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Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities

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 ass...

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Autores principales: Gomes Souza, Fernando, Pal, Kaushik, Ampah, Jeffrey Dankwa, Dantas, Maria Clara, Araújo, Aruzza, Maranhão, Fabíola, Domingues, Priscila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921263/
https://www.ncbi.nlm.nih.gov/pubmed/36770184
http://dx.doi.org/10.3390/ma16031175
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author Gomes Souza, Fernando
Pal, Kaushik
Ampah, Jeffrey Dankwa
Dantas, Maria Clara
Araújo, Aruzza
Maranhão, Fabíola
Domingues, Priscila
author_facet Gomes Souza, Fernando
Pal, Kaushik
Ampah, Jeffrey Dankwa
Dantas, Maria Clara
Araújo, Aruzza
Maranhão, Fabíola
Domingues, Priscila
author_sort Gomes Souza, Fernando
collection PubMed
description 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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spelling pubmed-99212632023-02-12 Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities Gomes Souza, Fernando Pal, Kaushik Ampah, Jeffrey Dankwa Dantas, Maria Clara Araújo, Aruzza Maranhão, Fabíola Domingues, Priscila Materials (Basel) Article 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). MDPI 2023-01-30 /pmc/articles/PMC9921263/ /pubmed/36770184 http://dx.doi.org/10.3390/ma16031175 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gomes Souza, Fernando
Pal, Kaushik
Ampah, Jeffrey Dankwa
Dantas, Maria Clara
Araújo, Aruzza
Maranhão, Fabíola
Domingues, Priscila
Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title_full Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title_fullStr Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title_full_unstemmed Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title_short Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities
title_sort biofuels and nanocatalysts: python boosting visualization of similarities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921263/
https://www.ncbi.nlm.nih.gov/pubmed/36770184
http://dx.doi.org/10.3390/ma16031175
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