TY - JOUR
T1 - Smart sustainable biorefineries for lignocellulosic biomass
AU - Culaba, Alvin B.
AU - Mayol, Andres Philip
AU - San Juan, Jayne Lois G.
AU - Vinoya, Carlo L.
AU - Concepcion, Ronnie S.
AU - Bandala, Argel A.
AU - Vicerra, Ryan Rhay P.
AU - Ubando, Aristotle T.
AU - Chen, Wei Hsin
AU - Chang, Jo Shu
N1 - Funding Information:
The authors would like to acknowledge the support of the University Research Coordination Office of De La Salle University (DLSU); the Office of the Vice Chancellor for Research and Innovation of DLSU; and the Engineering Research and Development for Technology grant of the Department of Science and Technology of the Philippines.
Publisher Copyright:
© 2021
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
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U2 - 10.1016/j.biortech.2021.126215
DO - 10.1016/j.biortech.2021.126215
M3 - Review article
C2 - 34728355
AN - SCOPUS:85120852953
SN - 0960-8524
VL - 344
JO - Bioresource technology
JF - Bioresource technology
M1 - 126215
ER -