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Formation of stable carbides during CO bond dissociation on small ruthenium nanoparticles (RuNPs) is demonstrated, both by means of DFT calculations and by solid state 13 C NMR techniques. Theoretical calculations of chemical shifts in several model clusters are employed in order to secure experimental spectroscopic assignations for surface ruthenium carbides. Mechanistic DFT investigations, carried out on a realistic Ru 55 nanoparticle model (∼1 nm) in terms of size, structure and surface composition, reveal that ruthenium carbides are obtained during CO hydrogenation. Calculations also indicate that carbide formation via hydrogen-assisted hydroxymethylidyne (COH) pathways is exothermic and occurs at reasonable kinetic cost on standard sites of the RuNPs, such as 4-fold ones on flat terraces, and not only in steps as previously suggested. Another novel outcome of the DFT mechanistic study consists of the possible formation of μ 6 ruthenium carbides in the tip-B 5 site, similar examples being known only for molecular ruthenium clusters. Moreover, based on DFT energies, the possible rearrangement of the surface metal atoms around the same tip-site results in a μ-Ru atom coordinated to the remaining RuNP moiety, reminiscent of a pseudo-octahedral metal center on the NP surface.

Given that the properties of metal nanoparticles (NPs) depend on several parameters (namely, morphology, size, surface composition, crystalline structure, etc.), a computational model that brings a better understanding of a structure-property relationship at the nanoscale is a significant plus in order to explain the surface properties of metal NPs and also their catalytic viability, in particular, when envisaging a new stabilizing agent. In this study we combined experimental and theoretical tools to obtain a mapping of the surface of ruthenium NPs stabilized by ethanoic acid as a new capping ligand. For this purpose, the organometallic approach was applied as the synthesis method. The morphology and crystalline structure of the obtained particles was characterized by state-of-the art techniques (TEM, HRTEM, WAXS) and their surface composition was determined by various techniques (solution and solid-state NMR, IR, chemical titration, DFT calculations). DFT calculations of the vibrational features of model NPs and of the chemical shifts of model clusters allowed us to secure the spectroscopic experimental assignations. Spectroscopic data as well as DFT mechanistic studies showed that ethanoic acid lies on the metal surface as ethanoate, together with hydrogen atoms. The optimal surface composition determined by DFT calculations appeared to be ca. [0.4-0.6] H/Rusurf and 0.4 ethanoate/RuSurf, which was corroborated by experimental results. Moreover, for such a composition, a hydrogen adsorption Gibbs free energy in the range -2.0 to -3.0 kcal mol-1 was calculated, which makes these ruthenium NPs a promising nanocatalyst for the hydrogen evolution reaction in the electrolysis of water.

Hydrogen-air mixtures are highly flammable. Hydrogen sensors are therefore of paramount importance for timely leak detection during handling. However, existing solutions do not meet the stringent performance targets set by stakeholders, while deactivation due to poisoning, for example by carbon monoxide, is a widely unsolved problem. Here we present a plasmonic metal-polymer hybrid nanomaterial concept, where the polymer coating reduces the apparent activation energy for hydrogen transport into and out of the plasmonic nanoparticles, while deactivation resistance is provided via a tailored tandem polymer membrane. In concert with an optimized volume-to-surface ratio of the signal transducer uniquely offered by nanoparticles, this enables subsecond sensor response times. Simultaneously, hydrogen sorption hysteresis is suppressed, sensor limit of detection is enhanced, and sensor operation in demanding chemical environments is enabled, without signs of long-term deactivation. In a wider perspective, our work suggests strategies for next-generation optical gas sensors with functionalities optimized by hybrid material engineering.

Working closely with experimentalists on the comprehension of the surface properties of catalytically active organometallic nanoparticles (NPs) requires the development of several computational strategies which significantly differ from the cluster domain where a precise knowledge of their optimal geometry is a mandatory prerequisite to computational modeling. Theoretical simulations can address several properties of organometallic nanoparticles: the morphology of the metal core, the surface composition under realistic thermodynamic conditions, the relationship between adsorption energies and predictive descriptors of reactivity. It is in such context that an integrated package has been developed or adapted in our group: (i) one tool aims at building a wide variety of the typical shapes exhibited by nanoparticles. Using Reverse Monte Carlo modeling, a given shape can be optimized in order to fit pair distribution function data obtained from X-ray diffraction measurements; (ii) trends in density functional theory (DFT) adsorption energies of surface species can be rationalized and predicted by making use of simple descriptors. This is why we have proposed an extension of the d-band center model, that leads to the formulation of a generalized ligand-field theory. A comparison between cobalt and ruthenium is proposed in the case of a 55-atoms nanocluster. The accuracy of the generalized coordination number [Angew. Chem., Int. Ed., 2014, 53, 8316], a very simple coordination-activity criterion, is also assessed; (iii) the builder package is completed by the steric-driven grafting of ligands on the surface of metal NPs. It easily generates structures with adjustable surface composition values and coordination modes; (iv) after a local optimization at the DFT level of theory, DFT energies and normal modes of vibration can feed a general tool based on the ab initio thermodynamics method. This method aims at easily calculating an optimal surface composition under realistic temperature and pressure conditions. In addition to that, we also show to what extent knowledge of the density of states (DOS) and of the crystal overlap Hamilton population (COHP), both projected from a plane-wave basis set to a local basis set, sheds light on metal core-ligand chemical bonding.

A deeper understanding of the relationship between experimental reaction conditions and the surface composition of nanoparticles is crucial in order to elucidate mechanisms involved in nanocatalysis. In the framework of the Fischer-Tropsch synthesis, a resolution of this complex puzzle requires a detailed understanding of the interaction of CO and H with the surface of the catalyst. In this context, the single- and co-adsorption of CO and H to the surface of a 1 nm ruthenium nanoparticle has been investigated with density functional theory. Using several indexes (d-band center, crystal overlap Hamilton population, density of states), a systematic analysis of the bond properties and of the electronic states has also been done, in order to bring an understanding of structure/property relationships at the nanoscale. The H : CO surface composition of this ruthenium nanoparticle exposed to syngas has been evaluated according to a thermodynamic model fed with DFT energies. Such ab initio thermodynamic calculations give access to the optimal H : CO coverage values under a wide range of experimental conditions, through the construction of free energy phase diagrams. Surprisingly, under the Fischer-Tropsch synthesis experimental conditions, and in agreement with new experiments, only CO species are adsorbed at the surface of the nanoparticle. These findings shed new light on the possible reaction pathways underlying the Fischer-Tropsch synthesis, and specifically the initiation of the reaction. It is finally shown that the joint knowledge of the surface composition and energy descriptors can help to identify possible reaction intermediates.