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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Simulations of grain growth in tungsten armor materials under ARC plasma edge operation conditions using an integrated plasma-edge/materials model

An integrated model of grain growth deuterium-exposed tungsten polycrystals, consisting of a two-dimensional vertex dynamics model fitted to atomistic data, has been developed to assess the grain growth kinetics of deuterium-exposed polycrystalline tungsten (W). The model tracks the motion of grain boundaries under the effect of driving forces stemming from grain boundary curvature and differential deuterium concentration accumulation. Here, we apply the model to experimentally synthesized tungsten polycrystals under deuterium-saturated conditions relevant to the ARC concept design. The results indicate rapid grain growth kinetics in the near-surface region adjacent to the plasma, where the temperature reaches 1400 K, whereas the microstructure remains stable deeper in the material with the lower temperature of 1000 K. The combined modeling and analysis further reveal that monolithic tungsten produced via conventional fabrication routes is highly susceptible to grain coarsening at temperatures exceeding 1000 K, largely independent of the magnitude of the applied driving force. Moreover, the accumulation of deuterium near grain boundaries has a pronounced inhibitory effect on grain boundary migration. High-angle grain boundaries ( > 50°) contribute more significantly to the overall grain growth process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Burning velocities of R-32/O 2 /N 2 mixtures: Experimental measurements and development of a validated detailed chemical kinetic model

This work entails characterizing the flammability of the refrigerant R-32 (CH 2 F 2 ) by both experimental measurements and modeling. Burning velocities S u were measured using a constant-volume spherical-flame method for R-32/O2/N 2 mixtures with O 2 /N 2 ratios ranging from 21% (synthetic air) to 40%, pressures of (1 to 3) bar, and equivalence ratios $\phi$ of (0.8 to 1.3). Based on a critical assessment of available data, and extended by our own calculations, a detailed chemical kinetic model was developed and key reactions determined using reaction path and sensitivity analyses. Initiation and combustion were identified as distinct kinetic regimes and burning velocities were found to be controlled by two primary reactions: unimolecular decomposition of CH 2 F 2 → CHF + HF and the subsequent reaction, CHF + O 2 → CHFO + O, the latter reaction initiating the radical chain propagating and branching by producing O atoms. Sensitive rate constants in the kinetic model were critically adjusted within their uncertainties and current knowledge bounds to best fit the experimental burning velocities. We found that rate constants in the model could be adjusted to match a given experimental S u for specific conditions (O 2 loading, P, T, $\phi$). This, however, then fixes predicted burning velocities for other all conditions within (3 to 4)% if physically realistic rate parameters are maintained. Thus, the entire set of experimental data is fit, not just to particular conditions. Relative random uncertainties in the experimental Su measurements were (4 to 6)%, but assumptions made for thermal radiation lost by the burned gas in the spherical-flame experiments add an additional systematic uncertainty. Systematic differences between the limiting cases of adiabatic (no thermal radiation lost) and optically-thin (all thermal radiation lost) varied significantly with conditions and ranged from (4 to 30)% at high to low velocities, respectively, translating into uncertainties of (2 to 15)% considering the average of two limiting cases. Comparison of experimental and kinetically modeled Su values suggests that the burned gas tends towards the optically-thin limit at the lowest pressures and fuel loadings and toward the adiabatic limit at the highest pressures and loadings. We tested and found support for this conclusion with a detailed analysis as a function of all the conditions (T, P, % O 2 , $\phi$). This behavior appears to transition from optically-thin to adiabatic as the density of the initial fuel increases, which results in increased CO 2 in the burned gas and thus increased absorption of the thermal radiation (consistent with the Beer-Lambert Law). The validated detailed model based on evaluated kinetics is shown to accurately predict burning velocities for R-32 O 2 /N 2 mixtures over a wide range of conditions and provides a reliable basis for extrapolation to other conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

New scaling law for turbulent boundary layers with high surface mass transfer

A fundamental understanding of the phenomena occurring in the turbulent boundary layer in the presence of surface blowing is limited, and considerable disagreements persist even in describing primary quantities, such as the boundary layer profile. The theories based on the linear boundary layer equations show that the thickness of the sublayer increases in the presence of surface blowing; therefore, the viscous sublayer and law of the wall modify. In this study, direct numerical simulations (DNS) of turbulent boundary layers with uniform surface mass transfers are carried out in order to scale the velocity profile. Emphasis is placed on moderate to high mass transfer rates, which are relevant to the most common hybrid rockets configuration. DNS data are used to establish a functional law of the wall and a law of wake by means of the relation between the wall shear stress and surface mass transfer. Analysis of the mean kinetic energy budget shows that the magnitude of turbulent kinetic energy increases by surface mass transfer, and the production rate extends significantly in the inner layer as the injection rate increases. DNS data of various surface blowing are used to complete the closure of turbulence kinetic energy equation and develop an eddy viscosity model. The predicted turbulent kinetic energy and eddy viscosity agree with DNS data for moderate to high blowing rates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

An Experimental Study of Uncertainty Considerations Associated with Predicting Auto-ignition Timing using Livengood-Wu Integral Method

The application of the Livengood-Wu (LW) integral method as a tool to estimate knock onset in spark ignited (SI) engines and combustion phasing in advanced compression ignition (ACI) engines has been demonstrated through simulations several times. In this study, the effect of uncertainties associated with parameters required for the LW integral method, when used as a tool for model based control of ignition timing in an ACI engine, were experimentally studied using five full boiling range gasoline fuels. As a first step, the method was applied to experimental data from a rapid compression machine and it was found that the ability of the LW integral method to predict ignition timing was very sensitive to the performance of the chemical kinetic model of each fuel. The method was subsequently applied to experimental data from a single-cylinder gasoline engine with simple approximations for the LW integral input parameters, and it was found that the predicted time of ignition was significantly different from the actual start of combustion. Systematic evaluation of various parametric uncertainties conducted thereafter showed that the uncertainty in cylinder charge temperature has the greatest influence. Improved methods of estimating cylinder charge temperature are proposed to account for the previously determined corrections, to enable the use of the LW integral method for model based control of ignition timing.

Compression Ignition↗
DOE OSTI2024

On the prediction of pressure effects for the combination kinetics of two alkyl radicals with the geometric mean rule

Here, alkyl combination reactions, along with their reverse alkane unimolecular decomposition reactions, are widely present in pyrolysis and combustion systems. These reactions occur mainly at temperatures at which their rate coefficients depend on pressure, and only a few studies have explored this dependence for large size alkyls. The accurate calculation of these kinetic data is limited by the size of the alkyl fragments involved, since the theoretical methods used are computationally expensive. Therefore, little reliable data is available for the modeling of real fuels alkane decomposition kinetics. In this paper, we propose an alternative approach that allows an accurate estimation of pressure-dependent kinetic rates for the combination of long-chain alkyl radicals, based on tabulated reaction models. The rates of combination of linear alkyls radicals forming ethane to pentane were calculated using the CASPT2-F12/cc-pVDZ-F12 level within VRC-TST theory combined with master-equation simulations. The computed high-pressure limit rate coefficients showed that n-propyl could be a minimum-size representative structure for larger n-alkyl chain, but this approach fails to capture the pressure dependence of the reaction that remains size-dependent for larger alkyls. The Geometric Mean Rule (GMR), a simple rule that links the self and cross-reactions of three alkyl radicals, is used to address this issue. Our theoretical calculations show for the first time that the GMR applies not only at the high-pressure limit, but also for every pressure explored. The GMR is shown to be accurate, with a maximum 22 % deviation in the falloff region for the estimation of rates for small alkyl combinations. Using this method, we propose a tabulated reaction rate rule for the combination of alkyl radicals up to C5+C5. The use of computed rate coefficients with the GMR approximation opens ways to develop pressure-dependent reaction rate rules for large n-alkyl combinations, based on accurate and computationally expensive theoretical calculations on smaller alkyl fragments.

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

A comprehensive experimental and kinetic modeling study of di-isobutylene isomers: Part 1

We report di-isobutylene has received significant attention as a promising fuel blendstock, as it can be synthesized via biological routes and is a short-listed molecule from the Co-Optima initiative. Di-isobutylene is also popularly used as an alkene representative in multi-component surrogate models for engine studies of gasoline fuels. However, there is limited experimental data available in the literature for neat di-isobutylene under engine-like conditions. Hence, most existing di-isobutylene models have not been extensively validated, particularly at lower temperatures (< 1000 K). Most gasoline surrogate models include the di-isobutylene sub-mechanism published by Metcalfe et al. with little or no modification. The current study is undertaken to develop a detailed kinetic model for di-isobutylene and validate the model using a wide range of relevant experimental data. Part 1 of this study exclusively focuses on the low- to intermediate temperature kinetics of di-isobutylene. An upcoming part 2 discusses the high-temperature model development and validation of the relevant experimental targets. Ignition delay time measurements for the di-isobutylene isomers were performed at pressures ranging from 15 - 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 diluted in air and in the temperature range 650 - 900 K using two independent rapid compression machine facilities. In addition, measurements of species identified during the oxidation of these isomers were performed in a jet-stirred reactor and in a rapid compression machine. A detailed kinetic model for the di-isobutylene isomers is developed to capture the wide range of new experimental targets. For the first time, a comprehensive low-temperature chemistry submodel is included. The differences in the important reaction pathways for the accurate prediction of the oxidation of the two DIB isomers are compared using reaction path analysis. In conclusion, the most sensitive reactions controlling the ignition delay times of the DIB isomers under the pressure and temperature conditions necessary for autoignition in engines are identified.

09 BIOMASS FUELS↗
DOE OSTI2025

Removal of Selenium Oxyanions from Aqueous Solutions by Ion Exchange: Equilibrium, Kinetics, and Mechanistic Modeling

Selenium (Se) is an essential micronutrient but toxic at high concentrations, posing challenges for water treatment. This study investigated the removal of selenate (SeO 4 2– ) and selenite (SeO 3 2– ) using the strong-base anion-exchange resin IRA-900, particularly in the presence of competing sulfate (SO 4 2– ). The performance of the commercially available resin IRA-900 was systematically investigated. The batch equilibrium behavior was studied in both single- and binary-component systems, and the kinetic behavior was investigated in single-component systems. Results confirmed a selectivity order of SeO 4 2– > SO 4 2– > SeO 3 2– , indicating preferential SeO 4 2– removal over competing SO 4 2– but lower affinity for SeO 3 2– . The maximum total exchange capacity was determined to be 2.04 mequiv/g. Furthermore, SeO 3 2– uptake was found to be pH-dependent, whereas SeO 4 2– uptake remained stable across a broad pH range. From a modeling perspective, the Law of Mass Action model effectively described equilibrium data, and a transport–reaction modeling framework captured removal kinetics of oxyanions including film and intraparticle diffusion. Finally, X-ray photoelectron spectroscopy confirmed ion exchange between chloride and Se oxyanions as the primary removal mechanism. These findings provide fundamental insights into the removal of Se oxyanions from aqueous solutions by ion exchange.

IRA-900↗
DOE OSTI2024

An experimental and chemical kinetic modeling study of 4-butoxyheptane combustion

Here, the combustion kinetics of a novel oxygenated bioblendstock for diesel, 4-butoxyheptane (4-BH), was investigated experimentally using a flow reactor and a heated, high-pressure shock tube. The flow reactor experiments employed oxygen as the oxidizer and helium as the diluent with oxidation conducted at atmospheric pressure and 10 bar for temperatures from 400 to 1000 K at 20-K intervals. The fuel, oxidizer, and diluent flow rates were varied at different temperatures to maintain a constant initial fuel mole fraction of 1000 ppm, with stoichiometric equivalence ratio, and a residence time of 2.0 s. The reacted gas was fed to two separate GC systems that could qualitatively and quantitatively detect product species. Additionally, real fuel-air ignition delay time (IDT) data were collected using a heated, high-pressure shock-tube facility. Fuel lean (φ = 0.5) and stoichiometric (φ = 1.0) mixtures were investigated at 10 atm as well as at 30 atm for the fuel lean case for temperatures between 847 and 1259 K. A detailed chemical kinetics mechanism was developed to model the product distribution from the flow reactor and IDTs from the shock tube. The proposed model was able to predict the double NTC behavior in flow reactor experiments reasonably well. Model predictions at low temperatures were observed to be highly sensitive to the rate constants of ketohydroperoxide (KHP) decomposition in the case of the OOH group in α position which were modeled based on existing literature studies on ethers. It was noted that in the absence of theoretical or experimental studies, the rate constants for KHP decomposition used in the literature were empirically set. Additional studies are required to address the gap in model prediction obtained in this study and to reduce the uncertainty in kinetics models for ether oxidation. Predicted product concentrations and IDTs showed some quantitative agreement with experimental data, but the overall reactivity of the IDTs is underpredicted. Additionally, significant deviation is observed for the IDT results at 10 atm for the stoichiometric case with minor deviations for the other cases. The reaction pathways to the missing products were then further analyzed theoretically through quantum-mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Kinetic model development for single step ethanol to butene rich olefin process over Cu-Y/Beta catalysts

Here, this study presents the first intrinsic kinetic model for the single-step conversion of ethanol to butene-rich olefins over bifunctional Cu-Y/Beta catalysts, addressing a critical gap in the design and scale-up of Sustainable Aviation Fuel (SAF) processes. The reaction network comprises ten global steps involving dehydrogenation, aldol condensation, hydrogenation, and dehydration reactions, distributed across Cu and rare-earth (Y) active sites. The model incorporates dual-site functionality (Cu and Y site) and explicitly accounts for key intermediates such as crotonaldehyde and butanal. Reaction rates are formulated using Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetics. Kinetic parameters are extracted by fitting the model to lab-scale packed-bed reactor data across a wide range of temperatures and space velocities, demonstrating strong agreement in ethanol conversion and product selectivity. The reaction kinetics developed in this work provide a foundational basis for constructing reactor models that enable process optimization and scale-up of ethanol-to-jet fuel technologies.

Cu-Y/Beta catalyst↗
DOE OSTI2023

Cold-cap structure in a slurry-fed electric melter

We report as glass batch is charged into an electric melter, a cold cap forms on the glass melt surface. Heat transfer to the cold cap from the molten glass below and the melter atmosphere above determines the melting rate. A mathematical model of the cold cap and the experimental kinetic data of the feed-to-glass conversion that were collected for several simulated low-activity and high-level waste melter feeds allowed us to develop relationships between the internal structure of the cold cap, its properties, its thickness, and the internal heat transfer. This contribution shows the distribution of major crystalline phases and the cumulative evolution of gases within the cold cap. It also examines the temperature, conversion degree, and heating rate the melter feed is experiencing during the passage through the cold cap and their effects on the cold-cap bottom temperature and morphology, which are important for the computational fluid dynamics simulations of melters.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Autoignition of cyclohexane at low-to-intermediate temperatures: Rapid compression machine experiments and improved comprehensive chemical kinetic model

Cycloalkanes are an important class of hydrocarbons found in conventional and alternative transportation fuels. Being one of the simplest practical cycloalkanes, cyclohexane is often used as a surrogate in studies to understand the oxidation, ignition, and sooting characteristics of cycloalkanes more broadly. Although cyclohexane has been extensively studied, very limited datasets for cyclohexane oxidation at low-to-intermediate temperatures are available in the literature. Moreover, the literature autoignition data from rapid compression machines (RCMs) did not provide information on volume histories or experimental heat transfer characteristics which can significantly impact model predictions, thereby hindering the detailed validation of chemical kinetic models. It has also been observed that the cyclohexane kinetic models developed so far are not able to predict the literature data across a wide range of operating and mixture conditions. Hence, further studies are recommended to understand and improve model predictions for cyclohexane oxidation. In this study, RCM experiments were conducted using cyclohexane/air mixtures at varying compressed pressures (P C =15, 20, and 30 bar), equivalence ratios (ϕ=0.5, 1.0, and 2.0), and compressed temperatures (T C =670–960 K). The current RCM results of cyclohexane were found to complement well with the literature data, with the first-stage IDTs at high pressures and volume histories at all test conditions being first reported for better development and validation of chemical kinetic models. Additionally, a detailed chemical kinetic model for the cyclohexane oxidation has been developed and validated using both newly acquired experimental IDTs in this study and literature experimental studies (IDTs in RCMs and STs, species profiles in jet-stirred reactors, and laminar burning velocities). Unlike literature models, the proposed model was observed to provide an overall better prediction for experimental results over a wide range of conditions. Chemical kinetic analysis of the developed model was further conducted to identify the reaction pathways controlling the autoignition of cyclohexane.

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

Biomass char gasification kinetic rates compared to data, including ash effects

This investigation provides both experimental and theoretical analyses of biomass char gasification kinetics over 1150–1350 °C in the environment of CO 2 , H 2 O and combinations of these reactants. The experimental data include continuous measurements of particle mass, external and internal temperatures, shape, and size with periodic but not continuous measurements of char porosity, pore size distribution, and pore surface area. The model describes heterogeneous char gasification for poplar wood, corn stover and switchgrass in different shapes and industrially relevant sizes (12.5 mm and smaller). Nonlinear least-squares regression produces optimized power-law model parameters for global kinetics that describe biomass char gasification with respect to both CO 2 and H 2 O separately and in combination. A single set of kinetic parameters describes reaction rates for all three fuels. Model simulations agree with measured data at all stages of char conversion even though the observed mass loss rates change significantly with conversion. In conclusion, the change in rate with conversion depends strongly on ash content, and this investigation provides a simple and theoretically based reaction rate expression that includes the effect of inert ash occupying an increasing portion of the reactive surface with increased conversion.

09 BIOMASS FUELS↗
DOE OSTI2022

Towards multi-fidelity deep learning of wind turbine wakes

We report engineering wake models that accurately predict wake in a computationally efficient manner are very important for tasks such as layout optimization and control of wind farms. In this paper, we explore an application of deep learning (DL) to learn the wake model from hierarchies of physics-based approaches ranging from analytical models to an approximate form of the Reynolds-averaged Navier-Stokes equations. We first illustrate the application of principal component analysis to obtain a lower-dimensional representation that allows a computationally tractable training and deployment of DL models. Then, the DL model is trained to learn the mapping from input parameter space to the principal components, which are then used to reconstruct the three-dimensional flow field. Additionally, we investigate a composite framework consisting of two neural networks to learn the correlation between low- and high-fidelity data with Gauss and curl models treated as proxies for low- and high-fidelity models, respectively. The prediction from both DL models matches well with the high-fidelity data with a maximum relative percentage error for the kinetic energy flux of <1%. This work opens up possibilities for data-efficient construction of surrogate models for wake prediction that can be used to study the influence of wind speed and yaw angles on wind farm power production.

17 WIND ENERGY↗
DOE OSTI2024

Direct Evidence for a Sequential Electron Transfer–Proton Transfer Mechanism in the PCET Reduction of a Metal Hydroxide Catalyst

Here, the proton-coupled electron transfer (PCET) mechanism for the reaction M ox -OH + e − + H + → M red -OH 2 was de-termined through kinetic resolution of the independent electron transfer (ET) and proton transfer (PT) steps. The reaction of interest was triggered by visible light excitation of [Ru II (tpy)(bpy′)H 2 O] 2+ , Ru II -OH 2 , where tpy is 2,2′:6′,2″-terpyridine and bpy′ is 4,4′-diaminopropylsilatrane-2,2′-bipyridine, anchored to In 2 O 3 :Sn (ITO) thin films in aqueous solutions. Interfacial kinetics for the PCET reduction reaction were quantified by nanosecond transient absorption spectroscopy as a function of solution pH and applied potential. Data acquired from pH = 5-10 revealed a stepwise electron-transfer proton-transfer (ET-PT) mechanism, while kinetic measurements made below the pK a (Ru III -OH/OH 2 ) = 1.3 were used to study the analogous interfacial reaction where electron transfer was the only mechanistic step. Analysis of this data with a recently reported multi-channel kinetic model was used to construct a PCET zone diagram and supported the assignment of an ET-PT mechanism from pH = 5-10. Ultimately, this study represents a unique example amongst M ox -OH/M red -OH 2 reactivity where the protona-tion and oxidation state of the intermediate was kinetically and spectrally resolved to firmly establish the PCET mechanism.

Charge transfer↗
DOE OSTI2022

Catalytic production of tetrahydropyran (THP): a biomass-derived, economically competitive solvent with demonstrated use in plastic dissolution

Tetrahydropyran (THP) is a five-carbon heterocyclic ether that is non-carcinogenic, non-peroxide forming, biodegradable, and economically competitive with tetrahydrofuran (THF) as a solvent. In this work, THP has been synthesized from renewable biomass at >99.8% selectivity and 98% yield via hydrogenation of furfural-derived 3,4-dihydropyran (DHP) over Ni/SiO 2 in a continuous flow reactor at 150–200 °C. The apparent activation energy of THP formation is 31 kJ mol -1 , and the reaction orders with respect to the partial pressures of H 2 , DHP, and THP are: 2, 1, and -0.3. The kinetic data has been fitted to a Hougen–Watson model where the rate limiting step is the hydrogenation of adsorbed DHP. Ni/SiO 2 is shown to have a low deactivation rate constant of 0.012 h -1 over 100 h time on stream and can be regenerated in situ. As a performance advantage, THP is shown to be resistant to ring opening polymerization under strongly acidic conditions that THF is not, revealing it to be a superior solvent. Further, the minimum selling price of THP is competitive with the market price of THF ($$900 – 1400 per ton ) at a DHP feedstock cost of $1000 per ton. Conductor-like Screening Model for Real Solvents (COSMO-RS) and molecular dynamics (MD) simulations with 1008 solvents and 8 common plastics have demonstrated that THP can serve as an alternative solvent to THF, 2-methyltetrahydrofuran (MeTHF), and cyclopentyl methyl ether (CPME) for plastic dissolution, especially low-density polyethylene (LDPE), polypropylene (PP), polystyrene (PS) and polyvinyl chloride (PVC). This work establishes THP as a green solvent with excellent thermal, chemical and peroxidative stability that can be used for numerous applications, including waste plastic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Unconventional gas-phase preparation of the prototype polycyclic aromatic hydrocarbon naphthalene (C 10 H 8 ) via the reaction of benzyl (C 7 H 7 ) and propargyl (C 3 H 3 ) radicals coupled with hydrogen-atom assisted isomerization

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the interstellar medium and in meteorites such as Murchison and Allende and signify the missing link between resonantly stabilized free radicals and carbonaceous nanoparticles (soot particles, interstellar grains). However, the predicted lifetime of interstellar PAHs of some 108 years imply that PAHs should not exist in extraterrestrial environments suggesting that key mechanisms of their formation are elusive. Exploiting a microchemical reactor and coupling these data with computational fluid dynamics (CFD) simulations and kinetic modeling, we reveal through an isomer selective product detection that the reaction of the resonantly stabilized benzyl (C 7 H 7 ) and the propargyl (C 3 H 3 ) synthesizes the simplest representative of PAHs – the 10π Hückel aromatic naphthalene (C 10 H 8 ) molecule – via the novel Propargyl Addition–BenzAnnulation (PABA) mechanism. The gas-phase preparation of naphthalene affords a versatile concept of the reaction of combustion and astronomically abundant propargyl radicals with aromatic radicals carrying the radical center at the methylene moiety (aromatic-CH 2 ) as a previously passed over source of aromatics in high temperature environments thus bringing us closer to an understanding of the aromatic universe we live in.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗