用于木质纤维素生物质的智能可持续生物精炼厂。
Smart sustainable biorefineries for lignocellulosic biomass.
机构信息
Department of Mechanical Engineering, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines; Center for Engineering Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines.
Center for Engineering Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines; Department of Manufacturing Engineering and Management, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines.
出版信息
Bioresour Technol. 2022 Jan;344(Pt B):126215. doi: 10.1016/j.biortech.2021.126215. Epub 2021 Oct 30.
Lignocellulosic biomass (LCB) is considered as a sustainable feedstock for a biorefinery to generate biofuels and other bio-chemicals. However, commercialization is one of the challenges that limits cost-effective operation of conventional LCB biorefinery. This article highlights some studies on the sustainability of LCB in terms of cost-competitiveness and environmental impact reduction. In addition, the development of computational intelligence methods such as Artificial Intelligence (AI) as a tool to aid the improvement of LCB biorefinery in terms of optimization, prediction, classification, and decision support systems. Lastly, this review examines the possible research gaps on the production and valorization in a smart sustainable biorefinery towards circular economy.
木质纤维素生物质 (LCB) 被认为是生物炼制厂的可持续原料，可用于生产生物燃料和其他生物化学品。然而，商业化是限制传统 LCB 生物炼制厂成本效益运营的挑战之一。本文重点介绍了一些关于 LCB 在成本竞争力和减少环境影响方面的可持续性研究。此外，开发计算智能方法，如人工智能 (AI)，作为一种工具，以帮助提高 LCB 生物炼制厂在优化、预测、分类和决策支持系统方面的水平。最后，本文综述了在向循环经济发展的智能可持续生物炼制厂中，关于生产和增值的可能研究空白。
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