Parametric optimization of the production of cellulose nanocrystals (CNCs) from South African corncobs via an empirical modelling approach

Abstract

In this study, cellulose nanocrystals (CNCs) were obtained from South African corncobs using an acid hydrolysis process. The delignification of corncobs was carried out by using alkali and bleaching pretreatment. Furthermore, the Box-Behnken Design (BBD) was used as a design of experiment (DOE) for statistical experimentations that will result in logical data to develop a model that explains the effect of variables on the response (CNCs yield). The effects (main and interactive) of the treatment variables (time, temperature, and acid concentration) were investigated via the response methodology approach and the obtained model was used in optimizing the CNCs yield. Surface morphology, surface chemistry, and the crystallinity of the synthesized CNC were checked using scanning electron microscopy (SEM), a Fourier Transform Infra-red spectroscopy (FTIR), and an X-ray diffraction (XRD) analysis, respectively. The SEM image of the raw corncobs revealed a smooth and compact surface morphology. Results also revealed that CNCs have higher crystallinity (79.11%) than South African waste corncobs (57.67%). An optimum yield of 80.53% CNCs was obtained at a temperature of 30.18 °C, 30.13 min reaction time, and 46 wt% sulfuric acid concentration. These optimized conditions have been validated to confirm the precision. Hence, the synthesized CNCs may be suitable as filler in membranes for different applications.