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

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 analyzed to identify the research hotspots. In addition to bibliometric analysis, machine learning and deep learning analyses have been carried out to determine the homogeneity of the dataset and predict the research evolution forecast. This study will uncover the current research trend on advanced biofuels, identify the research gaps, and predict future research direction, guiding future researchers working on this topic.

可再生能源是当下推动可持续发展的研究热点。生物燃料（biofuel）作为传统化石燃料的替代方案，凭借其可再生能源属性与零碳足迹特性，可助力环境可持续性发展。然而传统生物燃料以可食用生物质为原料制备，受全球粮食短缺问题影响，其长期应用可行性受到广泛质疑。目前科研人员正基于非食用生物质与废弃物原料开发先进生物燃料，该类燃料有望成为规模可观的可再生能源来源。本研究通过全面的文献计量分析，梳理先进生物燃料领域的研究进展全貌。研究团队从Scopus数据库中采集得到一套文献数据集，并从文献、作者、期刊、研究机构与国家多个维度对该数据集展开分析，以全面掌握先进生物燃料领域当前的研究趋势。此外还通过突现关键词分析，明确该领域的研究热点。除文献计量分析外，本研究还开展了机器学习与深度学习分析，以评估数据集的同质性，并预测该领域的研究演化方向。本研究旨在揭示先进生物燃料领域的当前研究态势，明确现有研究空白，预测未来研究方向，为该领域后续研究者提供参考。