Molecular-level descriptions of surface chemistry in kinetic models using density functional theory

Confining platinum clusters in indium-modified ZSM-5 zeolite to promote propane dehydrogenation

Designing highly active and stable catalytic sites is often challenging due to the complex synthesis procedure and the agglomeration of active sites during high-temperature reactions. Here, we report a facile two-step method to synthesize Pt clusters confined by In-modified ZSM-5 zeolite. In-situ characterization confirms that In is located at the extra-framework position of ZSM-5 as In+, and the Pt clusters are stabilized by the In-ZSM-5 zeolite. The resulting Pt clusters confined in In-ZSM-5 show excellent propane conversion, propylene selectivity, and catalytic stability, outperforming monometallic Pt, In, and bimetallic PtIn alloys. The incorporation of In+ in ZSM-5 neutralizes Brønsted acid sites to inhibit side reactions, as well as tunes the electronic properties of Pt clusters to facilitate propane activation and propylene desorption. The strategy of combining precious metal clusters with metal cation-exchanged zeolites opens the avenue to develop stable heterogeneous catalysts for other reaction systems.

Sulfur migration mechanism of pig manure in supercritical water: A combined experimental and DFT study

Pig manure (PM) is a high concentration organic waste rich in sulfur, and its biofuel contains various sulfur-containing pollutants, which reduces the safety of the products. Supercritical water (SCW) can dissolve most organic matter, which is a technology worthy of further study. In order to reduce sulfur pollution in the process of PM resource utilization and better control the conversion path of sulfur, it is necessary to explore the migration mechanism of sulfur in the whole PM-SCW gasification process. The experimental results indicated that H2S was the only gaseous product. Only inorganic compounds (S2-, S2O32- and SO42-) were detected in the liquid. Sulfur in the solid mainly included thiol/thioether, thiophene and sulfone. The influence of different reaction conditions (temperature, residence time, PM concentration and catalysts) on sulfur migration was studied in a batch reactor. It was worth noting that the catalysts had a significant effect on H2S absorption. The lowest H2S yield was 3.2 * 10-4 mol/kg and more than 70% of the sulfur was distributed in the liquid under the condition of addition of K2CO3. While, the RTH2110 fixed most of the sulfur of PM (the maximum value reached 50.94%) in the solid. Thus, adding the catalysts flexibly can choose composition of the products. Furthermore, six possible pathways of sulfur migration in the solid were designed and the kinetic parameters were calculated by density functional theory (DFT). The results provided a basis for controlling sulfur in PM. Subsequently, the sulfur migration pathways during PM-SCW gasification process were comprehensively summarized through the combination of experiment and DFT. It provided a method for sulfur treatment in PM, which had guiding significance for the realization of pollution-free treatment of PM.

A Method Probing High-Temperature Oxidation Behavior of Crystalline Materials

To date, the oxidation behavior of crystal materials is not fully understood; additional research is needed to understand the oxidation of materials. Herein, density functional theory (DFT) calculations and a 3D kinetic Monte Carlo (KMC) model are used to investigate the infiltration and diffusion behaviors of oxygen atoms within the crystal. Oxygen molecules readily adsorbes on crystal surfaces of the material and rapidly dissociates, verified by both first-principles calculations and energy-dispersive spectrometer (EDS) results. The infiltration ability of oxygen atoms into the inner crystal layers is affected by the surrounding oxygen atom, lattice compactness, and other factors. Energy-barrier calculations show that crystal thin/dense layers have significant effects on the crystal oxidation process, so high-pressure technology is used to investigate this correlation experimentally. KMC calculations and thermogravimetric analyses (TGA) show the infiltration behavior of oxygen atoms in the main crystal plane (211) toward the inner layers has the highest proportion to the actual high-temperature oxidation behavior of the title material. The results of both the KMC calculations and thermal experiments show the material peeled off upon further oxidation, which accelerates oxidation. At the same time, high-pressure treatment increases the oxidation resistance of materials at lower temperatures (<600 °C).

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.

The Entropy of van der Waals Fluid

Thermodynamic state functions are fundamental quantities in many fields. In this work, the van der Waals (vdW) equation of state and calculation formulas of state functions are derived with statistical thermodynamic method in three-dimensional (3D) and two-dimensional (2D) spaces. The heat capacity at constant volume (CV,m ) or area (CA,m ) is exactly the same as that of ideal gas, but the heat capacity at constant pressure (Cp,m ) and other state functions are different from those of ideal gas. The vdW equation of state is a cubic equation, which leads to the fact that the entropy and free energy changes of vdW fluid can be expressed as explicit expressions of volume rather than pressure. Therefore, the adsorbate entropy at constant area can still be theoretically proven to have a linear relationship with the gas-phase entropy at constant volume. However, the linear correlation between it and gas-phase entropy at constant pressure is no longer strictly true in theory. In addition, since the vdW equation of state is applicable to both gas and liquid, the linear correlation between adsorbate entropy and liquid-phase entropy can also be found. At last, the reference state for real gas or fluid at a constant molar volume is suggested.

Tuning the Hydrogenation Selectivity of an Unsaturated Aldehyde via Single-Atom Alloy Catalysts

Selective hydrogenation of α,β-unsaturated aldehydes to produce unsaturated alcohols remains a challenge in catalysis. Here, we explore, on the basis of first-principles simulations, single-atom alloy (SAA) catalysts on copper as a class of catalytic materials to enhance the selectivity for C═O bond hydrogenation in unsaturated aldehydes by controlling the binding strength of the C═C and C═O bonds. We show that on SAA of early transition metals such as Ti, Zr, and Hf, the C═O binding mode of acrolein is favored but the strong binding renders subsequent hydrogenation and desorption impossible. On SAA of late-transition metals, on the other hand, the C═C binding mode is favored and C═C bond hydrogenation follows, resulting in the production of undesired saturated aldehydes. Mid-transition metals (Cr and Mn) in Cu(111) appear as the optimal systems, since they favor acrolein adsorption via the C═O bond but with a moderate binding strength, compatible with catalysis. Additionally, acrolein migration from the C═O to the C═C binding mode, which would open the low energy path for C═C bond hydrogenation, is prevented by a large barrier for this process. SAA of Cr in Cu appears as an optimal candidate, and kinetic simulations show that the selectivity for propenol formation is controlled by preventing the acrolein migration from the more stable C═O to the less stable C═C binding mode and subsequent H-migration and by the formation of the O-H bond from the monohydrogenated intermediate. Dilute alloy catalysts therefore enable tuning the binding strength of intermediates and transition states, opening control of catalytic activity and selectivity.

Peroxidase mimics of platinum-group metals for in vitro diagnostics: opportunities and challenges

Platinum-group metal (PGM) nanostructures with peroxidase-like catalytic activities (i.e., peroxidase mimics) have been actively developed and applied to in vitro diagnostics in recent years. This article provides our viewpoints on this emerging field from the perspectives of materials science and solid-state chemistry angles. We start with an introduction to PGM peroxidase mimics, their catalytic efficiencies, and insights into catalysis from computational simulations. We then discuss chemical approaches to the synthesis of PGM peroxidase mimics with desired physicochemical parameters and catalytic properties. Then, we elaborate on general methods for functionalizing the surfaces of PGM mimics with bioreceptors. Thereafter, we highlight the applications of PGM mimics in in vitro diagnostics, emphasizing the interactions of PGM mimics with other components of a diagnostic system. We conclude this article with our opinions on the challenges and opportunities in this field.

Iterative multiscale and multi-physics computations for operando catalyst nanostructure elucidation and kinetic modeling

Modern heterogeneous catalysis has benefitted immensely from computational predictions of catalyst structure and its evolution under reaction conditions, first-principles mechanistic investigations, and detailed kinetic modeling, which are rungs on a multiscale workflow. Establishing connections across these rungs and integration with experiments have been challenging. Here, operando catalyst structure prediction techniques using density functional theory simulations and ab initio thermodynamics calculations, molecular dynamics, and machine learning techniques are presented. Surface structure characterization by computational spectroscopic and machine learning techniques is then discussed. Hierarchical approaches in kinetic parameter estimation involving semi-empirical, data-driven, and first-principles calculations and detailed kinetic modeling via mean-field microkinetic modeling and kinetic Monte Carlo simulations are discussed along with methods and the need for uncertainty quantification. With these as the background, this article proposes a bottom-up hierarchical and closed loop modeling framework incorporating consistency checks and iterative refinements at each level and across levels.

Large-scale benchmarks of the time-warp/graph-theoretical kinetic Monte Carlo approach for distributed on-lattice simulations of catalytic kinetics

Motivated by the need to perform large-scale kinetic Monte Carlo (KMC) simulations, in the context of unravelling complex phenomena such as catalyst reconstruction and pattern formation, we extend the work of Ravipati et al. [S. Ravipati, G. D. Savva, I.-A. Christidi, R. Guichard, J. Nielsen, R. Réocreux and M. Stamatakis, Comput. Phys. Commun., 2022, 270, 108148] in benchmarking the performance of a distributed-computing, on-lattice KMC approach. The latter, implemented in our software package Zacros, combines the graph-theoretical KMC framework with the Time-Warp algorithm for parallel discrete event simulations, and entails dividing the lattice into subdomains, each assigned to a processor. The cornerstone of the Time-Warp algorithm is the state queue, to which snapshots of the simulation state are saved regularly, enabling historical KMC information to be corrected when conflicts occur at subdomain boundaries. Focusing on three model systems, we highlight the key Time-Warp parameters that can be tuned to optimise performance. The frequency of state saving, controlled by the state saving interval, δ_snap, is shown to have the largest effect on performance, which favours balancing the overhead of re-simulating KMC history with that of writing state snapshots to memory. Also important is the global virtual time (GVT) computation interval, Δτ_GVT, which has little direct effect on the progress of the simulation but controls how often the state queue memory can be freed up. We also find that pre-allocating memory for the state queue data structure favours performance. These findings will guide users in maximising the efficiency of Zacros or other distributed KMC software, which is a vital step towards realising accurate, meso-scale simulations of heterogeneous catalysis.

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. A vast array of theoretical and computational methods have been developed to study electrochemical PCET. These methods can be used to calculate redox potentials and pK_a values for molecular electrocatalysts, proton-coupled redox potentials and bond dissociation free energies for PCET at metal and semiconductor interfaces, and reorganization energies associated with electrochemical PCET. Periodic density functional theory can also be used to compute PCET activation energies and perform molecular dynamics simulations of electrochemical interfaces. Various approaches for maintaining a constant electrode potential in electronic structure calculations and modeling complex interactions in the electric double layer (EDL) have been developed. Theoretical formulations for both homogeneous and heterogeneous electrochemical PCET spanning the adiabatic, nonadiabatic, and solvent-controlled regimes have been developed and provide analytical expressions for the rate constants and current densities as functions of applied potential. The quantum mechanical treatment of the proton and inclusion of excited vibronic states have been shown to be critical for describing experimental data, such as Tafel slopes and potential-dependent kinetic isotope effects. The calculated rate constants can be used as input to microkinetic models and voltammogram simulations to elucidate complex electrocatalytic processes.

Tailor the crystal planes of MIL-101(Fe) derivatives to enhance the activity of SCR reaction at medium and low temperature

Mainly exposed crystal facets and controllable morphology play a key role in the final performance of the preparation of specific nanomaterials. In the present study, a metal-organic framework pyrolysis method without adding solvent modifiers was developed. By adding CO in the calcination atmosphere to change atmosphere ratio, Fe₃O₄ nanostructures are exposed with different crystal planes and evaluated their performance in NH₃-SCR reaction. This study proves that SCR catalytic activity of Fe₃O₄ nanocrystals is dependent on morphology and crystal facet. Compared with materials exposed (100), catalysts with more (111) show stronger deNO_x performance. The preferential exposure of Fe₃O₄ (111) crystal facets increases the concentration of adsorbed oxygen on the catalyst, showing higher surface acidity, and enhances the interaction among NO, O₂ and catalyst, which is conducive to SCR reaction. This is supported by DFT calculations. The results present a great application prospect in preparing nanomaterials with specific crystal structures to effectively treat pollutants.

Efficient electrocatalytic water splitting by bimetallic cobalt iron boride nanoparticles with controlled electronic structure

Developing an efficient bifunctional catalyst for Hydrogen Evolution Reaction (HER) and Oxygen Evolution Reaction (OER) in water splitting technology is very attractive for clean energy. Here, a new Co-Fe-B ternary catalyst with improved crystallinity is successfully synthesized by combining the chemical reduction and subsequent solid-state reaction method. Synchrotron-based X-ray absorption near-edge structure (XANES) and X-ray photoelectron spectroscopy (XPS) indicate the electronic structure redistribution is favor for the improved performance. The overpotential is only 129 mV and 280 mV for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline condition, the corresponding Tafel slope is 67.3 mV dec^-1 and 38.9 mV dec^-1. Density functional theory calculations distinguish that the ternary crystalline Co-Fe-B catalysts are thermodynamically favorable for HER and OER. The actual active species of the ternary catalyst in OER is the CoOOH and FeOOH as indicated in ex situ Raman spectra. The present work may introduce promising crystallinity borides material for the anode and cathode of water splitting device.

Selective Methane Oxidation to Methanol on ZnO/Cu2O/Cu(111) Catalysts: Multiple Site-Dependent Behaviors

Because of the abundance of natural gas in our planet, a major goal is to achieve a direct methane-to-methanol conversion at medium to low temperatures using mixtures of methane and oxygen. Here, we report an efficient catalyst, ZnO/Cu₂O/Cu(111), for this process investigated using a combination of reactor testing, scanning tunneling microscopy, ambient-pressure X-ray photoemission spectroscopy, density functional calculations, and kinetic Monte Carlo simulations. The catalyst is capable of methane activation at room temperature and transforms mixtures of methane and oxygen to methanol at 450 K with a selectivity of ∼30%. This performance is not seen for other heterogeneous catalysts which usually require the addition of water to enable a significant conversion of methane to methanol. The unique coarse structure of the ZnO islands supported on a Cu₂O/Cu(111) substrate provides a collection of multiple centers that display different catalytic activity during the reaction. ZnO-Cu₂O step sites are active centers for methanol synthesis when exposed to CH₄ and O₂ due to an effective O-O bond dissociation, which enables a methane-to-methanol conversion with a reasonable selectivity. Upon addition of water, the defected O-rich ZnO sites, introduced by Zn vacancies, show superior behavior toward methane conversion and enhance the overall methanol selectivity to over 80%. Thus, in this case, the surface sites involved in a direct CH₄ → CH₃OH conversion are different from those engaged in methanol formation without water. The identification of the site-dependent behavior of ZnO/Cu₂O/Cu(111) opens a design strategy for guiding efficient methane reformation with high methanol selectivity.

Density functional theory studies of transition metal carbides and nitrides as electrocatalysts

Transition metal carbides and nitrides are interesting non-precious materials that have been shown to replace or reduce the loading of precious metals for catalyzing several important electrochemical reactions. The purpose of this review is to summarize density functional theory (DFT) studies, describe reaction pathways, identify activity and selectivity descriptors, and present a future outlook in designing carbide and nitride catalysts for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), nitrogen reduction reaction (N₂RR), CO₂ reduction reaction (CO₂RR) and alcohol oxidation reactions. This topic is of high interest to scientific communities working in the field of electrocatalysis and this review should provide theoretical guidance for the rational design of improved carbide and nitride electrocatalysts.

A reaction route network for methanol decomposition on a Pt(111) surface

A reaction route network for the decomposition reaction of methanol on a Pt(111) surface was constructed by using the artificial force-induced reaction (AFIR) method, which can search for reaction paths automatically and systematically. Then, the network was kinetically analyzed by applying the rate constant matrix contraction (RCMC) method. Specifically, the time hierarchy of the network, the time evolution of the population initially given to CH₃ OH to the other species on the network, and the most favorable route from CH₃ OH to major and minor products were investigated by the RCMC method. Consistently to previous studies, the major product on the network was CO+4H, and the most favorable route proceeded through the following steps: CH₃ OH → CH₂ OH+H → HCOH+2H → HCO+3H → CO+4H. Furthermore, paths to byproducts found on the network and their kinetic importance were discussed. The present procedure combining AFIR and RCMC was thus successful in explaining the title reaction without using any information on its product or the reaction mechanism.

Dynamic Microkinetic Modeling for Heterogeneously Catalyzed Hydrogenation Reactions: a Coverage-Oriented View

In most studies, the microkinetics for multistep reactions are numerically solved due to their complexity; the obtained numerical results are only valid under given reaction conditions at a static point. In this work, the microkinetics of heterogeneously catalyzed hydrogenation reactions are analytically solved as a function of three coupled physical parameters, which are energy, reaction rate, and coverage. The results correlate the surface reactions and the gaseous-phased reactant/product by energy and thus provide a dynamic view over the whole reaction process rather than at a static point. The analytical expressions are given for a simple hydrogenation reaction and three more complicated hypothetical hydrogenation reactions with side products, side reaction paths, or even multiple active sites. Compared with the numerical solution, the analytical solution is valid under all reaction conditions in practice and can provide more guidance to optimize the overall outcome or catalyst development.

Xenon Trapping in Metal-Supported Silica Nanocages

Xenon (Xe) is a valuable and scarce noble gas used in various applications, including lighting, electronics, and anesthetics, among many others. It is also a volatile byproduct of the nuclear fission of uranium. A novel material architecture consisting of silicate nanocages in contact with a metal surface and an approach for trapping single Xe atoms in these cages is presented. The trapping is done at low Xe pressures and temperatures between 400 and 600 K, and the process is monitored in situ using synchrotron-based ambient pressure X-ray photoelectron spectroscopy. Release of the Xe from the cages occurs only when heating to temperatures above 750 K. A model that explains the experimental trapping kinetics is proposed and tested using Monte Carlo methods. Density functional theory calculations show activation energies for Xe exiting the cages consistent with experiments. This work can have significant implications in various fields, including Xe production, nuclear power, nuclear waste remediation, and nonproliferation of nuclear weapons. The results are also expected to apply to argon, krypton, and radon, opening an even more comprehensive range of applications.

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.

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

Facet engineering accelerates spillover hydrogenation on highly diluted metal nanocatalysts

Hydrogen spillover is a well-known phenomenon in heterogeneous catalysis; it involves H₂ cleavage on an active metal followed by the migration of dissociated H species over an 'inert' support^1-5. Although catalytic hydrogenation using the spilled H species, namely, spillover hydrogenation, has long been proposed, very limited knowledge has been obtained about what kind of support structure is required to achieve spillover hydrogenation^1,5. By dispersing Pd atoms onto Cu nanomaterials with different exposed facets, Cu(111) and Cu(100), we demonstrate in this work that while the hydrogen spillover from Pd to Cu is facet independent, the spillover hydrogenation only occurs on Pd₁/Cu(100), where the hydrogen atoms spilled from Pd are readily utilized for the semi-hydrogenation of alkynes. This work thus helps to create an effective method for fabricating cost-effective nanocatalysts with an extremely low Pd loading, at the level of 50 ppm, toward the semi-hydrogenation of a broad range of alkynes with extremely high activity and selectivity.

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.

Fe Single Atoms and Fe2O3 Clusters Liberated from N-Doped Polyhedral Carbon for Chemoselective Hydrogenation under Mild Conditions

In the area of catalysis, selective reduction of nitro compounds to amino compounds is a colossal challenge due to the existence of competitive reducible functional groups. Herein, an Fe-based catalyst Fe_SAs/Fe₂O_3ACs/N-doped polyhedral carbon (NPC) has been designed and synthesized. As we expected, compared with Fe_SAs and Fe_NPs, Fe_SAs/Fe₂O_3ACs/NPC shows excellent catalytic performance (turnover frequency up to 1923 h^-1, calculated with nitrobenzene), chemoselectivity, and tolerance during the hydrogenation reaction of nitro compounds under room temperature because of the synergistic effects between Fe_SAs and Fe₂O_3ACs. The theoretical calculations show that Fe_SAs prefers to undergo hydrazine decomposition to generate hydrogen and the Fe₂O_3ACs surface is more active toward the nitrobenzene reduction to aniline.

Active learning-based framework for optimal reaction mechanism selection from microkinetic modeling: a case study of electrocatalytic oxygen reduction reaction on carbon nanotubes

The elucidation of complex electrochemical reaction mechanisms requires advanced models with many intermediate reaction steps, which are governed by a large number of parameters like reaction rate constants and charge transfer coefficients. Overcomplicated models introduce high uncertainty in the choice of the parameters and cannot be used to obtain meaningful insights on the reaction pathway. We describe a new framework of optimal reaction mechanism selection based on the mean-field microkinetic modeling approach (MF-MKM) and adaptive sampling of model parameters. The optimal model is selected to provide both the accurate fitting of experimental data within the experimental error and low uncertainty of model parameters choice. Generally, this approach can be applied for any complex heterogeneous electrochemical reaction. We use the "2e^-" electrocatalytic oxygen reduction reaction (ORR) on carbon nanotubes (CNTs) as a representative example of a sufficiently complex reaction. Rotating disk electrode (RDE) experimental data for both ORR in O₂-saturated 0.1 M KOH solution and hydrogen peroxide oxidation/reduction reaction (HPRR/HPOR) in Ar-purged 0.1 M KOH solution with different HO₂^- concentrations were used to show the dependence of the model parameters uniqueness on the completeness of the experimental dataset. It is demonstrated that the optimal reaction mechanism for ORR on CNT and available experimental data consists of O₂ adsorption step on the electrode surface and effective step of two-electron reduction to HO₂^- combined with its desorption from the electrode. The low uncertainty of estimated model parameters is provided only within the 2-step model being applied to the full available experimental dataset. The assessment of elementary step mechanisms on electro-catalytic materials including carbon-based electrodes requires more diverse experimental data and/or higher precision of experimental measurements to facilitate more precise microkinetic modeling of more complex reaction mechanisms.

A systematic theoretical study of the water gas shift reaction on the Pt/ZrO2 interface and Pt(111) face: key role of a potassium additive

K can enhance the activity of the WGSR on the Pt₄₀/ZrO₂ model by reducing both the H₂O and COOH dissociation barriers.

Understanding deep dehydrogenation and cracking of n-butane on Ni(111) by a DFT study

A DFT study on deep dehydrogenation and cracking of long-chain hydrocarbon involving the cleavage of different C–C bonds on nickel.

Thermal decomposition mechanism of O-acetyl-4-O-methylglucurono-xylan

O-acetyl-4-O-methylglucurono-xylan is selected as a model compound because of its abundant O-acetyl and 4-O-methylglucuronic acid groups as side chains of hemicellulose. The detailed decomposition pathways of O-acetyl-4-O-methylglucurono-xylan are investigated by using density functional theory (DFT) and transition state theory. In addition, the possible pyrolysis pathways of 4-O-methylglucuronic acid, based on the Mayer bond order values, are predicted. The results indicate that the most energetically favored initial reaction of O-acetyl-4-O-methylglucurono-xylan is the cleavage of the 4-O-methylglucuronic acid unit. Furfural can be obtained through the ring-opening of 4-O-methylglucuronic acid in three different pathways. The O-methyl group is predominantly responsible for the generation of CH₃OH. In addition, the formation pathways of a special furan-derived product 2-hydroxymethylene-tetrahydrofuran-3-one are first validated by DFT calculation. The rate-determining steps to form 2-hydroxymethylene-tetrahydrofuran-3-one are the cyclization reaction and enol-keto tautomerization. Anhydroxylopyranose and dianhydroxylopyranose can be produced through intramolecular dehydration and glycosidic bond cleavage reactions. Graphical abstract The main pyrolysis products distribution of O-acetyl-4-O-methylglucurono-xylan.