RESUMO
Supported gold nanoparticles have proven to be highly effective catalysts for the base-free oxidation of furfural, a compound derived from biomass. Their small size enables a high surface-area-to-volume ratio, providing abundant active sites for the reaction to take place. These gold nanoparticles serve as catalysts by providing surfaces for furfural molecules to adsorb onto and facilitating electron transfer between the substrate and the oxidizing agent. The role of the support in this reaction has been widely studied, and gold-support interactions have been found to be beneficial. However, the exact mechanism of furfural oxidation under base-free conditions remains an active area of research and is not yet fully understood. In this review, we delve into the essential factors that influence the selectivity of furfural oxidation. We present an optimization process that highlights the significant role of machine learning in identifying the best catalyst for this reaction. The principal objective of this study is to provide a comprehensive review of research conducted over the past five years concerning the catalytic oxidation of furfural under base-free conditions. By conducting tree decision making on experimental data from recent articles, a total of 93 gold-based catalysts are compared. The relative variable importance chart analysis reveals that the support preparation method and the pH of the solution are the most crucial factors determining the yield of furoic acid in this oxidation process.
RESUMO
The synthesis of methanol and dimethyl ether (DME) from carbon dioxide (CO2) and green hydrogen (H2) offers a sustainable pathway to convert CO2 emissions into value-added products. This heterogeneous catalytic reaction often uses copper (Cu) catalysts due to their low cost compared with their noble metal analogs. Nevertheless, improving the activity and selectivity of these Cu catalysts for these products is highly desirable. In the present study, a new architecture of Cu- and Cu/Zn-based catalysts supported on electrospun alumina nanofibers were synthesized. The catalysts were tested under various reaction conditions using high-throughput equipment to highlight the role of the hierarchical fibrous structure on the reaction activity and selectivity. The Cu or Cu/ZnO formed a unique structure of nanosheets, covering the alumina fiber surface. This exceptional morphology provides a large surface area, up to ~300 m2/g, accessible for reaction. Maximal production of methanol (~1106 gmethanolKgCu-1âh-1) and DME (760 gDMEKgCu-1âh-1) were obtained for catalysts containing 7% wt. Cu/Zn with a weight ratio of 2.3 Zn to Cu (at 300 °C, 50 bar). The promising results in CO2 hydrogenation to methanol and DME obtained here point out the significant advantage of nanofiber-based catalysts in heterogeneous catalysis.
RESUMO
In this paper, Raman spectroscopy is used as a tool to study the mechanism of furfural oxidation using H2O2 as a reagent on gold nanoparticles (NPs) supported on hydrotalcites (HTs). This reaction was repeated, under the same conditions, but with different reaction times in a parallel multireactor system. The reaction media were analyzed using a macro device associated with a multipass cell permitting us to enhance the Raman signal by reflecting the laser beam 3 times. The Raman spectra showed the conversion of furfural to furoic acid without any chemical intermediates, thus privileging a direct pathway. Combining the results of the catalytic tests with those of the Raman study, the mechanism of furfural oxidation to furoic acid using gold NPs supported on HTs is proposed. The key points of this mechanism were found to be as follows: (i) the in situ formation of a base, originating from the Mg leaching from the HT support, initiates the oxidation of furfural by deprotonation; (ii) H2O2 used as a reagent in the solution increases the catalytic activity by its dissociation to form hydroxide ions; and (iii) the oxidation of furfural occurs on the surface of gold NPs and leads to higher furoic acid yield.
