Rodrigo García-Muelas

Process optimization in heterogeneous catalysis relies on the control of competing reactions. The reaction mechanisms based on chemical knowledge can be evaluated via density functional theory unveiling experimental catalytic trends. However, this approach finds its limits when applied to complex reaction networks or large molecules, disregarding alternative paths and rare events. Here we present CARE, a foundational model for catalysis on metal surfaces with a rule-based reaction network generator for CxHyOz species built with GAME-Net-UQ, a graph neural network with uncertainty quantification targeting thermodynamic and kinetic parameters, coupled to microkinetic modeling. CARE reproduces experimental activity trends in methanol decomposition, selectivity to C3 products in electrochemical reduction processes, and models the Fischer-Tropsch synthesis to C6 products, including 370k reactions, breaking the current limits of network exploration. This comprehensive model opens the path towards the exploration of thermal and electrocatalytic surface processes previously not amenable to atomistic simulations.

A plethora of metal promoters have been applied to enhance the performance of In₂O₃ in CO₂ hydrogenation to methanol, a prospective energy carrier. However, the lack of systematic catalyst preparation and evaluation precludes a direct comparison of their speciation and promotional effects, and consequently, the design of an optimal system. Herein, flame spray pyrolysis (FSP) is employed as a standardized synthesis method to introduce nine metal promoters (0.5 wt.%) into In₂O₃. Methanol productivity generally increased on M‐In₂O₃ with selectivity following Pd ≈ Pt > Rh ≈ Ru ≈ Ir > Ni ≈ Co > Ag ≈ In₂O₃ > Au. In‐depth characterization, kinetic analyses, and theoretical calculations reveal a range of metal‐dependent speciation which dictate catalyst architecture and degree of promotion. Atomically‐dispersed promoters (Pd, Pt, Rh, Ru, and Ir) grant the highest improvement in performance, particularly Pd and Pt, which markedly promote hydrogen activation while hindering undesired CO formation. In contrast, metals in clustered (Ni and Co) and nanoparticle (Ag and Au) forms display moderate and no promotion, respectively. This study provides an atomic‐level understanding of In₂O₃ promotion based on a unified protocol, and highlights the potential of FSP to engineer complex catalytic systems toward more efficient energy transformations.

The mechanistic insights of CO₂ electrochemical reduction on Cu materials up to C₃ fragments are investigated by combining experiments and theory.

The mechanistic analysis in heterogeneous catalysis is based on listing all elementary steps and evaluating explicitly their energies. To this end, computational models based on Density Functional Theory have become a standard to estimate the information needed in mechanistic studies. Typically, either the minimum energy paths or those with the smaller span are summarized in reaction profiles. Such simplifications gather a lot of information, although further dimensionality reduction is required to obtain the most relevant descriptors of catalytic activity and generate the so‐called volcano plots. The selection of descriptors has been traditionally based on simple intermediates, such as central atoms in small molecules (as C in CH₄), which have good thermodynamic correlations to other fragments containing them. Yet, in emerging processes (recent studies), the number of intermediates involved increase, configurational effects and lateral interactions become significant, and complex materials with low symmetry are employed, thus the simple rules encapsulated in linear scaling relationships lose their predictive power due to error accumulation. At the same time, large datasets generated for the intermediates call for statistical analysis and thus these techniques are being leveraged to chemical systems, particularly to reduce their dimensionality.This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods

Metal promotion in heterogeneous catalysis requires nanoscale-precision architectures to attain maximized and durable benefits. Herein, we unravel the complex interplay between nanostructure and product selectivity of nickel-promoted In₂O₃in CO₂hydrogenation to methanol through in-depth characterization, theoretical simulations, and kinetic analyses. Up to 10 wt.% nickel, InNi₃patches are formed on the oxide surface, which cannot activate CO₂but boost methanol production supplying neutral hydrogen species. Since protons and hydrides generated on In₂O₃drive methanol synthesis rather than the reverse water-gas shift but radicals foster both reactions, nickel-lean catalysts featuring nanometric alloy layers provide a favorable balance between charged and neutral hydrogen species. For nickel contents >10 wt.%, extended InNi₃structures favor CO production and metallic nickel additionally present produces some methane. This study marks a step ahead towards green methanol synthesis and uncovers chemistry aspects of nickel that shall spark inspiration for other catalytic applications.

The electroreduction of CO₂ (CO₂RR) is a promising strategy toward sustainable fuels. Cu is the only Earth-abundant and pure metal capable of catalyzing CO₂-to-hydrocarbons conversion with significant Faradaic efficiencies; yet, its dynamic structure under operando CO₂RR conditions remains unknown. Here, we track the Cu structure operando by electrochemical scanning tunneling microscopy and Raman spectroscopy. Surprisingly, polycrystalline Cu surfaces reconstruct forming Cu nanocuboids whose size can be controlled by the polarization potential and the time employed in their in situ synthesis, without the assistance of organic surfactants and/or halide anions. If the Cu surface is covered by a graphene monolayer, smaller features with enhanced catalytic activity for CO₂RR can be prepared. The graphene-protecting layer softens the 3D morphological changes that Cu-based catalysts suffer when exposed to aggressive electrochemical environments and allows us to track the kinetic roughening process. This novel strategy is promising for improving Cu long-term stability, and consequently, it could be used as a platform to ultimately control product selectivity.

The oxygen evolution reaction (OER) is the bottleneck of hydrogen production via water splitting and using efficient electrocatalysts becomes paramount to render this process viable. Metal–organic framework (MOF) catalysts, which are porous solid materials at the frontier between homogeneous and heterogeneous catalysis, have emerged as promising candidates. Earth-abundant MOF-74 materials have recently shown great performance towards the OER, but the true nature of their active sites remains unclear. Here, we employ density functional theory (DFT + U) to elucidate the reaction mechanism and rationalize the electrocatalytic activity of Fe–MOF-74. Our results demonstrate that the open metal sites of the pristine catalyst do not promote the OER; instead, metal sites associated with defective structures do. This study provides new insights into guiding the rational synthesis and post-synthetic engineering of MOFs for electrocatalysis.