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Papers
61,005 resultsShowing papers similar to The assessment of particle selection and blank correction to enhance the analysis of microplastics with Raman microspectroscopy
ClearRapid 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.
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.
Selection of microplastics by Nile Red staining increases environmental sample throughput by micro-Raman spectroscopy
This study showed that pre-selecting particles with Nile Red staining prior to Raman spectroscopy analysis significantly increases sample throughput, enabling faster processing of environmental microplastic samples without sacrificing identification accuracy.
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.
An automatic method for accurate signal-to-noise ratio estimation and baseline correction of Raman spectra of environmental microplastics
Researchers developed an automatic method for estimating signal-to-noise ratios and correcting baselines in spectroscopic microplastic analysis, improving the reliability and reproducibility of polymer identification in complex environmental samples.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
A double sliding-window method for baseline correction and noise estimation for Raman spectra of microplastics
A double sliding-window method for baseline correction and noise estimation in Raman spectra of microplastics outperformed two commonly used methods for samples with low signal-to-noise ratios and elevated baselines, providing a more accurate automated preprocessing tool for environmental microplastic analysis.
A comparison of microscopic and spectroscopic identification methods for analysis of microplastics in environmental samples
Researchers compared microscopic and spectroscopic methods for analyzing microplastics in environmental samples, evaluating accuracy and efficiency and finding that spectroscopic confirmation substantially reduces misidentification errors.
Implementation of an open source algorithm for particle recognition and morphological characterisation for microplastic analysis by means of Raman microspectroscopy
An automated particle recognition algorithm was implemented to speed up the identification and measurement of microplastics in Raman spectroscopy images. Automated analysis reduces the time and subjectivity involved in manual microplastic counting, improving research efficiency.
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.
Towards 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.
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.
Inter-instrument definition of valid criteria for the automatic identification of microplastics by micro-Raman spectroscopy
Researchers developed a standardized methodology for automatically identifying microplastics using micro-Raman spectroscopy across different laboratory instruments. They determined optimal match algorithms and threshold values that achieved a 95% true positive rate with minimal false positives, even when spectra were collected on different spectrometers. The study addresses a key barrier to reliable, reproducible microplastic identification in environmental and health research.
Correction of panoramic raman spectra and its application for microplastics content analysis
Researchers developed a correction method for panoramic Raman spectra to eliminate artifacts created when stitching together individual spectral segments, improving the accuracy of wideband Raman spectroscopy applied to microplastic identification and analysis.