Electrochemical oxidation of CO on Cu single crystals under alkaline conditions

We perform a joint experimental-theoretical study of the electrochemical oxidation of CO on copper (Cu) under alkaline conditions. Using cyclic voltammetry on Cu single crystal surfaces, we demonstrate that both Cu terraces and steps show CO oxidation activity at potentials just slightly positive (0.03-0.14 V) of the thermodynamic equilibrium potential. The overpotentials are 0.23-0.12 V lower than that of gold (approx. 0.26 V), which up until now has been considered to be the most active catalyst for this process. Our theoretical calculations suggest that Cu's activity arises from the advantageous combination of simultaneous *OH adsorption under CO oxidation potentials and surmountable *CO-*OH coupling barriers. Experimentally observed onset potentials are in agreement with the computed onsets of *OH adsorption. We furthermore show that the onsets of *OH adsorption on steps are more affected by *CO-*OH interactions than on terraces due to a stronger competitive adsorption. Overall, Cu(100) shows the lowest overpotential (0.03 V) of the facets considered.Comment: 16 pages, 3 figures plus supplementary informatio

Solvation of furfural at metal–water interfaces: Implications for aqueous phase hydrogenation reactions

Metal-water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces' degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal-water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal-water interfaces compared to the metal-gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. Our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates

Kinetics of Graphene Growth on Liquid Copper by Chemical Vapor Deposition

We report a combined experimental and computational study of the kinetics of graphene growth during chemical vapor deposition on a liquid copper catalyst. The use of liquid metal catalysts offers bright perspectives for controllable large-scale, high-quality synthesis technologies of two-dimensional materials. We carried out a series of growth experiments varying CH4-to-H2 pressure ratios and deposition temperature. By monitoring the graphene flake morphology in real time during growth using in situ optical microscopy in radiation mode, we explored the morphology and kinetics of the growth within a wide range of experimental conditions. Following an analysis of the flakes' growth rates, we conclude that the growth mode was attachment-limited. The attachment and detachment activation energies of carbon species are derived as 1.9 +- 0.3 eV and 2.0 +- 0.1 eV, respectively. We also conducted free-energy calculations by a moment tensor potential trained to density functional theory data. Our simulations propose that carbon dimers are most likely the active carbon species during growth, with attachment and detachment barriers of 1.71 +- 0.15 eV and 2.09 +- 0.02 eV, respectively, being in good agreement with the experimental results

A foundation model for atomistic materials chemistry

Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations of ab initio quality on unprecedented time and length scales. However, they are currently limited by: (i) the significant computational and human effort that must go into development and validation of potentials for each particular system of interest; and (ii) a general lack of transferability from one chemical system to the next. Here, using the state-of-the-art MACE architecture we introduce a single general-purpose ML model, trained on a public database of 150k inorganic crystals, that is capable of running stable molecular dynamics on molecules and materials. We demonstrate the power of the MACE-MP-0 model - and its qualitative and at times quantitative accuracy - on a diverse set problems in the physical sciences, including the properties of solids, liquids, gases, chemical reactions, interfaces and even the dynamics of a small protein. The model can be applied out of the box and as a starting or "foundation model" for any atomistic system of interest and is thus a step towards democratising the revolution of ML force fields by lowering the barriers to entry.Comment: 119 pages, 63 figures, 37MB PD

Combining first-principles kinetics and experimental data to establish guidelines for product selectivity in electrochemical CO(2) reduction

The electrochemical reduction of CO(2) is envisioned as one of the most promising ways to close the industrial carbon cycle by producing high value chemicals and fuels using renewable electricity. Although the performance of CO2 electrolyzers has im proved substantially in the last decade, they still suffer from poor selectivity towards the most desired products, ethylene and ethanol. This is in part due to the fact that a detailed mechanistic understanding of the selectivity towards various products is still lacking, although such an understanding is essential for process optimization. Herein, we perform microkinetic simulations based on constant potential density functional theory to elucidate the reaction pathways for CO(2) electroreduction on Cu towards the major multi-carbon products. We find that ethylene is the first product that bifurcates from the oxygenates, followed by acetate. Acetaldehyde is a direct intermediate in the production of ethanol. We provide atomistic level insights on the major role played by the electrode potential and electrolyte pH in determining the selectivity towards ethylene, oxygenates and methane, and relate the origin of the selectivity to general trends in electrochemical reaction energetics. We verify the results of our microkinetic simulations to an experimental database of previously reported measurements. Finally, we suggest guidelines for improving the selectivity towards the specific products. Our study paves the way for the design of efficient CO2 electrolyzers for the production of targeted multi-carbon products, thereby moving a step closer towards their widespread adaptation

Number of sites based solver for determining coverages from steady-state mean-field micro-kinetic models

Kinetic models parameterised by ab-initio calculations have led to significant improvements in understanding chemical reactions in heterogeneous catalysis. These studies have been facilitated by implementations which determine steady-state coverages and rates of mean-field micro-kinetic models. As implemented in the open-source kinetic modelling program, CatMAP, the conventional solution strategy is to use a root-finding algorithm to determine the coverage of all intermediates through the steady-state expressions, constraining all coverages to be non-negative and to properly sum to unity. Though intuitive, this root-finding strategy causes issues with convergence to solution due to these imposed constraints. In this work, we avoid explicitly imposing these constraints, solving the mean-field steady-state micro-kinetic model in the space of number of sites instead of solving it in the space of coverages. We transform the constrained root-finding problem to an unconstrained least-squares minimisation problem, leading to significantly improved convergence in solving micro-kinetic models and thus enabling the efficient study of more complex catalytic reactions

OH binding energy as a universal descriptor of the potential of zero charge on transition metal surfaces

The potential of zero charge (U_PZC) is an important quantity of metal-water interfaces that are central in many electrochemical applications. In this work, we use ab initio molecular dynamics (AIMD) simulations to study a large number of (111), (100), (0001) and (211) and overlayers of transition metal-water interfaces in order to identify simple descriptors to predict their U_PZC. We find a good correlation between water coverage and the work function reduction Δφ which is defined by the difference of the work function in vacuum and in the presence of water. Furthermore, we determine the vacuum binding energies of H2O and *OH species as good descriptors for the prediction of water coverage and thereby of ∆φ. Our insights unify different facet geometries and mixed metal surfaces and thereby generalize recent observations. We further present a scheme to predict U_PZC based only on the *OH binding and the vacuum work function estimated from static DFT calculations. This formalism is applicable to all investigated metals and mixed metal surfaces including terrace and step geometries and does not require expensive AIMD simulations. To evaluate physical influences to U_PZC, we decompose ∆φ into its orientational (∆φ_orient) and electronic(∆φ_el) components. We find ∆φ_orient to be a facet dependent property and a major contributor to ∆φ on (211) surfaces, while ∆φ_sub strongly depends on the metal identity

Solvation at Metal/water Interfaces: An Ab Initio Molecular Dynamics Benchmark of Common Computational Approaches

Rationalizing the influence of the solvent on electrochemical reaction energetics is a central challenge in our understanding of electrochemical interfaces. To date, it is unclear how well existing methods predict solvation energies at solid/liquid interfaces since they cannot be assessed experimentally. Ab initio molecular dynamics (AIMD) simulations present a physically highly accurate, but also a very costly approach. In this work, we employ extensive AIMD simulations to benchmark solvation at charge-neutral metal/water interfaces against commonly applied continuum solvent models. We consider a variety of adsorbates including *CO, *CHO, *COH, *OCCHO, and *OH on Cu, Au, and Pt facets solvated by water. The surfaces and adsorbates considered are relevant, among other reactions, to electrochemical CO2 reduction and the oxygen redox reactions. We determine directional hydrogen bonds and steric water competition to be critical for a correct description of solvation at the metal/water interfaces. As a consequence, we find that the most frequently applied continuum sol- vation methods, which do not yet capture these properties, do not presently provide more accurate energetics over simulations in vacuum. We find most of the computed benchmark solvation energies to linearly scale with hydrogen bonding or competitive water adsorption, which strongly differs across surfaces. Thus, we determine solvation energies of adsorbates to be non-transferable between metal surfaces in contrast to standard practice. </div