Hydrogen-Induced Restructuring of a Cu(100) Electrode in Electroreduction Conditions

H and CO Co-Induced Roughening of Cu Surface in CO2 Electroreduction Conditions

The dynamic restructuring of Cu has been observed under electrochemical conditions, and it has been hypothesized to underlie the unique reactivity of Cu toward CO2 electroreduction. Roughening is one of the key surface phenomena for Cu activation, whereby numerous atomic vacancies and adatoms form. However, the atomic structure of such surface motifs in the presence of relevant adsorbates has remained elusive. Here, we explore the chemical space of Cu surface restructuring under coverage of CO and H in realistic electroreduction conditions, by combining grand canonical DFT and global optimization techniques, from which we construct a potential-dependent grand canonical ensemble representation. The regime of intermediate and mixed CO and H coverage─where structures exhibit some elevated surface Cu─is thermodynamically unfavorable yet kinetically inevitable. Therefore, we develop a quasi-kinetic Monte Carlo simulation to track the system's evolution during a simulated cathodic scan. We reveal the evolution path of the system across coverage space and identify the accessible metastable structures formed along the way. Chemical bonding analysis is performed on the metastable structures with elevated Cu*CO species to understand their formation mechanism. By molecular dynamics simulations and free energy calculations, the surface chemistry of the Cu*CO species is explored, and we identify plausible mechanisms via which the Cu*CO species may diffuse or dimerize. This work provides rich atomistic insights into the phenomenon of surface roughening and the structure of involved species. It also features generalizable methods to explore the chemical space of restructuring surfaces with mixed adsorbates and their nonequilibrium evolution.

Surface phase diagrams from nested sampling

Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite temperatures. The Bayesian-inference-based nested sampling (NS) algorithm allows for modeling phase equilibria at arbitrary temperatures by directly and efficiently calculating the partition function, whose relationship with free energy is well known. This work extends NS to calculate adsorbate phase diagrams, incorporating all relevant configurational contributions to the free energy. We apply NS to the adsorption of Lennard-Jones (LJ) gas particles on low-index and vicinal LJ solid surfaces and construct the canonical partition function from these recorded energies to calculate ensemble averages of thermodynamic properties, such as the constant-volume heat capacity and order parameters that characterize the structure of adsorbate phases. Key results include determining the nature of phase transitions of adsorbed LJ particles on flat and stepped LJ surfaces, which typically feature an enthalpy-driven condensation at higher temperatures and an entropy-driven reordering process at lower temperatures, and the effect of surface geometry on the presence of triple points in the phase diagrams. Overall, we demonstrate the ability and potential of NS for surface modeling.

CO2-Promoted Electrocatalytic Reduction of Chlorinated Hydrocarbons

Electrochemical reactions and their catalysis are important for energy and environmental applications, such as carbon neutralization and water purification. However, the synergy in electrocatalysis between CO2 utilization and wastewater treatment has not been explored. In this study, we find that the electrochemical reduction of chlorinated organic compounds such as 1,2-dichloroethane, trichloroethylene, and tetrachloroethylene into ethylene in aqueous media, which is a category of challenging reactions due to the competition of H2 evolution, can be substantially enhanced by simultaneously carrying out the reduction of CO2 on an easily prepared and cost-effective Cu metal catalyst. In the case of 1,2-dichloroethane dechlorination, a 6-fold improvement in Faradaic efficiency and a 19-fold increase in partial current density are demonstrated. Through electrochemical kinetic studies, in situ Raman spectroscopy, and computational simulations, we further find that CO2 reduction reduces hydrogen coverage on the Cu catalyst, which not only exposes more active sites for the dechlorination reaction but also enhances the effective reductive potential on the catalyst surface and reduces the kinetic barrier of the rate-determining step.

Understanding the Adiabatic Evolution of Surface States in Tetradymite Topological Insulators under Electrochemical Conditions

Nontrivial surface states in topological materials have emerged as exciting targets for surface chemistry research. In particular, topological insulators have been used as electrodes in electrocatalytic reactions. Herein, we investigate the robustness of the topological surface states and band topology under electrochemical conditions, specifically in the presence of an electric double layer. First-principles band structure calculations are performed on the electrified (111) surfaces of Bi2Te3, Bi2Se3, and Sb2Te3 using an implicit electrolyte model. Our results demonstrate the adiabatic evolution of the surface states upon surface charging. Under oxidizing potentials, the surface states are shifted upward in energy, preserving the Dirac point on the surface and the band inversion in the bulk. Conversely, under reduced potentials, hybridization is observed between the surface and bulk states, suggesting a likely breakdown of topological protection. The position of the Fermi level, which dictates the working states in catalytic reactions, should ideally be confined within the bulk bandgap. This requirement defines a potential window for the effective application of topological electrocatalysis.

Hydrogen-triggered metal filament rupture in Cu-based resistance switches

Cation-based resistance switches have been considered as promising candidates for memory cells and other novel devices. So far, the most accepted switching processes of such devices are based on the formation/rupture of metallic filaments between two electrodes. Although many recent studies have identified the existence of H2O (and resulting -OH groups) in such devices, their effects on the switching process are still unclear. In the present work, by taking Cu/Ta2O5/Pt device as an example, we have theoretically revealed that H ions may dissociate from -OH groups and accumulate onto the Cu filament in amorphous Ta2O5. After that, the adsorbed H ions will induce a series of changes, such as the elongation of the adjacent Cu-Cu bonds, the weakening of the Cu-Cu bonds, the increase of charge on Cu cations, and the enhancement of diffusivities of Cu cations, all of which eventually lead to the rupture of the Cu filament. Interestingly, our proposed 'H-triggered metal filament rupture' model is similar to the widely studied 'hydrogen embrittlement phenomenon'. The crucial point of this model is the high catalytic activity of Cu towards the splitting of -OH group. Consequently, it is expected that this model could be applicable to other Cu-cation based resistance switches.

H-Induced Restructuring on Cu(111) Triggers CO Electroreduction in an Acidic Electrolyte

In acidic conditions, the electroreduction of CO or CO2 (noted CO(2)RR) on metal surfaces is conventionally hindered by intense competition with the hydrogen evolution reaction (HER). In this study, we present first-principles calculations of a mechanism wherein the formation of H-induced Cu adatoms on Cu(111) serves as a pivotal trigger for CORR in acidic environments. Through an analysis of the grand canonical surface state population, we elucidate that these newly formed adatoms create an array of active sites essential for both CO adsorption and subsequent reduction. Our ensemble-based kinetic models unveil the role of adatoms, enhancing the HER while simultaneously initiating CORR. Notably, the cumulative activity of the HER and CORR is contingent upon the combination of various surface states, with their individual contributions varying based on the electrode potential and pH. The interplay between surface state dynamics and electrochemical activity sheds new light on the potential-dependent nature of the active site and reaction kinetics governing CORR on Cu(111) in acidic media.

SHINERS Study of Chloride Order-Disorder Phase Transition and Solvation of Cu(100)

Shell-isolated nanoparticle enhanced Raman spectroscopy (SHINERS) and density functional theory (DFT) are used to probe Cl- adsorption and the order-disorder phase transition associated with the c(2 × 2) Cl- adlayer on Cu(100) in acid media. A two-component ν(Cu-Cl) vibrational band centered near 260 ± 1 cm-1 is used to track the potential dependence of Cl- adsorption. The potential dependence of the dominant 260 cm-1 component tracks the coverage of the fluctional c(2 × 2) Cl- phase on terraces in good agreement with the normalized intensity of the c(2 × 2) superstructure rods in prior surface X-ray diffraction (SXRD) studies. As the c(2 × 2) Cl- coverage approaches saturation, a second ν(Cu-Cl) component mode emerges between 290 and 300 cm-1 that coincides with the onset and stiffening of step faceting where Cl- occupies the threefold hollow sites to stabilize the metal kink saturated Cu <100> step edge. The formation of the c(2 × 2) Cl- adlayer is accompanied by the strengthening of ν(O-H) stretching modes in the adjacent non-hydrogen-bonded water at 3600 cm-1 and an increase in hydronium concentration evident in the flanking H2O modes at 3100 cm-1. The polarization of the water molecules and enrichment of hydronium arise from the combination of Cl- anionic character and lateral templating provided by the c(2 × 2) adlayer, consistent with SXRD studies. At negative potentials, Cl- desorption occurs followed by development of a sulfate νs(S═O) band. Below -1.1 V vs Hg/HgSO4, a new 200 cm-1 mode emerges congruent with hydride formation and surface reconstruction reported in electrochemical scanning tunneling microscopy studies.

Machine-learning-accelerated simulations to enable automatic surface reconstruction

Understanding material surfaces and interfaces is vital in applications such as catalysis or electronics. By combining energies from electronic structure with statistical mechanics, ab initio simulations can, in principle, predict the structure of material surfaces as a function of thermodynamic variables. However, accurate energy simulations are prohibitive when coupled to the vast phase space that must be statistically sampled. Here we present a bi-faceted computational loop to predict surface phase diagrams of multicomponent materials that accelerates both the energy scoring and statistical sampling methods. Fast, scalable and data-efficient machine learning interatomic potentials are trained on high-throughput density-functional-theory calculations through closed-loop active learning. Markov chain Monte Carlo sampling in the semigrand canonical ensemble is enabled by using virtual surface sites. The predicted surfaces for GaN(0001), Si(111) and SrTiO3(001) are in agreement with past work and indicate that the proposed strategy can model complex material surfaces and discover previously unreported surface terminations.

Realistic Modeling of the Electrocatalytic Process at Complex Solid-Liquid Interface

The rational design of electrocatalysis has emerged as one of the most thriving means for mitigating energy and environmental crises. The key to this effort is the understanding of the complex electrochemical interface, wherein the electrode potential as well as various internal factors such as H-bond network, adsorbate coverage, and dynamic behavior of the interface collectively contribute to the electrocatalytic activity and selectivity. In this context, the authors have reviewed recent theoretical advances, and especially, the contributions to modeling the realistic electrocatalytic processes at complex electrochemical interfaces,  and illustrated the challenges and fundamental problems in this field. Specifically, the significance of the inclusion of explicit solvation and electrode potential as well as the strategies toward the design of highly efficient electrocatalysts are discussed. The structure-activity relationships and their dynamic responses to the environment and catalytic functionality under working conditions are illustrated to be crucial factors for understanding the complexed interface and the electrocatalytic activities. It is hoped that this review can help spark new research passion and ultimately bring a step closer to a realistic and systematic modeling method for electrocatalysis.

Core-shell nanostructured Cu-based bi-metallic electrocatalysts for co-production of ethylene and acetate

Direct electrocatalytic CCU routes to produce a myriad of valuable chemicals (e.g., methanol, acetic acid, ethylene, propanol, among others) will allow the chemical industry to shift away from the conventional fossil-based production. Electrofuels need to go beyond the current electroreduction of CO2 to CO, and we will here demonstrate the continuous flow electroreduction of syngas (i.e., CO and H2), which are the products from CO2-to-CO, with enhanced product selectivity (∼90% towards ethylene). To overcome current drawbacks, including bicarbonate formation that resulted in low CO2 utilisation and low C2+ product selectivity, the development of nanostructured core-shell bi-metallic electrocatalysts for direct electrochemical reduction of syngas to C2+ is proposed. Electrosynthesis of ethylene is performed in a state-of-the-art continuous flow three-compartment cell to produce ethylene (cathodic gas phase product) and acetate (cathodic liquid phase product), simultaneously.

Synthesis, Structural Characterization, and CO2 Reactivity of a Constitutionally Analogous Series of Tricopper Mono-, Di-, and Trihydrides

The formation of hydrides at heterogeneous copper surfaces results in dramatic structural and reactivity changes, yet the morphologies of these materials and their respective roles in catalysis are not well understood. Of particular interest is the reactivity of heterogeneous copper hydrides with carbon dioxide (CO₂), an early mechanistic branching point in the CO₂ reduction reaction. Herein, we report the synthesis, characterization, and reactivity of tricopper compounds supported by a facially biased, chelating tris(carbene) ligand scaffold. This sterically bulky environment affords access to an isolable series of tricopper hydrides: [LCu₃H]²⁺ (4), [LCu₃H₂]⁺ (3), and LCu₃H₃ (6). Single-crystal X-ray diffraction and solution NMR spectroscopy studies reveal both geometric flexibility within the Cu₃ core and fluxionality of hydride ligands across the Cu₃ cluster, providing both atomically precise experimental analogues of static surface species and emulating dynamic ligand behavior proposed for surfaces. Electronic structure calculations serve as a predictor of hydricity, which was likewise benchmarked experimentally via both protonolysis and hydride abstraction reactions. Increased hydride number (and commensurately lower cluster charge) results in more hydridic complexes, with a thermodynamic hydricity range spanning >30 kcal/mol. These thermochemical studies serve as an accurate predictor of CO₂ reactivity. Together, this Cu₃H_x series exhibits the structure/reactivity relationships proposed for catalytically active copper surfaces, validating the application of carefully designed molecular clusters toward elucidating mechanisms in surface science.