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Papers
61,005 resultsShowing papers similar to Discrete frequency infrared-guided image for microplastic analysis: Performance and limitations
ClearTargeted Analysis of Microplastics Using Discrete Frequency Infrared Imaging
Researchers developed a targeted microplastic analysis strategy using discrete frequency infrared (DFIR) imaging with a quantum cascade laser system, demonstrating that by scanning only 20% of particles at predetermined absorption wavelengths, the method could identify 87.7% of spiked polyethylene particles and achieve at least a fivefold improvement in sample throughput over full-spectrum imaging approaches.
Reviewing the fundamentals and best practices to characterize microplastics using state–of–the-art quantum-cascade laser reflectance-absorbance spectroscopy
Researchers reviewed best practices for using quantum cascade laser infrared imaging (a high-speed scanning technology) to reliably identify microplastic particles, addressing technical pitfalls like particle-size effects on spectral readings. Standardizing this method is important for generating consistent, comparable data as governments push for official microplastic monitoring programs.
Rapid Identification and Quantification of Microplastics in the Environment by Quantum Cascade Laser-Based Hyperspectral Infrared Chemical Imaging
Quantum cascade laser infrared microscopy was evaluated as a rapid method for identifying and quantifying microplastics in environmental samples. The technique showed potential for faster polymer identification compared to conventional FTIR mapping, offering advantages for high-throughput microplastic monitoring.
Mid infrared spectroscopy applications using quantum cascade lasers for the identification of microplastic contaminants in aqueous solution
Researchers reviewed the application of quantum cascade laser-based mid-infrared spectroscopy for identifying and quantifying microplastic contaminants in aqueous solution, examining how standalone compact laser sources, packaged liquid-phase spectrometers, and mid-IR microscopes can detect and classify individual plastic particles by their vibrational spectral signatures.
Sample-based subsampling strategies to identify microplastics in the presence of a high number of particles using quantum-cascade laser-based infrared imaging
Researchers developed a new subsampling strategy for identifying microplastics using quantum-cascade laser-based infrared imaging, which makes it practical to analyze samples containing very large numbers of particles. Their approach tailors the subsampling areas to each individual sample rather than using a one-size-fits-all method, significantly reducing errors. The technique could make large-scale microplastic monitoring in environmental samples much more feasible and accurate.
Improved method for rapid characterization of microplastics in environmental samples with QCL-IR based microscopy and micro spectroscopy (Conference Presentation)
Researchers presented a quantum cascade laser infrared (QCL-IR) microscopy method for rapidly characterizing microplastics in environmental samples. The approach combines spatial imaging with chemical identification to classify particles by size, shape, and polymer type faster than conventional FTIR microscopy. Improved throughput in microplastic characterization helps researchers process the large sample volumes needed for environmental monitoring studies.
MicroplasticMass Estimation Using Two-DimensionalChemical Images from Quantum-Cascade Laser-Based Infrared Spectrometers
Researchers developed a method to estimate microplastic particle mass using two-dimensional chemical images from quantum cascade laser-based infrared microscopy, addressing the inability of standard spectroscopic imaging to provide particle mass data critical for toxicological assessment.
Microplastic Mass Estimation Using Two-Dimensional Chemical Images from Quantum-Cascade Laser-Based Infrared Spectrometers
Researchers developed a method to estimate microplastic particle mass using two-dimensional chemical images from quantum cascade laser-based infrared microscopy, filling a gap in spectroscopic techniques that can characterize particles but not provide mass information relevant for toxicology.
A reliable method to determine airborne microplastics using quantum cascade laser infrared spectrometry
Researchers developed a faster and more reliable method for measuring airborne microplastics using a quantum cascade laser infrared spectrometer. They tested different passive sampling devices and sample digestion approaches, then optimized the automated instrument to distinguish fibers from particles with over 90% accuracy. Standardizing how airborne microplastics are measured is critical because air is a significant but poorly characterized route of human microplastic exposure.
Spatial distribution of microplastics in the tropical Indian Ocean based on laser direct infrared imaging and microwave-assisted matrix digestion
Researchers characterized microplastic distribution across the tropical Indian Ocean using a new quantum cascade laser imaging method, finding an average concentration of 50 particles per cubic meter at depths of 6 meters. The new analytical approach analyzed up to 1,000 particles per hour with over 97% identification accuracy, enabling faster and more reliable monitoring.
A reliable method for the isolation and characterization of microplastics in fish gastrointestinal tracts using an infrared tunable quantum cascade laser system
Researchers developed and validated a quantum cascade laser-based method for rapidly characterizing microplastics extracted from fish gastrointestinal tracts, addressing key sample processing challenges and accelerating the identification stage compared to conventional infrared spectroscopy.
Measurement of tyre-based microplastics using traditional and quantum cascade laser-based infrared spectrometry
Micro-transflectance infrared spectroscopy was demonstrated as a method to characterize tyre-based microplastics down to 20 µm, with traditional attenuated total reflectance suitable for larger particles, providing new analytical pathways for monitoring this important emerging contaminant.
Laser Direct Infrared Spectroscopy: A cutting-edge approach to microplastic detection in environmental samples
This review highlights Laser Direct Infrared spectroscopy as a faster and more efficient technology for detecting microplastics in environmental samples compared to traditional methods. The technique uses a quantum cascade laser to identify plastic particles as small as 10 micrometers with high accuracy and speed. Researchers suggest this technology could be a valuable tool for large-scale environmental monitoring of microplastic pollution.
Classification and Quantification of Microplastics (<100 μm) Using a Focal Plane Array–Fourier Transform Infrared Imaging System and Machine Learning
Researchers developed a method using focal plane array Fourier transform infrared imaging to classify and quantify microplastics smaller than 100 micrometers. The technique allows simultaneous chemical identification and size measurement of individual particles across a filter sample, significantly improving throughput compared to manual analysis. The study demonstrates that automated spectroscopic imaging can reliably detect and categorize very small microplastics that are often missed by conventional methods.
Enabling analytical precision in microplastic analysis: innovative solutions for precise method validation, evaluation and quality control
Researchers developed an innovative method for validating microplastic analytical techniques using potassium bromide pellets embedded with known quantities of microplastics. The approach enables precise method validation and quality control for Fourier Transform Infrared and Quantum-cascade laser imaging, addressing a key gap in standardized microplastic analysis protocols.
Focal plane array detector-based micro-Fourier-transform infrared imaging for the analysis of microplastics in environmental samples
Researchers developed an automated protocol using focal plane array FT-IR imaging to identify and count microplastics on filters without manual sorting, dramatically increasing throughput compared to manual methods. The approach represents an important step toward standardized, high-throughput microplastic monitoring in aquatic environments.
Quantum cascade laser imaging (LDIR) and machine learning for the identification of environmentally exposed microplastics and polymers
Researchers used quantum cascade laser imaging combined with two supervised machine learning models to identify weathered microplastics, achieving identification accuracy of 89.7% across 81,291 individual particles. The combination of supervised and unsupervised clustering enabled detection of additional particle subtypes that could not be labeled by the supervised approach alone.
Quantification and characterization of microplastics in coastal environments: Insights from laser direct infrared imaging
Researchers used laser direct infrared imaging to identify and quantify microplastics in sediment and seawater samples from coastal areas in Auckland, New Zealand. The study detected nine common plastic polymer types and demonstrated that this analytical technique provides efficient and accurate characterization of microplastic contamination in environmental samples.
Characterization of microplastics on filter substrates based on hyperspectral imaging: Laboratory assessments
Researchers evaluated near-infrared hyperspectral imaging as a method for characterizing microplastics on filter substrates, finding that 11 plastic polymers exhibited distinct spectral features at specific wavelength ranges enabling automatic identification, and also assessed the spectral compatibility of 11 different filter substrate materials.
Developing and testing a workflow to identify microplastics using near infrared hyperspectral imaging
Researchers developed a near-infrared hyperspectral imaging workflow with an open spectral database to rapidly identify microplastics by polymer type, achieving over 88% accuracy for polypropylene, polyethylene, PET, and polystyrene particles larger than 500 micrometers.
Chemical Imaging of Microparticles with Raman, FTIR and Quantum Cascade Laser Microscopy
This study compared three chemical imaging techniques — Raman spectroscopy, FTIR microscopy, and quantum cascade laser microscopy — for identifying and sizing microplastic particles in environmental samples. Each method has different strengths in resolution, speed, and water compatibility, and the paper helps establish which tool is best suited for different monitoring contexts. Reliable identification methods are foundational to understanding how much microplastic contamination exists and what types pose the greatest risk.
Development of a Near-Infrared Imaging System for Identifying Microplastics in Water
Researchers developed a near-infrared imaging system capable of automatically identifying and characterizing microplastics suspended in water, successfully obtaining material identification images without the manual sorting typically required by conventional methods.
Quantification and characterization of microplastics in surface water samples from the Northeast Atlantic Ocean using laser direct infrared imaging
Researchers quantified microplastics in Northeast Atlantic Ocean surface waters using laser direct infrared imaging, detecting particles down to 20 micrometers and revealing microplastic concentrations and polymer compositions across eight sampling locations.
A high-throughput, automated technique for microplastics detection, quantification, and characterization in surface waters using laser direct infrared spectroscopy
Researchers applied laser direct infrared spectroscopy in a high-throughput automated workflow to detect, quantify, and characterize microplastics in surface water from three urban creeks in Ohio. The method achieved 88.3% recovery and could identify particles as small as 20 micrometers by polymer type, size, and shape without manual intervention.