Forest derived cellulose nanofiber (CNF) bio-based composites have shown strong, sustainable, and cost-effective feedstocks for the use in large-scale 3D printers and other manufacturing processes. However, producing the CNF-composite feedstocks face challenges, such as, drying and fibrillation of CNFs, dispersion of CNFs in polymer matrix. Therefore, a thorough fundamental study in these areas is essential to understand the critical knowledge gaps, thereby help design CNF-composites in a predictive manner. In this talk, we will show how supercomputing can help design CNF-composite materials without doing multitude of wet-lab experiments. We will show long length- and time-scales coarse-grained simulations using Martini force-field that is comparable to the experimental length- and time-scales. We will demonstrate the use of various different solvents to enhance the fibrillation of strongly hydrophilic CNFs with low to no concentration of water. We will also show how to overcome CNFs agglomeration in composites by functionalization of CNFs with various different low molecular weight polymers.

Supercomputing in nanocellulose reinforced thermoplastic for additive manufacturing

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