First-Principles Microkinetic Modeling of Methane Oxidation over Pd(100) and Pd(111)

Cooperative adsorbate binding catalyzes high-temperature hydrogen oxidation on palladium

Atomic-scale structures that account for the acceleration of reactivity by heterogeneous catalysts often form only under reaction conditions of high temperatures and pressures, making them impossible to observe with low-temperature, ultra-high-vacuum methods. We present velocity-resolved kinetics measurements for catalytic hydrogen oxidation on palladium over a wide range of surface concentrations and at high temperatures. The rates exhibit a complex dependence on oxygen coverage and step density, which can be quantitatively explained by a density functional and transition-state theory-based kinetic model involving a cooperatively stabilized configuration of at least three oxygen atoms at steps. Here, two oxygen atoms recruit a third oxygen atom to a nearby binding site to produce an active configuration that is far more reactive than isolated oxygen atoms. Thus, hydrogen oxidation on palladium provides a clear example of how reactivity can be enhanced on a working catalyst.

Atomically dispersed MoNi alloy catalyst for partial oxidation of methane

The catalytic partial oxidation of methane (POM) presents a promising technology for synthesizing syngas. However, it faces severe over-oxidation over catalyst surface. Attempts to modify metal surfaces by incorporating a secondary metal towards C-H bond activation of CH4 with moderate O* adsorption have remained the subject of intense research yet challenging. Herein, we report that high catalytic performance for POM can be achieved by the regulation of O* occupation in the atomically dispersed (AD) MoNi alloy, with over 95% CH4 conversion and 97% syngas selectivity at 800 °C. The combination of ex-situ/in-situ characterizations, kinetic analysis and DFT (density functional theory) calculations reveal that Mo-Ni dual sites in AD MoNi alloy afford the declined O2 poisoning on Ni sites with rarely weaken CH4 activation for partial oxidation pathway following the combustion reforming reaction (CRR) mechanism. These results underscore the effectiveness of CH4 turnovers by the design of atomically dispersed alloys with tunable O* adsorption.

CO2 Hydrogenation to Gasoline and Aromatics: Mechanistic and Predictive Insights from DFT, DRIFTS and Machine Learning

The emission of CO2 from fossil fuels is the largest driver of global climate change. To realize the target of a carbon-neutrality by 2050, CO2 capture and utilization is crucial. The efficient conversion of CO2 to C5+ gasoline and aromatics remains elusive mainly due to CO2 thermodynamic stability and the high energy barrier of the C-C coupling step. Herein, advances in mechanistic understanding via Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), density functional theory (DFT), and microkinetic modeling are discussed. It further emphasizes the power of machine learning (ML) to accelerate the search for optimal catalysts. A significant effort has been invested into this field of research with volumes of experimental and characterization data, this study discusses how they can be used as input features for machine learning prediction in a bid to better understand catalytic properties capable of accelerating breakthroughs in the process.

Methane Oxidation over the Zeolites-Based Catalysts

Zeolites have ordered pore structures, good spatial constraints, and superior hydrothermal stability. In addition, the active metal elements inside and outside the zeolite framework provide the porous material with adjustable acid–base property and good redox performance. Thus, zeolites-based catalysts are more and more widely used in chemical industries. Combining the advantages of zeolites and active metal components, the zeolites-based materials are used to catalyze the oxidation of methane to produce various products, such as carbon dioxide, methanol, formaldehyde, formic acid, acetic acid, and etc. This multifunction, high selectivity, and good activity are the key factors that enable the zeolites-based catalysts to be used for methane activation and conversion. In this review article, we briefly introduce and discuss the effect of zeolite materials on the activation of C–H bonds in methane and the reaction mechanisms of complete methane oxidation and selective methane oxidation. Pd/zeolite is used for the complete oxidation of methane to carbon dioxide and water, and Fe- and Cu-zeolite catalysts are used for the partial oxidation of methane to methanol, formaldehyde, formic acid, and etc. The prospects and challenges of zeolite-based catalysts in the future research work and practical applications are also envisioned. We hope that the outcome of this review can stimulate more researchers to develop more effective zeolite-based catalysts for the complete or selective oxidation of methane.

CO2 coverage on Pd catalysts accelerates oxygen removal in oxy-combustion systems

Oxy-combustion systems result in enriched CO₂ in exhaust gases; however, the utilization of the concentrated CO₂ stream from oxy-combustion is limited by remnant O₂. CH₄ oxidation using Pd catalysts has been found to have high O₂-removal efficiency. Here, the effect of excess CO₂ in the feed stream on O₂ removal with CH₄ oxidation is investigated by combining experimental and theoretical approaches. Experimental results reveal complete CH₄ oxidation without any side-products, and a monotonic increase in the rate of CO₂ generation with an increase in CO₂ concentration in the feed stream. Density-functional theory calculations show that high surface coverage of CO₂ on Pd leads to a reduction in the activation energy for the initial dissociation of CH₄ into CH₃ and H, and also the subsequent oxidation reactions. A CO₂-rich environment in oxy-combustion systems is therefore beneficial for the reduction of oxygen in exhaust gases.

Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis

The recent rise of computational, data-driven research has significant potential to accelerate materials discovery. Automated workflows and materials databases are being rapidly developed, contributing to high-throughput data of bulk materials that are growing in quantity and complexity, allowing for correlation between structural-chemical features and functional properties. In contrast, computational data-driven approaches are still relatively rare for nanomaterials discovery due to the rapid scaling of computational cost for finite systems. However, the distinct behaviors at the nanoscale as compared to the parent bulk materials and the vast tunability space with respect to dimensionality and morphology motivate the development of data sets for nanometric materials. In this review, we discuss the recent progress in data-driven research in two aspects: functional materials design and guided synthesis, including commonly used metrics and approaches for designing materials properties and predicting synthesis routes. More importantly, we discuss the distinct behaviors of materials as a result of nanosizing and the implications for data-driven research. Finally, we share our perspectives on future directions for extending the current data-driven research into the nano realm.

Rational Design of Precious-Metal Single-Atom Catalysts for Methane Combustion

Supported precious-metal single-atom catalysts (PM SACs) have emerged as a new frontier of high-performance catalytic material with 100% atom utilization efficiency. However, the rational design of such material with guidance from fundamental understandings of the structure-activity relationship remains challenging. Here, we report the synthesis, characterizations, and mechanistic investigation of various PM SACs supported on nanoceria for CH₄ combustion. Using density functional theory, two descriptors as the d-band center of PMs and oxygen vacancy formation energy are established, which jointly govern the reactivity for CH₄ combustion. These descriptors are thus applied to predict a dual SAC consisting of proximate Pd and Rh sites, demonstrating a remarkable improvement versus Pd or Rh catalyst, respectively. Our results reveal the general strategy of integrating experimental and computational efforts for investigation of various PM SACs in methane combustion, thus paving the way for the next generation of advanced catalytic materials.

Understanding and tackling the activity and selectivity issues for methane to methanol using single atom alloys

The process for the direct oxidation of methane to methanol is investigated on single atom alloys using density functional theory. A catalyst search is performed across FCC metal single atom alloys. 7 single atom alloys are found as candidates and microkinetic modelling is performed. The activity and selectivity are remarkably improved over that of pure palladium metal, yet remain unideal.

Quantum effects in thermal reaction rates at metal surfaces

There is wide interest in developing accurate theories for predicting rates of chemical reactions that occur at metal surfaces, especially for applications in industrial catalysis. Conventional methods contain many approximations that lack experimental validation. In practice, there are few reactions where sufficiently accurate experimental data exist to even allow meaningful comparisons to theory. Here, we present experimentally derived thermal rate constants for hydrogen atom recombination on platinum single-crystal surfaces, which are accurate enough to test established theoretical approximations. A quantum rate model is also presented, making possible a direct evaluation of the accuracy of commonly used approximations to adsorbate entropy. We find that neglecting the wave nature of adsorbed hydrogen atoms and their electronic spin degeneracy leads to a 10× to 1000× overestimation of the rate constant for temperatures relevant to heterogeneous catalysis. These quantum effects are also found to be important for nanoparticle catalysts.

The origin of the particle-size-dependent selectivity in 1-butene isomerization and hydrogenation on Pd/Al2O3 catalysts

The selectivity of 1-butene hydrogenation/isomerization on Pd catalysts is known to be particle size dependent. Here we show that combining well-defined model catalysts, atmospheric pressure reaction kinetics, DFT calculations and microkinetic modeling enables to rationalize the particle size effect based on the abundance and the specific properties of the contributing surface facets.

Preparation of Pd/SiO2 Catalysts by a Simple Dry Ball-Milling Method for Lean Methane Oxidation and Probe of the State of Active Pd Species

A series of Pd/SiO2 catalysts were prepared with different Pd precursors by a dry ball-milling method and used in the catalytic oxidation of lean methane at low temperature. The effect of Pd precursors on the catalytic performance was investigated and the state of the most active Pd species was probed. The results indicate that dry ball-milling is a simple but rather effective method to prepare the Pd/SiO2 catalysts for lean methane oxidation, and palladium acetylacetonate is an ideal precursor to obtain a highly active Pd/SiO2-Acac catalyst with well- and stably dispersed Pd species, owing to the tight contact between acetylacetonate and Si–OH on the SiO2 support. Besides the size and dispersion of Pd particles, the oxidation state of Pd species also plays a crucial role in determining the catalytic activity of Pd/SiO2 in lean methane oxidation at low temperature. A non-monotonic dependence of the catalytic activity on the Pd oxidation state is observed. The activity of various Pd species follows the order of PdOx >> Pd > PdO; the PdOx/SiO2-Acac catalysts (in particular for PdO0.82/SiO2-Acac when x = 0.82) exhibit much higher activity in lean methane oxidation at low temperature than Pd/SiO2-Acac and PdO/SiO2-Acac. The catalytic activity of PdOx/SiO2 may degrade during the methane oxidation due to the gradual transformation of PdOx to PdO in the oxygen-rich ambiance; however, such degradation is reversible and the activity of a degraded Pd/SiO2 catalyst can be recovered through a redox treatment to regain the PdOx species. This work helps to foster a better understanding of the relationship between the structure and performance of supported Pd catalysts by clarifying the state of active Pd species, which should be beneficial to the design of an active catalyst in lean methane oxidation at low temperature.

C-H bond activation in light alkanes: a theoretical perspective

Alkanes are the major constituents of natural gas and crude oil, the feedstocks for the chemical industry. The efficient and selective activation of C-H bonds can convert abundant and low-cost hydrocarbon feedstocks into value-added products. Due to the increasing global demand for light alkenes and their corresponding polymers as well as synthesis gas and hydrogen production, C-H bond activation of light alkanes has attracted widespread attention. A theoretical understanding of C-H bond activation in light hydrocarbons via density functional theory (DFT) and microkinetic modeling provides a feasible approach to gain insight into the process and guidelines for designing more efficient catalysts to promote light alkane transformation. This review describes the recent progress in computational catalysis that has addressed the C-H bond activation of light alkanes. We start with direct and oxidative C-H bond activation of methane, with emphasis placed on kinetic and mechanistic insights obtained from DFT assisted microkinetic analysis into steam and dry reforming, and the partial oxidation dependence on metal/oxide surfaces and nanoparticle size. Direct and oxidative activation of the C-H bond of ethane and propane on various metal and oxide surfaces are subsequently reviewed, including the elucidation of active sites, intriguing mechanisms, microkinetic modeling, and electronic features of the ethane and propane conversion processes with a focus on suppressing the side reaction and coke formation. The main target of this review is to give fundamental insight into C-H bond activation of light alkanes, which can provide useful guidance for the optimization of catalysts in future research.

Investigating the innate selectivity issues of methane to methanol: consideration of an aqueous environment

The higher reactivity of the methanol product over the methane reactant for the direct oxidation of methane to methanol is explored. C-H activation, C-O coupling, and C-OH coupling are investigated as key steps in the selective oxidation of methane using DFT. These elementary steps are initially considered in the gas phase for a variety of fcc (111) pristine metal surfaces. Methanol is found to be consistently more reactive for both C-H activation and subsequent oxidation steps. With an aqueous environment being understood experimentally to have a profound effect on the selectivity of this process, these steps are also considered in the aqueous phase by ab initio molecular dynamics calculations. The water solvent is modelled explicity, with each water molecule given the same level of theory as the metal surface and surface species. Free energy profiles for these steps are generated by umbrella sampling. It is found that an aqueous environment has a considerable effect on the kinetics of the elementary steps yet has little effect on the methane/methanol selectivity-conversion limit. Despite this, we find that the aqueous phase promotes the C-OH pathway for methanol formation, which could enhance the selectivity for methanol formation over that of other oxygenates.

Microkinetic Modeling: A Tool for Rational Catalyst Design

The design of heterogeneous catalysts relies on understanding the fundamental surface kinetics that controls catalyst performance, and microkinetic modeling is a tool that can help the researcher in streamlining the process of catalyst design. Microkinetic modeling is used to identify critical reaction intermediates and rate-determining elementary reactions, thereby providing vital information for designing an improved catalyst. In this review, we summarize general procedures for developing microkinetic models using reaction kinetics parameters obtained from experimental data, theoretical correlations, and quantum chemical calculations. We examine the methods required to ensure the thermodynamic consistency of the microkinetic model. We describe procedures required for parameter adjustments to account for the heterogeneity of the catalyst and the inherent errors in parameter estimation. We discuss the analysis of microkinetic models to determine the rate-determining reactions using the degree of rate control and reversibility of each elementary reaction. We introduce incorporation of Brønsted-Evans-Polanyi relations and scaling relations in microkinetic models and the effects of these relations on catalytic performance and formation of volcano curves are discussed. We review the analysis of reaction schemes in terms of the maximum rate of elementary reactions, and we outline a procedure to identify kinetically significant transition states and adsorbed intermediates. We explore the application of generalized rate expressions for the prediction of optimal binding energies of important surface intermediates and to estimate the extent of potential rate improvement. We also explore the application of microkinetic modeling in homogeneous catalysis, electro-catalysis, and transient reaction kinetics. We conclude by highlighting the challenges and opportunities in the application of microkinetic modeling for catalyst design.

Self-sustained oscillations in oxidation of methane over palladium: the nature of “low-active” and “highly active” states

The oxidation of methane was studied in a flow reactor at atmospheric pressure using palladium foil as a catalyst.

Combining Computational Modeling with Reaction Kinetics Experiments for Elucidating the In Situ Nature of the Active Site in Catalysis

Microkinetic modeling based on density functional theory (DFT) derived energetics is important for addressing fundamental questions in catalysis. The quantitative fidelity of microkinetic models (MKMs), however, is often insufficient to conclusively infer the mechanistic details of a specific catalytic system. This can be attributed to a number of factors such as an incorrect model of the active site for which DFT calculations are performed, deficiencies in the hypothesized reaction mechanism, inadequate consideration of the surface environment under reaction conditions, and intrinsic errors in the DFT exchange-correlation functional. Despite these limitations, we aim at developing a rigorous understanding of the reaction mechanism and of the nature of the active site for heterogeneous catalytic chemistries under reaction conditions. By achieving parity between experimental and modeling outcomes through robust parameter estimation and by ensuring coverage-consistency between DFT calculations and MKM predictions, it is possible to systematically refine the mechanistic model and, thereby, our understanding of the catalytic active site in situ.Our general approach consists of developing ab initio informed MKM for a given active site and then re-estimating the energies of the transition and intermediate states so that the model predictions match quantities measured in reaction kinetics experiments. If (i) model-experiment parity is high, (ii) the adjustments to the DFT-derived energetics for a given model of the active site are rationalized within the errors of standard DFT exchange-correlation functionals, and (iii) the resultant MKM predicts surface coverages that are consistent with those assumed in the DFT calculations used to initialize the MKM, we conclude that we have correctly identified the active site and the reaction mechanism. If one or more of these requirements are not met, we iteratively refine our model by updating our hypothesis for the structure of the active site and/or by incorporating coverage effects, until we obtain a high-fidelity coverage-self-consistent MKM whose final kinetic and thermodynamic parameters are within error of the values derived from DFT.Using the catalytic reaction of formic acid (FA, HCOOH) decomposition over transition-metal catalysts as an example, here we provide an account of how we applied this algorithm to study this chemistry on powder Au/SiC and Pt/C catalysts. For the case of Au catalysts, on which the FA decomposition occurred exclusively through the dehydrogenation reaction (HCOOH → CO₂+H₂), our approach was used to iteratively refine the model starting from the (111) facet until we found that specific ensembles of Au atoms present in sub-nanometer clusters can describe the active site for this catalysis. For the case of Pt catalysts, wherein both dehydrogenation (HCOOH → CO₂ + H₂) and dehydration (HCOOH → CO + H₂O) reactions were active, our approach identified that a partially CO*-covered (111) surface serves as the active site and that CO*-assisted steps contributed substantially to the overall FA decomposition activity. Finally, we suggest that once the active site and the mechanism are conclusively identified, the model can subsequently serve as a high-quality basis for designing specific goal-oriented experiments and improved catalysts.

Mechanistic Insights for Dry Reforming of Methane on Cu/Ni Bimetallic Catalysts: DFT-Assisted Microkinetic Analysis for Coke Resistance

Density functional theory (DFT) calculations have been utilized to evaluate the complete reaction mechanism of methane dry reforming (DRM) over Ni2Cu (111) bimetallic catalyst. The detailed catalytic cycle on Ni2Cu (111) catalyst demonstrated superior coke resistance compared to pure Ni (111) and Ni2Fe (111) reported in the literature. Doping Cu in the Ni–Ni network enhanced the competitive CH oxidation by both atomic O and OH species with the latter having only 0.02 eV higher than the 1.06 eV energy barrier required for CH oxidation by atomic O. Among the C/CH oxidation pathways, C* + O* → CO (g) was the most favorable with an energy barrier of 0.72 eV. This was almost half of the energy barrier required for the rate-limiting step of CH decomposition (1.40 eV) and indicated enhanced coke deposition removal. Finally, we investigated the effect of temperature (800~1000 K) on the carbon deposition and elimination mechanism over Ni2Cu (111) catalyst. Under those realistic DRM conditions, the calculations showed a periodic cycle of simultaneous carbon deposition and elimination resulting in improved catalyst stability.

Low Temperature Activation of Methane on Metal-Oxides and Complex Interfaces: Insights from Surface Science

ConspectusThe abundance of cheap, natural gas has transformed the energy landscape, whereby revealing new possibilities for sustainable chemical technologies or impacting those that have relied on traditional fossil fuels. The primary component, methane, is underutilized and wastefully exhausted, leading to anthropogenic global warming. Historically, the manipulation of methane remained "clavis aurea," an insurmountable yet rewarding challenge and thus the focus of intense research. This is primarily due to an inability to dissociate C-H bonds in methane selectively, which requires a high energy penalty and is an essential prerequisite for the direct conversion of methane into a large set of value-added products. The discovery of such processes would promise an energy gainful use of natural gas benefiting several essential chemical processes associated with C1 chemistry. This first C-H bond dissociation step of the methane molecule appears in numerous catalytic mechanisms as the rate-determining step or most essential barrier sequence for all subsequent steps that follow in the production of C-C, C-O, or C_x-H_y-O_z bonds found in value added products. A main goal is to catalytically reduce the energy barrier for the first C-H bond dissociation to be able to achieve the activation of methane at low or moderate temperatures. As such there is great value in understanding the fundamental nature of the active sites responsible for bond breaking or formation and thus be able to facilitate better control of this chemistry, leading to the development of new technologies for fuel production and chemical conversion. Surface science studies offer enhanced perspectives for a careful manipulation of bonds over the last layer atoms of catalyst surfaces, an essential factor for the design of atomically precise catalysts and unravelling of the reaction mechanism. With the advent of new surface imaging, spectroscopy, and in situ tools, it has been possible to decipher the surface chemistry of complex materials systems and further our understanding of atomic active sites on the surfaces of metals, oxides, and carbides or metal-oxide and metal-carbide interfaces. The once considered near impossible step of C-H bond activation is now observed at low temperatures with high propensity over a collection of oxide, metal-oxide, and metal-carbide systems in a conventional or inverse configuration (oxide or carbide on metal). The enabling of C-H activation at low temperature has opened interesting possibilities for the specific production of chemicals such as methanol directly from methane, a step toward facile synthesis of liquid fuels. We highlight the most recent of these results and present the key aspects of active site configurations engineered from surface science studies which enable such a simple reactive event through careful manipulation of the last surface layer of atoms found in the catalyst structure. New concepts which help in the activation and conversion of methane are discussed.

Insight into the active site and reaction mechanism for selective oxidation of methane to methanol using H2O2 on a Rh1/ZrO2 catalyst

Five-coordinated Rh leads to the over-oxidation of CH₄, while four-coordinated Rh stabilizes CH₃ and facilitates methanol formation via the CH₃OOH intermediate.

Accessing the C-C transition state energy on transition metals

The search for catalysts that can efficiently convert large hydrocarbons has been an active area of research for decades. To gain insight into those reactions, electronic structure calculations are playing an increasing role but the screening efforts are impeded by the complexity of the reaction networks that can contain hundreds of elementary steps, presenting a large number of computationally expensive transition state barrier calculations. A large number of the sub reactions in the network involve C-C bond dissociation, a step that has been identified as rate determining in many studies. The purpose of this article is to present a methodology that allows for accurate and rapid assessment of transition state energies for C-C bond breaking in any hydrocarbon based on a small number of simple calculations. Our model significantly enhances the capability of expanding the search space for new and efficient catalysts.

Microkinetics of alcohol reforming for H2 production from a FAIR density functional theory database

The large-scale production of hydrogen from biomass under industrial conditions is fundamental for a sustainable future. Here we present a multiscale study of the available reforming technologies based on a density functional theory open database that allows the formulation of linear scaling relationships and microkinetics. The database fulfills the FAIR criteria: findability, accessibility, interoperability and reusability. Moreover, it contains more than 1000 transition states for the decomposition of C₂ alcohols on close-packed Cu, Ru, Pd, and Pt surfaces. The microkinetic results for activity, selectivity toward H₂, and stability can be directly mapped to experiments, and the catalytic performance is controlled by various types of poisoning. Linear scaling relationships provide valid quantitative results that allow the extrapolation to larger compounds like glycerol. Our database presents a robust roadmap to investigate the complexity of biomass transformations through the use of small fragments as surrogates when investigated under different reaction conditions.

The production of hydrogen from biomass is of fundamental importance for a sustainable future. Here, the authors present a multiscale method that allows the formulation of scaling relationships and microkinetics of C₁-C₂ alcohol decomposition based on a density functional theory open database.

Modelling complete methane oxidation over palladium oxide in a porous catalyst using first-principles surface kinetics

Modeled turnover frequencies for varying temperature and total pressure combined with reaction rate controlling regions.