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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mechanistic Insights into the Catalytic Condensation of Methyl Ketones on MgO Surfaces

Ketone coupling via aldol condensation is one of the promising routes to produce cyclic and value-added precursors for renewable hydrocarbon biofuels. A first-principles-based microkinetic modeling is performed to evaluate the surface-mediated reaction mechanisms and the role of water molecules in the observed activities for 2-pentanone and 3-pentanone aldol condensation on dehydroxylated MgO(111) surface and hydroxylated terminated surface[OH-MgO(111)]. Here, we have identified the enhancement of the surface OH group to MgO(111) surface catalytic activity by destabilizing the binding strength of reaction intermediates and reducing the energy barriers of rate-determining steps(proton transfer and dehydration steps). The 2-pentanone has one elementary step less in the complete reaction mechanism of aldol condensation and preferable energy barrier for proton transfer and dehydration steps, revealing 2-pentanone as terminal ketone is more reactive than 3-pentanone as central ketone. The water molecules dominated the OH-MgO( 111) surface after further addition of water, leading to the reduction of turnover frequency of the aldol condensation dimer product as the loss of aldol condensation reaction intermediates in competitive adsorption with water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiscale modeling of hydrogenolysis of ethane and propane on Ru(0001): Implications for plastics recycling

Plastic waste presents an environmental threat. Chemical recycling via hydrogenolysis can convert plastic waste into waxes, lubricants, and fuels. Among catalysts, Ru stands out for its superior activity and selectivity. The chemistry of light alkane hydrogenolysis can help understanding plastics deconstruction. Here, we perform first-principles calculations, develop descriptor-based relations, and conduct microkinetic modeling and analysis on ethane and propane. Predictions are in excellent agreement with experimental data. We identify a similar cracking pattern for both hydrocarbons entailing a deeply dehydrogenated species with the removal of four hydrogen atoms: CHCH*+* → 2CH* for ethane and CH 3 CCH*+2* → CH 3 C* + CH* for propane. We find that the rate-determining step is the C-C cracking for ethane and the first dehydrogenation from the terminal carbon (CH 3 CH 2 CH 3 *+* → CH 3 CH 2 CH 2 *+H*) for propane. The vinyl species CH 2 CH* produced from propane cracking is responsible for whether a single or multiple cracking events occur and effectively controls the selectivity. Specifically, ethane formation in propane hydrogenolysis is suppressed at elevated temperatures due to over-cracking via multiple (two here) cracking events being preferred over hydrogenation and desorption of ethane from the catalyst. Our workflow and models provide a baseline for future studies on heavier hydrocarbons. Insights into recent experimental studies of polyethylene over Ru-based catalysts are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Kinetics-Informed Neural Networks

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by differential algebraic equations (DAEs) that describe microkinetic models (MKMs). We present an algebraic framework for the mathematical description and classification of reaction networks, types of elementary reaction, and chemical species. Under this framework, we demonstrate that the simultaneous training of neural nets and kinetic model parameters in a regularized multi-objective optimization setting leads to the solution of the inverse problem through the estimation of kinetic parameters from synthetic experimental data. We analyze a set of scenarios to establish the extent to which kinetic parameters can be retrieved from transient kinetic data, and assess the robustness of the methodology with respect to statistical noise. Furthermore, this approach to inverse kinetic ODEs can assist in the elucidation of reaction mechanisms based on transient data.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Operational and scaling-up barriers of SOEC and mitigation strategies to boost H 2 production- a comprehensive review

Solid oxide electrolysis cells (SOECs) proffer a flexible and environmentally friendly solution to reduce CO 2 emissions and/or produce H 2 fuel for various applications. Here, the integration of this technology with renewable energy systems makes them even more promising in realizing a near-perpetual green energy infrastructure in the near future. SOEC technology has achieved stupendous improvement in recent years, and some of the limiting factors to the commercialization of this technology have been explored. It is, therefore, necessary to have a succinct outlook of the different factors that contribute to the recent developments in SOEC technology. The current work presents a comprehensive review of the state-of-the-art SOEC component materials and their degradation mechanisms, SOEC modeling essentials and efficiencies, and the scalability of SOECs. Although SOEC is considered a highly promising technology and sufficient multifaceted research has been done, yet not been widely commercialized. Despite the improvement to mitigate degradation of the SOEC materials, a large share of the degradation concerns sprang from charge transfer reaction at the triple-phase boundaries of the H 2 -electrode. Part of which can be improved by microkinetic modeling of these materials supported by their characterization to give insight into their development. Some other directions for the future in advancing this technology toward the commercialization stage are thoroughly addressed.

08 HYDROGEN↗
DOE OSTI2024

Catalytic resonance theory: Circumfluence of programmable catalytic loops

Chemical reactions on heterogeneous catalyst surfaces exhibit complex networks of elementary reactions with multiple pathways to fluid phase products, sometimes leading to surface reaction loops consisting of a closed cycle reaction pathway. While conventional catalysts at steady state exhibit zero net flux in either direction around a catalytic loop, the loop turnover frequency of three-species surface loops was evaluated in this work via microkinetic modeling to assess the reaction loop behavior resulting from a catalytic surface oscillating between two or more surface energy states. For dynamic heterogeneous catalysts undergoing applied oscillations of surface energy (i.e., programs), surface reaction loops of three species were shown to exhibit non-zero net flow of molecules around the loop, with the extent of loop turnover frequency varying with the applied frequency and amplitude of a sinusoidal or square wave oscillation. Alternatively, some dynamic surface reactions exhibited oscillations only between two surface species or resulted in surfaces covered by a single species at all times. Here, more complex behavior was observed for dynamic surface programs of three distinct electronic states, with the temporal order of applied states controlling the direction of flow of molecules within a three-molecule surface loop. Catalytic loops have the potential to limit overall catalytic reaction rates and use energy in programmable catalysts, while some applications could purposely impose non-zero loop turnover frequency for improved surface reaction control.

Catalysis↗
DOE OSTI2025

Mechanistic insights into nitrogen activation on atomic Ru clusters in self-pillared pentasil using operando atomistic models and experimental kinetics

Alternative catalysts to the industrial Haber Bosch process have been of significant interest in the field of heterogeneous catalysis, yet realizing ammonia synthesis under mild conditions (e.g., 300 °C and 10 bar) is challenging due to the low per-pass conversion. One strategy is to promote the associative ammonia synthesis mechanism which eschews direct N-N bond cleavage. Here, in this work, we use self-pillared pentasil, a self-pillared hierarchical zeolite built by thin MFI zeolite nanosheets, as a support for subnanometric Ru clusters to synthesize ammonia. We show that Ru remains well-dispersed during reaction and further demonstrate that ammonia synthesis rates are higher than Cs-Ru/MgO. Reaction kinetics show a positive order in H 2 providing evidence for the associative mechanism, which then becomes negative in H 2 if Ru is allowed to aggregate into nanoparticles. Operando Density Functional Theory models for Ru speciation in SPP, free energy diagrams, and microkinetic modeling were then applied to develop a reaction mechanism that involves sequential hydrogenation of N 2 from metallic Ru clusters. For this hydrogenation to occur, there are site requirements for N 2 to adopt a bridge-bound configuration that facilitates sequential hydrogenation on single sites and metal clusters. These site requirements in turn inform the design of improved zeolite-supported ammonia synthesis catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surface intermediates identified using IR spectroscopy during the catalytic oxidation of C 2 H 6 on IrO 2 (1 1 0) at near-ambient pressures

Characterizing surface intermediates during catalysis is essential for developing mechanistic models of catalytic reactions and for identifying rate-controlling steps. Here, in this work, we used polarization-dependent reflection absorption infrared spectroscopy (PD-RAIRS) to investigate surface intermediates that form on IrO 2 (1 1 0) during the catalytic oxidation of C 2 H 6 at pressures near 0.5 Torr. Our results show that adsorbed CO and HCO 2 are the only intermediates detectable with PD-RAIRS across a wide range of temperatures and reactant compositions during complete C 2 H 6 oxidation, giving rise to dominant peaks at about 2093 and 1310 cm −1 , respectively. These assignments were corroborated by RAIRS measurements following CO and HCOOH adsorption in ultrahigh vacuum, RAIRS with C 2 H 6 – 18 O 2 mixtures during catalysis and vibrational frequencies and IR intensities computed using density functional theory. We find that increasing the C 2 H 6 mole fraction in the reaction mixture raises the CO surface coverage relative to HCO 2 , correlating with increasing catalytic oxidation rates. The formation of CO and HCO 2 surface species at temperatures well below catalytic ignition indicates that the overall rate of C 2 H 6 oxidation on IrO 2 (1 1 0) is governed by steps late in the reaction sequence, such as H 2 O formation, CO oxidation and HCO 2 dehydrogenation. These findings provide key insight into the mechanism of alkane oxidation on IrO 2 (1 1 0) and valuable input for first-principles microkinetic modeling.

Pope, Connor [Univ. of Florida, Gainesville, FL (U↗
DOE OSTI2021

Ethylene oxidation on unpromoted silver catalysts: Reaction pathway and selectivity analysis using DFT calculations

Chemical conversions in catalytic partial oxidation processes of light hydrocarbons are responsible for the production of numerous industrial chemicals, plastics, and intermediates. These processes are relatively expensive to perform, and are typically operated at high thermodynamic inefficiency, so the development of novel, highly efficient catalysts would prove to be very cost effective. Herein, our study focused on surface catalytic mechanisms of the ethylene oxide (EO) formation process. Periodic plane-wave Density Functional Theory (DFT) methods were used to analyze related reaction mechanisms on the Ag(111) surface facet with low coverage. Energetic changes of related species and pathways were calculated. Key surface species are identified to suggest the factors for the observed selectivity during EO formation. Our results are consistent with previous kinetic modeling efforts in the literature which did not employ DFT analysis. Lastly, our study demonstrates how fundamental theoretical investigations and multi-scale modeling techniques are currently impacting the advancement of rational catalyst design and microkinetic modeling techniques in the light hydrocarbon processing industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. Here, 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 pKa 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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Modified Energy Span Analysis of Catalytic Parallel Pathways and Selectivity

Mechanistic modeling provides vital insights into catalytic reactions. To analyze complex reaction networks with parallel pathways, we leverage the graph theory approach of the Energy Span Model (ESM) to develop a modified energy span analysis (MESA). A new method of cycle plots is proposed to perform reaction pathways analysis visually. We demonstrate this method on two published models: one describing carbon monoxide oxidation and the other simulating ethylene conversion to propanal via hydroformylation or ethane via hydrogenation. Fundamental insights explain kinetic observables, such as a reactant’s negative reaction order. General principles are revealed, such as rate-determining surface species being outside the primary reaction flux cycle and pathway selectivity being a purely kinetic property when reaction conditions are not near equilibrium. Lastly, we demonstrate MESA’s consistency with published microkinetic modeling results, highlighting this technique’s extension of the ESM to heterogeneous catalysts using collision theory to describe adsorption steps and concentration effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cross-Scale Catalyst Modeling Applied to H 2 Storage and Release via Formic Acid

Here, we propose the Systems-to-Atoms (S2A) modeling framework that integrates the kinetics of reaction chemistry and structural configurations across various length scales with the aim of establishing a versatile template for multiscale modeling of reactive flow problems and to predict the operando activity of catalyst materials. The approach encompasses a microkinetic model to analyze surface reactions on individual facets of catalyst nanoparticles coupled with the computation of average surface reaction rates for catalyst nanoparticles of specific size distributions. Macro-homogeneous surface reaction kinetics are derived as a function of catalyst loading and used as input parameters for the continuum-scale reactor model. The cross-scale framework enables the optimization of catalyst utilization through reactor design and operating strategy. To demonstrate the framework, we studied the storage and release of hydrogen from formic acid, a promising liquid organic hydrogen carrier (LOHC), over Pd, Pt, and Cu catalysts. The framework predicts observed trends in formic acid dehydrogenation activity for catalysts with comparable weight loadings and metal particle diameters, demonstrating satisfactory quantitative alignment. Finally, the seamless transmission of parameter uncertainties between scales is also discussed.

08 HYDROGEN↗
DOE OSTI2020

A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Theoretical Investigation of Solvent Effects on the Hydrodeoxygenation of Propionic Acid over a Ni(111) Catalyst Model

The effect of two solvents, liquid water and 1,4-dioxane, has been studied from first principles on the hydrodeoxygenation of propionic acid over a Ni (111) catalyst surface model. A mean-field microkinetic model was developed to investigate these effects at a temperature of 473 K. Under all reaction conditions, a decarbonylation mechanism is favored significantly over a decarboxylation pathway. Although no significant solvent effects were observed on the decarbonylation rate, a substantial solvent stabilization of two key surface intermediates in the decarboxylation mechanism, CH 3 CCOO and CH 3 CHCOO, lead to a notable increase of the decarboxylation rate by two orders of magnitude in liquid water and by one order of magnitude in liquid 1,4-dioxane. Furthermore, a significant solvent stabilization of the transition state of C-H bond cleavage of the α-carbon of CH 3 CHCO, relative to the stabilization of the C-C bond cleavage of the α-carbon of CH 3 CHCO, leads to a change in dominant pathway in the liquid phase environments. Finally, a sensitivity analysis shows that the C-OH bond cleavage of propionic acid and C-C bond cleavage of the α-carbon of CH 3 CHCO are the most rate controlling states in the gas phase. In contrast, in solvents the dehydrogenation of CH 3 CHCO becomes the most influential step. This shift in rate controlling state is attributed to the solvent effect on the dehydrogenation of CH 3 CHCO, which is facilitated in aqueous phase. Altogether, it is likely that the investigated (111) facet of Ni is not active for the hydrodeoxygenation of propionic acid in neither the gas nor liquid phase and other Ni facets or phases must be responsible for the experimentally observed kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling Hydrogen Evolution Reaction Kinetics through Explicit Water–Metal Interfaces

Despite the apparent simplicity of the hydrogen evolution reaction (HER) and the decades of research into it, controversy remains in the literature regarding the identity of the active site and the competition between the Heyrovsky and Tafel steps. In this work, we use charge-extrapolated ab initio simulations with explicit water in conjunction with mean-field microkinetic modeling to explore the mechanism for HER on both close-packed (111) and stepped (211) transition metals. First, we show that atop H*, beyond a monolayer of hollow H*, is unlikely to play a role in the HER mechanism, given its very positive adsorption energies. The energetics suggests the Volmer–Heyrovsky mechanism to predominate on fcc transition metals under typical operating conditions. Here, we evaluate our theoretical results vs several experimental observations. We show that the Volmer–Heyrovsky mechanism predicts an activity volcano with its peak at a H* binding ΔG H* ≈ 0 eV, consistent with experiment. In contrast, the Volmer–Tafel volcano shows a broad rate plateau between ΔG H* ≈ 0 eV and ΔG H* ≈ – 0.4 eV. We find our theoretical Tafel slopes to be consistent with experimental ones on a range of transition metals. We show that, in line with experimental observations, the introduction of a CO(g) atmosphere shifts the strong binding metals toward the weak binding leg. Our study suggests that the simple thermodynamic approach to HER activity still holds, even when a detailed kinetic picture is considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Catalytic CO Oxidation on MgAl 2 O 4 -Supported Iridium Single Atoms: Ligand Configuration and Site Geometry

Probing and understanding the local chemical environment of an active site is essential for designing high-performance single-atom catalysts (SACs). Density functional theory (DFT) calculations were performed to investigate the ligand configuration and site geometry of MgAl 2 O 4 -supported iridium single atoms (Ir-1) toward catalytic carbon monoxide (CO) oxidation. We employed MgAl 2 O 4 (111) and MgAl 2 O 4 (211) as the model substrates with adsorbed Ir single atoms of different site geometries. DFT calculations revealed that the Mg-site on MgAl 2 O 4 (111) and the step site on MgAl 2 O 4 (211) are the most stable adsorption sites for Ir single atoms. Irrespective of site choices, CO oxidation on supported Ir single atoms follows the Eley-Rideal (E-R) mechanism, in which the surface oxygen vacancies close to the Ir single atoms activate molecular O 2 with a negligible barrier and the rate-limiting step is the gas-phase CO directly attacking the O-Ir species that is modulated by a CO ligand. Furthermore, first-principles X-ray absorption near-edge spectra of reaction intermediates along with in situ/operando X-ray absorption spectroscopy (XAS) suggest that Ir single atoms adsorb primarily on the step sites of MgAl 2 O 4 . However, microkinetic modeling predicts that a higher activity can be attained on the equally stable Mg-site, maximizing the population of which in catalyst synthesis might prove fruitful in future studies. Electronic structure analysis indicates that the CO ligand increases the reactivity of adsorbed oxygen atoms bound to Ir single atoms by increasing the antibonding nature of the O-Ir bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uncertainty Quantification and Error Propagation in the Enthalpy and Entropy of Surface Reactions Arising from a Single DFT Functional

Accounting for parametric uncertainty in models is essential for quantifying the models’ predictive ability. Recently, approaches have been introduced to estimate parametric uncertainty in kinetic models while accounting for correlations among energy parameters. However, correlations have been estimated indirectly and correlations in entropies have not been accounted for. For surface-catalyzed microkinetic models of >C2 (more than two carbon-containing) molecules, which consist of thousands of reaction steps and intermediate surface species, first-principles density functional theory (DFT) is costly, and thus, estimation of thermochemistry and reaction barriers requires surrogate methods of DFT, such as group additivity and Brønsted–Evans–Polanyi relationships, respectively. For such parametrization, model uncertainty is unclear. This work develops a framework to overcome these gaps using group additivity and a single DFT functional. We estimate correlations in parameters of kinetic models and quantify uncertainty for thermochemistry, reaction barriers, reaction paths, and ultimately reaction rates, accounting also for the contribution of entropic uncertainty. Furthermore, the approach is illustrated on propane combustion and ethane oxidative dehydrogenation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗