AIMC Topic: Plastics

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Identifying plastic materials in post-consumer food containers and packaging waste using terahertz spectroscopy and machine learning.

Waste management (New York, N.Y.)
Accurate identification of plastic materials from post-consumer food container and packaging waste is crucial for enhancing the purity and added value of recycled materials, thereby promoting recycling and addressing the issue of plastic pollution. H...

A three-dimensional marine plastic litter real-time detection embedded system based on deep learning.

Marine pollution bulletin
Marine plastic pollution has emerged as a significant ecological and biological issue impacting global marine ecosystems. To develop real-time cleaning systems for marine plastic litter, we implemented a three-dimensional marine plastic litter real-t...

A systematic review of plastic recycling: technology, environmental impact and economic evaluation.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
In this systematic review, advancements in plastic recycling technologies, including mechanical, thermolysis, chemical and biological methods, are examined. Comparisons among recycling technologies have identified current research trends, including a...

Raman spectroscopy integrated with machine learning techniques to improve industrial sorting of Waste Electric and Electronic Equipment (WEEE) plastics.

Journal of environmental management
Current industrial separation and sorting technologies struggle to efficiently identify and classify a large part of Waste of Electric and Electronic Equipment (WEEE) plastics due to their high content of certain additives. In this study, Raman spect...

Efficient and stable extraction of nano-sized plastic particles enabled by bio-inspired magnetic "robots" in water.

Environmental pollution (Barking, Essex : 1987)
In this research, a rationally-designed strategy was employed to address the crucial issue of removing nano-plastics (NPs) from aquatic environments, which was based on fabricating sea urchin-like structures of FeO magnetic robots (MagRobots). Throug...

AI-based plastic waste sorting method utilizing object detection models for enhanced classification.

Waste management (New York, N.Y.)
The export ban on plastic waste by China has brought domestic plastic recycling to the forefront of environmental concerns, with sorting being a crucial step in the recycling process. This study assessed the performance of advanced AI models, Mask R-...

Extraction of agricultural plastic greenhouses based on a U-Net convolutional neural network coupled with edge expansion and loss function improvement.

Journal of the Air & Waste Management Association (1995)
Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more ...

Assessment of type and quantities of food and beverage plastic packaging: A case study.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Plastic pollution has been identified as one of the most pressing environmental issues of the 21st century, driven by excessive consumption and inadequate plastic waste management. This issue is particularly reflected in short lifespan of plastic pro...

Design of Recyclable Plastics with Machine Learning and Genetic Algorithm.

Journal of chemical information and modeling
We present an artificial intelligence-guided approach to design durable and chemically recyclable ring-opening polymerization (ROP) class polymers. This approach employs a genetic algorithm (GA) that designs new monomers and then utilizes virtual for...

The development of classification-based machine-learning models for the toxicity assessment of chemicals associated with plastic packaging.

Journal of hazardous materials
Assessing chemical toxicity in materials like plastic packaging is critical to safeguarding public health. This study presents the development of classification-based machine learning models to predict the toxicity of chemicals associated with plasti...