Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields

Area of Science:

• Materials Science
• Nanotechnology
• Fluid Dynamics

Background:

• Bottom-up assembly of anisotropic nanoparticles offers tunable material properties.
• Understanding flow dynamics is crucial for optimizing nanoparticle alignment processes.

Purpose of the Study:

• Investigate the flow-assisted alignment of cellulose nanocrystals (CNCs) in different solvents.
• Quantify the relationship between solvent viscosity, particle interactions, and nanoparticle orientation.

Main Methods:

• Utilized *in situ* scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments.
• Employed a flow-focusing channel to model shear and extensional flow fields.
• Studied surface-charged CNCs dispersed in water and propylene glycol (PG).

Main Results:

• CNCs in PG exhibited slower Brownian dynamics and aligned at lower deformation rates due to higher viscosity.
• CNCs in PG formed tactoids with less ordering than in water due to weaker electrostatic interactions.
• CNCs in water maintained mesoscale structure at moderate flow but fragmented at higher rates, reducing alignment.

Conclusions:

• Solvent viscosity and electrostatic interactions significantly influence CNC alignment dynamics and structure.
• The findings provide fundamental insights into the behavior of anisotropic colloidal systems under flow.
• Optimizing alignment requires balancing flow forces, Brownian motion, and inter-particle interactions.