The pursuit of carbon neutrality confronts the twofold challenge of meeting energy demands and reducing pollution. This review article examines the potential of gasifying plastic waste and biomass as innovative, sustainable sources for hydrogen production, a critical element in achieving environmental reform. Addressing the problem of greenhouse gas emissions, the work highlights how the co-gasification of these feedstocks could contribute to environmental preservation by reducing waste and generating clean energy. Through an analysis of current technologies, the potential for machine learning to refine gasification for optimal hydrogen production is revealed. Additionally, hydrogen storage solutions are evaluated for their importance in creating a viable, sustainable energy infrastructure. The economic viability of these production methods is critically assessed, providing insights into both their cost-effectiveness and ecological benefits. Findings indicate that machine learning can significantly improve process efficiencies, thereby influencing the economic and environmental aspects of hydrogen production. Furthermore, the study presents the advancements in these technologies and their role in promoting a transition to a green economy and circular energy practices. Ultimately, the review delineates how integrating hydrogen production from unconventional feedstocks, bolstered by machine learning and advanced storage, can contribute to a sustainable and pollution-free future.
Keywords: Biomass; Gasification; Hydrogen storage; Machine learning; Plastic waste.
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