Fermentation is an oxygen-free biological process that produces hydrogen, a clean, renewable energy source with the potential to power a low-carbon economy. Bibliometric analysis is crucial in academic research to evaluate scientific production, identify trends and contributors, and map the development of a field, providing valuable information to guide researchers and promote scientific innovation. This review provides an advanced bibliometric analysis and a future perspective on fermentation for hydrogen production. By searching WoS, we evaluated and refined 62,087 articles to 4493 articles. This allowed us to identify the most important journals, countries, institutions, and authors in the field. In addition, the ten most cited articles and the dominant research areas were identified. A keyword analysis revealed five research clusters that illustrate where research is progressing. The outlook indicates that a deeper understanding of microbiology and support from energy policy will drive the development of hydrogen from fermentation.

This study aims to explore technological advances and prospects in phenol treatment by providing a detailed bibliometric survey of wastewater treatment applications, highlighting innovative advances in research. Using the Web of Science database, we identified 79,104 articles from 2003 to 2023, later refined to 1848. The keywords were used for the initial search: “phenol”, “wastewater”, “degradation”, “treatment” and “removal”. The bibliographic review details the occurrence of journals, authors, newspapers, countries, institutions, keywords, highly cited articles, and prominent predominant research fields. In particular, the field of “Engineering” was responsible for 32% of the published articles, followed by “Ecology of Environmental Sciences” (25%) and “Chemistry” (12%). In addition, a keyword analysis revealed five major groups of clusters that indicate where the research is progressing. This aspect is crucial for understanding the evolution and perspectives of research interests over time. Therefore, future research in the field should prioritize wastewater treatment and feedstock diversification. This focus is essential to address significant challenges, such as production costs, stability, and durability of treatment processes. Graphical Abstract

In this study, biodiesel was produced through the enzymatic esterification of vegetable oils from two common Brazilian palm trees: babassu and tucuman. The oils were hydrolyzed by a chemical route and their free fatty acids esterified with ethanol and methanol using the lipase enzyme Eversa^® Transform 2.0 in free forms and supported in iron magnetic nanoparticles (Fe₃O₄) (enzymatic load: 80 UpNPBg⁻¹). These enzymatic reactions were performed at an oil–alcohol molar ratio of 1:1, reaction temperature of 37 °C, agitation at 150 rpm, and reaction times of 2, 4, 6 and 8 h for the reactions catalyzed by the soluble enzyme and 8 h for the reactions using the biocatalyst. The conversions of fatty acids in ethyl and methyl esters obtained were monitored by gas chromatography (CG). The results obtained from ester synthesis using enzyme catalysts in free form were better: babassu 52.6% (methanol) and 57.5% (ethanol), and for tucuman 96.7% (methanol) and 93.4% (ethanol). In the case of immobilized enzymes, the results obtained ranged from 68.7% to 82.2% for babassu and from 32.5% to 86.0% for tucuman, with three cycles of reuse and without significant catalyst loss. Molecular coupling studies revealed the structures of lipase and that linoleic acid bonded near the active site of the enzyme with the best free energy of −6.5 Kcal/mol.

This study investigates enzymatic biodiesel production from safflower oil (Carthamus tinctorius), an underutilized edible oilseed feedstock. Fatty acid ethyl esters were produced using commercial Eversa^® Transform 2.0 lipase, and the process was optimized using a Taguchi L9 design that evaluated the fatty acid-to-ethanol molar ratio, biocatalyst loading, temperature, and reaction time. The highest observed conversion was 88.90 ± 0.02% at a 1:5 molar ratio, 9% biocatalyst loading, 25 °C, and 3 h. The mean signal-to-noise analysis indicated 1:5, 9%, 40 °C, and 3 h as the best factor-level combination, while ANOVA identified biocatalyst loading as the dominant factor, accounting for 65.22% of the explained variation. ¹H and ¹³C NMR confirmed ethyl-ester formation. GC–MS relative-area analysis identified ethyl oleate (35.75%), ethyl palmitate (8.53%), and ethyl stearate (6.93%), together with residual oleic acid (38.52%); therefore, chromatographic area percentages and acid-value conversion were interpreted as complementary rather than directly equivalent measures. DFT, molecular docking, and 100 ns molecular dynamics simulations were used to examine two experimentally detected ethyl esters and a branched long-chain methyl ester included as a structural comparator. The comparator produced the most favorable docking score (− 6.0 kcal mol⁻¹), while all simulated complexes retained the overall lipase fold during the trajectories. The results demonstrate the potential of Eversa^®-catalyzed esterification of safflower-oil-derived fatty acids, while indicating the need for a confirmation experiment at the predicted Taguchi condition and additional product-purification and fuel-property analyses before scale-up. Graphical Abstract