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61,005 resultsShowing papers similar to Optimizing spectral classification and oxidation estimation of environmental Microplastics
ClearOptimizing spectral classification and oxidation estimation of environmental Microplastics
Researchers performed an intercalibration exercise to optimize spectral classification and oxidation estimation methods for weathered environmental microplastics, finding that spectral libraries built from weathered particles improve polymer type identification accuracy compared to libraries based on pristine reference materials.
Optimizing microplastic analysis through comparative FTIR and raman spectroscopy: Addressing challenges in environmental degradation studies
Researchers compared FTIR and Raman spectroscopy for analyzing degraded microplastic polymers in environmental samples, evaluating how polymer aging affects identification accuracy. The study found that spectral databases based on pristine polymers can misidentify weathered microplastics, calling for updated reference libraries.
Optimizing microplastic analysis through comparative FTIR and raman spectroscopy: Addressing challenges in environmental degradation studies
This study optimized microplastic analysis by comparing FTIR and Raman spectroscopy approaches for identifying degraded polymer particles in environmental samples where photooxidation and mechanical fragmentation have altered spectral signatures. A combined spectroscopy approach outperformed either technique alone for accurately identifying degraded microplastics in complex environmental matrices.
Challenges of Raman spectra to estimate carbonyl index of microplastics: A case study with environmental samples from sea surface
Researchers assessed the feasibility of using carbonyl index (CI) values from Raman spectra as an indicator of polyethylene microplastic degradation, comparing them to CI values from FTIR spectra on the same environmental seawater samples. Despite some correlations observed between the two methods, the weak functional relationships suggest Raman CI cannot reliably substitute for FTIR CI as a degradation indicator.
Enhanced Identification of Weathered Plastics Through the Improvement of Infrared Spectral Libraries
Researchers developed an improved infrared spectral library specifically designed to identify weathered and degraded plastics that conventional libraries often misidentify. The new library increased match rates by 7.3% for thermally oxidized plastics and improved identification of mechanically abraded samples, addressing a significant gap in accurate microplastic detection and environmental risk assessment.
μATR-FTIR Spectral Libraries of Plastic Particles (FLOPP and FLOPP-e) for the Analysis of Microplastics
Researchers developed two novel FTIR spectral libraries (FLOPP and FLOPP-e) specific to microplastic particles, including weathered samples, demonstrating improved spectral matching accuracy for identifying environmental microplastics compared to conventional polymer databases.
Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research
This review critically evaluates image analysis and spectroscopic methods used to identify and classify microplastics, including optical microscopy, electron microscopy, FTIR, and Raman spectroscopy. The authors highlight the need for standardized color classification, improved spectral libraries, and shared data tools to make microplastics studies more comparable.
Fourier-Transform Infrared Spectroscopy of Environmentally Weathered Textile Fabrics for Enhanced Microplastic Identification
This study used infrared spectroscopy to identify microplastic fibers from clothing that had been weathered by ocean conditions, finding that environmental aging makes spectral identification more difficult. Accurate detection of these aged fibers is essential for understanding the true scale of textile microplastic pollution in the ocean.
Inter-equipment reliable identification of microplastics by micro-FTIR using low computational resources
Researchers developed a low-computational-resource method for reliable microplastic identification by micro-FTIR spectroscopy that performs consistently across different instruments. The approach, funded under the EU PlasticTrace metrology project, addresses inter-equipment variability — a major barrier to harmonized microplastic monitoring — enabling more comparable results across laboratories.
Inter-equipment reliable identification of microplastics by micro-FTIR using low computational resources
Researchers developed a low-computational-resource method for reliable microplastic identification by micro-FTIR spectroscopy that performs consistently across different instruments. The approach, funded under the EU PlasticTrace metrology project, addresses inter-equipment variability — a major barrier to harmonized microplastic monitoring — enabling more comparable results across laboratories.
Degradation degree analysis of environmental microplastics by micro FT-IR imaging technology
Researchers used micro-FTIR spectral-image fusion to classify the degradation degree of polyethylene microplastics collected from coastal environments, achieving 97.1% classification accuracy and enabling estimation of environmental persistence time from spectral data.
Automatic microplastic classification using dual-modality spectral and image data for enhanced accuracy
A dual-modality classification system combining FTIR spectral data and microscope images achieved 99% accuracy in automatically identifying five common microplastic polymer types. The study deployed a web application (MPsSpecClassify) that enables researchers to efficiently classify microplastics, addressing the time-consuming and error-prone nature of manual spectral analysis.
Development of a rapid detection protocol for microplastics using reflectance-FTIR spectroscopic imaging and multivariate classification
Reflectance-FTIR spectroscopy was evaluated as a faster and more automated detection method for microplastics in environmental samples, with results showing strong potential for high-throughput screening. The method could reduce the time and cost of routine microplastic monitoring programs.
A New Chemometric Approach for Automatic Identification of Microplastics from Environmental Compartments Based on FT-IR Spectroscopy
Researchers developed a new chemometric approach for automatic identification of microplastics from environmental samples, designed to handle the challenges of biofilm contamination and surface aging that typically impede standard spectroscopic characterisation methods.
Handheld portable FTIR spectroscopy for the triage of micro and meso sized plastics in the marine environment incorporating an accelerated weathering study and an aging estimation
Researchers tested a handheld portable FTIR spectrometer for rapidly identifying micro and mesosized plastic debris on beaches and in the marine environment. Portable FTIR devices enable fast field identification of plastic polymer types, making marine litter surveys more efficient.
Characterizing photochemical ageing processes of microplastic materials using multivariate analysis of infrared spectra
Researchers tracked how four common plastic types weather under UV light and sunlight over six months, using infrared spectroscopy and multivariate analysis to characterize surface chemistry changes. They found that polypropylene weathered fastest, while all plastics showed photooxidation at different rates depending on light source. The study proposes a multivariate spectral approach as a more broadly applicable method than the traditional carbonyl index for assessing microplastic aging.
Toward the Systematic Identification of Microplastics in the Environment: Evaluation of a New Independent Software Tool (siMPle) for Spectroscopic Analysis
A new free software tool called siMPle was developed to standardize microplastic identification from FTIR spectroscopy across instruments from different manufacturers, using a shared database and automated analysis pipeline. Testing across four different instrument types confirmed the tool produces consistent and comparable results, addressing a major bottleneck in microplastics monitoring.
Validated spreadsheet for the identification of PE, PET, PP and PS microplastics by micro-ATR-FTIR spectra with known uncertainty
Researchers developed and validated a spreadsheet tool for identifying four common microplastic polymer types (PE, PET, PP, PS) from micro-ATR-FTIR spectra, providing a reproducible method with quantified uncertainty for environmental monitoring.
Impact of weathering on the chemical identification of microplastics from usual packaging polymers in the marine environment
The impact of environmental weathering on the chemical identification of common microplastics was investigated, examining how UV radiation, mechanical abrasion, and microbial activity alter the spectroscopic signatures used for polymer identification. Weathered plastics were harder to correctly identify than pristine ones, highlighting the need for reference libraries that include aged material.
A Comparative Study of Machine Learning and Deep Learning Models for Microplastic Classification using FTIR Spectra
Researchers compared machine learning and deep learning models for classifying microplastics using FTIR spectra, evaluating multiple algorithmic approaches against standardised spectral datasets. The study assessed classification accuracy and computational efficiency, identifying which model architectures best discriminate between polymer types in environmental microplastic samples.
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.
Machine learning based workflow for (micro)plastic spectral reconstruction and classification
A machine learning pipeline combining two spectral reconstruction models with four classification algorithms can identify microplastic polymer types from spectral data with up to 98% accuracy on processed spectra. Applied to real environmental samples, the best model achieved 71% top-one accuracy and over 90% top-three accuracy. Automated, high-accuracy microplastic identification tools are critical for scaling up environmental monitoring and making large-scale surveys practical.
Optimized recognition of microplastic ATR-FTIR spectra with deep learning
Researchers developed an optimized deep learning method for identifying microplastics from ATR-FTIR spectra, improving classification accuracy for weathered and environmentally contaminated MP samples that challenge standard spectral library matching approaches.
Analytical tools in advancing microplastics research for identification and quantification across environmental media: from sample to insight
Researchers reviewed the analytical tools most commonly used for identifying and quantifying microplastics, focusing on FTIR and Raman spectroscopy as the two primary methods. The review compared their strengths and limitations and provided guidance for choosing between them based on particle size, sample matrix, and research objectives.