The dry reforming of methane (DRM), i.e., the reaction of methane and CO to form a synthesis gas, converts two major greenhouse gases into a useful chemical feedstock. In this work, we probe the effect and role of Fe in bimetallic NiFe dry reforming catalysts. To this end, monometallic Ni, Fe, and bimetallic Ni-Fe catalysts supported on a MgAlO matrix derived via a hydrotalcite-like precursor were synthesized. Importantly, the textural features of the catalysts, i.e., the specific surface area (172-178 m/g), pore volume (0.51-0.66 cm/g), and particle size (5.4-5.8 nm) were kept constant. Bimetallic, NiFe with Ni/(Ni + Fe) = 0.8, showed the highest activity and stability, whereas rapid deactivation and a low catalytic activity were observed for monometallic Ni and Fe catalysts, respectively. XRD, Raman, TPO, and TEM analysis confirmed that the deactivation of monometallic Ni catalysts was in large due to the formation of graphitic carbon. The promoting effect of Fe in bimetallic Ni-Fe was elucidated by combining operando XRD and XAS analyses and energy-dispersive X-ray spectroscopy complemented with density functional theory calculations. Under dry reforming conditions, Fe is oxidized partially to FeO leading to a partial dealloying and formation of a Ni-richer NiFe alloy. Fe migrates leading to the formation of FeO preferentially at the surface. Experiments in an inert helium atmosphere confirm that FeO reacts via a redox mechanism with carbon deposits forming CO, whereby the reduced Fe restores the original Ni-Fe alloy. Owing to the high activity of the material and the absence of any XRD signature of FeO, it is very likely that FeO is formed as small domains of a few atom layer thickness covering a fraction of the surface of the Ni-rich particles, ensuring a close proximity of the carbon removal (FeO) and methane activation (Ni) sites.

Transition metal nanoparticles (NPs) are typically supported on oxides to ensure their stability, which may result in modification of the original NP catalyst reactivity. In a number of cases, this is related to the formation of NP/support interface sites that play a role in catalysis. The metal/support interface effect verified experimentally is commonly ascribed to stronger reactants adsorption or their facile activation on such sites compared to bare NPs, as indicated by DFT-derived potential energy surfaces (PESs). However, the relevance of specific reaction elementary steps to the overall reaction rate depends on the preferred reaction pathways at reaction conditions, which usually cannot be inferred based solely on PES. Hereby, we use a multiscale (DFT/microkinetic) modeling approach and experiments to investigate the reactivity of the Ni/AlO interface toward water-gas shift (WGS) and dry reforming of methane (DRM), two key industrial reactions with common elementary steps and intermediates, but held at significantly different temperatures: 300 vs 650 °C, respectively. Our model shows that despite the more energetically favorable reaction pathways provided by the Ni/AlO interface, such sites may or may not impact the overall reaction rate depending on reaction conditions: the metal/support interface provides the active site for WGS reaction, acting as a reservoir for oxygenated species, while all Ni surface atoms are active for DRM. This is in contrast to what PESs alone indicate. The different active site requirement for WGS and DRM is confirmed by the experimental evaluation of the activity of a series of AlO-supported Ni NP catalysts with different NP sizes (2-16 nm) toward both reactions.

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The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.

The partial hydrogenation of benzene to cyclohexene is an economically interesting and technically challenging reaction. Over the last four decades, a lot of work has been dedicated to the development of an exploitable process and several approaches have been investigated. However, environmental constraints often represent a limit to their industrial application, making further research in this field necessary. The goal of this review is to highlight the main findings of the different disciplines involved in understanding the governing principles of this reaction from a sustainable chemistry standpoint. Special emphasis is given to ruthenium-catalyzed liquid phase batch hydrogenation of benzene.