2025 - Sustainable Industrial Processing Summit
SIPS2025 Volume 4. Matyjaszewski Intl. Symp. / Polymers
| Editors: | F. Kongoli, R.C. Advincula, B.Z. Tang, S. Thomas |
| Publisher: | Flogen Star OUTREACH |
| Publication Year: | 2025 |
| Pages: | 208 pages |
| ISBN: | 978-1-998384-44-0 (CD) |
| ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
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OPTIMIZATION OF GREEN DEEP EUTECTIC SOLVENT EXTRACTION PARAMETERS BY RESPONSE SURFACE METHODOLOGY TO MAXIMIZE THE YIELD OF LIGNIN FROM LIGNOCELLULOSIC FRUIT WASTES
Sayantan Ghosh1; Krishna Pramanik1;1NATIONAL INSTITUTE OF TECHNOLOGY, Rourkela, India;
Type of Paper: Regular
Id Paper: 343
Topic: 62
Abstract:
Deep eutectic solvent (DES)-based eco-friendly technologies for the isolation of lignin from lignocellulosic waste biomass have gained significant attention as sustainable alternatives to conventional extraction methods [1,2,3]. The present work aims to improve the yield of lignin extracted from pomegranate and banana peel biowastes using green choline chloride-oxalic acid (CC-OA) DES by optimizing the extraction parameters using response surface methodology approach. An empirical quadratic model was formulated using Response Surface Methodology based on Central Composite Design to optimize the yield of lignin from pomegranate and banana peel bioresources, respectively. The study revealed that the maximum lignin yield of 39.5% and 55.52% was obtained from pomegranate peel and banana peel using the green DES. This study further demonstrated that the yield of lignin is strongly impacted by reaction time, temperature, solvent-to-biomass ratio and CC:OA ratio. The lignin obtained with maximum yield under optimized condition was comprehensively characterized by Fourier Transform Infrared Spectroscopy, UV-Visible spectroscopy, Environmental Scanning Electron Microscopy, X-Ray Diffraction, 1H and 2D Nuclear Magnetic Resonance spectroscopy to confirm its structural and morphological properties. Overall, the yield of lignin recovered from fruit wastes was enhanced by optimizing the DES extraction parameters through response surface methodology.