DMREF/Collaborative Research: Accelerated Discovery of Sustainable Bioplastics: Automated, Tunable, Integrated Design, Processing and Modeling

University Of Vermont & State Agricultural College, Burlington VT

Investigators

Abstract

Despite years of recycling efforts, only about 10 percent of polymer waste ends up in recycling facilities, with the majority still accumulating in landfills or oceans, emphasizing the need for eco-friendly materials combining renewable sourcing, sustainable processing, and biodegradability. Thermoformable biopolymer assemblies or bioplastics are eco-friendly materials that could be sourced from biological cell or tissue (biomatter), without expensive and wasteful extraction and pre-processing. The most significant limitation in the ability to design these bioplastics is a poor understanding of the fundamental mechanisms controlling the transformation of biomatter to cohesive bioplastics. This Designing Materials to Revolutionize and Engineer our Future (DMREF) grant supports research that will combine high-throughput data capture, multiscale modeling, and machine learning to understand the molecular and chemical mechanisms controlling the transition from organism to bioplastic during processing. With that understanding, design pathways will be developed to tailor the processing and composition of the initial structure to control the macroscopic properties, and degradation that occurs during and after use. The broad impact of this work will be a new class of entirely biodegradable plastics with performance comparable to commodity plastics but manufactured sustainably. To support the next-generation sustainable materials workforce, the grant will also support mentoring of graduate and undergraduate students, active engagement in outreach activities, and efforts to enhance diversity and inclusivity in STEM. An emerging transformative concept in developing eco-friendly materials is to use biological matter without any extraction process to create bioplastics. Significant challenges remain in understanding how mixtures of biopolymers transform into thermoformable bioplastics and how the processing parameters control structure and properties. To provide key insights, this project will use high throughput methods to measure processing, spectroscopic, and morphology features and apply machine learning methods to identify the key descriptors controlling the transformation from organism to plastic. Molecular dynamics simulations and high-fidelity experiments will augment the understanding of the reactions towards bioplastic formation as well as biodegradation. Detailed structure and property measurements will be used to validate a finite element analysis tool that will enable the identification of the optimal structure to achieve properties comparable to commercial plastics using high throughput methods. Spirulina, an abundant photosynthetic microorganism that has been demonstrated to produce bioplastics when processed with heat and pressure will serve as a proof-of-concept system. The fundamental contribution of this project will be a design approach that accounts for the complexities of the transition of raw biomatter to bioplastics, exemplifying the Materials Genome Initiative's emphasis on predictive materials design and data-driven approaches to foster sustainable and innovative materials for a circular economy. This project is supported by the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) of the Directorate for Engineering (ENG), the Division of Materials Research (DMR) of the Directorate for Mathematical and Physical Sciences (MPS), and the Division of Information and Intelligent Systems (IIS) of the Directorate for Computer and Information Science and Engineering (CISE). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.