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At least 757 records · Page 42

Probing the Chemical Kinetics of Minimalist Functional Group Gasoline Surrogates

We report surrogate mixtures are routinely used for understanding gasoline fuel combustion in engine simulations. The general trend in surrogate formulation has been to increase the number of fuel components in a mixture to better emulate real fuel properties. Recently, a new surrogate design strategy based on functional group analysis of real gasolines was proposed using a minimal number of species [minimalist functional group (MFG)-approach]. MFG surrogates (having just one or two components) could experimentally capture the ignition delay time (IDT), threshold sooting index, and smoke point of different gasoline fuels with hundreds of components. However, other combustion characteristics were not explored, and kinetic modeling of MFG surrogates was not reported. These aspects are addressed in this paper, where the combustion behavior of MFG surrogates for various gasolines was assessed by simulating IDT, jet-stirred reactor oxidation, and premixed laminar flame speeds using chemical kinetic modeling. MFG simulations were compared with experimental data of the real gasolines as well as with the more complex multicomponent (five to nine species) surrogates. This study reveals that binary MFG surrogate mixtures are capable of accurately simulating the combustion behavior of more complex gasoline fuels with hundreds of components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental and Kinetic Modeling Study of 3-Methyl-2-butenol (Prenol) Oxidation

Longer chain alcohols with 4–5 carbon atoms are attractive alternative fuels as they can be derived from biological sources and since their combustion leads to lower exhaust gas levels of NO x and soot compared to commercial fossil fuels. The auto-ignition behavior of fuels that contain both a hydroxyl group and a C=C double bond in their molecular structure is not well established in the literature. Understanding the influence of these functional groups on the ignition behavior of fuels is critical in the development of tailor-made fuels for advanced combustion engines. In this study, ignition delay times of an unsaturated alcohol, 3-methyl-2-butenol (prenol), are measured using a high-pressure shock tube and a rapid compression machine at pressures of 15 and 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 in “air” in the temperature range 600–1400 K. Furthermore, a detailed kinetic model is developed and validated using the new experimental data in this study. In addition, speciation data in a jet-stirred reactor, ignition delay times, and laminar burning velocities available in the literature were also used to validate the new kinetic model. Fuel flux and sensitivity analyses are performed using this new model to determine the important fuel consumption pathways and critical reactions that affect the reactivity of prenol.

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Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model

In the explore the systematic construction of kinetic models from in silico reaction data for the decomposition of nitromethane. Our models are constructed in a computationally affordable manner by using reactions discovered through accelerated molecular dynamics simulations using the ReaxFF reactive force field. The reaction paths are then optimized to determine reaction rate parameters. We introduce a reaction barrier correction scheme that combines accurate thermochemical data from density functional theory with ReaxFF minimal energy paths. We validate our models across different thermodynamic regimes, showing predictions of gas phase CO and NO concentrations and high-pressure induction times that are similar to experimental data. The kinetic models are analyzed to find fundamental decomposition reactions in different thermodynamic regimes.

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Predicted Reaction Mechanisms, Product Speciation, Kinetics, and Detonation Properties of the Insensitive Explosive 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105)

2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105) is a relatively new and promising insensitive high-explosive (IHE) material that remains only partially characterized. IHEs are of interest for a range of applications and from a fundamental science standpoint, as the root causes behind insensitivity are poorly understood. In this work, we adopt a multitheory approach based on reactive molecular dynamic simulations performed with density functional theory, density functional tight-binding, and reactive force fields to characterize the reaction pathways, product speciation, reaction kinetics, and detonation performance of LLM-105. We compare and contrast these predictions to 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a prototypical IHE, and 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX), a more sensitive and higher performance material. The combination of different predictive models allows access to processes operative on progressively longer timescales while providing benchmarks for assessing uncertainties in the predictions. We find that the early reaction pathways of LLM-105 decomposition are extremely similar to TATB; they involve intra- and intermolecular hydrogen transfer. Additionally, the detonation performance of LLM-105 falls between that of TATB and HMX. We find agreement between predictive models for first-step reaction pathways but significant differences in final product formations. Predictions of detonation performance result in a wide range of values, and one-step kinetic parameters show the similar reaction rates at high temperatures for three out of four models considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Kinetic Modeling Analysis of Ar Addition to Atmospheric Pressure N 2 –H 2 Plasma for Plasma-Assisted Catalytic Synthesis of NH 3

Zero-dimensional kinetic modeling of atmospheric pressure Ar–N 2 –H 2 nonthermal plasma was carried out to gain mechanistic insights into plasma-assisted catalytic synthesis of ammonia. Ar dilution is a common technique for tailoring plasma discharge properties and has been shown to enhance NH 3 formation when added to N 2 –H 2 plasma. The kinetic model was developed for a coaxial dielectric barrier discharge quartz wool-packed bed reactor operating at near room temperature using a kHz-frequency plasma source. With 30% Ar mixed in a 1:1 N 2 –H 2 plasma at 760 Torr, we find that NH 3 production is dominated by Eley–Rideal (E-R) surface reactions, which heavily involve surface NH x species derived from N and H radicals in the gas phase, while the influence of excited N 2 molecules is negligible. This is contrary to the commonly proposed mechanism that excited N 2 molecules created by Penning excitation of N 2 by Ar(4s) and Ar(4p) play a significant role in assisting NH 3 formation. Our model shows that the enhanced NH 3 formation upon Ar dilution is unlikely due to the interactions between Ar and H species, as excited Ar atoms have a weak effect on H radical formation through H 2 dissociation compared to electrons. We find that excited Ar atoms contribute to 28% of the N radical production in the gas phase via N 2 dissociation, while the rest are dominated by electron-impact dissociation. Furthermore, Ar species play a negligible role in the product NH 3 dissociation. N 2 conversion sensitivity analyses were carried out for electron number density (ne) and reduced electric field (E/N), and contributions from Ar to gas-phase N radical production were quantified. Finally, the model can provide guidance on potential reasons for observing enhanced NH 3 formation upon Ar dilution in N 2 –H 2 plasma beyond changes in the discharge characteristics.

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Association Kinetics for Perfluorinated n -Alkyl Radicals

Radical-radical reaction channels are important in the pyrolysis and oxidation chemistry of perfluoroalkyl substances (PFAS). In particular, unimolecular dissociation reactions within unbranched n-perfluoroalkyl chains, and their corresponding reverse barrierless association reactions, are expected to be significant contributors to the gas-phase thermal decomposition of families of species such as perfluorinated carboxylic acids and perfluorinated sulfonic acids. Unfortunately, experimental data for these reactions are scarce and uncertain. Furthermore, obtaining reliable theoretical predictions for such reactions is a laborious and computationally intensive task. Here, in this work, the chemical kinetics of the various association/decomposition reactions producing/decomposing the C 2 -C 4 series of unbranched n-perfluoroalkanes (C 2 F 6 , C 3 F 8 , and C 4 F 10 ) are examined using state-of-the-art ab initio transition-state-theory-based master-equation calculations. The variable-reaction-coordinate transition-state theory (VRC-TST) formalism is employed in computing the microcanonical and canonical rates for the association reactions. Reaction thermochemistry is obtained via composite quantum chemistry calculations and the laddering of error-canceling reaction schemes via a connectivity-based hierarchy approach employing ANL1/ANL0-style reference energies. Lennard-Jones collision model parameters for the considered systems were estimated by a direct dynamics approach, and collisional energy transfer parameters were obtained from analogies to systems of similar size and heavy-atom connectivity. A one-dimensional master equation approach was used to convert the microcanonical rate coefficients from the VRC-TST analysis into temperature- and pressure-dependent rate constants for the association reactions and the reverse dissociation reactions. The data are reported in standardized formats for usage in comprehensive chemical kinetic models for PFAS thermal destruction.

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Ultrafast Relaxations in Ruthenium Polypyridyl Chromophores Determined by Stochastic Kinetics Simulations

Maximizing the efficiency of solar energy conversion using dye assemblies rests on understanding where the energy goes following absorption. Transient spectroscopies in solution are useful for this purpose, and the time-resolved data are usually analyzed with a sum of exponentials. This treatment assumes that dynamic events are well separated in time, and that the resulting exponential prefactors and phenomenological lifetimes are related directly to primary physical values. Such assumptions break down for coincident absorption, emission, and excited state relaxation that occur in transient absorption and photoluminescence of tris(2,2'-bipyridine)ruthenium(2+) derivatives, confounding the physical meaning of the reported lifetimes. Here, we use inductive modeling and stochastic chemical kinetics to develop a detailed description of the primary ultrafast photophysics in transient spectroscopies of a series of Ru dyes, as an alternative to sums of exponential analysis. Commonly invoked three-level schemes involving absorption, intersystem crossing (ISC), and slow nonradiative relaxation and incoherent emission to the ground state cannot reproduce the experimentally measured spectra. The kinetics simulations reveal that ultrafast decay from the singlet excited state manifold to the ground state competes with ISC to the triplet excited state, whose efficiency was determined to be less than unity. The populations predicted by the simulations are used to estimate the magnitudes of transition dipoles for excited state excitations and evaluate the influence of specific ligands. The mechanistic framework and methodology presented here are entirely general, applicable to other dye classes, and can be extended to include charge injection by molecules bound to semiconductor surfaces.

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Structure Sensitive Reaction Kinetics of Chiral Molecules on Intrinsically Chiral Surfaces

Enantiospecific heterogeneous catalysis utilizes chiral surfaces to resolve enantiomers via structure sensitive surface chemistry. The catalyst design challenge is the identification of chiral surface structures that maximize enantiospecificity. Herein, we develop data driven models for the enantiospecificity of tartaric acid reactions on chiral Cu(hkl) R&S surfaces. Measurements of enantiospecific rate constants were obtained by using curved Cu(hkl) R&S surfaces that enable kinetic measurements on hundreds of chiral surface orientations. One model uses feature vectors derived from generalized coordination numbers to capture the local structure around Cu atoms exposed by the Cu(hkl) R&S surfaces. The second model introduces the use of chiral cubic harmonic functions to capture the symmetry constraints of the face-centered cubic Cu structure. The model using 58 generalized coordination numbers has a fitting error similar to that of the model using only 5 cubic harmonic functions. The two models predict maxima in the enantiospecificity on surfaces with very similar surface orientations. The models developed in this work are applicable for any enantiospecific reaction happening on any chiral material with a cubic lattice structure, opening the way to understanding the surface structure sensitivity of the enantiospecific reaction kinetics.

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Discovering CO Adsorption and Desorption Pathways from Chemical Reaction Neural Network Modeling of Transient Kinetics Spectroscopy

Here, we demonstrate a data-driven approach to interpreting surface reactions by combining time-resolved gas pulsing infrared spectroscopy with chemical reaction neural networks (CRNNs). Using CO adsorption and desorption on Pd(111) at 460–490 K as a model system, we show how transient kinetic data can reveal detailed reaction mechanisms. Starting with a simple one-species model, we systematically evaluate increasingly complex mechanisms involving hollow and bridge site adsorption. Despite the similar goodness of fit to the same experimental absorbance data, our models predict distinct coverage dynamics for different adsorption sites. Through analysis of spectral peak stability and predicted dynamics, we identify a mechanism in which CO primarily adsorbs on bridge sites followed by rapid conversion to hollow sites as being the most physically consistent with experimental observations. This work provides a framework for extracting mechanistic insights from limited experimental data, demonstrating how machine learning can bridge the gap between transient kinetic measurements and a molecular-level understanding of surface reactions.

36 MATERIALS SCIENCE↗

Moving from Fundamental Knowledge of Kinetics and Mechanisms on Surfaces to Prediction of Catalyst Performance in Reactors

Catalysis is defined by kinetics, but after over a century of catalyst development our kinetic and mechanistic knowledge governing real-world catalysis is still severely lacking. This Perspective considers how we can use the precise knowledge available from both theoretical and fundamental experimental techniques to understand and even predict catalytic performance under operational conditions. Here, we describe advances that link fundamental and "real-world" measurements, crucial elements required to successfully recreate a reaction network, and avenues which appear to offer viable routes to success.

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Hydrodechlorination of 1,2-Dichloroethane on Platinum Catalysts: Insights from Reaction Kinetics Experiments, Density Functional Theory, and Microkinetic Modeling

Catalytic hydrodechlorination is a promising strategy for treating industrial 1,2-dichloroethane wastes, for which Pt and Pt-based alloy catalysts are widely used. Here, we performed a detailed mechanistic study for 1,2-dichloroethane hydrodechlorination on Pt using a synergistic approach combining density functional theory (DFT) calculations, reaction kinetics experiments, and microkinetic modeling. Using planewave DFT calculations, we evaluated the reaction energy and activation energy barrier of each elementary step involved in the reaction network on Pt(111). The calculated energetics were then incorporated into a comprehensive mean-field microkinetic model accounting for a total of 65 elementary steps. The model-predicted reaction rates were compared with the results from our reaction kinetics experiments on SiO2-supported Pt catalysts. Our results indicated that the hydrodechlorination of 1,2-dichloroethane on Pt(111) starts with a H-removal step; then, it proceeds through a sequence of alternating dechlorination and dehydrogenation steps until vinylidene (CH 2 C*) is formed; finally, CH 2 C* is hydrogenated to the final product, ethane, sequentially via vinyl (CH 2 CH*), ethylene, and ethyl (CH 3 CH 2 *) intermediates. After model parameter adjustments, we achieved good agreement between our theoretical model and experimental results; the adjustments to the calculated parameters are consistent with the typically anticipated coverage effects. Furthermore, our study offers valuable mechanistic insights, which are useful for improving catalysts for this chemistry.

1,2-dichloroethane↗

Unexpected Kinetic Solvent Effects Enhance Activity and Selectivity in Biphasic Systems

Biphasic dehydration of fructose to 5-hydroxymethylfurfural (HMF) has shown unprecedented increases in productivity, but a mechanistic understanding is lacking. Herein, we couple fast experimental reaction kinetics, multiscale modeling (phase behavior, classical molecular dynamics(MD), and quantum mechanics/molecular mechanics MD), in situ sampling, and IR and 13 C-NMR spectroscopy to elucidate the complex effects of nonpolar extracting organic solvents on the kinetics of fructose dehydration. We show that these organic solvents can reach significant mutual solubility with water at reaction temperatures, enabling the partition of the sugar and catalyst into the extracting phase. In the organic-rich environment, the dehydration of fructose proceeds faster and more selectively than in water due to increased relative abundance of the reactive furanose isomer, enhanced water–catalyst–substrate interactions driven by nanophase separation, and higher product stability stemming from preferential solvation. Furthermore, we demonstrate that these solvent effects impact other critical biphasic reactions in biomass upgrading and provide qualitative principles for solvent selection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanism and Kinetics of Ethanol–Acetaldehyde Conversion to 1,3-Butadiene over Isolated Lewis Acid La Sites in Silanol Nests in Dealuminated Beta Zeolite

Biomass-derived ethanol (EtOH) and acetaldehyde (AcH) conversion to 1,3-butadiene (1,3-BD) is an alternative process for 1,3-BD production. The present investigation reports the preparation and characterization of isolated La sites introduced into the silanol nests in DeAlBEA as well as detailed studies of the mechanism and kinetics for the conversion of an EtOH-AcH mixture to 1,3-BD. La sites supported on DeAlBEA are found to be present as (≡SiO) 2 La-OH groups that are H-bonded with adjacent Si-OH groups, possessing high C-C coupling activity and stability, superior to state-of-the-art Y-DeAlBEA. La sites supported on silica (La-SiO 2 ) with a similar chemical structure but no H-bonding interaction with Si-OH groups were prepared for comparison. Lewis acid La sites promote AcH aldol condensation, and the activity of such sites is nearly identical for both La-DeAlBEA and La-SiO 2 . Further, the rate of C 4 product formation increases by a factor of 4.8 upon addition of EtOH to the feed of AcH over La-DeAlBEA, whereas that over La/SiO 2 remains unchanged. Investigation of the mechanism and kinetics of AcH aldol condensation and EtOH-AcH conversion to 1,3-BD revealed two C-C bond forming pathways-AcH aldol condensation by Lewis acid La sites and direct coupling of EtOH-AcH over H-bonded (≡SiO) 2 La-OH···HO-Si≡ sites. This study provides important information about the role of the local environment of isolated Lewis acid sites and their effects on the direct coupling of EtOH and AcH to form 1,3-BD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reaction Mechanism of Vapor-Phase Formic Acid Decomposition over Platinum Catalysts: DFT, Reaction Kinetics Experiments, and Microkinetic Modeling

A combination of periodic density functional theory (DFT, PW91-GGA) calculations, reaction kinetics experiments, and mean-field microkinetic modeling is used to derive insights on the reaction mechanism and determine the nature of the active site under reaction conditions for the vapor-phase decomposition of formic acid (FA, HCOOH) over Pt/C catalysts. Microkinetic models formulated using DFT energetics derived on the clean Pt(100) and Pt(111) required large parameter adjustments to reproduce the experimentally measured apparent activation energies and reaction orders. Further, these models predicted high surface coverage of adsorbed carbon monoxide (CO*), inconsistent with the environment of the active site in the DFT calculations on the clean surfaces. Consequently, we reperformed DFT calculations for the entire reaction network on partially CO*-covered (4/9 monolayer, ML) Pt(111) and Pt(100). The resultant microkinetic models, with thermochemistry and kinetics explicitly dependent on CO* coverage, were able to reproduce the experimentally determined activation energies and reaction orders, in addition to being self-consistent in CO* coverage. Our results suggest that Pt(100) is likely poisoned by CO* under typical reaction conditions and does not contribute significantly to the experimentally observed reactivity. Instead, we find that Pt(111) better represents the active site for FA decomposition reaction on Pt/C catalysts. The optimized model on 4/9 ML CO*-covered Pt(111) suggests that the reaction occurs via the carboxyl (COOH*) intermediate and that the spectator CO*-assisted pathways play a significant role under reaction conditions. Lastly, this study underscores the importance of spectator species on the energetics and the mechanism of a catalytic reaction and their key role in developing a model that better addresses the nature of the active site under realistic catalytic reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic Analysis of Proton-Coupled Electron Transfer at an Electrode-Immobilized Complex

An alkyne-terminated cobalt complex, [Co(Cp)(dppe ≡H )(Cl)] + (Cp = cyclopentadienyl; dppe ≡H = 1,2-bis-(di-(4-ethynyl-phenyl)phosphino)ethane), (Co ≡H ) was immobilized onto a glassy carbon electrode using two attachment strategies: Cu(I) catalyzed azide–alkyne click chemistry and reductive electropolymerization. The modified electrodes prepared through reductive electropolymerization exhibit current densities and peak resolutions for the electrochemical reduction of the cobalt species, which are amenable to electroanalytical quantification of coupled chemical reactions. Through peak shift analysis of cyclic voltammograms recorded in the presence of 4-chloroanilinium tetrafluoroborate, we quantified the proton transfer rate constant for the stepwise proton-coupled electron transfer reaction that reduces the electrode-immobilized [Co(Cp)(dppe ≡H )(Cl)] + to [H–Co(Cp)(dppe ≡H )] + (k PT app = (9.3 ± 1.8) × 10 5 M –1 s –1 ). In conclusion, the extraction of kinetic parameters for an elementary proton-coupled electron transfer reaction of an electrode-immobilized complex represents the first experimental measurement of its type and lays crucial groundwork for kinetic analyses of hybrid catalyst–electrode architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decoupling Kinetics and Thermodynamics of Interfacial Catalysis at a Chemically Modified Black Silicon Semiconductor Photoelectrode

Understanding the interplay between the kinetics of interfacial catalytic reactions and the thermodynamics of an underlying semiconductor electrode is imperative for rational construction of efficient photoelectrocatalytic systems. Current understanding of the thermodynamic effects of molecular catalyst attachment to semiconductor electrodes is limited. We report the immobilization of a molecular cobalt bis(benzenedithiolate) proton reduction catalyst onto nanoporous black silicon (b-Si) electrodes through p–p interactions with a series of aromatic molecules covalently attached to the surface. Furthermore, intensity-modulated high-frequency resistivity and linear sweep voltammetry measurements are used to show that the kinetics of proton reduction are decoupled from the thermodynamic properties of the underlying b-Si photoelectrode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗

Kinetic Study of Polyvinyl Chloride Pyrolysis with Characterization of Dehydrochlorinated PVC

In this paper, we study the kinetics of polyvinyl chloride (PVC) decomposition using a combination of experimental and computational approaches. Here, we develop a simplified kinetic model that contains only two steps: dehydrochlorination of PVC and further decomposition of the PVC residue. The model is consistent with density functional theory (DFT) calculations and experimental data. Dehydrochlorination is an autocatalytic reaction that starts with a tertiary chloride (Cl) and generates hydrogen chloride (HCl) and benzene as the main products. Benzene and HCl formation rates showed similar trends, indicating that HCl likely catalyzes a homolytic carbon-carbon (C-C) bond cleavage, which gives rise to benzene and an aliphatic fragment. We characterized the structure of dehydrochlorinated PVC (PVC residue) by using thermal gravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). FTIR and NMR results indicate that the PVC residue contains 20% quaternary carbon content, indicating a high concentration of cross-linked molecules. We predict that the most probable structure in the cross-linked centers of the PVC residue is cyclohexadiene, which is supported by DFT calculations, FTIR, and NMR.

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