Abstract:
The exponential rise in the production and use of polymers, particularly in single use applications, has led to a dramatic increase in their environmental prevalence and problems with plastic waste management. One necessary component of the solution to this challenge is developing plastics that degrade more effectively in the environment, be it due to accidental release, composting, or presence in sewage. While this need has been widely known for decades, slow innovation cycles, inertia in our materials systems, and cost and performance barriers have dramatically limited the number of new materials that come to market.
This talk will present a vision for workflows of the future that can be used to accelerate materials innovation through a combination of high-throughput measurement, data science, and machine learning and will apply these workflows to facilitate the discovery of new materials that improve sustainability. First, acceleration of critical bottlenecks in metrology is addressed through the development of automated, high-throughput biodegradation testing, dramatically increasing the scope of what is testable and leading to fundamental new insights into structure-property relationships for polymer environmental fate. Finding ways to share all of the data from these studies necessitates the development and use of new informatics technologies and data systems for representing polymer information in a way that accurately preserves all of the structure-processing information across complex workflows, and for this we have developed the CRIPT data system.
Event Series
DMI Seminar Series