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Papers
61,005 resultsShowing papers similar to Permittivity‐Based Microparticle Classification by the Integration of Impedance Cytometry and Microwave Resonators
ClearRapid Differentiation between Microplastic Particles Using Integrated Microwave Cytometry with 3D Electrodes
Researchers developed a rapid microplastic identification system combining integrated microwave cytometry with 3D electrodes to differentiate single microparticles in the 14–20 micrometer range as they flow through a microfluidic channel. The system demonstrated the ability to distinguish particle types based on dielectric properties, offering a faster and flow-compatible alternative to conventional spectroscopic techniques for environmental microplastic monitoring.
Rapid Differentiation between Microplastic Particles Using Integrated Microwave Cytometry with 3D Electrodes
Researchers developed a microfluidic platform combining microwave capacitive sensing and resistive pulse sensing to rapidly differentiate between types of microplastic particles in liquid. Using 3D electrode arrangements, they successfully distinguished between polystyrene and polyethylene particles in the 10-24 micrometer range. The technology offers a promising approach for fast, flow-through microplastic detection in environmental water samples and biological fluids.
Detection of microplastics by microfluidic microwave sensing: An exploratory study
Researchers developed a compact microwave sensor on a microfluidic chip to detect microplastics in water samples. The system works by measuring how the presence of plastic particles changes the electrical properties of water. While the technology shows promise as a rapid and portable detection method, its current sensitivity needs improvement before it can detect the low microplastic concentrations typically found in natural freshwater.
A Droplet-Based Microfluidic Impedance Flow Cytometer for Detection of Micropollutants in Water
A droplet-based microfluidic impedance cytometer was designed and tested for in-situ detection of microplastic particles in water, offering a portable and rapid alternative to laboratory-based analytical methods.
Microplastics Detection with Microfluidic Near-Field Microwave Sensors
A new microfluidic sensor integrating a microwave detector was developed that can identify microplastics in water in real time without labelling, by measuring how particles change the dielectric properties of the water flowing through the device. This kind of low-cost, continuous-monitoring sensor could make routine environmental surveillance for microplastic contamination more practical.
A microfluidic approach for label-free identification of small-sized microplastics in seawater
Researchers developed a microfluidic approach for label-free identification of small microplastics in seawater, using impedance-based detection to distinguish different polymer types without chemical labeling, enabling faster and more practical environmental monitoring.
Microfluidic Microwave Sensor for Rapid Detection of Microplastics in Water: Optimization, Modeling, and Performance Evaluation
Researchers developed a microfluidic sensor that uses microwave technology to rapidly detect microplastics in water samples without physical contact. The sensor was optimized to distinguish between different concentrations and sizes of plastic particles with high sensitivity. The technology could enable faster and more practical on-site monitoring of microplastic contamination in water supplies.
Based on a size of Microplastics, Multi-Channel Microwave Resonant MEMS Sensor
Researchers designed a multi-channel MEMS sensor that can simultaneously measure the concentration of microplastics and sort them by size using microwave resonance technology. This miniaturized detection approach addresses a key technical challenge in microplastic monitoring — the need for rapid, size-resolved quantification at low concentrations in water.
Microwave Cytometry with Machine Learning for Shape-Resolved Microplastic Detection
Researchers developed a microwave cytometry platform paired with a random forest model trained on microscopy-derived shape data to electronically determine the major and minor axes of ellipsoidal microplastic particles with less than 8% average error, removing the spherical-particle assumption that limits existing flow-through sensors.
Size and concentration characterization of microplastic particles in aqueous samples using sensitivity-enhanced coupled planar microwave resonators
Researchers developed a novel microwave sensing platform for real-time detection and characterization of microplastic particles in water samples. The sensor uses an enhanced coupled planar microwave resonator design with a low-cost disposable sample holder, enabling rapid, non-destructive measurement of microplastic particle size and concentration without cross-contamination between tests.
Approaches to Detect Microplastics in Water Using Electrical Impedance Measurements and Support Vector Machines
Researchers developed an electrical impedance spectroscopy method enhanced with machine learning to detect microplastics in water, achieving over 98% classification accuracy for stationary samples and over 85% for dynamic flow measurements across different plastic materials and particle sizes.
Discrimination of Microplastics and Phytoplankton Using Impedance Cytometry
Researchers demonstrated that impedance cytometry can discriminate between microplastics and phytoplankton in ocean water samples. The study suggests this technique could enable high-throughput, deployable monitoring of both plankton communities and microplastic pollution levels, addressing a key gap in current marine monitoring capabilities.
Measuring Microplastic Concentrations in Water by Electrical Impedance Spectroscopy
Researchers developed a method using electrical impedance spectroscopy to measure microplastic concentrations in water samples without requiring complex laboratory equipment. The technique can distinguish between different concentrations and types of plastic particles based on their electrical properties. The study offers a potentially faster and more accessible approach for routine microplastic monitoring in water treatment and environmental settings.
RF MEMS Resonance Sensor for Measuring Microplastics Concentration
Researchers designed an RF MEMS resonance sensor capable of detecting microplastics in water at low cost, offering a practical alternative to expensive conventional particle analyzers for environmental monitoring.
A Microwave-Based Sensing Platform for Microplastic Detection and Quantification: A Machine Learning-Assisted Approach
Researchers developed a low-cost microwave sensor combined with machine learning to detect and quantify microplastics in water and identify polymer types in unknown samples. The platform achieved the highest sensitivity reported among microwave-based approaches for microplastic detection, offering a promising low-cost alternative to spectroscopy-based methods.
Microplastic Identification Using Impedance Spectroscopy and Machine Learning Algorithms
Scientists developed a new method to detect and classify microplastics in water using electrical measurements and machine learning. The system can identify different sizes of PET microplastic particles with high accuracy, offering a potential tool for real-time water quality monitoring. Better detection methods like this are important for understanding how much microplastic contamination exists in drinking water and other water sources.
Focusing, sorting, and separating microplastics by serial faradaic ion concentration polarization
Researchers demonstrated a microfluidic technique that uses electric fields to continuously separate two types of microplastic particles in flowing water. This lab-on-chip approach could be developed into tools for monitoring or removing specific microplastic types from water treatment systems.
Microplastics detection with microfluidics integrated with a microwave sensor
Researchers developed a microwave sensor integrated with a microfluidic channel for real-time microplastics detection in water, using finite-element simulations to optimize sensitivity and validating performance experimentally. The system achieved a sensitivity of 0.1 dB and detected microplastics as small as 600 micrometers through measurement of reflected signal variations.
A Magnetic Levitation System for Range/Sensitivity-Tunable Measurement of Density
Researchers developed a magnetic levitation (MagLev) system capable of measuring the density of small objects across a tunable range of sensitivity. The system can identify materials by their density, which has applications for sorting and identifying microplastics by polymer type. A versatile density-measurement tool could streamline microplastic characterization in environmental samples.
High-PrecisionRefractive Index-Based MicroparticleSorting Using Airy Beams
Researchers proposed an Airy beam-based optical sorting technique to separate microparticles by refractive index, enabling discrimination between particles of similar size but different composition. The method showed promise for identifying microplastic particles in complex mixtures and for medical diagnostic applications.
High-PrecisionRefractive Index-Based MicroparticleSorting Using Airy Beams
Researchers proposed an Airy beam-based optical sorting technique to separate microparticles by refractive index, enabling discrimination between particles of similar size but different composition. The method showed promise for identifying microplastic particles in complex mixtures and for medical diagnostic applications.
High-PrecisionRefractive Index-Based MicroparticleSorting Using Airy Beams
Researchers proposed an Airy beam-based optical sorting technique to separate microparticles by refractive index, enabling discrimination between particles of similar size but different composition. The method showed promise for identifying microplastic particles in complex mixtures and for medical diagnostic applications.
High-PrecisionRefractive Index-Based MicroparticleSorting Using Airy Beams
Researchers proposed an Airy beam-based optical sorting technique to separate microparticles by refractive index, enabling discrimination between particles of similar size but different composition. The method showed promise for identifying microplastic particles in complex mixtures and for medical diagnostic applications.
High-PrecisionRefractive Index-Based MicroparticleSorting Using Airy Beams
Researchers proposed an Airy beam-based optical sorting technique to separate microparticles by refractive index, enabling discrimination between particles of similar size but different composition. The method showed promise for identifying microplastic particles in complex mixtures and for medical diagnostic applications.