SUSTAINABLE PROCESS OPTIMIZATION FOR CELLULOSE RECOVERY FROM RICE HUSK AGRO-WASTE

Abstract

Rice husk, rich in lignocellulosic components, is an abundant agricultural waste and a promising renewable source for cellulose recovery. In this study, three different chlorine-free extraction methodologies were evaluated for the recovery of cellulose from rice husk agro-waste with a focus on process sustainability, yield, purity and structural integrity. The first method was ultrasound-assisted mild alkali treatment and hydrogen peroxide bleaching; the second method was ethanol-mediated Soxhlet dewaxing, stronger alkali treatment, autoclave assistance and hydrogen peroxide bleaching; and the third method was thermal pretreatment, ethanol/benzene Soxhlet extraction, intensified alkali treatment, repeated autoclaving and peracetic acid bleaching. The extracted cellulose samples were characterized by quantitative estimation of cellulose by the Updegraff–Anthrone method, solubility, scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The cellulose recovery increased progressively from RHC1 to RHC3, and the highest cellulose content was found to be above 78 % with RHC3 showing the best purification efficiency. SEM analysis showed increased separation of fibres and exposed fibrillar morphology in RHC3 indicating removal of lignin, hemicellulose, waxes and other non-cellulosic impurities. FTIR analysis confirms the presence of characteristic groups of cellulose and the removal of hemicellulose and lignin. XRD analysis also indicated the preservation of the native crystalline structure of cellulose and RHC3 possessed a crystallinity index of 78.2%. Overall, the third strategy was optimized and found to be most effective to obtain crystalline cellulose of high purity from rice husk. The study supports the valorization of rice husk waste to value-added cellulose for possible applications in sustainable biopolymer composites, biomedical materials, and hydrogel-based systems.