Smart sustainable biorefineries for lignocellulosic biomass

Area of Science:

• Biomass Valorization
• Sustainable Biorefining
• Circular Economy

Background:

• Lignocellulosic biomass (LCB) is a key sustainable feedstock for biorefineries.
• Commercialization and cost-effectiveness remain significant challenges for conventional LCB biorefineries.

Purpose of the Study:

• To review studies on the sustainability of LCB, focusing on cost-competitiveness and environmental impact.
• To explore the application of computational intelligence, including Artificial Intelligence (AI), in enhancing LCB biorefinery operations.
• To identify research gaps in smart sustainable biorefining for a circular economy.

Main Methods:

• Literature review of sustainability studies on LCB.
• Analysis of computational intelligence methods (AI) for biorefinery optimization, prediction, classification, and decision support.
• Examination of research gaps in LCB production and valorization.

Main Results:

• LCB offers potential for cost-competitive and environmentally sound biofuel and biochemical production.
• AI and computational intelligence can significantly improve biorefinery efficiency and decision-making.
• Identified research gaps highlight opportunities for advancing smart sustainable biorefineries.

Conclusions:

• LCB biorefineries can be made more sustainable and cost-effective.
• AI integration is crucial for optimizing LCB valorization and achieving circular economy goals.
• Further research is needed to bridge current gaps in smart sustainable biorefining.