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Papers
61,005 resultsShowing papers similar to Assessment of the Electrostatic Separation Effectiveness of Plastic Waste Using a Vision System
ClearTribo-Electrostatic Separation Analysis of a Beneficial Solution in the Recycling of Mixed Poly(Ethylene Terephthalate) and High-Density Polyethylene
Researchers optimized an electrostatic separation process for sorting PET and HDPE plastic particles, testing how different parameters affect separation efficiency for recycling. Improving plastic sorting technology is key to increasing recycling rates and reducing the amount of plastic waste that ultimately degrades into environmental microplastics.
Application of AI-Enabled Computer Vision Technology for Segregation of Industrial Plastic Wastes
Researchers developed an AI-powered computer vision system to segregate mixed industrial plastic wastes by polymer type, addressing a key barrier to effective plastic recycling. The system achieved high classification accuracy across common plastic categories, demonstrating that machine vision can improve sorting efficiency and recycled plastic quality.
A new approach in separating microplastics from environmental samples based on their electrostatic behavior
Researchers developed a novel electrostatic separation method to isolate microplastics from environmental matrices based on differences in electrostatic behavior between plastic particles and natural materials. The technique offers a low-cost, chemical-free approach to microplastic extraction that could complement or replace existing density separation methods in some applications.
Enhanced density separation efficiency of microplastics in presence of nonionic surfactants
Scientists improved the density-separation technique for sorting mixed microplastics by adding nonionic surfactants, boosting the purity of separated polymer types from as low as 69% to up to 96%. Better sorting methods are essential for both accurately measuring microplastic contamination and enabling recycling of plastic waste streams.
Advancing Plastic Waste Classification and Recycling Efficiency: Integrating Image Sensors and Deep Learning Algorithms
Researchers developed a deep learning approach combined with image sensors to improve plastic waste classification and recycling efficiency. The study demonstrates that this method can distinguish between chemically similar plastics like PET and PET-G that conventional near-infrared spectroscopy struggles to differentiate, potentially improving automated sorting systems.
Evaluation of Marker Materials and Spectroscopic Methods for Tracer-Based Sorting of Plastic Wastes
Researchers evaluated fluorescent and photoluminescent marker materials for tracer-based sorting of plastic waste, finding that spectroscopic detection methods could enable more precise identification of polymer types to improve recycling rates.
Evaluation of Electrostatic Separation of Microplastics From Mineral-Rich Environmental Samples
This study evaluated electrostatic separation as a technique for extracting microplastics from mineral-rich environmental samples like soil and sediment, finding that recovery rates varied significantly by polymer type. Electrostatic separation shows promise for processing large sample volumes but requires further optimization before it can be reliably used for routine microplastic monitoring.
Challenges to Increase Plastic Sorting Efficiency
This paper reviews the current challenges and future opportunities for improving plastic sorting rates in waste management systems. Higher sorting rates are essential for increasing plastic recycling and reducing the amount of plastic that ends up fragmented into microplastics in the environment.
Stepwise flotation separation of WEEE plastics by polymeric aluminum chloride towards source control of microplastics
Researchers developed a stepwise flotation separation process using polymeric aluminum chloride to sort and recover mixed plastics from waste electrical and electronic equipment (WEEE), demonstrating improved separation efficiency and positioning the approach as a strategy to reduce microplastic pollution from e-waste mismanagement.
Utilizing Electrosorptionfor Efficient Removal ofPolyethylene Microplastics from Water: Critical Factors and MechanisticInsights
An electrosorption method was developed to remove polyethylene microplastics from wastewater, demonstrating improved removal efficiency compared to conventional treatment, especially for smaller particles that typically escape standard wastewater treatment plants.
Removal of Microplastics from Wastewater by Methods of Electrocoagulation and Adsorption
This review examines electrocoagulation and adsorption methods for removing microplastics from wastewater, comparing them against conventional physical, chemical, and biological approaches in terms of removal efficiency, cost, and practical scalability.
Removal of microplastics from wastewater through electrocoagulation-electroflotation and membrane filtration processes
Researchers investigated electrocoagulation-electroflotation and membrane filtration for removing microplastics from wastewater, finding that combining these processes effectively recovers microplastic particles from treatment plant effluent.
The potential of NIR spectroscopy in the separation of plastics for pyrolysis
This study examined the potential of near-infrared (NIR) spectroscopy to identify and sort different plastic types for chemical recycling, finding it can effectively distinguish major polymer types. Better plastic sorting technology could improve recycling rates and reduce the amount of plastic that ends up as environmental microplastic pollution.
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.
Comparative Study of Chemometric Approaches and Machine Learning for Miniaturized Near-infrared (micronir) Spectroscopy in Plasticwaste Sorting
This study tested a miniaturized near-infrared (NIR) spectroscopy device combined with chemometric and machine learning methods to sort different types of plastic waste. The approach accurately identified polymer types, supporting more efficient plastic recycling operations that could reduce microplastic generation.
Chemical Recycling of Mixed Plastics in Electronic Waste Using Solvent-Based Processing
Researchers developed a solvent-based chemical recycling process capable of separating and recovering mixed plastics from electronic shredder residue, demonstrating that targeted solvent systems can selectively dissolve specific polymer types and enable higher-quality recycling of e-waste plastics.
Study of Micro-Plastics Separation From Sea Water With Electro-Magnetic Force
Researchers developed a method to remove microplastics from seawater using electromagnetic force, exploiting differences in electrical properties between plastics and water. The technique shows potential as a physical removal approach that avoids adding chemical agents to the marine environment.
Sorting microplastics from other materials in water samples by ultra-high-definition imaging
Researchers used a commercial particle analyzer with ultra-high-definition imaging to sort and identify microplastic particles in water samples. The device successfully distinguished between different plastic types based on how light scatters through or off their surfaces, and could separate microplastics from air bubbles and other non-plastic particles. The study demonstrates a relatively fast and accessible method for characterizing microplastic contamination in water.
Design and Development of Smart Beach Debris Collection and Segregation System
Researchers designed and built a smart automated system for collecting and segregating beach debris, using sensors and robotics to identify and sort plastic waste from natural material on shorelines. The system demonstrated effective separation of plastic debris in field tests.
The Study of Removal of Polyvinyl Chloride (PVC) Particles from Wastewater through Electrocoagulation
Researchers investigated electrocoagulation as a method for removing polyvinyl chloride (PVC) microplastic particles from wastewater, evaluating its efficiency as a low-cost treatment approach using simple chemicals and accessible equipment.
Evaluating the performance of electrocoagulation system in the removal of polystyrene microplastics from water
Researchers tested electrocoagulation, a water treatment method that uses electric current to clump particles together, for removing polystyrene microplastics from water. Using aluminum electrodes at neutral pH, they achieved over 90% removal efficiency. This technology could provide a practical and effective way to remove microplastics from drinking water and wastewater, reducing human exposure to these contaminants.
Removal of Microbeads from Wastewater Using Electrocoagulation
Researchers tested electrocoagulation as a method for removing microbeads from wastewater, finding it effectively reduced microbead concentrations and offering it as a promising complement to conventional wastewater treatment technologies.
Electrochemical treatment of wastewater to remove contaminants from the production and disposal of plastics: a review
Researchers reviewed electrochemical treatment methods for removing plastic-related contaminants from wastewater, including bisphenol A, phthalic acid esters, and benzotriazoles. The review confirmed that electrochemical treatments are a viable option for removing these persistent plastic contaminants, and assessed their effectiveness in terms of removal rates, transformation products, toxicity, and energy requirements.
Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning
Researchers used a portable near-infrared spectrometer combined with machine learning to rapidly identify and classify seven types of consumer plastic waste on-site without damaging the samples. Faster and cheaper plastic identification tools are important for improving plastic recycling efficiency and ultimately reducing the amount of plastic that ends up as microplastic pollution.