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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The landscape of disc outflows from black hole–neutron star mergers

ABSTRACT We investigate mass ejection from accretion discs formed in mergers of black holes (BHs) and neutron stars (NSs). The third observing run of the LIGO/Virgo interferometers provided BH–NS candidate events that yielded no electromagnetic (EM) counterparts. The broad range of disc configurations expected from BH–NS mergers motivates a thorough exploration of parameter space to improve EM signal predictions. Here we conduct 27 high-resolution, axisymmetric, long-term hydrodynamic simulations of the viscous evolution of BH accretion discs that include neutrino emission/absorption effects and post-processing with a nuclear reaction network. In the absence of magnetic fields, these simulations provide a lower limit to the fraction of the initial disc mass ejected. We find a nearly linear inverse dependence of this fraction on disc compactness (BH mass over initial disc radius). The dependence is related to the fraction of the disc mass accreted before the ouflow is launched, which depends on the disc position relative to the innermost stable circular orbit. We also characterize a trend of decreasing ejected fraction and decreasing lanthanide/actinide content with increasing disc mass at fixed BH mass. This trend results from a longer time to reach weak freezout and an increasingly dominant role of neutrino absorption at higher disc masses. We estimate the radioactive luminosity from the disc outflow alone available to power kilonovae over the range of configurations studied, finding a spread of two orders of magnitude. For most of the BH–NS parameter space, the disc outflow contribution is well below the kilonova mass upper limits for GW190814.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

r -process nucleosynthesis and kilonovae from hypermassive neutron star post-merger remnants

ABSTRACT We investigate r-process nucleosynthesis and kilonova emission resulting from binary neutron star (BNS) mergers based on a three-dimensional (3D) general-relativistic magnetohydrodynamic (GRMHD) simulation of a hypermassive neutron star (HMNS) remnant. The simulation includes a microphysical finite-temperature equation of state (EOS) and neutrino emission and absorption effects via a leakage scheme. We track the thermodynamic properties of the ejecta using Lagrangian tracer particles and determine its composition using the nuclear reaction network SkyNet. We investigate the impact of neutrinos on the nucleosynthetic yields by varying the neutrino luminosities during post-processing. The ejecta show a broad distribution with respect to their electron fraction Ye, peaking between ∼0.25–0.4 depending on the neutrino luminosity employed. We find that the resulting r-process abundance patterns differ from solar, with no significant production of material beyond the second r-process peak when using luminosities recorded by the tracer particles. We also map the HMNS outflows to the radiation hydrodynamics code SNEC and predict the evolution of the bolometric luminosity as well as broadband light curves of the kilonova. The bolometric light curve peaks on the timescale of a day and the brightest emission is seen in the infrared bands. This is the first direct calculation of the r-process yields and kilonova signal expected from HMNS winds based on 3D GRMHD simulations. For longer-lived remnants, these winds may be the dominant ejecta component producing the kilonova emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Systematic exploration of heavy element nucleosynthesis in protomagnetar outflows

ABSTRACT We study the nucleosynthesis products in neutrino-driven winds from rapidly rotating, highly magnetized and misaligned protomagnetars using the nuclear reaction network SkyNet. We adopt a semi-analytic parametrized model for the protomagnetar and systematically study the capabilities of its neutrino-driven wind for synthesizing nuclei and eventually producing ultra-high energy cosmic rays (UHECRs). We find that for neutron-rich outflows (Ye < 0.5), synthesis of heavy elements ($\overline{A}\sim 20-65$) is possible during the first $\sim 10\, {\rm s}$ of the outflow, but these nuclei are subjected to composition-altering photodisintegration during the epoch of particle acceleration at the dissipation radii. However, after the first $\sim 10\, {\rm s}$ of the outflow, nucleosynthesis reaches lighter elements ($\overline{A}\sim 10-50$) that are not subjected to subsequent photodisintegration. For proton-rich (Ye ≥ 0.5) outflows, synthesis is more limited ($\overline{A}\sim 4-15$). These suggest that while protomagnetars typically do not synthesize nuclei heavier than second r-process peak elements, they are intriguing sources of intermediate/heavy mass UHECRs. For all configurations, the most rapidly rotating protomagnetars are more conducive for nucleosynthesis with a weaker dependence on the magnetic field strength.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Gamma-ray signatures of 𝑟-process radioactivity from the collapse of magnetized white dwarfs

We predict the gamma-ray line emission from 𝑟-process nuclei synthesized in the ejecta of the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf. Using ejecta from a two-dimensional general-relativistic neutrino-magnetohydrodynamic simulation, further evolved with a radiation-hydrodynamics code coupled to an in situ nuclear reaction network, we construct angle-dependent gamma-ray spectra in the 0.01–10 MeV band via composition-dependent ray tracing through the ejecta. The emission between ∼1 and 10 d is dominated by 132 I (𝑡 1/2 = 2.3 h), continuously replenished by the decay of its parent 132 Te (𝑡 1/2 = 3.2 d), with additional contributions from 131 I, 133 Xe, and 132 Te . At 𝑡 ≳ 20 d, 56 Co (from 56 Ni decay) becomes the primary emitter. The simultaneous presence of 𝑟 process and iron-peak gamma-ray lines is distinctive of AIC ejecta and absent in binary neutron star mergers, where iron-peak nuclei are generally not synthesized. Comparing with the 3⁢𝜎 continuum sensitivities of planned MeV gamma-ray telescopes (COSI, AMEGO-X, e-ASTROGAM, GRAMS, GammaTPC), we find the brightest 𝑟-process lines detectable to ∼10 Mpc by GammaTPC and GRAMS, with the signal approaching their sensitivity threshold at 30 Mpc. As a result, the 𝑟-process spectral features survive time integration over ∼30 d exposures, demonstrating robustness against the long observation times required by gamma-ray detectors.

Nuclear reactions↗
DOE OSTI2024

Summary Report of the Technical Meeting on International Network of Nuclear Reaction Data Centres IAEA Headquarters, Vienna, Austria

This report summarizes the IAEA Technical Meeting on the International Network of Nuclear Reaction Data Centres held at the IAEA Headquarters in Vienna, Austria from 14 to 17 May 2024. The meeting was attended by 26 participants representing 13 cooperative Centres from eight Member States (China, Hungary, India, Japan, Korea, Russia, Ukraine and USA) and two International Organisations (NEA, IAEA). A summary of the meeting is given in this report along with the conclusions and actions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Heavy Elements and Electromagnetic Transients from Neutron Star Mergers

Compact binary mergers involving neutron stars can eject a fraction of their mass to space. Being extremely neutron rich, this material undergoes rapid neutron capture nucleosynthesis, and the resulting radioactivity powers fast, short-lived electromagnetic transients known as kilonova or macronova. Such transients are exciting probes of the most extreme physical conditions and their observation signals the enrichment of the Universe with heavy elements. Here the current understanding of the mass ejection mechanisms, the properties of the ejecta, and the resulting radioactive transients are reviewed. The first well-observed event in the aftermath of GW170817 delivered a wealth of insights, but much of today's picture of such events is still based on a patchwork of theoretical studies. Apart from summarizing the current understanding, questions where no consensus has been reached yet are also pointed out, and possible directions for the future research are sketched. In an appendix, a publicly available heating rate library based on the WinNet nuclear reaction network is described, and a simple fit formula to alleviate the implementation in hydrodynamic simulations is provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Catalytic Activation of Polyethylene Model Compounds Over Metal-Exchanged Beta Zeolites

Decomposition of polymers by heterogeneous catalysts presents a promising approach for reuse of waste plastics. Here, we demonstrated non-hydrogenative decomposition of model polyolefins over proton-form and metal (Cu, Ni) ion-exchanged beta zeolites at moderate temperatures (ca. 300 degrees C). Near complete polyolefin decomposition was observed in batch reactions monitored by thermogravimetric analysis, while decomposition at partial conversion was studied in flow reactions. Ni-exchanged zeolites produced H 2 at substantially higher rates (> 10x) than other catalysts while also uniquely resisting deactivation over time. Application of the delplot formalism offered insights into the reaction network for polyolefin decomposition over Ni/BEA, most notably that H 2 is solely a primary product. We deduce that H 2 production is catalyzed by activation of C-H bonds at ionic Ni sites, and H 2 prevents buildup of polyaromatic coke species in Ni-exchanged zeolites that deactivate Cu-exchanged and protonic zeolites.

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

Tailoring olefin distribution via tuning rare earth metals in bifunctional Cu-RE/beta-zeolite catalysts for ethanol upgrading

Bioethanol to middle distillate technologies have offered a unique solution to produce renewable aviation fuel for decarbonizing the hard-to-electrify sectors. Here, we have developed the series of bimetallic Cu- and rare earth-containing (RE) Beta zeolite catalysts that yield high C 3+ alkene selectivity from ethanol upgrading (>80% selectivity at ~100% conversion, 623 K). The formation rates of butene isomers to C 5+ alkenes are linearly correlated with the strength of Lewis acidic RE identity, which follows the sequence of Yb 12 /Beta >Y 7 /Beta > Gd 12 /Beta > Ce 10 /Beta > La 12 /Beta. Rate measurements indicate that the RE selection plays the vital role in altering the rate of the key competitive reactions within the ethanol-to-alkenes reaction network, namely C 4 alcohol dehydration and C-C chain growth, which dictate alkene product distributions. Finally, these findings indicate a feasible and promising method for tailoring alkene product distributions from ethanol upgrading, which is of notable significance to the generation of renewable middle distillates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Selective oxidation of 3-hydroxypropionic acid to malonic acid over Pd/C: Mechanistic and kinetic study

Malonic acid (MA) is a high-value dicarboxylic acid with strong industrial demand, yet its current production heavily relies on petrochemical feedstocks. Here, we report the first systematic study for sustainable production of MA via oxidation of 3-hydroxypropionic acid (3-HP) with a Pd/Carbon catalyst. The effects of oxidant type (O 2 and H 2 O 2 ), pH, and temperature on the reaction chemistry were comprehensively evaluated. Guided by experimental observation and DFT-calculated thermochemical energetics, reaction networks for 3-HP oxidation with both oxidants are proposed and validated through kinetic modeling. MA was identified as the primary oxidation product, while further oxidation yields acetic acid and oxalic acid. The kinetic model validated the network, displaying excellent agreement (R 2 > 0.95). Kinetic observations also enabled a direct comparison between O 2 and H 2 O 2 and revealed their distinct behaviors. The model was further developed into a temperature-time map, providing insight into conditions that maximize MA production. Malonic acid selectivity of 56.9 % and yield of 50.5 % were achieved at 3 bar oxygen, equimolar NaOH:3-HP ratio, and 50 °C.

3-hydroxypropionic acid↗
DOE OSTI2023

Theoretical assessments of CO 2 activation and hydrogenation pathways on transition-metal surfaces

Carbon dioxide (CO 2 ) hydrogenation on transition-metal active sites offers a promising carbon utilization route toward mitigating greenhouse gas emissions. C 1 products are often formed in parallel during CO 2 hydrogenation, prompting investigations into the intrinsic properties of transition metals that drive activity and product selectivity. Here, in this work, close-packed surfaces of a selection of transition-metal catalysts (Ni, Co, Rh, Ru, Pd, and Pt) were studied with density functional theory (DFT) calculations to understand their fundamental reactivities for CO 2 transformation reactions. Results indicate that CO 2 conversion proceeds through CO* formation and hydrogenation to form C 1 products (* denotes an adsorbed species). Ni, Co, Rh, and Ru favor CO/CH 4 formation, while Pd and Pt favor CO/CH 3 OH formation. The ability of a metal to dissociate C-O bonds drives selectivity between CH 4 and CH 3 OH, while competition between CO* desorption and surface hydrogenation describes CO selectivities. The C-O bond dissociation steps often impose the highest barrier along CH 4 formation reaction profiles, suggesting their kinetic relevance for CH 4 formation rates. The provided DFT-derived data sets detail a comprehensive reaction network of elementary steps relevant to C 1 chemistries, ultimately offering a benchmark for insights into design strategies for materials that exploit transition-metal active sites in carbon capture or utilization processes.

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

Accuracy of predictions made by machine learned models for biocrude yields obtained from hydrothermal liquefaction of organic wastes

Hydrothermal liquefaction (HTL) has potential for converting abundant wet organic wastes into renewable fuels. Because HTL consists of a complex reaction network, deterministic, physics-based prediction of its biocrude yield is prohibitively difficult. Data-driven methods provide an alternative to the physics-based approach; however, rigorous testing must be performed to ensure the accuracy of predictions made by data-driven methods. To this end, a data set was assembled consisting of 570 data points appearing in the open literature. The data set was divided into training, validation, and test sub-sets and used for evaluating different machine learning regression approaches to predict biocrude yield. Among the tested algorithms, Random Forest and eXtreme Gradient Boosting (XGBoost) predicted biocrude yields in a test set that had not been used for training with the greatest accuracy, with root mean square errors (RMSE) of 8.34 and 8.57, respectively. Further refinement of the Random Forest model reduced its RMSE to 8.07. In comparison, predictions of a series of literature models resulted in RMSE ranging from 9.16 in the most accurate case to 27.6 in the least accurate; most literature models yielded RMSE values > 10. Using biocrude yield predictions from the most accurate Random Forest model and a probabilistic economic analysis found that the model accuracy is sufficient to prioritize allocation of resources based on projected minimum fuel selling price. In our report the models and analysis represent a major advance in the ability to use readily available data to predict biocrude yields on new feedstocks that have not previously been studied.

42 ENGINEERING↗
DOE OSTI2025

Degrees of rate control and AutoDiff-driven direct sensitivity analysis in heterogeneous catalysis

Despite the wide application and benefits of the degree of rate control (DRC) analysis, several details remain argued, particularly about the conservation of DRCs at transient (TR) and steady-state (SS) conditions, especially for complex reaction networks. This work argues that previous proofs about the conservation properties of DRCs have been incomplete, and we provide new mathematical proofs at TR and SS conditions. In addition, we use both analytical (automatic differentiation) and numerical (finite difference) approaches to compute DRCs for the case study of ethane hydrogenolysis (EH) over Pt(111). This work confirms that at both TR and SS conditions, the sum of all DRCs, i.e., sum of the degrees of kinetic (DKRC) and thermodynamic rate control (DTRC), is conserved at zero. At SS conditions, the sum of DKRC is conserved at 1 while the sum of DTRC is conserved at −1. In corroboration of previous works, we show that the DTRC for any adsorbate at SS is equal to the product of the species coverage and a constant. In contrast, at TR conditions, the individual sums of both DTRC and DKRC are not conserved and can be any real number, with potential implications for the novel field of dynamic catalysis. Finally, we show that the conventional finite difference (FD) approach, only useful at SS, is prone to inaccuracy and very sensitive to the value of the differential change applied. The optimal differential value also varies significantly with system and rate definition. Consequently, we describe and illustrate in this work the application of the automatic differentiation (AD) approach for the more accurate determination of DRCs at both TR and SS conditions.

Automatic differentiation↗
DOE OSTI2023

Balanced Fast-SpaciMS capillary configurations provide practically noninvasive channel-average measurements in catalytic monoliths

Spatially resolved capillary-inlet mass spectrometry (SpaciMS) provides a detailed picture of the spatiotemporal evolution of reaction network in catalytic monoliths. In the present work, we combine the SpaciMS experiments with a newly developed non-isothermal 3D CFD model for heterogeneously catalyzed reactive flows, including diffusion and permeation through the coated catalyst and channel wall. We explore how the capillary size and sampling rate can be balanced to minimize the impact on probed-channel conversions and provide species concentration measurements representative of the free channel average. In all studied configurations, the balanced sampling-rate fraction is noticeably higher than the corresponding capillary occlusion fraction. For a typical 350-micron capillary that occupies 11% of the channel cross- section, the balanced sampling rate represents 43% of the channel flow. Furthermore, the present work shows that together, a balanced SpaciMS configuration and numerical simulation provide accurate channel-averaged information of a monolithic catalyst under realistic operation conditions.

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

Recent progress toward catalyst properties, performance, and prediction with data-driven methods

Herein, data-driven approaches are currently renovating the field of heterogenous catalysis and open a door to advance catalyst design. Their success depends heavily on the synergy among machine learning (ML), experimental data, and quantum mechanical (QM) calculations. In this brief survey of recent progress, we examine catalysis informatics in the context of (1) ML-aided catalyst characterizations, (2) knowledge extractions from experimental data, (3) predictions of catalytic properties and constructions of reaction networks, and (4) ML-enabled large-scale QM simulations. An outlook on the current challenges of this rapidly evolving field is also provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cool flame chemistry of diesel surrogate compounds: n -Decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane

Elucidating the formation of combustion intermediates is crucial to validate reaction pathways, develop reaction mechanisms and examine kinetic modeling predictions. While high-temperature pyrolysis and oxidation intermediates of alkanes have been thoroughly studied, comprehensive analysis of cool flame intermediates from alkane autoxidation is lacking and challenging due to the complexity of intermediate species produced. Here, jet-stirred reactor autoxidation of four C 10 alkanes: n -decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane, as model compounds of diesel fuel, was investigated from 500 to 630 K using synchrotron vacuum ultraviolet photoionization molecular beam mass spectrometry (SVUV-PIMS). Around 100 intermediates were detected for each fuel. The classes of molecular structures present during the autoxidation of the representative paraffinic functional groups in transport fuels, i.e., n -alkanes, branched alkanes, and cycloalkanes were established and were found to be similar from the oxidation of various alkanes. A theoretical approach was applied to estimate the photoionization cross sections of the intermediates with the same carbon skeleton as the reactants, e.g., alkene, alkenyl keto, cyclic ether, dione, keto-hydroperoxide, diketo-hydroperoxide, and keto-dihydroperoxide. These species are indicators of the first, second, and third O 2 addition reactions for the four C 10 hydrocarbons, as well as bimolecular reactions involving keto-hydroperoxides. Chemical kinetic models for the oxidation of these four fuels were examined by comparison against mole fraction of the reactants and final products obtained in additional experiments using gas chromatography analysis, as well as the detailed species pool and mole fractions of aforementioned seven types of intermediates measured by SVUV-PIMS. This works reveals that the models in the literature need to be improved, not only the prediction of the fuel reactivity and final products, but also the reaction network to predict the formation of many previous undetected intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A kinetic model for simulating non-equilibrium mass transport in oxides applied to hematite growth under irradiation

We propose an approach to simulating the dynamic evolution and transport of charged point defects within and through the oxide scales that form during corrosion. The method follows the cluster dynamics formalism widely adopted for radiation damage in solids, which can apply in both quasi-static and far from equilibrium conditions, such as in radiation environments. By treating each charged defect as a cluster of an atomic defect and associated unit charges, the proposed model flexibly allows charge state transitions and shifts in the Fermi level by absorption and emission of charge carriers from point defects in a reaction network with rates constrained by local equilibrium. Applying this model to hematite predicts changes in self-diffusion and oxidation kinetics in irradiation environments, surprisingly showing reduced oxidation rates in many conditions, despite enhanced self-diffusion. In conclusion, the origin of this effect lies in a change in Fermi level induced by excess vacancies formed under irradiation, which in turn suppresses the transport of cation interstitials which facilitate hematite growth.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Performance of biochar assisted catalysts during hydroprocessing of non-edible vegetable oil: Effect of transition metal source on catalytic activity

Biochar-supported catalysts were developed from nickel (Ni) - and cobalt (Co)- nitrates and hydroxides and tested for the hydrotreatment of carinata oil. Nitrate-based (from water-soluble salts) and hydroxide-based (from water-insoluble salts) catalysts of Ni and Co were prepared via wetness impregnation and aqueous dispersion methods, respectively. The catalysts were characterized using various tools such as, confocal XRF, BET specific surface area analyzer, NH3-TPD, and SEM-EDS. Synchroton method showed nitrate-sourced metals were dispersed mostly in the pores while, the hydroxide-sourced metals were distributed mainly on the catalyst surface. C = C saturation and cracking of triglycerides, decarboxylation, and hydrogenation of aromatic structures appeared to be dominant on the hydroxides of transition metals, hence took place on catalyst surface. Methanation and dehydrogenation (thus aromatization), however, seemed to be a pore phenomenon, catalyzed more over nitrate-based catalysts. A reaction network was proposed based on chemical analysis of upgraded carinata oil and erucic acid model compound. Catalytic cracking followed by hydrotreatment performed better in terms of fuel properties than other approaches in this study.

Biochar catalysts↗