4.7 Article

Cellulose nanofibrils and nanocrystals in confined flow: Single-particle dynamics to collective alignment revealed through scanning small-angle x-ray scattering and numerical simulations

Journal

PHYSICAL REVIEW E
Volume 101, Issue 3, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.101.032610

Keywords

-

Funding

  1. National Science Foundation [DMR-1808690]
  2. Alf de Ruvo Foundation (SCA)
  3. Hans Werthen Foundation (IVA)
  4. National Institute of Health, National Institute of General Medical Sciences (NIGMS) [P41 GM111244]
  5. DOE Office of Biological and Environmental Research [KP1605010]
  6. NIH [S10 OD012331]
  7. US Department of Energy, Office of Basic Energy Sciences Program [DE-SC0012704]
  8. U.S. DOE Office of Science Facility, at Brookhaven National Laboratory [DE-SC0012704]

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Nanostructured materials made through flow-assisted assembly of proteinaceous or polymeric nanosized fibrillar building blocks are promising contenders for a family of high-performance biocompatible materials in a wide variety of applications. Optimization of these processes relies on improving our knowledge of the physical mechanisms from nano- to macroscale and especially understanding the alignment of elongated nanoparticles in flows. Here, we study the full projected orientation distributions of cellulose nanocrystals (CNCs) and nanofibrils (CNFs) in confined flow using scanning microbeam SAXS. For CNCs, we further compare with a simulated system of dilute Brownian ellipsoids, which agrees well at dilute concentrations. However, increasing CNC concentration to a semidilute regime results in locally arranged domains called tactoids, which aid in aligning the CNC at low shear rates, but limit alignment at higher rates Similarly, shear alignment of CNF at semidilute conditions is also limited owing to probable bundle or flock formation of the highly entangled nanofibrils. This work provides a quantitative comparison of full projected orientation distributions of elongated nanoparticles in confined flow and provides an important stepping stone towards predicting and controlling processes to create nanostructured materials on an industrial scale.

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