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At least 19 records

Incorporating Coverage-Dependent Reaction Barriers into First-Principles-Based Microkinetic Models: Approaches and Challenges

Mean-field microkinetic models (MKMs) are appealing for their relatively facile construction, computational tractability, and high-throughput catalyst screening capabilities. As such, they will continue to be a valuable tool for materials design in heterogeneous catalysis even as the field aims to describe more complex systems. Numerous prior reports have provided the groundwork for constructing first-principles-based MKMs, including the analysis of strategies for incorporating lateral interactions into thermodynamic parameters (e.g., adsorption energies). Yet, there remains a need for concerted dialogue on methods for calculating and incorporating coverage-dependent kinetic parameters into MKMs. In this Perspective, we assess strategies for doing so, including the corresponding key physical implications and computational challenges. Here, we emphasize that decoupling thermodynamic and kinetic parameters within MKMs can violate thermodynamic consistency and risk unphysical solutions. For some reactions and catalyst materials, scaling relationships can predict coverage-dependent activation energies, but there are several exceptions evident in the literature, indicating that this approach is not universally applicable and that the field could benefit from research aimed at elucidating the limitations. Conducting high-coverage transition state searches is a rigorous but computationally costly strategy, and the effects of various methods for mitigating this cost on resulting energetics have yet to be broadly explored and validated. The goal of this Perspective is to generate discussion on and inspire focused research into the physical relevance of approaches for describing coverage-dependent reaction barriers in MKMs, including the development of computationally tractable methodologies, to advance the applicability of MKMs across diverse reaction chemistries and conditions.

36 MATERIALS SCIENCE↗

Impact of microkinetic modeling assumptions on predicted kinetics and mechanisms over undercoordinated sites

Accurate modeling of catalytic reactions on undercoordinated sites requires accounting for the structural and ensemble-specific nature of the active sites. This study examines how common microkinetic modeling (MKM) assumptions affect predicted kinetics and mechanisms on the stepped Pt(211) facet for the ethane dehydrogenation (EDH) and the ethane hydrogenolysis (EH). Six (211) MKMs were developed, differing in (i) the number of active sites represented, (ii) adsorbate site occupancy treatment, and (iii) inclusion of cross-facet interactions. These models are benchmarked against a particle-based microkinetic model (PB-MKM), which best represents step-edge behavior. MKM assumptions caused deviations in turnover frequencies exceeding ten orders of magnitude and led to contrasting mechanistic and selectivity predictions. Multi-site MKMs overestimate activity by inflating free site availability, single-site models underestimate activity, and uniform occupancy models overpredict coverage of multi-dentate intermediates, leading to reaction-specific artifacts. Overall, the Combined Site Edge Model (CSEM), a single-site MKM accounting for site occupancy and cross-facet interactions, most closely approximates PB-MKM predictions. All models predict similar kinetics when surfaces are clean or primarily occupied by monodentate species. This work provides practical guidance for selecting MKM frameworks for undercoordinated catalytic surfaces and highlights the critical role of modeling assumptions in catalytic predictions.

(211) facet↗

A Unified Workflow for Sensitivity-Based Kinetic Analysis in Microkinetic Models

Degrees of rate control (DRC), apparent activation energies, and apparent reaction orders are established local sensitivity diagnostics for interpreting microkinetic models, but applying them routinely to large mechanisms often requires substantial reaction-specific bookkeeping, perturbation design, and postprocessing. Here, in this study, we present a unified derivative-based workflow that evaluates these quantities from a single compiled reaction-network model and target-rate definition. For any user-provided microkinetic model, the workflow compiles the mechanism into stoichiometrically consistent mass-action rate equations, solves the surface dynamics, and uses automatic differentiation to compute sensitivities with respect to rate constants, temperature, and gas partial pressures. By combining their calculations in the same framework, the workflow clearly demonstrates the relationships between different DRCs and the apparent activation energy. Using existing examples of propylene partial oxidation and methane oxidation on Pd(100), we verify expected transient redistribution of rate control, distinguish net Campbell DRCs from one-sided directional sensitivities, and show how apparent activation energy can be reconstructed either from one-sided DRCs or from state-based DRCs while critical mechanistic insights are obtained consistently. In the methane oxidation case, a pathway-subset test further illustrates how a simplified mechanism preserves key kinetic signatures of a full model, showing the potential of our user-friendly tool for model construction beyond kinetic analysis.

36 MATERIALS SCIENCE↗

Acetylene Semi-Hydrogenation on a Perovskite Oxyhydride Surface: Insights from First Principles and Microkinetic Modeling

Although perovskite oxyhydrides (POHs) have shown promise as a support for selective hydrogenation, it is unknown if they themselves can catalyze alkyne semi-hydrogenation. Here, we use first-principles density functional theory, coupled with microkinetic modeling, to investigate acetylene semi-hydrogenation on a prototypical POH, cubic BaTiO 2.5 H 0.5 (BTOH). Two different mechanisms are examined on a representative surface of BTOH under the reaction conditions: both are based on the Horiuti–Polanyi mechanism, but the way of H 2 dissociation is different. In mechanism 1, a lattice hydride H atom and then a surface adsorbed H atom sequentially hydrogenate the adsorbed acetylene. In mechanism 2, two lattice hydride H atoms from the BTOH sequentially hydrogenate the adsorbed acetylene. In both mechanisms, the H atoms are replenished from gas phase H 2 dissociation. Using density functional theory (DFT), we have calculated pathways for these two mechanisms in hydrogenation of acetylene to ethylene, as well as further to ethane. Microkinetic modeling based on the DFT energetics indicates that at 523 K, hydrogenation to ethylene and ethane via mechanism 1 occurs at a rate up to two orders of magnitude faster than via mechanism 2. A selectivity analysis for the temperature range of 373–673 K shows that the product observed is essentially only ethylene within the more active mechanism 1. This is because at the steady state, there is a significant amount of surface anion vacancies that facilitate heterolytic H 2 dissociation and help stabilize a vinyl intermediate. In conclusion, the present findings suggest that POHs are capable of selective hydrogenation, thanks to their rich hydrogen surface-redox chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanisms of Ethylene Epoxidation over Silver from Machine Learning-Accelerated First-Principles Modeling and Microkinetic Simulations

In this work we employed machine learning-augmented density functional theory (DFT) thermodynamic calculations to assess the stability of different AgO x structures under catalytic ethylene epoxidation reaction conditions. We found that there are multiple AgO x surface motifs that could co-exist under the relevant conditions. These included Ag surface oxides (e.g., AgO_p(4 × 4) and Ag 1.83 O) and atomic oxygen-covered Ag(111) surfaces. Furthermore, we employed DFT calculations to evaluate the energetics of different reaction mechanisms by which ethylene and oxygen can react on these surfaces. These studies revealed several energetically viable reaction pathways for ethylene epoxidation. Microkinetic modeling analyses, based on the DFT-calculated reaction pathways, showed that ethylene epoxidation can proceed on all surfaces and that multiple pathways, including those involving Langmuir–Hinshelwood and Eley–Rideal mechanisms, could be involved in selective and unselective reactions. The diversity of mechanisms that we discovered in the context of the relatively simple ethylene epoxidation reaction on Ag suggests that the richness and complexity of surface chemistry are most likely a rule rather than an exception in heterogeneous catalytic chemical transformations on metal surfaces and that the concept of a single or even a dominant mechanism and reaction intermediates might need to be revisited for many reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pore-Scale Transport Effects in Electrochemical CO 2 Reduction on Gold via Coupled Microkinetic-Transport Modeling

A pore-resolved modeling framework is developed to quantify how pore-scale transport affects the intrinsic microkinetics of CO 2 -to-CO on Au. A DFT-informed microkinetic model is coupled self-consistently to a Generalized-Modified Poisson–Nernst–Planck (GMPNP) transport description in a single, electrolyte-filled cylindrical pore, allowing local concentrations and potential to feed back into site-specific reaction rates. FIB-SEM is used to determine pore sizes within realistic electrode materials. Across pore diameters, d p = 10–6000 nm, the surface-averaged CO 2 reduction rate is systematically reduced relative to the ideal microkinetic baseline where mass transport is not accounted for; the effectiveness factor 𝜂 𝑠,CO 2 , which quantifies this ratio, decreases rapidly at more negative potentials and is about 1% near −1.0 V vs SHE due to reactant depletion. Spatial maps reveal pore-bulk alkalization that emerges at higher cathodic bias, with a small, near-wall pH dip due to electrostatic repulsion of hydroxide at the cathode interface. For a fixed aspect ratio L p /d p , narrower pores exhibit larger 𝜂 𝑠,CO 2 by shortening diffusion paths, whereas variations in the aspect ratio L p /d p play a secondary role. A dimensionless analysis (surface/bulk Damköhler numbers) delineates operating regimes. In conclusion, this work offers a concept for incorporating microkinetic models into homogenized porous-electrode models through effectiveness factors and pore-size distribution.

Au-catalyst↗

Unraveling the CO Oxidation Mechanism over Highly Dispersed Pt Single Atom on Anatase TiO 2 (101)

Catalysts with noble metals deposited as single atoms on metal oxide supports have recently been studied extensively due to their maximized metal utilization and potential for performing difficult chemical conversions owing to their unique electronic properties. Understanding of the reaction mechanisms on supported single-metal atoms is still limited but is highly important for designing more efficient catalysts. In this study, we report the complexity of the CO oxidation reaction mechanism on Pt single atoms supported on anatase TiO 2 (Pt SA /a-TiO 2 ) by coupling density functional theory (DFT) calculations and microkinetic analysis with kinetic measurements, in situ/operando infrared, and X-ray absorption spectroscopies. Starting from the adsorbed Pt SA occupying an O vacancy induced by reductive pretreatment, we show that CO oxidation follows a complex mechanism consisting of initiation steps to reorganize the active site and multibranch reactive cycles, with the Pt SA /a-TiO 2 catalyst not returning to its initial configuration. The initiation step consists of CO and O 2 adsorption healing the O vacancy, followed by CO oxidation using gas-phase CO to form Pt(CO). The reactive cycle alternates O 2 adsorption and dissociation to oxidize the catalyst to Pt(O)(O)(CO) and branching pathways of competing Langmuir–Hinshelwood (LH)- or Eley–Rideal (ER)-type CO oxidation steps to reduce it again to Pt(CO). In situ/operando infrared experiments, including cryogenic CO adsorption and isotopic CO exchange, confirm the combined involvement of strongly adsorbed CO and gas-phase CO in an Eley–Rideal step along the reaction cycle. Microkinetic modeling shows that Pt single atoms are present in a mixture of Pt(CO), Pt(CO)(O 2 ), Pt(O)(CO)(O 2 ), and Pt(CO)(CO 3 ) structures as the main intermediates during steady-state CO oxidation, all having the C–O vibrational stretch close to the experimentally observed value of 2115 cm –1 . Microkinetic modeling also shows that the fractional orders of CO and O 2 measured experimentally originate from multiple steps with a high degree of rate control and not from a simple competitive adsorption. The results demonstrate the complex reaction pathways that even CO oxidation on a simple single-atom system can follow, providing mechanistic insights for designing efficient Pt-based single-atom catalysts. Here, we further show that microkinetic modeling results are sensitive to changes in energies of intermediate and transition states within errors of density functional theory, which can ultimately lead to incorrect conclusions regarding the reaction pathways and most abundant reaction intermediates if not accounted for by experiments.

36 MATERIALS SCIENCE↗

Enhanced Selectivity for C 2 H 4 Production from C 2 H 6 on Partially Chlorinated IrO 2 (110) Surfaces

Modifying metal oxide surfaces to limit their oxidizing activity can provide a means of improving catalytic selectivity toward the partial oxidation of light alkanes. Here, in this study, we investigated the oxidation of C 2 H 6 on Cl-modified IrO 2 (110) surfaces using temperature-programmed reaction spectroscopy (TPRS) and first-principles microkinetic modeling. We find that substituting Cl for O in the IrO 2 (110) surface enhances the selectivity for C 2 H 6 conversion to C 2 H 4 during TPRS by suppressing extensive oxidation to CO x products, while also either enhancing C 2 H 4 production or altering it to a lesser extent, depending on the initial C 2 H 6 coverage. The C 2 H 4 selectivity increased with increasing C 2 H 6 and Cl coverage, but reached a limiting value below 50%. The Cl coverage changed negligibly during C 2 H 6 oxidation, and the surface reactivity decreased only marginally for Cl coverages up to 0.5 ML (monolayer). TPRS simulations using a microkinetic model predict C 2 H 4 and CO x product yields as a function of the Cl coverage that agree closely with the experimental results. According to the simulations, C 2 H 6 conversion to C 2 H 4 occurs on Cl-IrO 2 (110) by the hydrogenation of C 2 H 3 * species adsorbed in blocked states, in which neighboring sites are occupied only by unreactive HO and Cl species. The microkinetic modeling shows that H-hopping away from surface HO groups provides a relatively efficient route for C 2 H 3 * to escape blocked configurations and dehydrogenate, and that this process can limit the C 2 H 4 selectivity on Cl-IrO 2 (110) under the conditions studied. Overall, our results demonstrate that Cl-substitution into IrO 2 (110) enhances the selectivity for C 2 H 4 production from C 2 H 6 and provides insights into the reaction mechanism that can guide strategies to further improve the C 2 H 4 selectivity.

IrO2↗

Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties**

Abstract The study presents an ab‐initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF‐vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first‐principles‐based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange‐correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT‐constrained microkinetic model optimization for other heterogeneously catalyzed systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolving the Coverage Dependence of Surface Reaction Kinetics with Machine Learning and Automated Quantum Chemistry Workflows

Microkinetic models for catalytic systems require estimation of many thermodynamic and kinetic parameters that can be calculated for isolated species and transition states using ab initio methods. However, the presence of nearby coadsorbates on the surface can dramatically alter these thermodynamic and kinetic parameters causing them to be dependent on species coverage fractions. As there are combinatorially many coadsorbed configurations on the surface, computing the coverage dependence of these parameters is far less straightforward. We present a framework for generating and applying machine learning models to predict coverage-dependent parameters for microkinetic models. Our toolkit enables automatic calculation and evaluation of coadsorbed configurations allowing us to sample 2,000 coadsorbed adsorbates and transition states (TSs) for a diverse set of 9 reactions on Cu(111), a challenging surface, with four possible coadsorbates. This dataset was then used to train subgraph isomorphic decision trees (SIDTs) to predict the stability and association energy of configurations. We were able to achieve mean absolute errors (MAEs) of 0.106 eV on adsorbates, 0.172 eV on TSs, and due to natural error cancellation in SIDTs for relative properties, 0.130 eV on reaction energies and 0.180 eV on activation barriers. In conclusion, we describe how to use these models to predict coverage-dependent corrections for adsorbates and TSs and demonstrate on H*, HO*, and O* comparing the generated SIDT model with an iteratively refined version.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗