4.6 Article

Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities

Journal

MATERIALS
Volume 16, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/ma16031175

Keywords

nanocatalyst; biodiesel; oil; production; reaction; data mining; visualization of similarities method; python; pandas

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Using renewable resources to produce biofuels is a significant theme in modernity, attracting the attention of many countries and being an essential part of the global geopolitical chessboard due to increasing energy needs. The advancement of personal computing and open-source software production has facilitated the exploration and understanding of complex scenarios. Through the analysis of 1071 scientific articles in the Scopus database, researchers discovered that the most recent associations focus on producing biofuels from microorganisms' oils and using cerium oxide nanoparticles to enhance fuel mixtures' performance by reducing hydrocarbon and nitrogen oxide emissions.
Among the most relevant themes of modernity, using renewable resources to produce biofuels attracts several countries' attention, constituting a vital part of the global geopolitical chessboard since humanity's energy needs will grow faster and faster. Fortunately, advances in personal computing associated with free and open-source software production facilitate this work of prospecting and understanding complex scenarios. Thus, for the development of this work, the keywords biofuel and nanocatalyst were delivered to the Scopus database, which returned 1071 scientific articles. The titles and abstracts of these papers were saved in Research Information Systems (RIS) format and submitted to automatic analysis via the Visualization of Similarities Method implemented in VOSviewer 1.6.18 software. Then, the data extracted from the VOSviewer were processed by software written in Python, which allowed the use of the network data generated by the Visualization of Similarities Method. Thus, it was possible to establish the relationships for the pair between the nodes of all clusters classified by Link Strength Between Items or Terms (LSBI) or by year. Indeed, other associations should arouse particular interest in the readers. However, here, the option was for a numerical criterion. However, all data are freely available, and stakeholders can infer other specific connections directly. Therefore, this innovative approach allowed inferring that the most recent pairs of terms associate the need to produce biofuels from microorganisms' oils besides cerium oxide nanoparticles to improve the performance of fuel mixtures by reducing the emission of hydrocarbons (HC) and oxides of nitrogen (NOx).

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