Kiran
Sultana
SURF Characterization of polymer blend nanocomposites using Cellulose Nanocrystals (CNCs) across different size scales
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Authors:
Kiran Sultana
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Cellulose Nanocrystals (CNCs) are widely studied as fillers to reinforce polymers due to their high aspect ratio and stiffness. Thermoplastic matrices like poly (lactic acid), polyvinyl alcohol, polyethylene glycol, polyvinyl pyrrolidone, etc. reinforced with cellulose fibers have garnered significant attention as high performance sustainable materials with outstanding mechanical, thermal, and barrier properties. A typical production method involves using polymer-CNC solutions or emulsions with the CNCs in suspension, followed by film casting. This method is favoured due to excellent stability of cellulose nanoparticles in water, however, the resulting materials from solution-based processes are difficult to scale up to larger product dimensions and potentially create more waste during manufacturing in contract to solventless processing. Thus, the focus of this research is to fabricate solventless polymer blend nanocomposites using CNCs with thickness ranging from the nanoscale to millimetres, while observing the morphology and mechanical properties with resulting properties compared to solution-based analogs. For solution casting, multiple samples of 2.5 wt% and 5 wt% of homopolymers: PVA and PVP along with their blends and varying ratios of CNCs (2.5 and 5 wt%) were prepared in deionized water. Thicker samples were prepared by solution casting and preliminary works on fabricating the thickest samples (millimetres) were done using micro compounder in a solutionless process. Morphological study was performed using optical and polarized light microscope. Quartz crystal microbalance and tensile tester were used for mechanical characterization. We found the polymer blend microstucture, including dispersion of CNCs, was altered by changing the weight ratios of PVP/PVA and CNCs which greatly affected the material properties of the final composite specimen.
Source:
Purdue University / 2023
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Co-authors:
Kiran Sultana