Advanced biofuels research: A Scopus database-driven bibliometric evaluation and future directions forecast via machine learning and deep learning

Abstract

Renewable energy is a research hotspot in the present day to promote sustainability. Biofuel, an alternative to conventional fossil fuels, can contribute to environmental sustainability through being a renewable energy source and having a zero carbon footprint. However, traditional biofuels are generated from edible biomass, which raises questions about the use of traditional biofuels in the long run due to global food scarcity. Advanced biofuels are now being developed from non-edible biomass and waste sources, which are expected to be a colossal renewable energy source. This study conducted a complete bibliometric analysis to get an overview of research progress on advanced biofuels. A bibliographic dataset has been collected from the Scopus database. The dataset has been investigated based on articles, authors, journals, institutions, and countries to get a complete overview of current research trends on advanced biofuels. Burst keywords have also been analysed to identify the research hotspots. In addition to bibliometric analysis, machine learning and deep learning algorithms have been used to perform natural language processing (NLP), execute topic modelling, and carry out the research evolution forecast. This study will uncover the current research trend on advanced biofuels, identify the research gaps, and predict future research direction. The significance of the identified research gaps lies in their potential to guide future researchers towards areas that need further exploration, thereby contributing to advancing knowledge in this field.