This book covers all current technological, industrial status, and future prospects of biofuel production with the concept of artificial intelligence including environmental and socioeconomic impact assessment of biofuel production from lignocellulosic biomass. It discusses the status and future scope of artificial intelligence for the advancement of biofuel research. It summarizes machine learning models in addressing the issues of biofuel supply chains, case studies, scientific challenges, and future directions.

Features:

• Covers the use of machine learning within the context of the processing of advanced biofuel feedstocks for biofuel production.


• Includes larger alcohols, ethers, levulinates, GTL fuels, and furans production using machine learning approach.


• Discusses how machine learning and biomass-based biofuel production can be integrated.


• Reviews sustainability and cost analysis of artificial intelligence–based biofuel production.


• Explores prediction of the potentiality of lignocellulosic biomass for biofuel applications.

This book is aimed at researchers and graduate students in energy and fuels, chemical engineering, and machine learning.