Optimization of Cellulose Nanocrystal Isolation from Ayous Sawdust Using Response Surface Methodology  

作　　者：Tchigo Alifa Hamida Aminatou Oumar Said Jean-Bosco Tchatchueng Tchigo Alifa;Hamida Aminatou;Oumar Said;Jean-Bosco Tchatchueng(Department of Chemical Engineering, School of Chemical Engineering and Mineral Industries, University of Ngaoundere, Ngaoundere, Cameroon;Department of Applied Chemistry, National Advanced School of Agro-Industrial Sciences, University of Ngaoundere, Ngaoundere, Cameroon;Department in Charge of Coordination and Valorisation of Research, National Advanced School of Engineering, University of Yaounde 1, Yaounde, Cameroon)

机构地区：[1]Department of Chemical Engineering, School of Chemical Engineering and Mineral Industries, University of Ngaoundere, Ngaoundere, Cameroon [2]Department of Applied Chemistry, National Advanced School of Agro-Industrial Sciences, University of Ngaoundere, Ngaoundere, Cameroon [3]Department in Charge of Coordination and Valorisation of Research, National Advanced School of Engineering, University of Yaounde 1, Yaounde, Cameroon

出　　处：《Journal of Materials Science and Chemical Engineering》2024年第1期36-55,共20页材料科学与化学工程（英文）

摘　　要：This study focuses on the extraction of cellulose nanocrystals (CNC), from microcrystalline cellulose (MCC), derived from Ayous sawdust. The process involves multiple steps and a large amount of chemical products. The objective of this research was to determine the effects of factors that impact the isolation process and to identify the optimal conditions for CNC isolation by using the response surface methodology. The factors that varied during the process were the quantity of MCC, the concentration of sulfuric acid, the hydrolysis time and temperature, and the ultrasonic treatment time. The response measured was the yield. The study found that with 5.80 g of microcrystalline cellulose, a sulfuric acid concentration of 63.50% (w/w), a hydrolysis time of 53 minutes, a hydrolysis temperature of 69˚C, and a sonication time of 19 minutes are the ideal conditions for isolation. The experimental yield achieved was (37.84 ± 0.99) %. The main factors influencing the process were the sulfuric acid concentration, hydrolysis time and temperature, with a significant influence (p < 0.05). Infrared characterization results showed that nanocrystals were indeed isolated. With a crystallinity of 35.23 and 79.74, respectively, for Ayous wood fiber and nanocrystalline cellulose were observed by X-ray diffraction, with the formation of type II cellulose, thermodynamically more stable than native cellulose type I.This study focuses on the extraction of cellulose nanocrystals (CNC), from microcrystalline cellulose (MCC), derived from Ayous sawdust. The process involves multiple steps and a large amount of chemical products. The objective of this research was to determine the effects of factors that impact the isolation process and to identify the optimal conditions for CNC isolation by using the response surface methodology. The factors that varied during the process were the quantity of MCC, the concentration of sulfuric acid, the hydrolysis time and temperature, and the ultrasonic treatment time. The response measured was the yield. The study found that with 5.80 g of microcrystalline cellulose, a sulfuric acid concentration of 63.50% (w/w), a hydrolysis time of 53 minutes, a hydrolysis temperature of 69˚C, and a sonication time of 19 minutes are the ideal conditions for isolation. The experimental yield achieved was (37.84 ± 0.99) %. The main factors influencing the process were the sulfuric acid concentration, hydrolysis time and temperature, with a significant influence (p < 0.05). Infrared characterization results showed that nanocrystals were indeed isolated. With a crystallinity of 35.23 and 79.74, respectively, for Ayous wood fiber and nanocrystalline cellulose were observed by X-ray diffraction, with the formation of type II cellulose, thermodynamically more stable than native cellulose type I.

关 键 词：Ayous Sawdust Lignocellulosic Waste ISOLATION Cellulose Nanocrystals OPTIMIZATION Response Surface Methodology 

分 类 号：TB3[一般工业技术—材料科学与工程]