ANALYSIS OF ADVANCES IN SUSTAINABLE BIOETHANOL PRODUCTION USING LIGNOCELLULOSIC BIOMASS SUPPORTED BY ARTIFICIAL INTELLIGENCE

Abstract

Introduction:

Lignocellulosic biomass is an abundant and cost-effective renewable source for bioethanol production. Its utilization reduces dependence on fossil fuels and provides a means for valorizing agro-industrial residues Objective: To examine technological and strategic advances in bioethanol production within the framework of biorefineries, with the support of Artificial Intelligence (AI).

Materials and Methods:

A search was conducted in the specialized literature, highlighting innovative strategies and the use of innovative strategies and the use of artificial intelligence (AI) in biorefineries, using tools such as DeepSeek and Perplexity.

Results and Discussion:
Promising substrates such as sugarcane straw and bagasse were identified due to their high cellulose content. Innovative pretreatments (steam explosion-assisted, ultrasound, eutectic solvents, biphasic) were also analyzed to improve the release of fermentable sugars. Enzymes reuse and the use of native enzymatic cocktails emerge as key strategies to reduce production costs by optimizing the hydrolysis stage. The integration of the biorefinery concept allows for the valorization of waste within a circular economy model. AI, through artificial neural networks and machine learning, emerges as a powerful tool to optimize processes, predict yields, and reduce experimental costs.

Conclusions:

The sustainable production of bioethanol from lignocellulosic biomass is enhanced by the combination of advanced technologies and the support of AI. This synergy positions itself as a key technology to overcome the challenges of scaling and profitability, driving the development of intelligent and sustainable biorefineries.