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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).

In this work, intelligent materials were developed from the cotton fabric modified with polyaniline (PAni). PAni was used in different oxidation states (Emeraldine Salt, Emeraldine, Leucoemeraldine and Pernigraniline Base). The obtained materials were tested as colorimetric hydrogen sulfide gas sensors. The intelligent fabrics were analyzed by Infrared Spectrometry (FTIR), X‐ray powder diffraction (XRD), Thermogravimetric Analysis (TGA), Energy Dispersive X‐Ray Spectroscopy (EDS), Optical Microscopy and Electrical Resistivity Analysis. Smart fabrics were exposed to hydrogen sulfide gas, and colorimetric analyses were performed before and after exposure to identify fabrics capacity of detection. The obtained results allowed inferring that the best material was the one modified with Emeraldine base. This low‐cost material can be easily obtained, constituting a valuable hydrogen sulfide gas detection tool.

Environmental impacts are increasingly due to the human polluting activities. Therefore, there is a need to develop technologies capable of removing contamination and driving the impacted environment as close as possible to its inherent characteristics. One of the major problems still faced is the spill of oil into water. Therefore, to solve the environmental problem, this work shows the use of magnetically modified geopolymer materials as an oil remover from water with a magnet’s aid. The results obtained were outstanding since the average intrinsic oil removal capability (IORC) was 150 g/g. The presented IORC is the largest found in the materials produced by our research group, constituting an extremely encouraging result, mainly because of the ease of preparing the magnetic geopolymer system. Furthermore, the low cost of production and the material’s capability to be reused as filler of polymer or even cementitious matrices allows us to project that this nanocomposite can be widely used, constituting an economically viable alternative for more efficient environmental recovery processes.

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