Computational Investigation of Model Biomass Compounds Conversion on Isolated and Supported Metal Cluster

Hydrodeoxygenation and bio-oil decomposition processes, produced by pyrolysis of biomass, represent one of the most effective strategies to obtain biofuels. The scope of the investigations performed in this PhD project, framed in a context of constant demand for renewable and eco-sustainable alternatives energy technologies, was a mapping as complete as possible of the reactions of two biomass model compounds, namely guaiacol and isoeugenol, as they occur when catalyzed by metal clusters. The density functional theory studies of the energetics associated to the investigated processes enabled to conduct an innovative Christiansen-like microkinetic analysis that returns the kinetic constants at selected temperatures, providing as input the calculated direct and inverse energy barriers for all the elementary steps included in the various reaction mechanisms. Microkinetic analysis allowed an unbiased interpretation of DFT results in order to find the most likely decomposition channels. Indeed, the possible reaction pathways of small molecules with so many functional groups, such as guaiacol, are affected by the structure and the shape of the metal catalyst, and the influence could be remarkably strong when ultra-small, subnanometric, metal clusters are considered, where different coordination numbers are present for the same atoms. Useful information was achieved by exploring a large number of different mechanisms (some of which are new if compared to those documented in the existing literature) both in absence and in presence of molecular hydrogen fragmented on the metal catalyst model. This allowed to distinguish the most important elementary steps and to creating a computational reference for cluster catalysis in the subnanometer size regime, necessary to undertake cumbersome investigations of the same reactions on supported clusters. In particuar, The kinetic and thermodynamic analysis of the hydrodeoxygenation reaction of guaiacol and isoeugenol revealed a clear preference for the direct deoxygenation mechanism pathway at all considered temperatures, opposing to the deoxygenation-through-hydrogenation mechanism. The results suggest that oxygen removal occurs sequentially: the -OCH3 group is removed as methanol, followed by removal of the -OH group as a water molecule. From the point of view of the supported cluster, an original growing algorithm was devised to determine the most stable geometries of Ptn and Nin clusters (n = 1-10) on a defective graphene support; their structures were interpreted in terms on inter-cluster and cluster-defect interactions. The atom-by-atom accretion of clusters on graphene surface with single vacancy was examined, showing that defective graphene improves the dispersion of metal clusters, preventing sintering and agglomeration phenomena, which limit the effectiveness of catalysts over time. In addition, graphene increases the stability of the clusters, enhancing their catalytic activity and reducing deactivation caused by coke formation or sintering in HDO reactions, a factor of high relevance for industrial applications where long-term stability is essential to ensure process efficiency. The use of graphene as a support also allows for a reduction in the amount of noble metals needed, lowering costs and improving the sustainability of catalytic processes, in line with the principles of green chemistry. The DFT results highlighted differences in the interactions of Pt and Ni with oxygen: nickel, in particular, shows a stronger interaction with the oxygen atom than platinum, a behaviour that doesn’t appear to be affected by π interactions in the system, suggesting a significant impact on catalytic reactivity. The Pt10/C and Ni10/C were later employed to detail the energetics of two important elementary processes for guaiacol valorization: the loss of the oxigenated hydroxy and methoxy groups. The results obtained in this PhD project provide new perspectives for the use of advanced materials such as graphene in the design of more efficient and stable catalysts, improving the understanding of hydrodeoxygenation mechanisms of biomass-derived compounds and opening new possibilities for sustainable industrial applications.