations like surface-enhanced Raman techniques that improve detection sensitivity, while also addressing challenges like fluorescence interference in complex samples.
Raman imaging spectroscopic solutions for microplastics advanced analysis: Insights from Choqueyapu river basin (La Paz, Bolivia)
This review surveys Raman imaging spectroscopy solutions for characterizing microplastics, covering advances in instrumentation, data analysis, and high-throughput methods that improve the speed and chemical specificity of microplastic identification in complex samples.
Assessment of compressive Raman spectroscopy to image and classify microplastics from natural marine environment
Researchers assessed compressive Raman spectroscopy as a tool for imaging and classifying microplastics collected from natural marine environments, evaluating whether this compressed sensing approach could accurately distinguish polymer types and particle characteristics. The study compared performance to conventional Raman mapping methods for environmental microplastic identification.
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.
Identification and visualisation of microplastics / nanoplastics by Raman imaging (iii): algorithm to cross-check multi-images
This study developed an improved Raman mapping algorithm with cross-checking across multiple images to more reliably identify microplastics and nanoplastics when spectral signals are weak, reducing false positives in environmental sample analysis.