Dependency of solvation effects on metal identity in surface reactions

Stay Hydrated! Impact of Solvation Phenomena on the CO2 Reduction Reaction at Pb(100) and Ag(100) surfaces

Herein, a comprehensive computational study of the impact of solvation on the reduction reaction of CO2 to formic acid (HCOOH) and carbon monoxide on Pb(100) and Ag(100) surfaces is presented. Results further the understanding of how solvation phenomena influence the adsorption energies of reaction intermediates. We applied an explicit solvation scheme harnessing a combined density functional theory (DFT)/microkinetic modeling approach for the CO2 reduction reaction. This approach reveals high selectivities for CO formation at Ag and HCOOH formation on Pb, resolving the prior disparity between ab initio calculations and experimental observations. Furthermore, the detailed analysis of adsorption energies of relevant reaction intermediates shows that the total number of hydrogen bonds formed by HCOO plays a primary role for the adsorption strength of intermediates and the electrocatalytic activity. Results emphasize the importance of explicit solvation for adsorption and electrochemical reaction phenomena on metal surfaces.

Accelerating explicit solvent models of heterogeneous catalysts with machine learning interatomic potentials

Realistically modelling how solvents affect catalytic reactions is a longstanding challenge due to its prohibitive computational cost. Typically, an explicit atomistic treatment of the solvent molecules is needed together with molecular dynamics (MD) simulations and enhanced sampling methods. Here, we demonstrate the utility of machine learning interatomic potentials (MLIPs), coupled with active learning, to enable fast and accurate explicit solvent modelling of adsorption and reactions on heterogeneous catalysts. MLIPs trained on-the-fly were able to accelerate ab initio MD simulations by up to 4 orders of magnitude while reproducing with high fidelity the geometrical features of water in the bulk and at metal-water interfaces. Using these ML-accelerated simulations, we accurately predicted key catalytic quantities such as the adsorption energies of CO*, OH*, COH*, HCO*, and OCCHO* on Cu surfaces and the free energy barriers of C-H scission of ethylene glycol over Cu and Pd surfaces, as validated with ab initio calculations. We envision that such simulations will pave the way towards detailed and realistic studies of solvated catalysts at large time- and length-scales.

The application of QM/MM simulations in heterogeneous catalysis

The QM/MM simulation method is provenly efficient for the simulation of biological systems, where an interplay of extensive environment and delicate local interactions drives a process of interest through a funnel on a complex energy landscape. Recent advances in quantum chemistry and force-field methods present opportunities for the adoption of QM/MM to simulate heterogeneous catalytic processes, and their related systems, where similar intricacies exist on the energy landscape. Herein, the fundamental theoretical considerations for performing QM/MM simulations, and the practical considerations for setting up QM/MM simulations of catalytic systems, are introduced; then, areas of heterogeneous catalysis are explored where QM/MM methods have been most fruitfully applied. The discussion includes simulations performed for adsorption processes in solvent at metallic interfaces, reaction mechanisms within zeolitic systems, nanoparticles, and defect chemistry within ionic solids. We conclude with a perspective on the current state of the field and areas where future opportunities for development and application exist.

Adsorption Energy in Oxygen Electrocatalysis

Adsorption energy (AE) of reactive intermediate is currently the most important descriptor for electrochemical reactions (e.g., water electrolysis, hydrogen fuel cell, electrochemical nitrogen fixation, electrochemical carbon dioxide reduction, etc.), which can bridge the gap between catalyst's structure and activity. Tracing the history and evolution of AE can help to understand electrocatalysis and design optimal electrocatalysts. Focusing on oxygen electrocatalysis, this review aims to provide a comprehensive introduction on how AE is selected as the activity descriptor, the intrinsic and empirical relationships related to AE, how AE links the structure and electrocatalytic performance, the approaches to obtain AE, the strategies to improve catalytic activity by modulating AE, the extrinsic influences on AE from the environment, and the methods in circumventing linear scaling relations of AE. An outlook is provided at the end with emphasis on possible future investigation related to the obstacles existing between adsorption energy and electrocatalytic performance.

Liquid-Phase Effects on Adsorption Processes in Heterogeneous Catalysis

Aqueous solvation free energies of adsorption have recently been measured for phenol adsorption on Pt(111). Endergonic solvent effects of ∼1 eV suggest solvents dramatically influence a metal catalyst's activity with significant implications for the catalyst design. However, measurements are indirect and involve adsorption isotherm models, which potentially reduces the reliability of the extracted energy values. Computational, implicit solvation models predict exergonic solvation effects for phenol adsorption, failing to agree with measurements even qualitatively. In this study, an explicit, hybrid quantum mechanical/molecular mechanical approach for computing solvation free energies of adsorption is developed, solvation free energies of phenol adsorption are computed, and experimental data for solvation free energies of phenol adsorption are reanalyzed using multiple adsorption isotherm models. Explicit solvation calculations predict an endergonic solvation free energy for phenol adsorption that agrees well with measurements to within the experimental and force field uncertainties. Computed adsorption free energies of solvation of carbon monoxide, ethylene glycol, benzene, and phenol over the (111) facet of Pt and Cu suggest that liquid water destabilizes all adsorbed species, with the largest impact on the largest adsorbates.

Hydrogen Spillover-Enhanced Heterogeneously Catalyzed Hydrodeoxygenation for Biomass Upgrading

Hydrodeoxygenation (HDO) is regarded as a promising technology for biomass upgrading to obtain sustainable and competitive chemicals and fuels. In fact, biomass HDO over heterogeneous solid catalysts is often accompanied by the phenomenon of hydrogen spillover, which further affects the catalytic performance. Thus, it is necessary to gain in-depth understand the promoting effect of hydrogen spillover in the biomass HDO process to obtain desired conversion and selectivity. This Review summarized the extensive research on hydrogen spillover in biomass refining and discussed in detail the regulation mechanism of hydrogen spillover in biomass HDO process, mainly by regulating different active center sites on catalyst supports, such as metal sites, acid sites, surface functional groups, and defective sites, which exhibit independent and synergistic characteristics promoting catalyst activity, selectivity, and stability. Finally, the prospective of hydrogen spillover in biomass HDO applications was critically evaluated, and the key technical challenges in developing "hydrogen-free" HDO and upgrading biofuels were highlighted. The presentation of hydrogen spillover-enhanced catalytic biomass HDO in this Review will hopefully provide insight and guidance for further development of efficient catalysts and preparation of high-value chemicals in the future.

Addressing Dynamics at Catalytic Heterogeneous Interfaces with DFT-MD: Anomalous Temperature Distributions from Commonly Used Thermostats

Density functional theory-based molecular dynamics (DFT-MD) has been widely used for studying the chemistry of heterogeneous interfacial systems under operational conditions. We report frequently overlooked errors in thermostated or constant-temperature DFT-MD simulations applied to study (electro)catalytic chemistry. Our results demonstrate that commonly used thermostats such as Nosé-Hoover, Berendsen, and simple velocity-rescaling methods fail to provide a reliable temperature description for systems considered. Instead, nonconstant temperatures and large temperature gradients within the different parts of the system are observed. The errors are not a "feature" of any particular code but are present in several ab initio molecular dynamics implementations. This uneven temperature distribution, due to inadequate thermostatting, is well-known in the classical MD community, where it is ascribed to the failure in kinetic energy equipartition among different degrees of freedom in heterogeneous systems (Harvey et al. J. Comput. Chem. 1998, 726-740) and termed the flying ice cube effect. We provide tantamount evidence that interfacial systems are susceptible to substantial flying ice cube effects and demonstrate that the traditional Nosé-Hoover and Berendsen thermostats should be applied with care when simulating, for example, catalytic properties or structures of solvated interfaces and supported clusters. We conclude that the flying ice cube effect in these systems can be conveniently avoided using Langevin dynamics.