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Papers
61,005 resultsShowing papers similar to Microplastic rapid screening method development using automated mineralogy
ClearThe marine nano- and microplastics characterisation by SEM-EDX: The potential of the method in comparison with various physical and chemical approaches
Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) was evaluated as a method for characterizing marine micro- and nanoplastics, and compared with optical, spectroscopic, and chemical approaches. The study finds that SEM-EDX offers complementary information on particle morphology and surface chemistry that aids in identifying plastic particles at small 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.
Novel characterisation of microplastics and other contaminant particles using new scanning electron microscopy technologies
Researchers applied a new scanning electron microscopy technology combining backscattered electron and X-ray imaging (SEM-BEX) to environmental samples and found it characterized microplastics and other contaminant particles up to 18 times faster than standard SEM while providing simultaneous elemental composition data.
Methods of Analyzing Microsized Plastics in the Environment
This review covers sampling, extraction, identification, and quantification methods for microsized plastics across environmental matrices, finding that manual sorting and chemical analysis are needed for larger particles while automated spectroscopy methods are required for analyzing smaller microplastics.
Rapid chemical screening of microplastics and nanoplastics by thermal desorption and pyrolysis mass spectrometry with unsupervised fuzzy clustering
Researchers developed a rapid screening method using thermal desorption and pyrolysis mass spectrometry combined with machine learning to identify microplastics and nanoplastics by chemical composition. Faster, more automated identification tools are essential for scaling up environmental monitoring of microplastic contamination.
Quantification of small (1–10 µm) microplastic particles in soil matrices using automated scanning electron microscopy: possibilities and limitations
Researchers developed an automated SEM-EDX method for quantifying small (1-10 µm) microplastic particles in soil matrices, applying a gold coating to polycarbonate membranes to improve elemental contrast and using Monte Carlo simulations to optimise an acceleration voltage of 3 kV for particle detection. They achieved largely concentration-independent recoveries of ~70% for polyethylene and ~50% for PVC from soil suspensions, demonstrating both the promise and current limitations of this approach for small microplastic analysis.
A promising method for fast identification of microplastic particles in environmental samples: A pilot study using fluorescence lifetime imaging microscopy
Researchers piloted fluorescence lifetime imaging microscopy as a fast method for identifying microplastic particles in environmental samples. The study suggests this technique could simplify microplastic analysis by potentially eliminating the need for extensive extraction steps, enabling more direct identification of plastic particles in complex matrices.
A Novel Approach for Identifying Nanoplastics by Assessing Deformation Behavior with Scanning Electron Microscopy
Researchers adapted scanning electron microscopy (SEM) to identify nanoplastics by observing how different polymer types deform under an electron beam — a distinctive behavior that distinguishes plastics from common environmental materials like clay and algae. This novel detection method, enhanced by a computer vision algorithm, could help overcome one of the biggest obstacles in nanoplastic research: identifying particles too small to characterize with standard analytical tools.
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.
Overcome the obstacle of NP analysis – a concept of chemical/microscopic methods combined with artificial intelligence
Researchers tested an innovative combination of µ-Raman spectroscopy, scanning electron microscopy with energy-dispersive X-ray analysis, and artificial intelligence to achieve full chemical and morphological characterisation of nanoplastics across the complete nanoscale range in soil samples, aiming to overcome the analytical bottleneck in NP environmental assessment.
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.
Fast identification of microplastics in complex environmental samples by a thermal degradation method
Researchers developed a fast identification method for microplastics in complex environmental samples using thermal analysis, offering a high-throughput alternative to spectroscopic techniques for polymer identification.
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.
The assessment of particle selection and blank correction to enhance the analysis of microplastics with Raman microspectroscopy
Researchers improved the efficiency of Raman microspectroscopy analysis for microplastics by implementing automated particle selection and optimized blank correction methods, significantly reducing analysis time while maintaining accuracy for complex environmental samples.
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 Monitoring Approach for Microplastics Using Portable Pyrolysis-Mass Spectrometry
Researchers developed a rapid monitoring method for microplastics using a portable pyrolysis-mass spectrometry system that can identify polymer types and quantify particles smaller than 5 mm in the field without lengthy laboratory preparation. The approach offers a promising tool for fast, on-site microplastic surveillance in environmental samples.
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.
The Emerging of Microplastic and Nanoplastic as Pollutants and their Characterization and Analysis
This review presents an integrated approach to sampling, sample preparation, and analytical methods for detecting microplastics and nanoplastics in solid and aqueous environmental samples, discussing current challenges and emerging methodologies for more accurate characterization.
Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods
This study presents a batch analysis approach using multi-angle light scattering combined with chemometrics to measure microplastic size and concentration in water samples more quickly than single-particle methods. Faster analytical approaches are needed to scale up environmental microplastic monitoring.
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.
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.
Rapid and efficient method for assessing nanoplastics by an electromagnetic heating pyrolysis mass spectrometry
Researchers developed an electromagnetic heating pyrolysis mass spectrometry method for rapid nanoplastic characterization, demonstrating fast polymer identification and quantification at low concentrations in complex environmental samples compared to conventional thermal analysis.
Rapid Chemical Screening of Microplastics and Nanoplastics by Thermal Desorption and Pyrolysis Mass Spectrometry with Unsupervised Fuzzy Clustering
Researchers developed a rapid chemical screening method for microplastics and nanoplastics using thermal desorption and pyrolysis mass spectrometry combined with unsupervised fuzzy clustering, enabling polymer identification without requiring manual spectral matching. The method addresses the challenge of characterizing physically and chemically variable plastic particles in environmental samples.
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.