Bayesian-assisted mechanochemical synthesis of carboxylated cellulose nanocrystals and its application in Pickering emulsion.

The preparation of carboxylated cellulose nanocrystals (CNCs) by ammonium persulfate (APS) oxidation is a relatively common method, but the low reaction efficiency limits its application. In this study, carboxylated CNCs (CNCs-COOH) were efficiently synthesized by mechanochemistry and assisted by the Bayesian Optimization Algorithm (BOA). Under the optimal conditions: reaction temperature of 60 °C, oscillation frequency of 30 Hz, reaction time of 25 min, ball-to-material ratio of 31.8, liquid addition amount of 2 μL/mg, and APS concentration of 0.5 M, the maximum CNCs-COOH yield of 90.45 % was achieved. CNCs-COOH had crystallinity of 78.26 % and particle size of 196.15 ± 18.23 nm, which has better physicochemical property than the carboxylated CNCs (AOCNC) prepared by the conventional solution method. Furthermore, CNCs-COOH was used as suspension stabilizer for the preparation of oil-in-water vitamin A acetate Pickering emulsion, which showed excellent physical and thermal stability. Therefore, mechanochemical APS oxidation is a green and economical alternative to prepare CNCs-COOH, which has prospect in application as suspension stabilizer.