Bayesian-assisted mechanochemical synthesis of carboxylated cellulose nanocrystals and its application in Pickering
Xinyu Lin1, Weike Su2, Qihong Zhang1
1National Engineering Research Center for Process Development of Active Pharmaceutical Ingredients, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang Key Laboratory of Green Manufacturing Technology for Chemical Drugs, Zhejiang University of Technology, Hangzhou 310014, PR China.
Abstract:
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.
