Clear route to biodegradable polymers

Products made from polymers – ranging from plastic bags to clothing to cookware to electronics – provide many comforts and support today’s standard of living, but since they do not decompose easily, they pose long-term environmental challenges. Developing polymers with a more sustainable life cycle is a critical step in making progress toward a green economy and addressing this piece of the global climate-change crisis. The development of biodegradable polymers, however, remains limited by current biodegradation testing methods.

To address this limitation, a team of researchers at Massachusetts Institute of Technology (MIT) led by Bradley Olsen, a professor in the Department of Chemical Engineering, has developed an expansive biodegradation dataset to help determine whether or not a polymer is biodegradable. The researchers report their work in a paper in the Proceedings of the National Academy of Sciences.

“Despite polymer waste being a known and significant contributor to the climate crisis, the study of polymer biodegradation has been limited to a small number of polymers because current biodegradation testing methods are time- and resource-intensive,” says Olsen. “This limited scope slows new material innovation, so we are working to open that up to a much broader portfolio of materials.”

The dataset Olsen’s team has developed, with support from the MIT Climate and Sustainability Consortium (MCSC), the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) and DIC Corporation, includes more than 600 distinct polyester chemistries.

“The ingenuity of our work is pushing the screening to be high-throughput, which accelerates the pace of discovery,” says Sarah Av-Ron, a PhD candidate at MIT. High-throughput synthesis methods allow large quantities of samples to be screened rapidly, to identify products with the desired property or function. In this case, the high-throughput approach was conducted using a method called clear-zone assay, which detects polymer biofragmentation and identifies polymer degrading bacteria.

This biodegradation dataset can then reveal structure-property relationships, a concept central to materials science and engineering, where relationships between the chemical structure and properties of polymers can be established and used to build a biodegradation prediction model. When developing these models to predict biodegradation, the researchers were interested in looking into the potential linearity and nonlinearity of the relationships between structure and biodegradability.

“We consider our scientific breakthrough to be having this large dataset, and the qualitative relationships and predictive models such a substantial amount of data enabled,” explains Av-Ron. “It was captivating to figure out how to integrate the high complexity of polymer chemical representation with predictive machine-learning models. I was very excited to get a validation accuracy of 82% for one representation/model combination. With additional data we might be able to improve our predictions even more.”

The team’s work focuses largely on polyesters. The development of biodegradable polyesters presents a key opportunity for addressing the polymer sustainability crisis and reducing the environmental burden of the polymer life cycle.

The biodegradation test that these data create is accessible and cost-effective to put in place; initial industry feedback has been positive. The datasets are also more reproducible than many other standards in this space.

“With our method, there is one strain of bacteria, so you know exactly what you’re testing,” says Av-Ron. This speaks to the uniqueness of the team’s approach.

“When polymers are developed, normally the strength of the material is examined first, and then once the material is developed, whether or not it biodegrades comes second,” says Katharina Fransen, another PhD candidate at MIT.

Olsen and his team are examining the opposite – developing the biodegradability screen first, to help filter and focus what to look for in a material. This way, the team’s infrastructure can assess a lot of different options quickly.

“There has been big movement recently in developing sustainable polymers,” concludes Fransen, “and having something like this that is quick, tangible and relatively inexpensive could add a lot of value to that community.”

This story is adapted from material from MIT, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.