Abstract
We address how surface topology controls the multiscale flow alignment of cellulose nanocrystal (CNC) suspensions using a single in-situ experiment that combines rheology, polarized light imaging (PLI), and small-angle X-ray scattering (SAXS). Across a series of azetidinium-based dialkyl linker topologies, we resolve the propagation of alignment from the mesoscale (PLI) to the nanoscale (SAXS). While pristine CNC suspensions exhibit nearly-simultaneous onset of mesoscale birefringence and nanoscale alignment, surface-modified systems show a pronounced decoupling between these processes. In particular, the appearance of the Maltese-cross pattern in PLI systematically precedes detectable nanoscale alignment in SAXS. This is strongly dependent on linker topology. Extending the analysis beyond the Hermans parameter, S2, to higher-order anisotropy parameters and benchmarking their evolution against a generalized Maier-Saupe-type anisotropy distribution function, we show that higher-order anisotropy parameters qualitatively distinguish alignment regimes that are indistinguishable from S2 alone. The work establishes linker topology as a controlling variable for multiscale flow alignment in CNC systems and highlights the higher-order character of their alignment behavior.
| Original language | English |
|---|---|
| Article number | 140913 |
| Journal | Journal of Colloid and Interface Science |
| DOIs | |
| Publication status | Published - Dec 2026 |
| MoE publication type | A1 Journal article-refereed |
Funding
AAM and RK are grateful to European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955,605 YIELGAP and to Tetra Pak AB for their funding. AKS, KS, MB, GW and RK are grateful for the financial support of the Wallenberg Wood Science Centre (WWSC 3.0: KAW 2021.0313). RK acknowledges the additional financial support of the Chalmers Areas of Advance Materials, Nano and Production and that of the “2D material-based technology for industrial applications” 2D-TECH Vinnova Competence Centre (Ref. 2019-00068).
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