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Multi-Objectives AI-based Optimization Model for Microplastics- free Water Bottles
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Researchers used artificial intelligence to optimize the composition of biodegradable plastic materials mixed with natural additives like cotton and cellulose, aiming to produce water bottle materials that break down in the environment rather than fragmenting into microplastics. The AI model balanced mechanical performance, cost, and environmental impact to identify optimal formulations.
In response to the environmental hazards associated with plastic waste and its effect on the environment once it is thrown away, considerable recent interest has been in the development and production of biodegradable plastics. This study aims to highlight a new class of biodegradable plastics mixed with external natural additives such as cotton, cellulose, and other catalytic additives to degrade under environmental effects such as sunlight and moisture. The mechanical, physical, economic, and environmental aspects of several biodegradable composite materials were investigated and evaluated utilizing a multi-objective expert Artificial Intelligence (AI) model using Java and Graphical User Interface (GUI). The proposed model calculates the best alternative to the existing non-sustainable plastic to package water plastic bottles. Maj or findings revealed that Polyethylene Terephalate could potentially be the best biodegradable plastic substitute for eco-water bottles based on its material properties. The suggested prototype provides a reliable and cost-effective tool for a wide range of biodegradable plastics applications.
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