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Papers
20 resultsShowing papers similar to Development of a Compact and Portable Terahertz Imaging System for Industrial Applications
ClearOptical parameters extraction of soil and its microplastics contamination using terahertz spectroscopy
Researchers used terahertz spectroscopy to detect and quantify low-density polyethylene microplastics mixed into soil at different concentrations, finding that the technique could distinguish contaminated from clean soil based on changes in refractive index and signal attenuation. Terahertz spectroscopy is non-destructive and rapid, making it a potentially valuable tool for in-field soil microplastic screening without the need for laboratory extraction.
Towards a fast and generalized microplastic quantification method in soil using terahertz spectroscopy
Researchers compared terahertz and near-infrared spectroscopy for quantifying microplastics in soil, finding that terahertz spectroscopy offered a faster and more accurate approach than NIR for distinguishing household microplastics from standard reference polymers in soil matrices.
Study on Rapid Quantitative Detection of Soil MPs Based on Terahertz Time-Domain Spectroscopy
Researchers developed a rapid method for detecting and quantifying microplastics in soil using terahertz time-domain spectroscopy combined with machine learning algorithms. The classification models achieved high accuracy in identifying different types of microplastics including polyethylene, polystyrene, and polypropylene. The study suggests that terahertz spectroscopy could provide a faster and more efficient alternative to current methods for monitoring microplastic contamination in agricultural soils.
Microplastic detection in soil by THz Time-Domain hyperspectral imaging combined with unsupervised learning analysis
Researchers applied terahertz time-domain hyperspectral imaging combined with multiple unsupervised machine-learning algorithms to detect and spatially map low-density polyethylene microplastics in soil, demonstrating that all five methods consistently separated plastic from soil without requiring labeled training data, establishing a reference-free detection approach.
Detection of Microplastic in Salts Using Terahertz Time-Domain Spectroscopy
Researchers demonstrated that terahertz spectroscopy can detect microplastics embedded in table salt at different concentrations. This technology could offer a new non-destructive method for screening food products for microplastic contamination.
Identification and characterization of various plastics using THz-spectroscopy
Researchers used terahertz spectroscopy, which has reached spatial resolutions of a few micrometres and interacts with molecular vibrations without ionizing samples or damaging DNA, to identify and characterize various plastic types, demonstrating the technique's potential for building materials databases and biological imaging applications.
Characterizations of high-density polyethylene by terahertz time-domain spectroscopy
Researchers characterized the optical properties of high-density polyethylene (HDPE) particles using terahertz time-domain spectroscopy and found the method can distinguish different particle sizes and filler contents. The technique can also detect how HDPE adsorbs other substances onto its surface. Terahertz spectroscopy could be developed as a rapid, non-destructive tool for identifying and characterizing HDPE microplastics in environmental samples.
A field deployable imaging system for detecting microplastics in the aquatic environment
Researchers built a portable imaging system for detecting microplastics in water that can be deployed directly in the field rather than requiring laboratory analysis. The system uses a de-scattering algorithm to produce clear images even in turbid water conditions and can identify particles as small as 50 micrometers. This low-cost tool could make routine microplastic monitoring of rivers, lakes, and coastal waters much more practical and accessible.
Application of hyperspectral imaging technology in the rapid identification of microplastics in farmland soil
Researchers applied hyperspectral imaging technology combined with machine learning to rapidly screen and classify microplastics in farmland soil samples, demonstrating an efficient non-destructive identification method for soil microplastic contamination.
A novel way to rapidly monitor microplastics in soil by hyperspectral imaging technology and chemometrics
Hyperspectral imaging combined with chemometrics was demonstrated as a novel way to rapidly detect and map multiple types of microplastics in soil samples, identifying particles of different polymer types based on their spectral signatures. The approach could enable faster and more spatially detailed monitoring of microplastic contamination in agricultural and environmental soils.
Study on detection method of microplastics in farmland soil based on hyperspectral imaging technology
Researchers developed a method using hyperspectral imaging and machine learning to rapidly detect and classify different types of microplastics in farmland soil. The technology achieved high accuracy in identifying common plastic types like polyethylene and polypropylene in soil samples. Better detection tools like this are essential for monitoring microplastic contamination in agricultural land and understanding its potential impact on food safety.
Research on Identification and Classification Methods for Soil Microplastics in Hyperspectral Detection
Hyperspectral imaging was tested as a rapid, large-area detection method for identifying and classifying microplastics in soil, offering an alternative to time-consuming particle-by-particle Raman or FTIR spectroscopy. The approach could allow researchers to map microplastic distribution across soil samples far more efficiently. Faster detection technology is important for expanding the geographic scope of soil microplastic monitoring and for assessing contamination in agricultural land.
Accurate detection of low concentrations of microplastics in soils via short-wave infrared hyperspectral imaging
Researchers combined short-wave infrared hyperspectral imaging with machine learning algorithms to detect low concentrations of polyamide and polyethylene microplastics in soil samples, achieving accurate classification with implications for fast, non-destructive screening of agricultural land for plastic contamination.
Identification of the Compounds Used in Waste Bottle Caps Using Terahertz Radiation for Sustainable Resource Recycling to Benefit International Cooperation
Not relevant to microplastics — this study proposes using terahertz wave spectroscopy to distinguish between polypropylene and polyethylene plastic bottle caps, addressing the limitations of near-infrared sorting technology in recycling facilities and enabling higher-purity material recovery.
Efficient screening of microplastics in soils using hyperspectral imaging in the short-wave infrared range coupled with machine learning – A laboratory-based experiment
Researchers tested short-wave infrared hyperspectral imaging combined with machine learning to detect three types of microplastics in soil, finding it could identify elevated contamination but was not sensitive enough for typical environmental background levels. The technique shows most promise for screening heavily polluted sites like landfills and industrial areas.
Cost-Effective and Wireless Portable Device for Rapid and Sensitive Quantification of Micro/Nanoplastics
Researchers developed a wireless portable device for rapid quantification of micro- and nanoplastics in water samples, offering a field-deployable alternative to laboratory-based analysis for environmental monitoring.
Critical evaluation of hyperspectral imaging technology for detection and quantification of microplastics in soil
Researchers evaluated whether hyperspectral imaging technology can reliably detect and quantify microplastics in soil under varying real-world conditions. They found that near-infrared imaging generally works well but is significantly affected by factors like soil moisture, microplastic color, and particle size. The study recommends sorting microplastics by size before analysis and further research into moisture effects, providing the first comprehensive evaluation of this emerging detection technology for soil monitoring.
Rapid Detection of Microplastics in Plastic-covered Soil Using FT-NIR and ATR-FTIR Spectral Data Fusion
Scientists developed a new method to quickly detect tiny plastic particles in farm soil by combining two different light-based detection techniques. This method can accurately measure microplastic pollution in agricultural fields where plastic covers are used for growing crops. This matters because microplastics in farm soil can potentially enter our food chain through the fruits and vegetables we eat.
Rapid Detection of Microplastics in Plastic-covered Soil Using FT-NIR and ATR-FTIR Spectral Data Fusion
Scientists developed a faster way to detect tiny plastic particles in farm soil by combining two different scanning methods. This new technique can accurately measure microplastic pollution in agricultural fields where plastic covers are used to help crops grow. This matters because microplastics in farm soil can potentially enter our food supply, so having better detection methods helps us monitor and control this type of pollution.
Laboratory Designed Portable Device for Density Separation and Characterization of Microplastics in Environmental Soil Samples
Scientists designed a small, portable device for extracting microplastics from soil and sediment samples using a density separation method with different salt solutions, successfully isolating PET, LDPE, PVC, and PP from samples collected in school yards, lakesides, and agricultural fields. A portable, low-cost device lowers the barrier to field-based microplastic monitoring and could enable wider participation in pollution surveys.