In-situ conversion of hemicellulose to furfural by Lewis acid-enhanced deep eutectic solvents to maintain stable pretreatment performance and trigger profitable biorefining processes.

Journal: International journal of biological macromolecules
Published Date:

Abstract

Deep eutectic solvents (DESs) are gaining attention for lignocellulose pretreatment, yet screening methods and stable cyclic processes remain underexplored. This study compared solubility and machine learning to predict delignification, screening the optimal DESs combination from 168 recombinant ternary DESs. The selected DESs were utilized to develop a stable, recyclable pretreatment process (delignification and hemicellulose removal) via Lewis acid-catalyzed conversion of hemicellulose to furfural. Results suggested the multilayer perceptron model within the machine learning framework achieved the highest accuracy (R = 0.96, RMSE = 4.13) and generalization ability for delignification prediction. Lewis acid was employed to enhance the screened DESs (chloride: lactic acid: glycol = 1:5:1) for catalyzing the in situ conversion of hemicellulose to furfural (89.92 %), enhanced delignification (93.15 %) and maintained stable pretreatment performance even after 10 cycles. The cellulose-rich material exhibited higher enzymatic hydrolysis efficiency (78.17 %) and can be used to prepare nanocellulose with a narrower diameter (5.59 nm). Additionally, the lignin isolated by Lewis acid-enhanced DESs exhibited stronger antioxidant activity (IC50 = 0.03 mg/mL) and ultraviolet shielding capability. This work conducts a comprehensive investigation, from DESs screening to establishing a stable and recyclable pretreatment process, advancing the scalable application of DESs pretreatment for biomass processing.

Authors

  • Qinghao Zhao
    Department of Cardiology, Peking University People's Hospital, Beijing, China.
  • Ming-Jun Zhu
    School of Biology and Biological Engineering, Guangdong Key Laboratory of Fermentation and Enzyme Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Panyu, Guangzhou 510006, China; The Key Laboratory of Biological Resources and Ecology of Pamirs Plateau in Xinjiang Uygur Autonomous Region, The Key Laboratory of Ecology and Biological Resources in Yarkand Oasis at Colleges & Universities under the Department of Education of Xinjiang Uygur Autonomous Region, College of Life and Geographic Sciences, Kashi University, Kashi 844006, China. Electronic address: mjzhu@scut.edu.cn.
  • Lu Zhao
    Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.