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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

First-Principles Framework for the Prediction of Intersystem Crossing Rates in Spin Defects: The Role of Electron Correlation

Optically active spin defects in solids are promising platforms for quantum technologies. In this work, we present a first-principles framework to investigate intersystem crossing processes, which represent crucial steps in the optical spin-polarization cycle used to address spin defects. Considering the nitrogen-vacancy center in diamond as a case study, we demonstrate that our framework effectively captures electron correlation effects in the calculation of many-body electronic states and their spin-orbit coupling and electron-phonon interactions, while systematically addressing finite-size effects. We validate our predictions by carrying out measurements of fluorescence lifetimes, finding excellent agreement between theory and experiments. The framework presented here provides a versatile and robust tool for exploring the optical cycle of varied spin defects entirely from first principles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Preliminary System Interface Failure Mode Analysis for Two Advanced Reactors

This study explores two distinct Balance of Plant (BOP) configurations: the Rankine cycle for a sodium-cooled fast reactor (SFR) and the Brayton cycle for a gas-cooled reactor (GCR). As representative designs, the Power Reactor Innovative Small Module (PRISM) by GE Hitachi Nuclear Energy was selected for the SFR, while the Gas Turbine Modular Helium Reactor (GT MHR) by General Atomics was chosen for the gas-cooled reactor. Both configurations were adapted to deliver high-quality heat for industrial applications. A Failure Modes and Effects Analysis (FMEA) was conducted for each system to identify critical failure modes affecting key components. This study marks the first phase of a two-step design optimization approach, integrating FMEA into the design process. Based on the analysis, design modifications and mitigation strategies were proposed to enhance system resilience. The second phase, to be detailed in a subsequent report, will focus on the role of the control system in mitigating these failures. The FMEA serves as a foundation for defining the control topology, ensuring system resilience against component failures that could compromise essential functions, such as electricity and heat production.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

High-frequency Data Integration for Landscape Model Calibration of Carbon Fluxes Across Diverse Tidal Marshes

Terrestrial Aquatic Interfaces (TAIs), and tidal wetlands in particular, store large amounts of carbon yet are not well represented in Earth System Models (ESMs). Predictions of carbon cycling and greenhouse gas (GHG) emissions in tidal wetlands are highly uncertain. Eddy covariance (EC) towers provide ecosystem-scale GHG flux data at a temporal resolution (every 30min) that is helpful for parameterizing and improving mechanistic realism in ESMs. We propose to use a network of eddy covariance towers and standardized ancillary data streams, along with mesocosm experiments and statistical analyses, across diverse tidal wetlands of North America to develop and improve biogeochemical modeling at the TAI. Our overarching objective is to improve understanding and process-based modeling of gross primary productivity (GPP) and CH4 emission responses, both non-linear and asynchronous, to stressors including plant inundation, disturbance, salinity and nitrogen loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ZPRD Database: ZPPR-15 Monte Carlo Results

The ZPPR-15 experiments [1] were mockups of a 330 MWe Integral Fast Reactor (IFR). The ZPPR-15 assembly consisted of a clean, two zone, approximately circular core surrounded by a thin depleted uranium (DU) blanket with sodium (Na) cooling and a thick stainless steel reflector. The ZPPR-15 program was conducted in four phases: A, B, C, and D. Each phase was marked by a particular composition of the reference assembly, with the last three being representative of the three stages of the IFR fuel cycle. This report documents all MCNP [2] runs of the ZPPR-15 loadings that were included in the ZPRD database on GitLab. In the present work, eigenvalues and associated standard deviations were computed for each ZPPR-15 loading with the use of the three data libraries (ENDF/B-VII.0 [3], ENDF/B-VII.1 [4] and ENDF/B-VIII.0 [5]). Relevant results from the obtained outputs are also discussed in this report with two main objectives: a) provide and evaluate updated calculated values with respect to previous reports, notably Refs. [6] and [7] that were based on the use of the ENDF/B-VII.0 library. b) address any change in the observed reactivity effects relevant to the analysis of the experimental data when a different data library is used (previously reported results were mostly based on the use of ENDF/B-VII.0 data only).

Aliberti, Gerardo↗
DOE OSTI2022

XMM and NuSTAR Observations of an Optically Quiescent Quasar

Optically quiescent quasars (OQQs) represent a recently systematized class of infrared-luminous active galactic nuclei (AGNs) that have galaxy-like optical continua. They may represent an interesting, brief phase in the AGN life cycle, e.g., either cocooned within high-covering-factor media or indicative of recent triggering, though their nature remains unclear. Here, we present the first targeted simultaneous X-ray observations of an OQQ, our previously identified prototype, SDSS J075139.06+402811.2 at z = 0.587. The source is significantly detected over 0.5–16 keV with XMM-Newton and NuSTAR, unambiguously confirming the presence of current accretion activity. Spectral modeling yields an intrinsic luminosity L 2–10 keV ≈ 4.4 × 10 43 erg s -1 , well within the AGN regime, but underluminous relative to its infrared power. It is lightly obscured, with log N H [cm -2 ] ≈ 22.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Application of sensitivity analysis in DYMOND/Dakota to fuel cycle transition scenarios

The ability to perform sensitivity analysis has been enabled for the nuclear fuel cycle simulator DYMOND through its coupling with the design and analysis toolkit Dakota. To test and demonstrate these new capabilities, a transition scenario and multi-parameter study were devised. The transition scenario represents a partial transition from the US nuclear fleet to a closed fuel cycle with small modular LWRs and fast reactors fueled by reprocessed used nuclear fuel. Four uncertain parameters in this transition were studied – start date of reprocessing, total reprocessing capacity, the nuclear energy demand growth, and the rate at which the fast reactors are deployed – with respect to their impact on four response metrics. The responses – total natural uranium consumed, maximum annual enrichment capacity required, total disposed mass, and total cost of the nuclear fuel cycle – were chosen based on measures known to be of interest in transition scenarios and to be significantly impacted by the varying parameters. Furthermore, analysis of this study was performed both from the direct sampling and through surrogate models developed in Dakota to calculate the global sensitivity measures Sobol’ indices. This example application of this new capability showed that the most consequential parameter to most metrics was the share of new build capacity that is fast reactors. However, for the cost metric, the scaling factor of the energy demand growth was significant and had synergistic behavior with the fast reactor new build share.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Techno-economic Analysis and Life-Cycle Analysis of Renewable Diesel Fuels Produced with Waste Feedstocks

Wet waste feedstocks represent an important category of resources that could be utilized to produce biofuels. Diversion of the wet waste resources from going through conventional waste management practices to utilization as feedstocks for energy production also benefits from avoided cost and pollutant emissions of waste management and disposal. This study investigates the economic and environmental implications of producing bio-blendstocks for mixing controlled compression ignition (MCCI) engines from two waste-to-fuel pathways: hydroprocessed esters and fatty acids (HEFA) from yellow grease, and swine manure hydrothermal liquefaction (HTL) followed by biocrude upgrading. Detailed process models were developed for both pathways, which informed the techno-economic analysis (TEA) and life-cycle analysis (LCA). Conventional swine manure management practice was also modeled in detail as the business-as-usual (BAU) scenario for the swine manure HTL pathway. The estimated minimum fuel selling prices (MFSP) were $4.47/gasoline gallon equivalent (GGE) and $3.57/GGE for the yellow grease to HEFA and swine manure HTL pathways, respectively. The life-cycle greenhouse gas (GHG) emissions of the two pathways were 11.2 and -33.3 g CO2e/MJ, respectively, for the yellow grease to HEFA and swine manure HTL pathways. The credits of avoided emissions from conventional swine manure management were the main reason for the negative GHG emissions of the swine manure HTL pathway. The marginal GHG emissions abatement costs were estimated to be $100 – $253/tonne CO2e and $5 – $103/tonne CO2e for the yellow grease HEFA and swine manure HTL pathways, respectively, for a diesel price ranging between $2.0/GGE and $3.5/GGE. Since the yellow grease HEFA pathway is already commercialized, it can benefit from the $200/tonne carbon credit in the California Low Carbon Fuel Standard (LCFS) market, which could help the yellow grease HEFA pathway to achieve near-zero marginal GHG emissions abatement cost.

renewable diesel, techno economic analysis, life c↗
DOE OSTI2024

Uncertainty in determining carbon dioxide removal potential of biochar

A quantitative and systematic assessment of uncertainty in life-cycle assessment is critical to informing sustainable development of carbon dioxide removal (CDR) technologies. Biochar is the most commonly sold form of CDR to date and it can be used in applications ranging from concrete to agricultural soil amendments. Previous analyses of biochar rely on modeled or estimated life-cycle data and suggest a cradle-to-gate range of 0.20–1.3 kg CO 2 net removal per kg of biomass feedstock, with the range reported driven by differences in energy consumption, pyrolysis temperature, and feedstock sourcing. Herein, we quantify the distribution of CDR possible for biochar production with a compositional life-cycle inventory model paired with scenario-aware Monte Carlo simulation in a 'best practice' (incorporating lower transportation distances, high pyrolysis temperatures, high energy efficiency, recapture of energy for drying and pyrolysis energy requirements, and co-generation of heat and electricity) and 'poor practice' (higher transportation distances, lower pyrolysis temperatures, low energy efficiency, natural gas for energy requirements, and no energy recovery) scenarios. In the best-practice scenario, cradle-to-gate CDR (which is representative of the upper limit of removal across the entire life cycle) is highly certain, with a median removal of 1.4 kg of CO 2 e/kg biomass and results in net removal across the entire distribution. In contrast, the poor-practice scenario results in median net emissions of 0.090 kg CO 2 e/kg biomass. Whether this scenario emits (66% likelihood) or removes (34% likelihood) carbon dioxide is highly uncertain. The emission intensity of energy inputs to the pyrolysis process and whether the bio-oil co-product is used as a chemical feedstock or combusted are critical factors impacting the net carbon dioxide emissions of biochar production, together responsible for 98% of the difference between the best- and poor-practice scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tracking the Oxidation of Silicon Anodes Using Cryo-EELS upon Battery Cycling

Silicon is a high-capacity material for the anode of a rechargeable lithium-ion battery. One of the fundamental challenges for using Si in anodes is capacity fading, which has been revealed to be partially associated with the interfacial instability between the Si and liquid electrolyte due to the large volume swing of Si upon charging and discharging. Smart nanoscale design concepts, either pre-synthesized or formed in-situ, have led to the mitigation of the detrimental factors associated with the volume swing of Si. However, it has never been clear as how the chemical state of Si evolves and contributes to the capacity fading upon battery cycling. Here, we use cryo-electron energy loss spectroscopy (EELS) to directly monitor, at sub-nanometer scale, the chemical evolution of Si upon battery cycling. We discover that during the cycling process, Si particles are progressively oxidized to form SiO 2 , which is initiated from the particle surface and gradually penetrates toward the interior of the particle, directly contributing to the capacity fading. Possible mechanisms of Si oxidation are postulated. We further show how the cycling stability can be improved by an electrolyte additive to form an effective passivation layer, representatively, even a small concentration of fluoroethylene carbonate (FEC) causes the formation of an LiF layer on the Si nanoparticle surface that prevents Si oxidation and improves cycling stability. Furthermore, the present work unveils Si oxidation as a previously unrecognized factor that contributes to capacity fading, therefore providing insight into the design of anodes with Si based materials.

25 ENERGY STORAGE↗
DOE OSTI2026

Nuclear Data Impact on Key Metrics for a Representative Molten Chloride Fast Reactor Model

Nuclear data are an essential component of the foundation on which all modeling and simulation methods and tools are relying upon, from the front end to the back end of the nuclear fuel cycle. In this study, the impact of uncertainties in nuclear data is investigated for a representative molten chloride fast reactor, for several important metrics, including eigenvalue, reactivity differences, and nuclide inventories in fuel at 5-yr irradiation. Uncertainty of keff for a full core model was found to be similar between the fresh fuel and the irradiated fuel states (1.7-1.8%), with its primary driver being the uncertainty in the 235U (n,γ) cross section. The results obtained for the reactivity differences show large uncertainties, of over 100%, in elastic scattering sensitivities of several nuclides, which led to large uncertainties of temperature reactivity differences for cladding and reflector. These results provide evidence that the currently applied methods may not be sufficiently adequate for ensuring the reliable determination of such metrics.

Procop, Germina [ORNL] (ORCID:0000000342226393)↗
DOE OSTI2021

Dynamic Simulation of a Sub-Critical Coal Fired Power Plant

In order to address the demanding operating conditions for remaining coal-fired power plants, a dynamic model and a suite of tools have been developed for studying load cycling and to find optimization opportunities. A sub-critical steam cycle power plant was modeled in a flow-sheet modeling tool, APROS™. The model represented the firing system, economizer, evaporator, superheat, and reheat systems. Four loads from 100% TMCR to 25% TMCR were calibrated and tested such that low-to-high cycling could be studied. The model was run through various load cycles; one of which is presented here. This modeling is a prototype for general use in developing cutting edge controls products and for maximizing economic, low-emissions, and efficient operation of the existing coal power fleet.

Braun, Timothy↗
DOE OSTI2026

TES: Modelling Microbes to Predict Post-Fire Carbon Cycling in the Boreal Forest across Burn Severities (Exploratory Proposal)

Wildfires in boreal ecosystems represent a globally significant ecological process that is expected to be sensitive to changing climate as well as forest management strategies, but is currently insufficiently understood and represented in models. We sought to determine whether linking belowground microbial community composition, size, and activity to aboveground properties of burn severity and plant community composition (upland jack pine and upland spruce) would allow us to better model post-fire soil CO 2 fluxes using the Carbon, Organisms, Rhizosphere and Protection in the Soil Environment (CORPSE) model. We used an integrated modelling experimental approach, with mechanistic laboratory experiments designed to inform models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Techno-Economic Analysis of CSP Incorporating sCO2 Brayton Power Cycles: Trade-Off Between Cost and Performance

Concentrating solar power (CSP) plants, thanks to the implementation of cost-competitive thermal energy storage, represent a dispatchable zero-emission alternative to traditional fossil fuel power plants. Next generation solar towers are expected to adopt high temperature receivers (>700 degrees C) coupled to sCO2-based power blocks, which optimal design is generally pushed towards the maximum cycle efficiency, often neglecting the economic impact with the justification that the main share of the capital cost is represented by the heliostat field. As result, the scientific literature lacks in comprehensive studies on techno-economic evaluation of CSP+sCO2 power plants addressing the important correlation that exists between system cost and performances. This work provides a preliminary techno-economic analysis of a solar power tower comparing four different cycle configurations for the sCO2 power block. Results have been reported on a Pareto front, highlighting the tradeoff between the plant investment cost and the solar-to-electricity plant efficiency. The trends of the optimization variables and cycle results have been reported to give useful insights about proper assumptions for the sCO2 power block design. The recompressed cycle with intercooling resulted as the most promising configuration and it has been further analyzed through a comparison of different solutions on the Pareto front. The cost breakdown of the sCO2 power block has been reported to highlight which components have the greatest impact on the overall plant cost and how they vary along the optimal solutions front. Eventually, the optimization has been repeated introducing a correlation to compute the turbomachinery isentropic efficiencies, to investigate their effect on the techno- economic analysis.

concentrated solar power↗
DOE OSTI2022

The Madden–Julian Oscillation in the Energy Exascale Earth System Model Version 1

Abstract The present study examines the characteristics of the Madden–Julian Oscillation (MJO) events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and moist static energy (MSE) anomalies associated with the MJO. As in observations, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MJO MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the precipitation diurnal cycle. On the MJO impact over the midlatitude, E3SMv1 reasonably captures the pattern of the MJO teleconnections across the North Pacific and North America, with improvement in the performance in a high‐resolution version, despite the magnitude being a bit weaker than the observed. Regarding the interannual variability of the MJO, the El Niño‐Southern Oscillation (ENSO) modulation of the zonal extent of MJO’s eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, are well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi‐Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process‐oriented diagnostics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Atmospheric ice nuclei concentration measurements over a high altitude-station in the Western Ghats, India

Mixed-phase and ice clouds play a significant role in modulating the Indian summer monsoon rainfall, and modeling studies suggest that inaccurate representation of ice nucleating particles (INP) is one of the factors, which have resulted in a deficiency in the prediction of cloud properties and hydrological cycle. We do not understand the ice nucleation mechanisms to represent the ice formation in the model, and therefore more INP measurements at various supercooled temperatures are needed. This study reports for the first time real-time INP concentration at a high altitude station in the Western Ghats region of India, and these results will be used to constrain the ice nucleation parameterizations in the model. The variation of INP for any particular cloud condition can have strong microphysical responses of mixed-phase precipitation formation processes. Also, to improve the representation of heterogeneous ice nucleation, INP measurements of various types of aerosols commonly observed over the Indian region are needed. This study presents, the INP concentrations and daily concentration of non-refractory chemical composition (organics, sulfate, nitrate, ammonium, and chloride), cloud condensation nuclei (CCN), and aerosol size distribution. Spectrometer for Ice Nuclei (SPIN) was operated to measure INP concentration at the mountain site from August to December 2018. INP measurements were performed at three different temperatures (-25, -30, and - 34 °C) in the immersion freezing mode relevant for mixed-phase cloud conditions. The average INP concentrations approximately varied from 0.18 to 12.4 L-1, 0.39 to 24 L-1, 1.1 to 40.2 L-1 at -25, -30, and - 34 °C, respectively. These concentrations are within the concentrations reported in the literature from different regions across the globe. The air mass back trajectory analysis showed that continental air mass contains more INP compared to maritime air mass. The information on INP concentration and chemical characteristics of aerosol will help to improve heterogeneous ice nucleation parameterization in numerical models.

Kumar, Anil V.↗
DOE OSTI2024

Chemical preintercalation of magnesium ions into ⍺-MoO 3 structure for improved electrochemical stability in Li-ion cells

Chemical preintercalation of layered materials, used as electrodes in intercalation-based energy storage devices, represents a promising strategy to enhance electrochemical stability and extend cycle life. However, standardized synthesis approaches for the chemical preintercalation of diverse ions into various layered materials are lacking, necessitating the development of specific synthesis routes for each ion and layered phase combination. In this study, we present the first successful demonstration of Mg 2+ ion chemical preintercalation into the interlayer region of α-MoO 3 , revealing its stabilizing effect during cycling in non-aqueous Li-ion cells. Using ethanol during hydrothermal treatment facilitated molybdenum reduction, which was critical for Mg 2+ ion preintercalation. Interestingly, we found that Mg preintercalation was accompanied by the incorporation of water. Mg-preintercalated α-MoO 3 exhibited enhanced charge storage capacity, electrochemical stability, and power capability compared to pristine α-MoO 3 electrodes. This improved performance is attributed to the structural stabilization provided by Mg 2+ pillars, which prevent undesirable phase transformations during repeated Li intercalation/deintercalation, and increased Li + ion diffusion due to the shielding of electrostatic interactions between electrochemically cycled ions and the α-MoO 3 lattice, enabled by structural water. In conclusion, our study offers new insights into developing chemical preintercalation synthesis approaches that can be broadly applied to a wide range of pillaring ions and layered material hosts.

25 ENERGY STORAGE↗
DOE OSTI2024

Global-Scale Convergence Obscures Inconsistencies in Soil Carbon Change Predicted by Earth System Models

Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO 2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

54 ENVIRONMENTAL SCIENCES↗