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Papers
61,005 resultsShowing papers similar to Design and Development of an Advanced Sensor Prototype for the Detection of Microplastics
ClearA Portable Optical Sensor for Microplastic Detection: Development and Calibration
Researchers built a portable, low-cost optical sensor prototype designed to detect microplastics by shining multiple wavelengths of light through water samples. The device measures how different plastic particles absorb and scatter light, producing color spectra that can help identify microplastics. The sensor offers an affordable field-deployable option for environmental monitoring, with potential future improvements using machine learning for automated identification.
Eco-Sensing System for Water Pollution and Microplastic Detection
This study evaluates new sensor-based and spectroscopic technologies for detecting microplastics in water in real time, comparing them with traditional lab-based methods. The portable systems showed improved accuracy and efficiency for field use, making it possible to monitor microplastic contamination as it happens. Better detection tools are essential for protecting drinking water sources and understanding the true scale of human microplastic exposure.
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.
Field-Portable Microplastic Sensing in Aqueous Environments: A Perspective on Emerging Techniques
This review examines emerging field-portable technologies for detecting and quantifying microplastics in aqueous environments, discussing optical, spectroscopic, and electrochemical sensing approaches. Researchers identify the lack of a standardized, rapid on-site method as the primary bottleneck limiting accurate real-world microplastic monitoring.
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.
The power of a multi-technique approach for the reliable quantification of microplastics in water
Researchers applied a multi-technique analytical approach combining several spectroscopic and microscopic methods to improve the reliability of microplastic quantification in environmental samples. The combined approach reduced false positives and improved polymer identification accuracy compared to any single method used alone.
Innovative Approaches for Microplastic Pollution Detection and Remediation in Aquatic Ecosystems
This study evaluated new technologies for detecting and cleaning up microplastic pollution in water environments, including advanced spectroscopy, sensor-based detection, bioremediation, and improved filtration systems. Researchers found that these innovative approaches significantly outperformed traditional methods in both identifying and removing microplastics. The work highlights the potential for emerging technologies to provide more effective solutions for tackling plastic pollution in rivers, lakes, and oceans.
A prototype of a portable optical sensor for the detection of transparent and translucent microplastics in freshwater
Researchers developed a portable prototype optical sensor capable of detecting transparent and translucent microplastics in freshwater by simultaneously measuring specular laser light reflection and transmission, offering a feasibility pathway for field-deployable microplastic monitoring.
Portable On-Site Optical Detection and Quantification of Microplastics
Researchers built a portable, on-site optical device to detect and quantify microplastics in water. The device addresses the challenge of detecting small, often translucent particles without a laboratory setting. Portable microplastic detection tools could enable real-time monitoring in the field, supporting faster environmental assessments.
Microplastic Detection in Water Using a Sensor Network, An Electronic Tongue and Spectroscopy Impedance
Researchers developed an electronic sensor system using impedance spectroscopy to detect microplastics in drinking water without needing expensive laboratory equipment. By running 160 experiments with different water contaminant combinations, they showed that the technique can distinguish microplastic contamination using electrochemical signals and statistical analysis. Affordable, portable detection systems like this are important for monitoring water supplies in regions where lab infrastructure is limited.
Compact low-cost sensor for microplastics detection and classification in marine and aquatic environments
Researchers developed a compact, low-cost sensor for detecting and classifying microplastics in marine and aquatic environments, designed to reduce the economic burden of MP monitoring along coastlines and enable more frequent and scalable environmental surveillance.
Compact low-cost sensor for microplastics detection and classification in marine and aquatic environments
Researchers developed a compact, low-cost sensor for detecting and classifying microplastics in marine and aquatic environments, designed to reduce the economic burden of MP monitoring along coastlines and enable more frequent and scalable environmental surveillance.
Raman Spectroscopy and Machine Learning for Microplastics Identification and Classification in Water Environments
Researchers combined Raman spectroscopy with machine learning algorithms for automated identification and classification of microplastics in water environments, achieving high accuracy in distinguishing different polymer types based on spectral fingerprints.
A Microwave-Based Sensing Platform for Microplastic Detection and Quantification: A Machine Learning-Assisted Approach
Researchers developed a low-cost microwave spiral sensor that can detect and differentiate three common types of microplastic (PTFE, PVC, PET) in water, achieving the highest sensitivity reported for microwave-based approaches and using machine learning to identify unknown polymer types. Affordable, reliable detection tools like this are critical for routine environmental monitoring of microplastic contamination in drinking water and waterways.
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.
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.
Identifying microplastic contamination in drinking water: analysis and evaluation using spectroscopic methods
Researchers developed analytical methods to identify and quantify microplastic contamination in drinking water, evaluating extraction efficiency and detection accuracy across different water types and plastic particle sizes. The study assessed health implications based on measured plastic loads in treated water.
Detection and identification of microplastics directly in water by hyperspectral imaging
Researchers used hyperspectral imaging to identify different types of microplastics mixed together in water, demonstrating that the technique can distinguish polymer types based on their spectral signatures. This non-destructive, real-time method could improve the speed and accuracy of microplastic monitoring in water samples.
The development and application of advanced analytical methods in microplastics contamination detection: A critical review
This review evaluated advanced analytical methods for detecting microplastic contamination, covering techniques from visual identification and spectroscopy to emerging approaches, and highlighted the need for standardized, efficient methods to improve environmental monitoring.
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.
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.
Rapid Monitoring Approach for Microplastics Using Portable Pyrolysis-Mass Spectrometry
Researchers developed a rapid monitoring method for microplastics using a portable pyrolysis-mass spectrometry system that can identify polymer types and quantify particles smaller than 5 mm in the field without lengthy laboratory preparation. The approach offers a promising tool for fast, on-site microplastic surveillance in environmental samples.
Portable Multichannel Measurement System for Real-Time Microplastics Assessment Using Microwave Sensors
Scientists developed a portable multichannel electronic system that uses microwave sensors to detect microplastics in water in real time, capable of simultaneously reading up to four sensors targeting particles of different sizes. The system combines radio-frequency integrated circuits with signal-conditioning hardware for field-deployable monitoring. This kind of low-cost, portable sensing technology could make routine microplastic screening much more practical at waterways and treatment facilities.
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.