| Title |
Smart sustainable biorefineries for lignocellulosic biomass |
| ID_Doc |
20638 |
| Authors |
Culaba, AB; Mayol, AP; Juan, JLGS; Vinoya, CL; Concepcion, RS; Bandala, AA; Vicerra, RRP; Ubando, AT; Chen, WH; Chang, JS |
| Title |
Smart sustainable biorefineries for lignocellulosic biomass |
| Year |
2022 |
| Published |
|
| DOI |
10.1016/j.biortech.2021.126215 |
| Abstract |
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. |
| Author Keywords |
Lignocellulosic biomass; Circular economy; Biomass conversion technologies; Artificial intelligence; Neural networks; Biorefinery |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000732999000012 |
| WoS Category |
Agricultural Engineering; Biotechnology & Applied Microbiology; Energy & Fuels |
| Research Area |
Agriculture; Biotechnology & Applied Microbiology; Energy & Fuels |
| PDF |
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