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Papers
61,005 resultsShowing papers similar to Trapping tiny pollutants: SERS-driven strategies for microplastics and nanoplastics detection
ClearLatest Advances and Developments to Detection of Micro‐ and Nanoplastics Using Surface‐Enhanced Raman Spectroscopy
This review examines the latest developments in using surface-enhanced Raman spectroscopy (SERS) to detect micro- and nanoplastics in various environmental samples. Researchers found that SERS offers significantly improved sensitivity compared to conventional methods, enabling detection of smaller plastic particles. The study suggests that SERS-based approaches hold promise for advancing nanoplastic detection, though challenges around standardization and reproducibility remain.
Strategies and Challenges of Identifying Nanoplastics in Environment by Surface-Enhanced Raman Spectroscopy
Researchers reviewed the use of surface-enhanced Raman spectroscopy (SERS) as a tool for detecting nanoplastics, which are plastic particles smaller than one micrometer. The study found that SERS offers high sensitivity for identifying individual nanoparticles, but significant challenges remain in applying this technique to complex environmental samples. The review outlines strategies for improving SERS-based nanoplastic detection to better assess environmental and health risks.
A review of recent progress in the application of Raman spectroscopy and SERS detection of microplastics and derivatives
This review covers advances in using Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) to detect and identify microplastics in the environment. These techniques offer high resolution and sensitive detection that can identify specific plastic types even at very small sizes. Better detection methods are essential for understanding the true extent of microplastic contamination and its potential risks to human health.
Advances in Surface‐Enhanced Raman Spectroscopy for Detection of Aquatic Environmental Pollutants
This review examines surface-enhanced Raman scattering (SERS) as a technique for detecting aquatic pollutants, highlighting its exceptional sensitivity and molecular fingerprinting capability for identifying microplastics and other contaminants at trace concentrations.
In situ surface-enhanced Raman spectroscopy for detecting microplastics and nanoplastics in aquatic environments
This study evaluated surface-enhanced Raman spectroscopy (SERS) as a method for detecting and identifying microplastics and nanoplastics in aquatic environments, demonstrating its potential for detecting particles too small for conventional spectroscopy while noting remaining challenges for field deployment.
Advanced microplastic monitoring using Raman spectroscopy with a combination of nanostructure-based substrates
Researchers reviewed advances in Raman spectroscopy and surface-enhanced Raman scattering (SERS) — a technique that amplifies light signals using metallic nanostructures — for detecting micro- and nanoplastics at trace concentrations in environmental samples, highlighting new plasmonic materials, 3D substrates, and microfluidic chip platforms that enable on-site monitoring.
Research Progress of Surface-Enhanced Raman Scattering (SERS) Technology in Food, Biomedical, and Environmental Monitoring
This review covers advances in SERS (Surface-Enhanced Raman Scattering) technology, a powerful detection method that can identify trace amounts of contaminants at the molecular level. The technology has been applied to detecting microplastics, pesticide residues, heavy metals, and disease biomarkers in food, medical, and environmental samples. Better detection tools like SERS are important because they could help scientists measure exactly how much microplastic contamination is present in food and water.
Superhydrophobic Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Sensitive Detection of Trace Nanoplastics in Water
Researchers developed a new method to detect extremely small nanoplastics in water by combining a water-repelling surface that concentrates particles with a technique called SERS that amplifies their chemical signal. The method can identify common nanoplastics like polystyrene and PMMA at very low concentrations, which is an important step toward monitoring these tiny pollutants that are difficult to detect with current tools.
Integrating Metal Phenolic Networks-Mediated Separation and Machine Learning-Aided SERS for High-Precision Quantification and Classification of Nanoplastics
Scientists combined metal-phenolic network chemistry — which rapidly concentrates and captures nanoplastics — with machine-learning-enhanced surface-enhanced Raman spectroscopy (SERS) to accurately identify and quantify nanoplastics at very low environmental concentrations. This integrated approach addresses one of the biggest technical obstacles in nanoplastic research: detecting particles that are too small and too sparse for conventional methods to reliably find.
Advancing SERS-based detection of micro and nanoplastics in Agroecosystems: Current progress, challenges, and future directions
This review examines the potential of surface-enhanced Raman spectroscopy (SERS) as a point-of-care detection tool for micro- and nanoplastics in agroecosystems, highlighting its sensitivity advantages over conventional methods. It covers SERS substrate design, pre-treatment strategies, and recent applications in soil and plant matrices.
Breaking the Size Barrier: SERS-Based Ultrasensitive Detection and Quantification of Polystyrene Plastics in Real Water Samples
Researchers developed a surface-enhanced Raman spectroscopy (SERS) method capable of detecting and quantifying polystyrene plastic particles of various sizes — including nanoplastics — in real environmental water samples at ultrasensitive concentrations.
On-Site Detection of Nanoplastics in Liquid Phase by SERS Method
Researchers developed an on-site detection method for nanoplastics in liquid samples using surface-enhanced Raman spectroscopy (SERS), achieving sensitive identification without the laboratory infrastructure required by conventional GC-MS approaches. The SERS method successfully differentiated nanoplastic types in environmental water samples, offering a practical tool for rapid field-deployable nanoplastic monitoring.
Imaging and identification of single nanoplastic particles and agglomerates
Scientists used a surface-enhanced Raman scattering (SERS) technique to detect and identify individual nanoplastic particles as small as 100 nanometers, a size range that has been extremely difficult to measure with existing methods. The approach can distinguish between single particles and clumps, and works significantly faster than previous imaging techniques. The study represents a meaningful advance in nanoplastic detection that could help researchers better understand the true extent of nanoplastic pollution.
Identification of polystyrene nanoplastics using surface enhanced Raman spectroscopy
Researchers demonstrated for the first time that surface-enhanced Raman spectroscopy (SERS) using silver nanoparticles can identify polystyrene nanoplastics as small as 50 nm in real water samples, providing a rapid detection method that bypasses conventional sample preparation and could advance environmental monitoring of nanoplastics previously invisible to standard analytical techniques.
Highly sensitive superhydrophobic SERS substrate combined with machine learning for precise identification and classification of nanoplastics
Researchers fabricated a superhydrophobic surface-enhanced Raman scattering (SERS) substrate that concentrates nanoplastics in a tiny detection zone, then combined it with machine learning to identify seven types of nanoplastics in real lake water with 99.88% accuracy, offering a practical high-throughput environmental monitoring approach.
Detection of Polystyrene Microplastics up to the Single Nanoparticle Limit Using SERS and Advanced ANN Design (KANformer)
Researchers developed a new detection method that can identify a single polystyrene nanoparticle using surface-enhanced Raman spectroscopy combined with an advanced machine learning algorithm. By heating microplastic samples to melt them into plasmonic hot spots on a sensor surface, they overcame a key limitation of previous detection approaches. The technique also works for other common plastics like polyethylene and polypropylene, offering a powerful tool for monitoring microplastic contamination at extremely low concentrations.
Surface-Enhanced Raman Spectroscopy Facilitates the Detection of Microplastics <1 μm in the Environment
Researchers developed a method using surface-enhanced Raman spectroscopy to detect and identify individual microplastic particles smaller than one micrometer. This technique addresses a major gap in environmental monitoring, since most current methods cannot reliably detect the smallest microplastics that may pose the greatest risk due to their ability to enter cells and tissues.
Development of SERS metal sensors
This French-language doctoral thesis reviews the development of SERS-based metal sensors for detecting environmental pollutants. Surface-enhanced Raman spectroscopy is an emerging analytical tool for identifying and measuring microplastics and chemical contaminants in environmental samples.
Optical innovations in microplastic analysis: a critical review of detection strategies
This review surveys advances in optical methods for microplastic detection, including spectroscopic techniques, imaging systems, and sensor technologies. Researchers found that emerging approaches like surface-enhanced Raman spectroscopy combined with machine learning are enhancing automation and detection accuracy. The study identifies the need for standardized protocols and improved techniques to handle the challenges of detecting microplastics in complex environmental and biological samples.
Plasmonic-based Raman sensor for ultra-sensitive detection of pharmaceutical waste
This paper is not relevant to microplastics research; it describes a plasmonic Raman sensor for detecting pharmaceutical contaminants in water and food — the sensor uses surface-enhanced Raman spectroscopy (SERS) but is focused on pharmaceutical waste, not plastic particles.
Hydrophobicity-driven self-assembly of nanoplastics and silver nanoparticles for the detection of polystyrene microspheres using surface enhanced Raman spectroscopy
Researchers developed a highly sensitive method for detecting nanoplastic particles using surface-enhanced Raman spectroscopy (SERS) on a super-hydrophobic (water-repelling) surface that concentrates the particles into a small spot. The technique detected polystyrene nanoplastics at concentrations as low as 0.5 mg/L, far below what conventional approaches can achieve. Better detection tools for nanoplastics are urgently needed since these ultra-small particles are the hardest to find yet potentially the most biologically hazardous fraction of plastic pollution.
Detection of Polystyrene Microplastics up to the SingleNanoparticle Limit Using SERS and Advanced ANN Design (KANformer)
Researchers developed a surface-enhanced Raman spectroscopy (SERS) platform combined with a KANformer neural network to detect polystyrene microplastics down to the single nanoparticle level, offering a highly sensitive monitoring tool for environmental plastic contamination.
Quantitative analysis of microplastics in seawater based on SERS internal standard method
Researchers developed a new method using surface-enhanced Raman scattering (SERS) to quantitatively detect microplastics in seawater. By using an internal standard approach, they improved accuracy compared to existing techniques that struggle with particles smaller than one micrometer. The method offers a more sensitive and practical way to measure microplastic concentrations in marine environments.
Co-Self-Assembled Monolayer Enables Sensitive SERS Detection of Nanoplastics via Spontaneous Hotspot Entrapment
Researchers developed a new detection method that can identify and measure nanoplastics at concentrations as low as 0.01 micrograms per milliliter by trapping the tiny particles within a single layer of silver nanoparticles. The technique uses surface-enhanced Raman scattering, which amplifies the chemical signal of nanoplastics that are spontaneously captured in the detection hotspots. This approach offers a faster and more sensitive way to monitor nanoplastic pollution in water compared to existing methods.