Predictive Design for Chiral Self-Assembly of Cellulose Nanocrystals
발표자
조은수 (포항공과대학교)
연구책임자
김영기 (포항공과대학교)
초록
내용
Cellulose nanocrystals (CNCs) are bio-derived materials that exhibit chiral self-assembly and consequent Bragg reflection at wavelengths set by the helical pitch P; however, a quantitative framework linking P to controllable design remains elusive. Here, an Oseen–Frank model incorporating Straley’s chiral torque reduces pitch control to a single metric—the elasticity-to-torque ratio K2/KT. Guided by this metric, we program P across the entire visible spectrum using three design strategies: (i) length fractionation, (ii) ionic-strength (HCl/NaCl) screening, and (iii) chiral-dopant addition. The model quantitatively predicts reflection wavelengths of CNC films under systematic variations in polydispersity, ionic strength, and dopant concentration. The resulting design map enables scalable, eco-friendly, wavelength-selective reflectors such as security photonics, cosmetics, and optical coatings. Supported by the NRF (RS-2023 00212739, RS-2024-00411809, RS-2023-00302586).