Breakthrough in lignocellulosic biomass pretreatment for sustainable biorefineries
Nanjing University of Science and Technology develops efficient biomass densification pretreatment method
Journal of Bioresources and Bioproducts
In a significant stride towards sustainable biorefineries, a team of researchers led by Xinchuan Yuan and Guannan Shen at the School of Environmental and Biological Engineering, Nanjing University of Science and Technology, has developed an innovative densification pretreatment method for lignocellulosic biomass. This method, known as DLCA(SA-MS), involves the use of sulfuric acid and metal salts to densify biomass, followed by autoclave treatment, resulting in a high yield of fermentable sugars and an efficient conversion process.
The study, published in the Journal of Bioresources and Bioproducts, addresses the challenges of low working mass, high sugar loss, and additional costs associated with solid-liquid separation and water washing in traditional pretreatment methods. The DLCA(SA-MS) method, conducted under mild conditions at 121°C with a high biomass working mass of up to 400 kg/m³, achieved over 95% sugar retention and 90% enzymatic sugar conversion, leading to a high concentration of fermentable sugar (212.3 g/L) with superior fermentability.
A key innovation of this research is the valorization of lignin-rich residue post hydrolysis or fermentation, which significantly contributes to the economy and sustainability of lignocellulosic biorefineries. The bio-adsorbent derived from the DLCA(SA-MS) biomass residue demonstrated high adsorptive capacity, making it suitable for dyeing wastewater treatment and providing a feasible method for full-component utilization of biomass.
The findings indicate that the DLCA(SA-MS) pretreatment enables comprehensive utilization of biomass, enhancing the economic viability of lignocellulosic biorefineries. This research not only advances the field of biomass pretreatment but also contributes to the development of environmentally sustainable technologies.
See the article:
DOI
https://doi.org/10.1016/j.jobab.2024.09.004
Original Source URL
https://www.sciencedirect.com/science/article/pii/S2369969824000586
Journal
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