The issue of plastic waste accumulating in natural environments is a major concern due to its negative impact on ecosystems and aquatic life. Material scientists have been actively seeking all-natural alternatives to plastic for packaging and manufacturing purposes.
Prof. Po-Yen Chen, co-author of the paper, shared that his research was inspired by a visit to Palau in 2019. Witnessing the devastating effects of plastic pollution on marine life, such as fish being deceived by floating plastic films and sea turtles ingesting plastic waste, motivated him to focus on finding solutions.
Traditional methods of searching for sustainable plastic alternatives have been slow and often ineffective, leading to materials that lack the desirable properties of plastic. The new approach introduced in this study utilizes a machine learning model developed by Chen.
This innovative method not only speeds up the search for materials but also increases the likelihood of finding alternatives suitable for manufacturing and industrial use. Chen collaborated closely with colleagues Teng Li and Liangbing Hu to apply the machine learning technique to discover all-natural plastic alternatives.
2024-04-13 14:00:03
Article from phys.org