Importance of the gas-phase error correction for O2 when using DFT to model the oxygen reduction and evolution reactions

Toward Realistic Models of the Electrocatalytic Oxygen Evolution Reaction

The electrocatalytic oxygen evolution reaction (OER) supplies the protons and electrons needed to transform renewable electricity into chemicals and fuels. However, the OER is kinetically sluggish; it operates at significant rates only when the applied potential far exceeds the reversible voltage. The origin of this overpotential is hidden in a complex mechanism involving multiple electron transfers and chemical bond making/breaking steps. Our desire to improve catalytic performance has then made mechanistic studies of the OER an area of major scientific inquiry, though the complexity of the reaction has made understanding difficult. While historically, mechanistic studies have relied solely on experiment and phenomenological models, over the past twenty years ab initio simulation has been playing an increasingly important role in developing our understanding of the electrocatalytic OER and its reaction mechanisms. In this Review we cover advances in our mechanistic understanding of the OER, organized by increasing complexity in the way through which the OER is modeled. We begin with phenomenological models built using experimental data before reviewing early efforts to incorporate ab initio methods into mechanistic studies. We go on to cover how the assumptions in these early ab initio simulations─no electric field, electrolyte, or explicit kinetics─have been relaxed. Through comparison with experimental literature, we explore the veracity of these different assumptions. We summarize by discussing the most critical open challenges in developing models to understand the mechanisms of the OER.

A Theoretical Benchmark of the Geometric and Optical Properties for 3d Transition Metal Nanoclusters via Density Functional Theory

Understanding structure-property relationships in atomically precise metal nanoclusters is vital in finding selective and tunable catalysts. In this study, density functional theory (DFT) was used to benchmark seven exchange correlation functionals at different basis sets for 17 atomically precise nanoclusters against experimentally determined geometries, band gaps, and optical gaps. The set contains both monometallic and bimetallic clusters that possess at least two types of 3d transition metals (specifically, Cu, Ni, Fe, or Co). The benchmark highlights that PBE0 is a good functional to use regardless of the basis set, and Minnesota functionals do well with respect to specific metals. Further, while long-range corrected functionals overestimate band and optical gaps, they model absorption features better than the other considered functionals. The study additionally looks at the photoinduced hydrogen evolution reaction (HER) and the CO2 reduction mechanism on nanoclusters reported from the literature.

Computational chemistry for water-splitting electrocatalysis

Electrocatalytic water splitting driven by renewable electricity has attracted great interest in recent years for producing hydrogen with high-purity. However, the practical applications of this technology are limited by the development of electrocatalysts with high activity, low cost, and long durability. In the search for new electrocatalysts, computational chemistry has made outstanding contributions by providing fundamental laws that govern the electron behavior and enabling predictions of electrocatalyst performance. This review delves into theoretical studies on electrochemical water-splitting processes. Firstly, we introduce the fundamentals of electrochemical water electrolysis and subsequently discuss the current advancements in computational methods and models for electrocatalytic water splitting. Additionally, a comprehensive overview of benchmark descriptors is provided to aid in understanding intrinsic catalytic performance for water-splitting electrocatalysts. Finally, we critically evaluate the remaining challenges within this field.

First-principles study of MXene properties with varying hydrofluoric acid concentration

With varying hydrofluoric acid (HF) concentrations under three etching conditions, we presented a comparative study of the effects of both the ordered and randomly ternary mixed terminated Ti3C2Tx surfaces with a wide variation of O/OH/F stoichiometry on the thermodynamic stability and electronic properties. Regardless of the HF concentration, an OH-rich surface is found to be thermodynamically stable and the electrical conductivity of Ti3C2Tx is substantially affected by the OH concentration. The charge density difference and electron localization function demonstrated a significant electron localization at the hydroxyl group on the O/OH/F mixed terminated surface, which could yield a locally induced dipole on the surface that renders favorable reaction sites on the functionalized surface. In addition, a large tunability in the work function (ΔΦ ∼ 3.5 eV) is predicted for Ti3C2Tx. These findings provide a pathway for strategically tuning the electronic and structural properties of Ti3C2 MXenes etched with HF.

The DFT and Machine Learning Method Accelerated the Discovery of DMSCs with High ORR and OER Catalytic Activities

The oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) are crucial for the conversion of clean energy. Recently, dual-metal-site catalysts (DMSCs) have gained much attention due to their high atom utilization, stronger stability, and better catalytic performance. An advanced method that combines density functional theory (DFT) and machine learning (ML) has been employed in this study to investigate the adsorption free energies of adsorbates on hundreds of potential catalysts, with the aim of screening for catalysts that are highly active for the ORR and OER. The result of this study is that 30 DMSCs with ORR activity superior to Pt, 10 DMSCs with OER activity superior to RuO2, and 4 bifunctional catalysts for the OER and ORR are identified. This work provides guidance for the rational selection of metals on DMSCs to prepare catalysts with a high electrocatalytic performance for renewable energy applications.

Importance of the Walden Inversion for the Activity Volcano Plot of Oxygen Evolution

Since the birth of the computational hydrogen electrode approach, it is considered that activity trends of electrocatalysts in a homologous series can be quantified by the construction of volcano plots. This method aims to steer materials discovery by the identification of catalysts with an improved reaction kinetics, though evaluated by means of thermodynamic descriptors. The conventional approach for the volcano plot of the oxygen evolution reaction (OER) relies on the assumption of the mononuclear mechanism, comprising the * OH, * O, and * OOH intermediates. In the present manuscript, two new mechanistic pathways, comprising the idea of the Walden inversion in that bond-breaking and bond-making occurs simultaneously, are factored into a potential-dependent OER activity volcano plot. Surprisingly, it turns out that the Walden inversion plays an important role since the activity volcano is governed by mechanistic pathways comprising Walden steps rather than by the traditionally assumed reaction mechanisms under typical OER conditions.

Modeling Single-Atom Catalysis

Electronic structure calculations represent an essential complement of experiments to characterize single-atom catalysts (SACs), consisting of isolated metal atoms stabilized on a support, but also to predict new catalysts. However, simulating SACs with quantum chemistry approaches is not as simple as often assumed. In this work, the essential factors that characterize a reliable simulation of SACs activity are examined. The Perspective focuses on the importance of precise atomistic characterization of the active site, since even small changes in the metal atom's surroundings can result in large changes in reactivity. The dynamical behavior and stability of SACs under working conditions, as well as the importance of adopting appropriate methods to solve the Schrödinger equation for a quantitative evaluation of reaction energies are addressed. The Perspective also focuses on the relevance of the model adopted. For electrocatalysis this must include the effects of the solvent, the presence of electrolytes, the pH, and the external potential. Finally, it is discussed how the similarities between SACs and coordination compounds may result in reaction intermediates that usually are not observed on metal electrodes. When these aspects are not adequately considered, the predictive power of electronic structure calculations is quite limited.

Minimum conditions for accurate modeling of urea production via co-electrolysis

Co-electrolysis of carbon oxides and nitrogen oxides promise to simultaneously help restore the balance of the C and N cycles while producing valuable chemicals such as urea. However, co-electrolysis processes are still largely inefficient and numerous knowledge voids persist. Here, we provide a solid thermodynamic basis for modelling urea production via co-electrolysis. First, we determine the energetics of aqueous urea produced under electrochemical conditions based on experimental data, which enables an accurate assessment of equilibrium potentials and overpotentials. Next, we use density functional theory (DFT) calculations to model various co-electrolysis reactions producing urea. The calculated reaction free energies deviate significantly from experimental values for well-known GGA, meta-GGA and hybrid functionals. These deviations stem from errors in the DFT-calculated energies of molecular reactants and products. In particular, the error for urea is approximately -0.25 ± 0.10 eV. Finally, we show that all these errors introduce large inconsistencies in the calculated free-energy diagrams of urea production via co-electrolysis, such that gas-phase corrections are strongly advised.

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.

Automated versus Chemically Intuitive Deconvolution of Density Functional Theory (DFT)-Based Gas-Phase Errors in Nitrogen Compounds

Catalysis models involving metal surfaces and gases are regularly based on density functional theory (DFT) calculations at the generalized gradient approximation (GGA). Such models may have large errors in view of the poor DFT-GGA description of gas-phase molecules with multiple bonds. Here, we analyze three correction schemes for the PBE-calculated Gibbs energies of formation of 13 nitrogen compounds. The first scheme is sequential and based on chemical intuition, the second one is an automated optimization based on chemical bonds, and the third one is an automated optimization that capitalizes on the errors found by the first scheme. The mean and maximum absolute errors are brought down close to chemical accuracy by the third approach by correcting the inaccuracies in the NNO and ONO backbones and those in N–O and N–N bonds. This work shows that chemical intuition and automated optimization can be combined to swiftly enhance the predictiveness of DFT-GGA calculations of gases.

The Ir-OOOO-Ir transition state and the mechanism of the oxygen evolution reaction on IrO2(110)

Carefully assessing the energetics along the pathway of the oxygen evolution reaction (OER), our computational study reveals that the "classical" OER mechanism on the (110) surface of iridium dioxide (IrO₂) must be reconsidered. We find that the OER follows a bi-nuclear mechanism with adjacent top surface oxygen atoms as fixed adsorption sites, whereas the iridium atoms underneath play an indirect role and maintain their saturated 6-fold oxygen coordination at all stages of the reaction. The oxygen molecule is formed, via an Ir-OOOO-Ir transition state, by association of the outer oxygen atoms of two adjacent Ir-OO surface entities, leaving two intact Ir-O entities at the surface behind. This is drastically different from the commonly considered mono-nuclear mechanism where the O₂ molecule evolves by splitting of the Ir-O bond in an Ir-OO entity. We regard the rather weak reducibility of crystalline IrO₂ as the reason for favoring the novel pathway, which allows the Ir-O bonds to remain stable and explains the outstanding stability of IrO₂ under OER conditions. The establishment of surface oxygen atoms as fixed electrocatalytically active sites on a transition-metal oxide represents a paradigm shift for the understanding of water oxidation electrocatalysis, and it reconciles the theoretical understanding of the OER mechanism on iridium oxide with recently reported experimental results from operando X-ray spectroscopy. The novel mechanism provides an efficient OER pathway on a weakly reducible oxide, defining a new strategy towards the design of advanced OER catalysts with combined activity and stability.

The Role of Steps on Silver Nanoparticles in Electrocatalytic Oxygen Reduction

Hydrogen fuel cell technology is an essential component of a green economy. However, it is limited in practicality and affordability by the oxygen reduction reaction (ORR). Nanoscale silver particles have been proposed as a cost-effective solution to this problem. However, previous computational studies focused on clean and flat surfaces. High-index surfaces can be used to model active steps presented in nanoparticles. Here, we used the stable stepped Ag(322) surface as a model to understand the ORR performance of steps on Ag nanoparticles. Our density functional theory (DFT) results demonstrate a small dissociation energy barrier for O2 molecules on the Ag(322) surface, which can be ascribed to the existence of low-coordination number surface atoms. Consequently, the adsorption of OOH* led to the associative pathway becoming ineffective. Alternatively, the unusual dissociative mechanism is energetically favored on Ag(322) for ORR. Our findings reveal the importance of the coordination numbers of active sites for catalytic performance, which can further guide electrocatalysts’ design.

Revealing the Nature of Active Sites on Pt-Gd and Pt-Pr Alloys during the Oxygen Reduction Reaction

For large-scale applications of hydrogen fuel cells, the sluggish kinetics of the oxygen reduction reaction (ORR) have to be overcome. So far, only platinum (Pt)-group catalysts have shown adequate performance and stability. A well-known approach to increase the efficiency and decrease the Pt loading is to alloy Pt with other metals. Still, for catalyst optimization, the nature of the active sites is crucial. In this work, electrochemical scanning tunneling microscopy (EC-STM) is used to probe the ORR active areas on Pt₅Gd and Pt₅Pr in acidic media under reaction conditions. The technique detects localized fluctuations in the EC-STM signal, which indicates differences in the local activity. The in situ experiments, supported by coordination-activity plots based on density functional theory calculations, show that the compressed Pt-lanthanide (111) terraces contribute the most to the overall activity. Sites with higher coordination, as found at the bottom of step edges or concavities, remain relatively inactive. Sites of lower coordination, as found near the top of step edges, show higher activity, presumably due to an interplay of strain and steric hindrance effects. These findings should be vital in designing nanostructured Pt-lanthanide electrocatalysts.

Water on porous, nitrogen-containing layered carbon materials: The performance of computational model chemistries

Porous, layered materials containing sp2-hybridized carbon and nitrogen atoms, offer through their tunable properties, a versatile route towards tailormade catalysts for electrochemistry and photochemistry. A key molecule interacting with these...