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Signatures of Reaction Mechanisms in the Vibrational Level Population Distribution of Reaction Products
The aim of this research program has been to develop model for qualitative and quantitative understanding of complex processes in small molecules, such as vibronic coupling, predissociation, photodissociation, and isomerization.
Converged three-dimensional quantum mechanical reaction probabilities for the F + H2 reaction on a potential energy surface with realistic entrance and exit channels and comparisons to results for three other surfaces
Accurate three-dimensional quantum mechanical reaction probabilities are presented for the reaction F + H2 yields HF + H on the new global potential energy surface 5SEC for total angular momentum J = 0 over a range of translational energies from 0.15 to 4.6 kcal/mol. It is found that the v-prime = 3 HF vibrational product state has a threshold as low as for v-prime = 2.
Characterization of plasma catalytic decomposition of methane: role of atomic O and reaction mechanism
In this work, we investigated atmospheric pressure plasma jet (APPJ)-assisted methane oxidation over a Ni-SiO 2 /Al 2 O 3 catalyst. We evaluated possible reaction mechanisms by analyzing the correlation of gas phase, surface and plasma-produced species. Plasma feed gas compositions, plasma powers, and catalyst temperatures were varied to expand the experimental parameters. Real-time Fourier-transform infrared spectroscopy was applied to quantify gas phase species from the reactions. The reactive incident fluxes generated by plasma were measured by molecular beam mass spectroscopy using an identical APPJ operating at the same conditions. A strong correlation of the quantified fluxes of plasma-produced atomic oxygen with that of CH 4 consumption, and CO and CO 2 formation implies that O atoms play an essential role in CH 4 oxidation for the investigated conditions. With the integration of APPJ, the apparent activation energy was lowered and a synergistic effect of 30% was observed. We also performed in-situ diffuse reflectance infrared Fourier-transform spectroscopy to analyze the catalyst surface. The surface analysis showed that surface CO abundance mirrored the surface coverage of CH n at 25 °C. This suggests that CH n adsorbed on the catalyst surface as an intermediate species that was subsequently transformed into surface CO. We observed very little surface CH n absorbance at 500 °C, while a ten-fold increase of surface CO and stronger CO 2 absorption were seen. This indicates that for a nickel catalyst at 500 °C, the dissociation of CH 4 to CHn may be the rate-determining step in the plasma-assisted CH 4 oxidation for our conditions. We also found the CO vibrational frequency changes from 2143 cm –1 for gas phase CO to 2196 cm –1 for CO on a 25 °C catalyst surface, whereas the frequency of CO on a 500 °C catalyst was 2188 cm –1 . Here, the change in CO vibrational frequency may be related to the oxidation of the catalyst.
Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z
As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.
Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism
Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.
Ultrafast Reaction Mechanisms in Perovskite Based Photocatalytic C–C Coupling
Solar driven carbon-carbon (C-C) bond formation is a new direction in solar energy utilization. Earth abundant nanocrystal based photocatalysts are highly sought after as they can potentially eliminate expensive noble metal catalysts. A detailed understanding of the underlying reaction mechanisms could provide guidance in designing new systems that can activate a larger class of small molecules. Here, we employ transient absorption spectroscopy to study a model C-C bond formation reaction, i.e., a-alkylation of aldehydes catalyzed by colloidal CsPbBr3 nanocrystals (NCs). We find that both electrons and holes undergo ultrafast charge transfer (~50 ps) from photoexcited perovskite NCs to reactant molecules. A charge separated state lives for more than 0.8 µs, enabling a radical mechanism to form the C-C bonds. We discuss the differences between the NCs photoredox catalysts and the molecular catalyst.
A Garnet-Type Solid-Electrolyte-Based Molten Lithium–Molybdenum–Iron(II) Chloride Battery with Advanced Reaction Mechanism
Solid-electrolyte-based molten-metal batteries have attracted considerable attention for grid-scale energy storage. Although ZEBRA batteries are considered one of the promising candidates, they still have the potential concern of metal particle growth and ion exchange with the β”-Al 2 O 3 electrolyte. Herein, a Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 solid-electrolyte-based molten lithium–molybdenum–iron(II) chloride battery (denoted as Li–Mo–FeCl 2 ) operated at temperature of 250 °C, comprising a mixture of Fe and LiCl cathode materials, a Li anode, a garnet-type Li-ion ceramic electrolyte, and Mo additive, is designed to overcome these obstacles. Different from conventional battery reaction mechanisms, this battery revolutionarily synchronizes the reversible Fe–Mo alloying–dealloying reactions with the delithiation–lithiation processes, meaning that the porous Mo framework derived from Fe–Mo alloy simultaneously suppresses the growth of pure Fe particles. By adopting a Li anode and a Li-ion ceramic electrolyte, the corrosion problem between the cathode and the solid electrolyte is overcome. With similar battery cost ($12 kWh –1 ), the theoretical energy density of Li–Mo–FeCl 2 battery surpasses that of a Na–FeCl 2 ZEBRA battery over 25%, to 576 Wh kg –1 and 2216 Wh L –1 , respectively. Experimental results further prove this cell has excellent cycling performance (472 mAh g LiCl –1 after 300 cycles, 50 mg active material) and strong tolerance against the overcharge–overdischarge (3–1.6 V) and freezing–thawing (25–250 °C) incidents.
Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms
Understanding and controlling solid-electrolyte interphase (SEI) formation to stabilize cell performance is a significant challenge for next-generation Li-ion battery technologies. In recent years, computational modeling has become an essential tool in providing fundamental insights into SEI properties and dynamics. However, neither atomistic nor continuum-level approaches alone can capture the complexities of SEI chemistry across all relevant length and time scales. In this work, a continuum-level model is developed that is informed by reaction mechanisms obtained from first-principle calculations. The atomistically informed continuum-level model is used to understand electrolyte degradation, including the decomposition of ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). The model presented here is the most chemically complex continuum-level SEI model in the literature to date. The SEI model is calibrated against experimental irreversible leakage currents and shows qualitative agreement with expected SEI growth trends. The model framework is expected to accelerate fundamental understanding of SEI formation, facilitate mechanism development feedback, and dynamically interact with experimental insights.
Key Chemical Kinetic Steps in Reaction Mechanisms for Fuels from Biomass: A Perspective
Detailed chemical kinetic modeling has been a significant part of combustion research since the entry of the computer into the research community. For most of that time, fuels have largely been provided from petrochemicals, and the combustion chemistry that was developed reflected that source of fuels. Furthermore, renewable fuels from biomass have always made important contributions as fuel sources. Current trends show that renewable fuels are gaining an even more important role as fuel sources, and chemical kinetic modeling of those fuels is playing an essential role in these advances. Interactions between fuels research and chemical kinetic modeling are discussed in this paper, with emphasis on the close and continuous coupling between them. In many cases, new fuels from biomass have structural or compositional features never before seen in real fuels, so entirely new reaction mechanisms are required.
Calcium-Magnesium-Alumino-Silicates (CMAS) Reaction Mechanisms and Resistance of Advanced Turbine Environmental Barrier Coatings for SiC/SiC Ceramic Matrix Composites
Environmental barrier coatings (EBCs) and SiC/SiC ceramic matrix composites (CMCs) systems will play a crucial role in future turbine engines for hot-section component applications because of their ability to significantly increase engine operating temperatures, reduce engine weight and cooling requirements. The development of prime-reliant environmental barrier coatings is an essential requirement to enable the applications of the 2700-3000 F EBC - CMC systems. This presentation primarily focuses on the reaction mechanisms of advanced NASA environmental barrier coating systems, when in contact with Calcium-Magnesium Alumino-Silicates (CMAS) at high temperatures. Advanced oxide-silicate defect cluster environmental barrier coatings are being designed for ultimate balanced controls of the EBC temperature capability and CMAS reactivity, thus improving the CMAS resistance. Further CMAS mitigation strategies are also discussed.
Decoupling electrode kinetics to elucidate reaction mechanisms in alkaline water electrolysis
Alkaline water electrolysis (AWE) presents key advantages, including reduced material costs, enhanced operational stability, and compatibility with non-precious metal catalysts, positioning it as a scalable route for hydrogen production. In this study, we introduce a minimally invasive single-cell configuration incorporating a reference electrode via diaphragm extension to form an internal ion channel. This setup, combined with an interfaced potentiostat and auxiliary electrometer, enables real-time, independent monitoring of anode and cathode behavior, offering high-resolution electrochemical diagnostics. While it is well established that the hydrogen evolution reaction (HER) exhibits sluggish kinetics in alkaline media, our study reveals that this limitation persists even in practical AWE systems where nickel-based substrates are used as electrodes. This observation is supported by both experimental data and voltage breakdown modeling. Arrhenius-type analysis reveals that localized electric fields induced by catalysts shift the reaction kinetics from classical Butler–Volmer behavior toward a Marcus-like regime, where interfacial molecular dynamics and bimolecular charge transfer dominate. We propose a semi-empirical model and a surficial reaction mechanism to describe these dynamics. This work underscores the critical need for cathode innovation and provides a rational framework for designing advanced catalysts and electrode architectures to optimize AWE performance.
Uncertainty analysis of correlated parameters in automated reaction mechanism generation
Abstract Uncertainty analysis is a useful tool for inspecting and improving detailed kinetic mechanisms because it can identify the greatest sources of model output error. Owing to the very nonlinear relationship between kinetic and thermodynamic parameters and computed concentrations, model predictions can be extremely sensitive to uncertainties in some parameters while uncertainties in other parameters can be irrelevant. Error propagation becomes even more convoluted in automatically generated kinetic models, where input uncertainties are correlated through kinetic rate rules and thermodynamic group values. Local and global uncertainty analyses were implemented and used to analyze error propagation in Reaction Mechanism Generator (RMG), an open‐source software for generating kinetic models. A framework for automatically assigning parameter uncertainties to estimated thermodynamics and kinetics was created, enabling tracking of correlated uncertainties. Local first‐order uncertainty propagation was implemented using sensitivities computed natively within RMG. Global uncertainty analysis was implemented using adaptive Smolyak pseudospectral approximations as implemented in the MIT Uncertainty Quantification Library to efficiently compute and construct polynomial chaos expansions to approximate the dependence of outputs on a subset of uncertain inputs. Cantera was used as a backend for simulating the reactor system in the global analysis. Analyses were performed for a phenyldodecane pyrolysis model. Local and global methods demonstrated similar trends; however, many uncertainties were significantly overestimated by the local analysis. Both local and global analyses show that correlated uncertainties based on kinetic rate rules and thermochemical groups drastically reduce a model's degrees of freedom and have a large impact on the determination of the most influential input parameters. These results highlight the necessity of incorporating uncertainty analysis in the mechanism generation workflow.
Impact of supersonic and subsonic aircraft on ozone: Including heterogeneous chemical reaction mechanisms
Preliminary calculations suggest that heterogeneous reactions are important in calculating the impact on ozone from emissions of trace gases from aircraft fleets. In this study, three heterogeneous chemical processes that occur on background sulfuric acid aerosols are included and their effects on O3, NO(x), Cl(x), HCl, N2O5, ClONO2 are calculated.
A Reaction Mechanism for Carbon Soot in Post-Detonation Flows
This report documents the generation of a mechanism to predict the inclusion of carbon soot particles in a high explosive flow. The mechanism includes gasification and oxidation reactions, formation, sublimation, radiation, and agglomeration. Each part of the mechanism is derived from properties in the literature. The influence of each part of the mechanism is explored using simple, example simulations consisting of a 12 mm diameter 2,4,6-Trinitrotoluene charge detonated in ambient air. The mechanism has not been quantitatively compared to experiments. Additional efforts will be required to tune and validate it, which will require continued advancements in experimental diagnostics and simulation techniques.
Towards the Accurate Thermodynamic Characterization of Enzyme Reaction Mechanisms
We employed QM/MM molecular dynamics (MD) simulations to characterize the rate-limiting step of the glycosylation reaction of pancreatic α-amylase with combined DFT/molecular dynamics methods (PBE/def2-SVP : AMBER). Upon careful choice of four starting active site conformations based on thorough reactivity criteria, Gibbs energy profiles were calculated with umbrella sampling simulations within a statistical convergence of 1 -2 kcal · mol -1 . Nevertheless, Gibbs activation barriers and reaction energies still varied from 11.0 to 16.8 kcal · mol -1 and -6.3 to +3.8 kcal · mol -1 depending on the starting conformations, showing that despite significant state-of-the-art QM/MM MD sampling (0.5 ns/profile) the result still depends on the starting structure. In conclusion, the results supported the one step dissociative mechanism of Asp197 glycosylation preceded by an acid-base reaction by the Glu233, which are qualitatively similar to those from multi-PES QM/MM studies, and thus support the use of the latter to determine enzyme reaction mechanisms.
Understanding Electrochemical Reaction Mechanisms of Sulfur in All‐Solid‐State Batteries through Operando and Theoretical Studies **
Abstract Due to its outstanding safety and high energy density, all‐solid‐state lithium‐sulfur batteries (ASLSBs) are considered as a potential future energy storage technology. The electrochemical reaction pathway in ASLSBs with inorganic solid‐state electrolytes is different from Li‐S batteries with liquid electrolytes, but the mechanism remains unclear. By combining operando Raman spectroscopy and ex situ X‐ray absorption spectroscopy, we investigated the reaction mechanism of sulfur (S 8 ) in ASLSBs. Our results revealed that no Li 2 S 8, Li 2 S 6, and Li 2 S 4 were formed, yet Li 2 S 2 was detected. Furthermore, first‐principles structural calculations were employed to disclose the formation energy of solid state Li 2 S n (1≤ n ≤8), in which Li 2 S 2 was a metastable phase, consistent with experimental observations. Meanwhile, partial S 8 and Li 2 S 2 remained at the full lithiation stage, suggesting incomplete reaction due to sluggish reaction kinetics in ASLSBs.