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Papers
20 resultsShowing papers similar to Identification of microplastics using Raman spectroscopy: Latest developments and future prospects
ClearRaman 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.
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.
A review of recent progress in the application of Raman spectroscopy and SERS detection of microplastics and derivatives
This review covers advances in using Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) to detect and identify microplastics in the environment. These techniques offer high resolution and sensitive detection that can identify specific plastic types even at very small sizes. Better detection methods are essential for understanding the true extent of microplastic contamination and its potential risks to human health.
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 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.
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.
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.
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.
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.
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.
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 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.
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.
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 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.
Detection of microplastics based on spatial heterodyne Raman spectroscopy
Researchers developed a spatial heterodyne Raman spectroscopy method for detecting microplastics, offering advantages over existing techniques by reducing detection time, lowering false detection rates, and using more affordable equipment.
Machine learning assisted Raman spectroscopy: A viable approach for the detection of microplastics
This review covers how machine learning combined with Raman spectroscopy can improve the detection and identification of microplastics in environmental samples. Traditional detection methods are slow and have limitations in resolution and particle size analysis, but AI algorithms can process spectral data more quickly and accurately. Better detection tools are essential for understanding the true scale of microplastic contamination in our water, food, and environment.
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.
Raman Spectroscopy for the Analysis of Microplastics in Aquatic Systems
This review outlined the current status of Raman spectroscopy for analyzing microplastics in aquatic systems, highlighting its high spatial resolution advantage for detecting small particles while critically assessing its drawbacks and best practices for effective use.
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.