Synthesis and application of a magnetically recoverable biological nanocomposite material for waste cooking oil removal and commercial product recovery in wastewater treatment

Saejung, Chewapat; Raksapon, Dawich; Chaiyarat, Anuwat

doi:10.1016/j.jclepro.2022.132425

Cited by 8 publications

(1 citation statement)

References 45 publications

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“…Considering this, several studies have been conducted over the years to assess the emission reduction potential of replacing conventional fuels with biofuel. Of particular interest, more recent studies have paid keen attention to nanocatalysts as additives for improving the cleaner combustion of both pure fossil fuels and their blends with biofuels for limiting the production of greenhouse gasses [ 234 , 235 , 236 , 237 , 238 , 239 , 240 , 241 , 242 , 243 , 244 , 245 , 246 , 247 ]. Despite the significant contributions to the existing literature on biofuels and nanocatalysts, there is a considerable research gap regarding this field’s evolutionary trends, research hotspots, and characteristics.…”

Section: Discussion and Resultsmentioning

confidence: 99%

Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities

et al. 2023

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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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