Testing the breakdown of biodegradable plastics in the environment has traditionally been a lengthy process, often taking months or even years of laboratory work. This can hinder the development and deployment of more sustainable materials.
Researchers at the Agricultural University of Athens have introduced a novel machine-learning tool designed to predict the degradation rates of biodegradable plastics more efficiently.
This innovative approach not only saves time but also enhances the accuracy of predictions, potentially leading to better environmental outcomes and faster adoption of biodegradable materials.