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

Unified Approach to Implicit and Explicit Solvent Simulations of Electrochemical Reaction Energetics

One of the major open challenges in ab initio simulations of the electrochemical interface is the determination of electrochemical barriers under a constant driving force. Existing methods to do so include extrapolation techniques based on fully explicit treatments of the electrolyte, as well as implicit solvent models which allow for a continuous variation in electrolyte charge. Emerging hybrid continuum models have the potential to revolutionize the field, since they account for the electrolyte with little computational cost while retaining some explicit electrolyte, representing a “best of both worlds” method. In this work, we present a unified approach to determine reaction energetics from both fully explicit, implicit, and hybrid treatments of the electrolyte based on a new multi-capacitor model of the electrochemical interface. A given electrode potential can be achieved by a variety of interfacial structures; a crucial insight from this work is that the effective surface charge gives the true driving force of electrochemical processes. In contrast, we show that the traditionally considered work function gives rise to multi-valued functions depending on the simulation cell size. Furthermore, we show that the reaction energetics are largely insensitive to the countercharge distribution chosen in hybrid implicit/explicit models, which means that any of the myriad implicit electrolyte models can be equivalently applied. This work thus paves the way for the accurate treatment of ab initio reaction energetics of general surface electrochemical processes using both implicit and explicit electrolyte. </div

Implications of Occupational Disorder on Ion Mobility in Li₄Ti₅O₁₂ Battery Materials

Lithium–titanium-oxide (Li₄Ti₅O₁₂, LTO) is unique among battery materials due to its exceptional cyclability and high rate capability. This performance is believed to derive at least partly from the occupational disorder introduced via mixed Li/Ti occupancy in the LTO spinel-like structure. We explore the vast configuration space accessible during high-temperature LTO synthesis by Monte Carlo sampling and indeed find lowest-energy structures to be characterized by a high degree of microscopic inhomogeneity. Dynamical simulations in corresponding configurations reveal the dominant fraction of Li ions to be immobile on nanosecond time scales. However, Ti antisite-like defects stabilized by the configurational disorder give rise to a novel correlated ion diffusion mechanism. The resulting fast but localized diffusion could be a key element in the sudden rise in conductivity found in LTO in the early stages of charging and questions the validity of ion mobility measurements for this and other configurationally disordered materials

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

Kinetic models parameterized 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 modeling 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 minimization problem, leading to significantly improved convergence in solving micro-kinetic models and thus enabling the efficient study of more complex catalytic reactions

First step of the oxygen reduction reaction on Au(111): A computational study of O2 adsorption at the electrified metal/water interface

Local field effects at the electrical double layer change the energies of reaction intermediates in heterogeneous electrocatalysis. The resulting dependence on (absolute) electrode potential can be pivotal to a catalyst\u27s performance in acid or alkaline media. And yet, such local field effects are very difficult to describe theoretically and are often ignored. In this work, we focus on O2 adsorption as the first step of the oxygen reduction reaction (ORR) on Au(111). Different physical effects of the local field are elucidated and compared by systematically improving the model of the double layer: from an applied saw-tooth potential in vacuum, to an implicit solvent model, and explicitly modeled water via ab initio molecular dynamics (AIMD). We find all models predict a dominant dipole-field type interaction that significantly strengthens O2 binding at increasingly reducing conditions. However, only an atomically-resolved solvent model such as provided by AIMD can properly capture the additional stabilization due to explicit H-bonding from the water network. This contribution comes with the formation of a peroxo-like surface species and a more dramatic field response around the ORR onset. Our results overall demonstrate the importance of including local electric field effects in models of the electrochemical interface, while assessing the level of detail that is required to be accounted for