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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A statistical model for the product energy distribution in reactions leading to prompt dissociation

Direct dynamics calculations have been performed for three reactions: C 3 H 8 + H → i-C 3 H 7 + H 2 , C 3 H 8 + H → n-C 3 H 7 + H 2 , and C 2 H 3 + O 2 → HCO + CH 2 O. The fraction of the population for the radical products that promptly dissociates is computed. Here the results for C 3 H 8 + H are qualitatively similar to previous results for C 3 H 8 + OH, but the new results exhibit a slightly higher branching fraction for prompt dissociation products, owing to the fact that a greater fraction of the internal energy in the transition state ends up in the radical. For C 2 H 3 + O 2 → HCO + CH 2 O, the fraction of HCO that promptly dissociates is in excess of 99%. Consequently, the main product for C 2 H 3 + O 2 at lower temperatures should be written as H + CO + CH 2 O and not HCO + CH 2 O. These results are then compared with four previous systems: CH 2 O + H → HCO + H 2 , CH 2 O + OH → HCO + H 2 O, C 3 H 8 + OH → i-C 3 H 7 + H 2 O, and C 3 H 8 + OH → n-C 3 H 7 + H 2 O. Based upon these seven system, several statistical models are presented. The goal of these statistical models is to predict the fraction of the transition state energy that ends up in the rovibrationally excited radical. On average, these statistical models provide an excellent prediction of product energy distribution. Consequently, these models can be used instead of costly trajectory simulations for predicting prompt radical dissociation for larger species.

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

The highly exothermic hydrogen abstraction reaction H 2 Te + OH → H 2 O + TeH: comparison with analogous reactions for H 2 Se and H 2 S

The “gold standard” CCSD(T) method is adopted along with the correlation consistent basis sets up to aug-cc-pV5Z-PP to study the mechanism of the hydrogen abstraction reaction H 2 Te + OH. Here, the predicted geometries and vibrational frequencies for reactants and products are in good agreement with the available experimental results. With the ZPVE corrections, the transition state in the favorable pathway of this reaction energetically lies 1.2 kcal mol -1 below the reactants, which is lower than the analogous relative energies for the H 2 Se + OH reaction (-0.7 kcal mol -1 ), the H 2 S + OH reaction (+0.8 kcal mol -1 ) and the H 2 O + OH reaction (+9.0 kcal mol -1 ). Accordingly, the exothermic reaction energies for these related reactions are predicted to be 47.8 (H 2 Te), 37.7 (H 2 Se), 27.1 (H 2 S), and 0.0 (H 2 O) kcal mol -1 , respectively. Geometrically, the low-lying reactant complexes for H 2 Te + OH and H 2 Se + OH are two-center three-electron hemibonded structures, whereas those for H 2 S + OH and H 2 O + OH are hydrogen-bonded. With ZPVE and spin–orbit coupling corrections, the relative energies for the reactant complex, transition state, product complex, and the products for the H 2 Te + OH reaction are estimated to be -13.1, -1.0, -52.0, and -52.6 kcal mol -1 , respectively. Finally, twenty-eight DFT functionals have been tested systematically to assess their ability in describing the potential energy surface of the H 2 Te + OH reaction. The best of these functionals for the corresponding energetics are -9.9, -1.4, -46.4, and -45.4 kcal mol -1 (MPWB1K), or -13.1, -2.4, -57.1, and -54.6 kcal mol -1 (M06-2X), respectively.

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

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗
DOE OSTI2025

Doping Effects on Multivalence States, Electronic Structure, and Optical Band Gap in LaCrO 3 under Varied Atmospheres: An Integrated Experimental and Density Functional Theory Study

Doping effects on the valence state, electronic structure, and optical band and the effects on electrical conductivity were studied on the doped lanthanum chromite (LaCrO 3 ) system. The specific compositions studied were La 1–x Ca x CrO 3 (LCCx), La 1–x Sr x CrO 3 (LSCx), and La 0.8 Sr 0.2 Cr 1–x Mn x O 3 (LSCMx) (0.1 ≤ x ≤ 0.4). The powders were synthesized using a modified Pechini sol–gel method, and the ceramic samples were densified using a reactive sintering method resulting in densities >96% theoretical. X-ray photoelectron spectroscopy (XPS) was completed to characterize the defect states and cationic valence compensation as a result of divalent (Ca 2+ or Sr 2+ ) and trivalent (Mn 3+ ) substitutions. XPS was completed for samples tested in oxidizing and reducing atmospheres (up to 1500 °C), which provided insights into the oxidation state transitions induced by the Ca 2+ and Sr 2+ dopants. The work notably demonstrated, for the first time, the oxidation/reduction transitions of Cr 4+ to Cr 3+ in Sr 2+ /Mn 3+ co-doped samples under reducing atmospheres. Reflectance UV–vis spectrophotometry optical band gap measurements were also completed for the same materials; a decrease in the optical band gap (2.81–3.12 eV) was shown with increased substitution, suggesting electronic structure modifications in the LaCrO 3 perovskite. Density functional theory calculations validated experimental trends, predicting a diminishing band gap with a rising dopant concentration. The transition in Cr oxidation states was attributed to the presence of divalent/trivalent cations. These findings contribute some insights into methods to tune the LaCrO 3 electrical properties for various low- and high-temperature applications.

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

Oxidation and pyrolysis of methyl propyl ether

The ignition, oxidation, and pyrolysis chemistry of methyl propyl ether (MPE) was probed experimentally at several different conditions, and a comprehensive chemical kinetic model was constructed to help understand the observations, with many of the key parameters computed using quantum chemistry and transition state theory. Experiments were carried out in a shock tube measuring time variation of CO concentrations, in a flow tube measuring product concentrations, and in a rapid compression machine (RCM) measuring ignition delay times. The detailed reaction mechanism was constructed using the Reaction Mechanism Generator software. Sensitivity and flux analyses were used to identify key rate and thermochemical parameters, which were then computed using quantum chemistry to improve the mechanism. Validation of the final model against the 1-20 bar 600-1500 K experimental data is presented with a discussion of the kinetics. The model is in excellent agreement with most of the shock tube and RCM data. Strong non-monotonic variation in conversion and product distribution is observed in the flow-tube experiments as the temperature is increased, and unusually strong pressure dependence and significant heat release during the compression stroke is observed in the RCM experiments. These observations are largely explained by a close competition between radical decomposition and addition to O2 at different sites in MPE; this causes small shifts in conditions to lead to big shifts in the dominant reaction pathways. The validated mechanism was used to study the chemistry occurring during ignition in a diesel engine, simulated using Ignition Quality Test (IQT) conditions. At the IQT conditions, where the MPE concentration is higher, bimolecular reactions of peroxy radicals are much more important than in the RCM.

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

A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes

Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.

Chemical engineering↗
DOE OSTI2022

Cryptic Methane-Cycling by Methanogens During Multi-Year Incubation of Estuarine Sediment

As marine sediments are buried, microbial communities transition from sulfate-reduction to methane-production after sulfate is depleted. When this biogenic methane diffuses into the overlying sulfate-rich sediments, it forms a sulfate-methane transition zone (SMTZ) because sulfate reducers deplete hydrogen concentrations and make hydrogenotrophic methanogenesis exergonic in the reverse direction, a process called the anaerobic oxidation of methane (AOM). Microbial participation in these processes is often inferred from geochemistry, genes, and gene expression changes with sediment depth, using sedimentation rates to convert depth to time. Less is known about how natural sediments transition through these geochemical states transition in real-time. We examined 16S rRNA gene amplicon libraries and metatranscriptomes in microcosms of anoxic sediment from the White Oak River estuary, NC, with three destructively sampled replicates with methane added (586-day incubations) and three re-sampled un-amended replicates (895-day incubations). Sulfate dropped to a low value (∼0.3 mM) on similar days for both experiments (312 and 320 days, respectively), followed by a peak in hydrogen, intermittent increases in methane-cycling archaea starting on days 375 and 362 (mostly Methanolinea spp. and Methanosaeta spp., and Methanococcoides sp. ANME-3), and a methane peak 1 month later. However, methane δ 13 C values only show net methanogenesis 6 months after methane-cycling archaea increase and 4 months after the methane peak, when sulfate is consistently below 0.1 mM and hydrogen increases to a stable 0.61 ± 0.13 nM (days 553–586, n = 9). Sulfate-reducing bacteria (mostly Desulfatiglans spp. and Desulfosarcina sp. SEEP-SRB1) increase in relative abundance only during this period of net methane production, suggesting syntrophy with methanogens in the absence of sulfate. The transition from sulfate reduction to methane production in marine sediments occurs through a prolonged period of methane-cycling by methanogens at low sulfate concentrations, and steady growth of sulfate reducers along with methanogens after sulfate is depleted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The gallium solar neutrino capture cross section revisited

Solar neutrino flux constraints from the legacy GALLEX/GNO and SAGE experiments continue to influence contemporary global analyses of neutrino properties. The constraints depend on the neutrino absorption cross sections for various solar sources. Following recent work updating the 51 Cr and 37 Ar neutrino source cross sections, we reevaluate the 71 Ga solar neutrino cross sections, focusing on contributions from transitions to 71 Ge excited states, but also revising the ground-state transition to take into account new 71 Ge electron-capture lifetime measurements and various theory corrections. The excited-state contributions have been traditionally taken from forward-angle (𝑝, 𝑛) cross sections. Here we correct this procedure for the ≈ 10%–20% tensor operator contribution that alters the relationship between Gamow-Teller and (𝑝, 𝑛) transition strengths. Using state-of-the-art nuclear shell-model calculations to evaluate this correction, we find that it lowers the 8 B and hep neutrino cross sections. However, the addition of other corrections, including contributions from near-threshold continuum states that radiatively decay, leads to an overall increase in the 8 B and hep cross sections of ≈ 10% relative to the values recommended by Bahcall. Uncertainties are propagated using Monte Carlo simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

System risk quantification and decision making support using functional modeling and dynamic Bayesian network

Risk-informed decision-making requires a probabilistic assessment of the likelihood of success of control action, given the system status. This paper presents a systematic state transition modeling approach integrating dynamic probabilistic risk assessment with a decision-making process using a dynamic Bayesian network (DBN) coupled with functional modeling. A functional model designed with multilevel flow modeling (MFM) technique was used to build a system state structure inferred by energy, mass, and information flow so that one can verify the developed model with respect to system functionality. The MFM model represents the causal relationship among the nodes, which captures the structure of process parameters and control units. Each node may have multiple possible states, and the DBN structured by the MFM model represents the time-domain transitions among the defined states. Furthermore, the MFM-DBN integrated state transition modeling is a white-box approach that allows one to draw the system's risk profile by updating the system states and supports the decisions probabilistically with physical inference. An example of a simple heating system has been used to illustrate this process, including decision-making support based on quantitative risk profile. For demonstrating its applicability to a complex system operational decision making, a case study of station blackout accident scenario leading to the seal loss of coolant accident in a nuclear power plant is presented. The proposed approach effectively provided the risk profile along time for each option so that the operators can make the best decision, which minimizes the plant risk.

42 ENGINEERING↗
DOE OSTI2024

Shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Abstract Root nodule symbiosis (RNS) is a complex trait that enables plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. Pinpointing the evolutionary origins of RNS is critical for understanding its genetic basis, but building this evolutionary context is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for the NFC and an RNS trait database to reconstruct the evolution of RNS. Our analysis identifies evolutionary rate heterogeneity associated with a two-step process: An ancestral precursor state transitioned to a more labile state from which RNS was rapidly gained at multiple points in the NFC. We illustrate how a two-step process could explain multiple independent gains and losses of RNS, contrary to recent hypotheses suggesting one gain and numerous losses, and suggest a broader phylogenetic and genetic scope may be required for genome-phenome mapping.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

New measurement of the E c.m . = 323 keV resonance in the 19 F(p,γ) 20 Ne reaction

At temperatures below 0.1 GK, the 19 F(p, γ) 20 Ne reaction is the only breakout path out of the CNO cycle. Experimental studies of this reaction are challenging from a technical perspective due to copious γ -ray background from the far stronger 19 F(p, α) 16 O reaction channel. Here, we present the first inverse kinematics study of the 19 F(p, γ) 20 Ne reaction, in which we measure the strength of the 323-keV resonance. We find a strength value of ωγ = $3.3$$^{+1.1}_{–0.9}$ meV, which is a factor of two larger than the most recent previous study. Here, the discrepancy is likely the result of a direct to ground state transition which previous studies were not sensitive to. We also observe the transition to the first 2 – state, which has not been observed for this resonance in previous studies. A new thermonuclear reaction rate is calculated and compared with the literature.

20 ≤ A ≤ 38↗
DOE OSTI2023

Concepts Relevant for the Kinetic Analysis of Reversible Reaction Systems

The net rate of a reversible chemical reaction is the difference between unidirectional rates of traversal along forward and reverse reaction paths. In a multistep reaction sequence, the forward and reverse trajectories, in general, are not the microscopic reverse of one another; rather, each unidirectional route is comprised of distinct rate-controlling steps, intermediates, and transition states. Consequently, traditional descriptors of rate (e.g., reaction orders) do not reflect intrinsic kinetic information but instead conflate unidirectional contributions determined by (i) the microscopic occurrence of forward/reverse reactions (i.e., unidirectional kinetics) and (ii) the reversibility of reaction (i.e., nonequilibrium thermodynamics). This review aims to provide a comprehensive resource of analytical and conceptual tools which deconvolute the contributions of reaction kinetics and thermodynamics to disambiguate unidirectional reaction trajectories and precisely identify rate- and reversibility-controlling molecular species and steps in reversible reaction systems. The extrication of mechanistic and kinetic information from bidirectional reactions is accomplished through equation-based formalisms (e.g., De Donder relations) grounded in principles of thermodynamics and interpreted in the context of theories of chemical kinetics developed in the past 25 years. Here, the aggregate of mathematical formalisms detailed herein is general to thermochemical and electrochemical reactions and encapsulates a diverse body of scientific literature encompassing chemical physics, thermodynamics, chemical kinetics, catalysis, and kinetic modeling.

42 ENGINEERING↗
DOE OSTI2024

Analysis of differential scanning calorimetry data for aged plutonium

Differential scanning calorimetry data for samples of a 52 year old plutonium alloy with 3.3 at. % Ga that were heated beyond the melting point is analyzed using transition state theory to find activation energies for the δ to ε and ε to liquid phase transitions. A Bayesian statistical method involving a Gaussian process model is used to find mean values and confidence intervals for the activation energies. The activation energy for the δ to ε phase transition increases by 3.3 ± 3.8% per decade, relative to the case when all age related plutonium lattice point defects have been removed through annealing. The corresponding increase in activation energy for the ε to liquid transition is shown to be 7.1 ± 1.8% per decade. It is postulated that the change in activation energy with age for both phase transitions is caused, in part, by the accumulation of the same type of lattice point defects associated with the observed increase in elastic bulk modulus over time.

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

Infrared spectroscopic signature of a hydroperoxyalkyl radical (•QOOH)

Infrared (IR) action spectroscopy is utilized to characterize a prototypical carbon-centered hydroperoxyalkyl radical (•QOOH) transiently formed in the oxidation of volatile organic compounds. The •QOOH radical formed in isobutane oxidation, 2-hydroperoxy-2-methylprop-1-yl, •CH 2 (CH 3 ) 2 COOH, is generated in the laboratory by H-atom abstraction from tert-butyl hydroperoxide (TBHP). IR spectral features of jet-cooled and stabilized •QOOH radicals are observed from 2950 to 7050 cm –1 at energies that lie below and above the transition state barrier leading to OH radical and cyclic ether products. The observed •QOOH features include overtone OH and CH stretch transitions, combination bands involving OH or CH stretch and a lower frequency mode, and fundamental OH and CH stretch transitions. Most features arise from a single vibrational transition with band contours well simulated at a rotational temperature of 10 K. In each case, the OH products resulting from unimolecular decay of vibrationally activated •QOOH are detected by UV laser-induced fluorescence. Assignments of observed •QOOH IR transitions are guided by anharmonic frequencies computed using second order vibrational perturbation theory, a 2 + 1 model that focuses on the coupling of the OH stretch with two low-frequency torsions, as well as recently predicted statistical •QOOH unimolecular decay rates that include heavy-atom tunneling. Most of the observed vibrational transitions of •QOOH are readily distinguished from those of the TBHP precursor. Furthermore, the distinctive IR transitions of •QOOH, including the strong fundamental OH stretch, provide a general means for detection of •QOOH under controlled laboratory and real-world conditions.

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

High-resolution CH stretch spectroscopy of jet-cooled cyclopentyl radical: First insights into equilibrium structure, out-of-plane puckering, and IVR dynamics

First, high-resolution sub-Doppler infrared spectroscopic results for cyclopentyl radical (C 5 H 9 ) are reported on the α-CH stretch fundamental with suppression of spectral congestion achieved by adiabatic cooling to T rot ≈ 19(4) K in a slit jet expansion. Surprisingly, cyclopentyl radical exhibits a rotationally assignable infrared spectrum, despite 3N – 6 = 36 vibrational modes and an upper vibrational state density (ρ ≈ 40–90 #/cm –1 ) in the critical regime (ρ ≈ 100 #/cm –1 ) necessary for onset of intramolecular vibrational relaxation (IVR) dynamics. Such high-resolution data for cyclopentyl radical permit detailed fits to a rigid-rotor asymmetric top Hamiltonian, initial structural information for ground and vibrationally excited states, and opportunities for detailed comparison with theoretical predictions. Specifically, high level ab initio calculations at the coupled-cluster singles, doubles, and perturbative triples (CCSD(T))/ANO0, 1 level are used to calculate an out-of-plane bending potential, which reveals a C 2 symmetry double minimum 1D energy surface over a C 2v transition state. Here, the inversion barrier [V barrier ≈ 3.7(1) kcal/mol] is much larger than the effective moment of inertia for out-of-plane bending, resulting in localization of the cyclopentyl wavefunction near its C 2 symmetry equilibrium geometry and tunneling splittings for the ground state too small (<1 MHz) to be resolved under sub-Doppler slit jet conditions. The persistence of fully resolved high-resolution infrared spectroscopy for such large cyclic polyatomic radicals at high vibrational state densities suggests a “deceleration” of IVR for a cycloalkane ring topology, much as low frequency torsion/methyl rotation degrees of freedom have demonstrated a corresponding “acceleration” of IVR processes in linear hydrocarbons.

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

Enhanced Sampling of Crystal Nucleation with Graph Representation Learnt Variables

In this study, we present a graph neural network-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures. These variables are then biased in enhanced sampling to observe state-to-state transitions and reliable thermodynamic weights. Our approach uses simple convolution and pooling methods. To verify the effectiveness of our protocol, we examined the nucleation of various allotropes and polymorphs of iron and glycine from their molten states. Our graph latent variables when biased in well-tempered metadynamics consistently show transitions between states and achieve accurate free energy calculations in agreement with experiments, both of which are indicators of dependable sampling. This underscores the strength and promise of our graph neural net variables for improved sampling. Furthermore, the protocol shown here should be applicable for other systems and with other sampling methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗