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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Coupling of Pronghorn and RELAP-7 for a Pebble Bed Reactor

High temperature gas cooled reactors (HTGR) are a candidate for timely Gen-IV reactor technology deployment because of high technology readiness and walk-away safety. Among HTGRs, pebble bed reactors (PBRs) have attractive features such as low excess reactivity and online refueling. Pebble bed reactors pose unique challenges to analysts and reactor designers such as continuous burnup distribution depending on pebble motion and recirculation, radiative heat transfer across a variety of gas-filled gaps, and long design basis transients such as pressurized and depressurized loss of forced circulation. Modeling and simulation is essential for both the PBR’s safety case and design process. In order to verify and validate the new generation codes the Nuclear Energy Agency (NEA) Data bank provide a set of benchmarks data together with solutions calculated by the participants using the state of the art codes of that time. An important milestone to test the new PBR simulation codes is the OECD NEA PBMR-400 benchmark which includes thermal hydraulic and neutron kinetic standalone exercises as well as coupled exercises and transients scenarios. In this work, the reactor multiphysics code MAMMOTH and the thermal hydraulics code Pronghorn, both developed by the Idaho National Laboratory (INL) within the multiphysics object-oriented simulation environment (MOOSE), have been used to solve Phase 1 exercises 1 and 2 of the PBMR-400 benchmark. The steady state results are in agreement with the other participants’ solutions demonstrating the adequacy of MAMMOTH and Pronghorn for simulating PBRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Experimental Investigation of Uranium Volatility during Vapor Condensation

The predictive models that describe the fate and transport of radioactive materials in the atmosphere following a nuclear incident (explosion or reactor accident) assume that uranium-bearing particulates would attain chemical equilibrium during vapor condensation. Here, we show that kinetically driven processes in a system of rapidly decreasing temperature can result in substantial deviations from chemical equilibrium. This can cause uranium to condense out in oxidation states (e.g., UO 3 vs UO 2 ) that have different vapor pressures, significantly affecting uranium transport. To demonstrate this, we synthesized uranium oxide nanoparticles using a flow reactor under controlled conditions of temperature, pressure, and oxygen concentration. The atomized chemical reactants passing through an inductively coupled plasma cool from ~5000 to 1000 K within milliseconds and form nanoparticles inside a flow reactor. The ex situ analysis of particulates by transmission electron microscopy revealed 2–10 nm crystallites of fcc-UO 2 or α-UO 3 depending on the amount of oxygen in the system. α-UO 3 is the least thermodynamically preferred polymorph of UO 3 . The absence of stable uranium oxides with intermediate stoichiometries (e.g., U 3 O 8 ) and sensitivity of the uranium oxidation states to local redox conditions highlight the importance of in situ measurements at high temperatures. Therefore, we developed a laser-based diagnostic to detect uranium oxide particles as they are formed inside the flow reactor. Our in situ measurements allowed us to quantify the changes in the number densities of the uranium oxide nanoparticles (e.g., UO 3 ) as a function of oxygen gas concentration. Our results indicate that uranium can prefer to be in metastable crystal forms (i.e., α-UO 3 ) that have higher vapor pressures than the refractory form (i.e., UO 2 ) depending on the oxygen abundance in the surrounding environment. This demonstrates that the equilibrium processes may not dominate during rapid condensation processes, and thus kinetic models are required to fully describe uranium transport subsequent to nuclear incidents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Heat Pipe Reactor Dynamic Response Tests: SAFE-100 Reactor Core Prototype

The SAFE-I00a test article at the NASA Marshall Space Flight Center was used to simulate a variety of potential reactor transients; the SAFEl00a is a resistively heated, stainless-steel heat-pipe (HP)-reactor core segment, coupled to a gas-flow heat exchanger (HX). For these transients the core power was controlled by a point kinetics model with reactivity feedback based on core average temperature; the neutron generation time and the temperature feedback coefficient are provided as model inputs. This type of non-nuclear test is expected to provide reasonable approximation of reactor transient behavior because reactivity feedback is very simple in a compact fast reactor (simple, negative, and relatively monotonic temperature feedback, caused mostly by thermal expansion) and calculations show there are no significant reactivity effects associated with fluid in the HP (the worth of the entire inventory of Na in the core is .<el, so fluid movement and temperature changes will cause very minor effects). In previous SAFE-100 tests, the point kinetics model was based on core thermal expansion via deflection measurements. It was found that core deflection was a strung function of how the SAFE-100 modules were fabricated and assembled (in terms of straightness, gaps, and other tolerances). To remove the added variable of how this particular core expands as compared to a different concept, it was decided to use a temperature based feedback model (based on several thermocouples placed throughout the core).

Bragg-Sitton, Shannon M.↗
DOE OSTI2023

Optimal Chloride Salt Mixture for a Fusion Blanket

Deuterium-tritium fusion reactors cannot operate for a significant period without a closed tritium fuel cycle, according to a recent National Academies of Sciences (NAS) report on bringing fusion reactors to the US electrical grid. This fact places breeder blankets as one of the foundational systems for self-sustained fusion reactor operation. The typical functional requirements for a breeder blanket system include producing tritium, absorbing kinetic energy, transporting thermal energy, and being environmentally attractive. State-of-the-art research on liquid blankets has converged to primarily focus on (LiF) 2 and BeF 2 (FLiBe) molten salts and a metallic eutectic of lead and lithium (PbLi), but “virtually all of the technologies related to the tritium fuel cycle are at a low technological readiness level”. This work sought to explore optimum blanket configurations as it aligned with the Oak Ridge National Laboratory (ORNL) FY 2023 Laboratory Directed Research and Development Program’s research priority of developing and expanding the current understanding of fusion blanket science and technology. This purpose of this work was to address ORNL research priorities and NAS recommendations by investigating novel liquid blanket materials that could provide self-sustaining operation and draw on experience from research on molten salts used for advanced fission reactors, concentrated solar, and thermal energy storage. The hypothesis when proposing this research was that there could be chloride-based blanket designs that can exceed the tritium breeding ratios of (FLiBe) molten salt blankets while reducing the use of Be (FLiBe), avoiding the generation of HF (FLiBe), and minimizing magnetohydrodynamic (MHD)-perturbed flow fields (PbLi). The fastest and most cost-effective path to deploying liquid fusion breeder blankets could be from maximizing the synergistic technological overlap between fusion, fission, concentrated solar, and thermal energy storage industries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Condensed Phase Guerbet Reactions of Ethanol/Isoamyl Alcohol Mixtures

The self-condensation and cross-condensation reactions of ethanol and isoamyl alcohol are examined to better understand the potential routes to value-added byproducts from fuel ethanol production. Reactions have been carried out in both batch autoclave and continuous condensed-phase reactors using a lanthanum-promoted, alumina-supported nickel catalyst at near-critical condensed phase conditions. Analysis of multiple candidate kinetic models led to a Langmuir–Hinshelwood rate expression that is first-order in alcohol with water as the strongly adsorbed species. This model provides the best fit of data from both batch and continuous reactor experiments. Activation energies for primary condensation reactions increase as carbon chain lengths increase. Selectivities to higher alcohols of 94% and 87% for ethanol and isoamyl alcohol, respectively, were observed at different operating conditions.

Nezam, Iman (ORCID:0000000277598069)↗
DOE OSTI2023

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, are a widely employed class of methods. Recently, an alternative technique that focuses on higher-order statistical interactions, co-kurtosis PCA (CoK-PCA), has been shown to effectively provide a low-dimensional representation by capturing the stiff chemical dynamics associated with spatiotemporally localized reaction zones. While its effectiveness has only been demonstrated based on a priori analyses with linear reconstruction, in this work, we employ nonlinear techniques to reconstruct the full thermo-chemical state and evaluate the efficacy of CoK-PCA compared to PCA. Specifically, we combine a CoK-PCA-/PCA-based dimensionality reduction (encoding) with an artificial neural network (ANN) based reconstruction (decoding) and examine, a priori, the reconstruction errors of the thermo-chemical state. In addition, we evaluate the errors in species production rates and heat release rates, which are nonlinear functions of the reconstructed state, as a measure of the overall accuracy of the dimensionality reduction technique. We employ four datasets to assess CoK-PCA/PCA coupled with ANN-based reconstruction: zero-dimensional (homogeneous) reactor for autoignition of an ethylene/air mixture that has conventional single-stage ignition kinetics, a dimethyl ether (DME)/air mixture which has two-stage (low and high temperature) ignition kinetics, a one-dimensional freely propagating premixed ethylene/air laminar flame, and a two-dimensional dataset representing turbulent autoignition of ethanol in a homogeneous charge compression ignition (HCCI) engine. Finally, results from the analyses demonstrate the robustness of the CoK-PCA based low-dimensional manifold with ANN reconstruction in accurately capturing the data, specifically from the reaction zones.

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

The RAPTR furnace: a rapid heating and cooling sample furnace for in situ X-ray scattering studies of temperature-induced reactions

In situX-ray scattering provides valuable insights into the mechanisms and kinetics of reactions and structural transformations. For reactions and structural transformations primarily driven by temperature, and not coupled to chemical/electrochemical triggers, our ability to initiate and quench processes thermally is a practical limit for probing fast reactive phenomena. Meaningful quantitative analysis requires the dynamic phenomena to be triggered on fast time scales relative to the reaction/transformation kinetics. This article describes a new sample furnace, the Rapid-Actuating Pneumatic Thermal Reactor or RAPTR, for time-resolvedin situX-ray scattering studies initiated by temperature. The RAPTR quickly heats and cools samples by translating them into and out of a pre-heated hot zone. Using diffraction thermometry, it is shown that the samples can be heated/cooled in 10 s or less, with temperatures up to ∼1000°C being accessible. The application of the RAPTR furnace is demonstrated by exploring a fast solid-state reaction: the synthesis of scheelite-type lead tungstate, PbWO 4 , from PbO and WO 3 for which Pb 3 WO 6 is identified as a previously unrecognized reaction intermediate.

Chemistry↗
DOE OSTI2020

Substrate-explicit Modeling Tutorial

This tutorial Narrative demonstrates how to apply thermodynamic theory, also known as lambda theory, to convert molecular formulas of compounds (derived from FTICR-MS peaks using Formulatiry and R codes) into stoichiometric and kinetic forms of biogeochemical reactions and how to use the resulting kinetic equations to simulate dynamic conversion of compounds in batch and continuous stirred tank reactors. It will address under what conditions respiration rates are driven by thermodynamics, and how respiration rates respond to the variations in parameters and input variables and how to interpret the results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Field Testing of an Affordable Zero-Liquid-Discharge Arsenic-Removal Technology for a Small-Community Drinking Water System in Rural California

Arsenic contamination in groundwater threatens public health, particularly in small, low-income communities lacking affordable treatment solutions. This study investigated the field implementation of novel air cathode assisted iron electrocoagulation (ACAIE) technology for arsenic removal in Allensworth, California, where groundwater arsenic concentrations exceeded 250 µg/L. Over four months, a pilot-scale ACAIE system, operating at 600 L/h, consistently reduced arsenic levels to below the EPA’s maximum contaminant level of 10 µg/L. Laboratory experiments informed the optimization of charge dosage and flow rates, which were validated during field testing of the ACAIE 600 L/h system. The in-situ generation of hydrogen peroxide at the cathode speeded up the reaction kinetics, ensuring high arsenic removal efficiency while allowing high throughput, even with a compact reactor size. An economic analysis demonstrated a treatment cost of USD 0.02/L excluding labor, highlighting the system’s affordability compared to conventional methods. Adding labor costs increased the treatment cost to USD 0.09/L. The regeneration of air cathodes extended their operational life, addressing a key maintenance challenge, thus reducing the costs slightly. Intermittent challenges were encountered with filtration and secondary contaminant removal; these issues highlight opportunities for further operational improvements. Despite these challenges, ACAIE’s low operational complexity, scalability, and cost-effectiveness make it a promising solution for underserved small communities. These findings provide critical insights into deploying sustainable arsenic remediation technologies that are tailored to the needs of rural, low-resource communities.

Bandaru, Siva R S↗
NASA NTRS1980

Cell module and fuel conditioner

The computer code for the detailed analytical model of the MK-2 stacks is described. An ERC proprietary matrix is incorporated in the stacks. The mechanical behavior of the stack during thermal cycles under compression was determined. A 5 cell stack of the MK-2 design was fabricated and tested. Designs for the next three stacks were selected and component fabrication initiated. A 3 cell stack which verified the use of wet assembly and a new acid fill procedure were fabricated and tested. Components for the 2 kW test facility were received or fabricated and construction of the facility is underway. The definition of fuel and water is used in a study of the fuel conditioning subsystem. Kinetic data on several catalysts, both crushed and pellets, was obtained in the differential reactor. A preliminary definition of the equipment requirements for treating tap and recovered water was developed.

Hoover, D. Q., Jr.↗
DOE OSTI2022

Data for Catalyst and Reactor Design Considerations for Selective Production of Acids by Oxidative Cleavage of Alkenes with H2O2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η2-O2) complexes vs. H2O2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H2O2 concentrations. Semi-batch reactors with continuous introduction of H2O2 solutions offer the means to maintain low H2O2 concentrations while providing sufficient quantities of H2O2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. This kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H2O2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H2O2 feed rate increases selectivity towards oxidative cleavage products and selective use of H2O2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semi-batch reactors with optimized molar feed rates of H2O2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H2O2 selectivity (3% to 30%). In addition, semi-batch reaction conditions used avoid H2O2-mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H2O2.

Catalysis↗
DOE OSTI2023

Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Catalytic production of δ-valerolactone (DVL) from biobased 2-hydroxytetrahydropyran (HTHP) – Combined experimental and modeling study

δ-Valerolactone (DVL) is a five-carbon (C5) cyclic ester that can undergo ring-opening polymerization to yield high-performance, biocompatible polyesters. But current market prices of C5 chemicals like DVL are very high due to poor availability of C5 feedstock in petroleum. Herein, we demonstrate a novel route to DVL synthesis via dehydrogenation of biomass-derived 2-hydroxytetrahydropyran (HTHP) over Cu/SiO 2 without the use of toxic reagents. Since HTHP exists in thermal equilibrium with 3,4-dihydropyran (DHP) via dehydration, and with 2,2’-oxybis(tetrahydropyran) and 5-(tetrahydropyran-2-yloxy)pentanal via acetalization, we have also determined the thermochemistry (ΔH rxn and ΔG rxn ) of each competing reaction using density functional theory (DFT) calculations at the M06-2X/cc-pVTZ level. Finally, by developing a kinetic model of all 8 reactions involved, we have achieved 84% selectivity to DVL at 150°C in a packed bed reactor for over 72 hours of time on stream.

42 ENGINEERING↗
NASA NTRS2017

Modeling a Packed Bed Reactor Utilizing the Sabatier Process

A numerical model is being developed using Python which characterizes the conversion and temperature profiles of a packed bed reactor (PBR) that utilizes the Sabatier process; the reaction produces methane and water from carbon dioxide and hydrogen. While the specific kinetics of the Sabatier reaction on the RuAl2O3 catalyst pellets are unknown, an empirical reaction rate equation1 is used for the overall reaction. As this reaction is highly exothermic, proper thermal control is of the utmost importance to ensure maximum conversion and to avoid reactor runaway. It is therefore necessary to determine what wall temperature profile will ensure safe and efficient operation of the reactor. This wall temperature will be maintained by active thermal controls on the outer surface of the reactor. Two cylindrical PBRs are currently being tested experimentally and will be used for validation of the Python model. They are similar in design except one of them is larger and incorporates a preheat loop by feeding the reactant gas through a pipe along the center of the catalyst bed. The further complexity of adding a preheat pipe to the model to mimic the larger reactor is yet to be implemented and validated; preliminary validation is done using the smaller PBR with no reactant preheating. When mapping experimental values of the wall temperature from the smaller PBR into the Python model, a good approximation of the total conversion and temperature profile has been achieved. A separate CFD model incorporates more complex three-dimensional effects by including the solid catalyst pellets within the domain. The goal is to improve the Python model to the point where the results of other reactor geometry can be reasonably predicted relatively quickly when compared to the much more computationally expensive CFD approach. Once a reactor size is narrowed down using the Python approach, CFD will be used to generate a more thorough prediction of the reactors performance.

Reactor↗
NASA NTRS2016

A-Priori Tuning of Modified Magnussen Combustion Model

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for that particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor simulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for simulations.

Norris, A. T.↗
DOE OSTI2020

Consequences of product inhibition in the quantification of kinetic parameters

While the potential for product inhibition in catalytic reactions is well known, the impact of neglected inhibition on measured kinetic parameters is often overlooked. The presence of product inhibition, most often caused by the competitive adsorption of products with reactants on catalytic active sites, is difficult to determine a priori for an arbitrary catalytic system. The significance of product inhibition relies on the concentration of the products, their adsorption thermodynamics on catalytically relevant sites, and process parameters such as temperature and pressure. When inhibition is significant, however, apparent activation energies and reaction orders vary from the differential-reactor apparent activation energy by a factor of 1/(1 - δ), where δ is the total inhibition order (e.g., the factor (1 - δ) = 1.6 for a system with product inhibition of -0.6 order). This is illustrated here with the kinetics of NO oxidation over Cu ion clusters (Cu x O y ) in Cu-SSZ-13, for which the product NO 2 inhibits the forward reaction. Furthermore, in the presence of inhibition, when only reactants are fed to a flow reactor or placed in a batch reactor, there is often no practical conversion that is low enough to guarantee differential behavior. Inclusion of products in the feed solves this problem, allowing accurate determination of kinetic parameters such as apparent reaction orders and activation energies. We also demonstrate that evaluation of the necessity of co-feeding products to assure measurement of differential-reactor data in a given catalytic system is straightforward from a plot of the log of the rate (or conversion) versus the log of the space time in a flow reactor or elapsed time in a batch reactor. We encourage inclusion of this test in all kinetic analyses that are reasonably approximated by power law rate expressions.

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

Sensitivity study of parameters important to Molten Salt Reactor Safety

This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗