Green solvent-based extraction of cellulose from hemp bast fibers: From treatment efficacy to characterizations and optimization

• Published in: International journal of biological macromolecules 2024-12, p.138689
• Main Authors: Firouzi, Maryam, Siddiqua, Sumi, Kazemian, Hossein, Kiamahalleh, Meisam Valizadeh
• Format: Article
• Language: English
• ISSN: 1879-0003

This study assessed the efficacy of deep eutectic solvents (DESs) as green solvents for cellulose extraction from hemp bast fiber. Three DES mixtures were applied, and the combination of choline chloride and glycerol was selected for further experimentation due to its superior performance. The impact of four key parameters- treatment time, treatment temperature, DES-to-hemp ratio, and glycerol-to-choline chloride ratio was analyzed using Central-Composite Design (CCD) within response surface methodology (RSM) to optimize cellulose extraction. The optimal conditions achieved cellulose: lignin ratio of 70.817. Machine learning (ML) algorithms, including Multilayer Perceptron, Instance-Based Learner (IBK), Random Committee, Random Forest and Random Tree were conducted to predict the extraction process based on the RSM results. The results showed that the Random Tree demonstrated superiority by providing a predicted R value of 0.8548. Various characterization techniques such as SEM, FTIR, TGA, and XRD confirmed the removal of impurities. TGA and XRD results indicate a crystallinity index of 81.4 % and an increase in cellulose yield from 58.108 % in untreated hemp to 69.731 % in the h-12 sample, respectively, consistent with RSM findings. These findings indicate the high potential of DES as a green, cost-effective, and environmentally friendly solvent for cellulose extraction from hemp.