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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uncertainty quantification and sensitivity analysis for SPERT III E-core reactivity measurement benchmarking

The Special Power Excursion Reactor Test (SPERT) III E-core experiment is important because it provides critical data on reactor behavior under significant reactivity insertions, which is essential for validating computer simulations and ensuring the safety of modern light water reactors. Its design similarities to contemporary reactors make it a valuable resource for understanding and mitigating extreme hazards in nuclear operations. The current study details the application of formal parametric uncertainty quantification and sensitivity analysis to a model of the SPERT-III E-core model for zero power reactivity benchmarking. Additionally, the reactivity impact from various modeling assumptions is quantified. Overall, an conservative estimate for an uncertainty in k$_{\text{eff}}$ of $\pm$1257 was observed. A less conservative, more realistic, uncertainty estimate of $\pm$1096 pcm can be justified by the potential for various parametric uncertainties to become negligible when sampled independently across the ~1400 pins in the core. The experimental results fall within both of these uncertainty bounds. Standardized regression coefficient as well as Sobol indices are used to identify the guide tube thicknesses as the primary contributors to the uncertainty in k$_{\text{eff}}$. Overall, this study provides information on how the uncertainties in input parameters and modeling methods impact simulated k$_{\text{eff}}$ values and can be used to aid model building efforts for future code validation with the SPERT-III E-core experiment.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A framework to quantify mass flow and assess food loss and waste in the US food supply chain

Abstract Reducing food loss and waste can improve the efficiency of food supply chains and provide food security. Here we estimate mass flow as well as food loss and waste along the US food supply chain for 10 commodity groups and nine management pathways to provide a baseline for designing efficient strategies to reduce, recycle, and recover food loss and waste. We estimate a total food loss and waste of 335.4 million metric tonnes from the U.S. food supply chain in 2016. Water evaporation (19%), recycling (55%), and landfill, incineration, or wastewater treatment (23%) accounted for most of the loss and waste. The consumption stage accounted for 57% of the food loss and waste disposed of through landfill, incineration, or wastewater treatment. Manufacturing was the largest contributor to food loss and waste (61%) but had a high recycling rate. High demand, perishable products accounted for 67% of food waste. We suggest that funding for infrastructure and incentives for earlier food donation can promote efficiency and sustainability of the supply chain, promote FLW collection and recycling along the U.S. FSC, and improve consumer education in order to move towards a circular economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

INGENIOUS - Great Basin Regional Dataset Compilation

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Fuel convergence sensitivity in indirect drive implosions

In inertial confinement fusion experiments at the National Ignition Facility, a spherical shell of deuterium–tritium fuel is imploded in an attempt to reach the conditions needed for fusion, self-heating, and eventual ignition. Since theory and simulations indicate that ignition efficacy in 1D improves with increasing imploded fuel convergence ratio, it is useful to understand the sensitivity of the scale-invariant fuel convergence on all measurable or inferable 1D parameters. In this paper, we develop a simple isobaric and isentropic compression scaling model incorporating sensitivity to the in-flight adiabat inferred from shock strengths, to measured implosion velocity, and to known initial ablator and fuel aspect ratio and mass ratio. The model is first benchmarked to 1D implosion simulations spanning a variety of relevant implosion designs. We then use the model to compare compressibility trends across all existing indirect-drive layered implosion data from the facility spanning three ablators [CH, carbon (C), and Be], for which in-flight fuel adiabats varied from 1.6 to 5 by varying the number of drive shocks from 2 to 4, peak implosion velocities varied by 1.4×, capsule radii by 50%, and initial fuel aspect ratios by 1.4×. We find that the strength of the first shock is the dominant contributor setting the maximum fuel convergence. We also observe additional sensitivities to successive shock strengths and fuel aspect ratios that improve the agreement between the expected and measured compression for carbon and Be designs with adiabats above 3. A principal finding is that the adiabat 2.5 C-shell designs exhibit less convergence than CH-shell designs of similar inferred in-flight adiabat.

Landen, O. L. (ORCID:0000000214998217)↗
DOE OSTI2025

The Atlantic Meridional Overturning Circulation’s Response to CO2 Increase: Assessing the Roles of Surface Flux and Oceanic Advection Feedbacks

Abstract The Atlantic meridional overturning circulation (AMOC) is projected to slow down in climate models due to greenhouse gas emissions. However, the physical mechanisms determining the rate of the projected AMOC slowdown remain unclear. Accordingly, this study isolates the roles of oceanic advection and surface flux feedbacks that might accelerate or decelerate the AMOC’s weakening using carbon dioxide (CO 2 ) quadrupling simulations in the CESM1.2 model. Surface flux feedbacks are isolated in partially coupled experiments in which either all surface flux components or the momentum flux responses to AMOC’s weakening that might provide feedback are suppressed, while a tracer decomposition of ocean density anomalies isolates the advection feedbacks. Comparing the ocean density components in the experiments shows that the AMOC’s response is initially determined by CO 2 -induced anomalous surface heat fluxes, and afterward, feedbacks determine its response. In the fully coupled case, surface heat flux feedback strongly promotes AMOC slowdown and causes its near shutdown, while a weaker but active AMOC is maintained when the surface flux feedback is inhibited in the partially coupled case. The positive surface heat flux feedback works by canceling out the negative oceanic heat advection feedback on deep-water formation in the subpolar North Atlantic (SPNA). With the heat advection feedback thus reduced, the positive salinity advection feedback becomes the dominant contributor to SPNA density changes and deep-water formation. In the partially coupled case, negative ocean heat advection feedback and the CO 2 -induced subtropical Atlantic saline anomalies imported into the SPNA play a stabilizing role. The results highlight the importance of SPNA salinity gradients and gyre circulation strength in determining the AMOC’s response rate or recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigating Particle Phase State Dependencies during a Historic Pacific Northwest Wildfire Event

The function and lifetime of an atmospheric particle are greatly dependent upon its phase state. Studying particle phase states from specific ambient source types is often challenging due to uncontrolled environmental conditions and multiple source contributions. However, a historic Pacific Northwest wildfire event occurred in September 2020, providing a rare opportunity to study a pseudo-single particle type ambient sample (i.e., wildfire) over time. Sampling was performed in Richland, Washington, capturing aged particles from shifting wildfire sources. In addition to source variability, temporal variation in wildfire particle phase state was observed from single particle analyses. Despite this, single particle elemental compositions were homogenous over time (=87% carbonaceous) with no significant temporal variation in organic functional group abundances within individual particles either (e.g., 4% relative standard deviation in alkene contributions). While particle composition is indeed known to affect phase state, water uptake appeared to be the most significant contributor to phase state variability amongst single particles here, as particle aspect ratios (related to phase state) linearly correlated with ambient relative humidity during sampling (R2 = 0.65). Therefore, while limited to a case study, meteorological considerations are found to convey greater comparative importance than particle composition for aged particle phase state predictions.

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

The importance of localized modes spectral contribution to thermal conductivity in amorphous polymers

Abstract Polymers are a unique class of materials from the perspective of normal mode analysis. Polymers consist of individual chains with repeating units and strong intra-chain covalent bonds, and amorphous arrangements among chains with weak inter-chain van der Waals and for some polymers also electrostatic interactions. Intuitively, this strong heterogeneity in bond strength can give rise to special features in the constituent phonons, but such effects have not been studied deeply before. Here, we use lattice dynamics and molecular dynamics to perform modal analysis of the thermal conductivity in amorphous polymers. We find an abnormally large population of localized modes in amorphous polymers, which is fundamentally different from amorphous inorganic materials. Contrary to the common picture of thermal transport, localized modes in amorphous polymers are found to be the dominant contributors to thermal conductivity. We find that a significant portion of the localization happens within individual chains, but heat is dominantly conducted when localized modes involve two chains. These results suggest localized modes generally play a key role in thermal transport for different polymers. The results provide an alternative perspective on why polymer thermal conductivity is generally quite low and gives insight into how to potentially change it.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Zr 3 Mn 3 Sn 4 Ga: A new hetero-kagome bilayer antiferromagnet

Here, we report the magnetic and electrical transport properties of single-crystalline Zr 3 Mn 3 Sn 4 Ga, featuring two distinct kagome lattices: a non-magnetic breathing Zr 3 Sn 4 lattice and a magnetic intact Mn 3 Ga lattice. The material undergoes an antiferromagnetic phase transition at T N = 87 K, with neutron diffraction confirming commensurate ordering characterized by k = (1/3,1/3,0). Transport measurements show metallic behavior, a resistivity anomaly near T N , and 12% magnetoresistance at 2 K under 9 T. Deviations from the conventional second-order power law, along with negative magnetoresistance and nonlinear Hall slope variations near T N , suggest strong magneto-electronic coupling. Resonant photoemission spectroscopy identifies Zr 4d and Mn 3d orbitals as dominant contributors to the valence band, linking the material’s unique electronic properties to its kagome layers. Zr 3 Mn 3 Sn 4 Ga offers a valuable platform to study interactions between magnetism and topological electronic bands in hetero-kagome systems using the co- existence of magnetic and non-magnetic kagome layers and its tunable electronic structure.

Crystal structure↗
DOE OSTI2025

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. As a result, this approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Bacteria↗
DOE OSTI2024

Investigation of pedestal parameters and divertor heat fluxes in small ELM regimes in DIII-D

Abstract Divertor heat flux and its correlation with pedestal parameters within various small edge localized mode (ELM) regimes, including high beta poloidal, type-II and ELMs with negative triangularity H-modes were investigated in DIII-D. The parallel energy fluences of type-II and high beta poloidal small ELM regimes fall below the linear scaling with pedestal electron pressure for type-I ELMs put forward in Eich et al 2017 ( Nucl. Mater. Energy 12 84–90). The negative triangularity of H-mode ELMs follow the Eich scaling for type-I ELMs. The parallel heat flux and total heat loads to the divertor were determined using high-time resolution infrared thermography, while pedestal parameters were obtained through self-consistent kinetic equilibrium reconstructions. Linear regressions for the type-II and high beta poloidal regimes demonstrate that an equivalent 7.5 MA small ELM scenario in ITER would fall below the ~5 MJ m − 2 leading edge melting limit for tungsten (Gunn et al 2017 Nucl. Fusion 57 046025). Utilizing fast thermography, the scrape-off layer power fall-off length for both inter-ELM and intra-ELM was determined and compared to the Eich scaling with poloidal magnetic field in Eich et al (ASDEX Upgrade Team and JET EFDA Contributors 2013 Nucl. Fusion 53 093031). Except for the high beta poloidal scenario, all the small ELM regimes during both inter- and intra-ELM periods had power fall-off lengths ( λ q ) larger then would be expected from the B pol , MP − 1 scaling associated with type-I ELMs, signifying their potential in managing heat loads and offering a solution for core–edge integration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Chemical Reactor Network Modeling of Ammonia Rich-Quench-Lean Combustion Using a Partially Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However, low flammability and a propensity for high nitrogen oxide (NO x ) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NO x emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NO x concentrations below those of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing nonadiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and postflame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors' past work, this arrangement has demonstrated the significant sensitivity of exit NO x to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and nonpremixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NO x emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have been shown to create conditions that are conducive to increased N 2 O formation in the lean stage. In conclusion, the results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia.

Combustion↗
DOE OSTI2022

Conformal Pressure and Fast-Charging Li-Ion Batteries

Batteries capable of extreme fast-charging (XFC) are a necessity for the deployment of electric vehicles. Material properties of electrodes and electrolytes along with cell parameters such as stack pressure and temperature have coupled, synergistic, and sometimes deleterious effects on fast-charging performance. We develop a new experimental testbed that allows precise and conformal application of electrode stack pressure. We focus on cell capacity degradation using single-layer pouch cells with graphite anodes, LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathodes, and carbonate-based electrolyte. In the tested range (10–125 psi), cells cycled at higher pressure show higher capacity and less capacity fading. Additionally, Li plating decreases with increasing pressure as observed with scanning electron microscopy (SEM) and optical imaging. While the loss of Li inventory from Li plating is the largest contributor to capacity fade, electrochemical and SEM examination of the NMC cathodes after XFC experiments show increased secondary particle damage at lower pressure. We infer that the better performance at higher pressure is due to more homogeneous reactions of active materials across the electrode and less polarization through the electrode thickness. Our study emphasizes the importance of electrode stack pressure in XFC batteries and highlights its subtle role in cell conditions.

25 ENERGY STORAGE↗
DOE OSTI2026

PV Fleet Performance Data Initiative 2026 Update

We provide an update on the PV Fleet Performance Data Initiative at the 2026 PV Reliability Workshop. Our latest runs incorporate additional data sources and an integrated analysis pipeline run on our Kestrel HPC cluster. Initial degradation findings suggest that single-axis tracked PV systems exhibit higher performance loss rates than fixed-tilt systems, an increase of 0.5 %/yr, almost double. We discuss multiple methods for identifying stuck tracker rows, which are suspected to be a contributor to the enhanced degradation. Through satellite image detection and data-driven approaches we address the topic of identifying when stuck trackers are occuring and to what extent the problem exists. Preliminary results suggest that the increased performance loss detected for the tracked systems would be consistent with stuck tracker rows affecting on the order of 5% - 10% of the system.

14 SOLAR ENERGY↗
DOE OSTI2025

Boundary scattering in topological Kondo insulator SmB 6

We have studied the effects of phonon-boundary scattering on the thermal transport of topological Kondo insulator SmB6. The studies have been performed using the 3ω method across a temperature range 3–300 K. Our results indicate that the thermal conductivity of micro-sized SmB 6 is of an order of magnitude smaller than that of a bulk single crystal. Using the Callaway model, we analyzed the low-temperature lattice thermal conductivity of the microcrystal and demonstrated that phonon scattering at the sample boundaries is a major contributor to the thermal resistance in this topological material. Furthermore, our study reveals that the temperature dependence of the lattice thermal conductivity exhibits a double-peak structure, suggesting strong phonon–phonon or phonon–defect interactions in this material, characteristic of resonant scattering. Furthermore, these findings will help in a better understanding of thermal transport in advanced materials and devices at the micro scale.

Physics - Condensed matter physics↗
DOE OSTI2024

Unveiling the purely young star formation history of the SMC’s northeastern shell from colour–magnitude diagram fitting

ABSTRACT We obtain a quantitative star formation history (SFH) of a shell-like structure (‘shell’) located in the northeastern part of the Small Magellanic Cloud (SMC). We use the Survey of the MAgellanic Stellar History to derive colour–magnitude diagrams (CMDs), reaching below the oldest main-sequence turnoff, from which we compute the SFHs with CMD-fitting techniques. We present, for the first time, a novel technique that uses red clump (RC) stars from the CMDs to assess and account for the SMC’s line-of-sight depth effect present during the SFH derivation. We find that accounting for this effect recovers a more accurate SFH. We quantify an $\sim$7 kpc line-of-sight depth present in the CMDs, in good agreement with depth estimates from RC stars in the northeastern SMC. By isolating the stellar content of the northeastern shell and incorporating the line-of-sight depth into our calculations, we obtain an unprecedentedly detailed SFH. We find that the northeastern shell is primarily composed of stars younger than $\sim$500 Myr, with significant star formation enhancements around $\sim$250 and $\sim$450 Myr. These young stars are the main contributors to the shell’s structure. We show synchronicity between the northeastern shell’s SFH with the Large Magellanic Cloud’s (LMC) northern arm, which we attribute to the interaction history of the SMC with the LMC and the Milky Way (MW) over the past $\sim$500 Myr. Our results highlight the complex interplay of ram pressure stripping and the influence of the MW’s circumgalactic medium in shaping the SMC’s northeastern shell.

Sakowska, Joanna D. (ORCID:0000000215941466)↗
DOE OSTI2025

4.0 MOOSE: Enabling massively parallel Multiphysics simulation

Approaching 18 years of existence, MOOSE—the Multiphysics Object-Oriented Simulation Environment—is being developed at a higher pace than ever before. With significant support from four research institutions across the globe, and dozens of new contributors, the capabilities of the framework are being expanded to meet modeling challenges in a wide variety of fields from nuclear system design, to geomechanics, to material science. This includes new development in equation discretization techniques, solver methods, meshing capabilities, application deployment, and user interface improvements. Applications built on MOOSE benefit from all these improvements.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Strategies for community-sourced biocuration in bioinformatics: a case study on MIBiG 4.0

Biocuration is essential to transform molecular sequence data into standardized, machine-readable resources. Such curated datasets enable comparative analysis, predictive modeling, and data integration across bioinformatics platforms. While professional biocuration is resource-intensive and usually limited to institutional settings, community-driven approaches can mobilize large-scale annotation of specialized datasets and are more resilient to disruptions in scientific funding. Here, we present a model for community-powered curation applied to the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) repository. Through a framework of workflows for metadata capture, annotation validation, and contributor coordination, the MIBiG 4.0 initiative recruited 267 scientists across 178 institutions from 33 countries, volunteering an estimated 4000 h of work. These efforts expanded the MIBiG repository by 22% and enhanced its usability in downstream molecular data analyses in comparative genomic analyses, natural product discovery, and machine learning applications. We provide strategies and actionable lessons for adopting this model, supporting the sustainability of curated bioinformatics resources central to nucleic acid research and related fields.

biocuration↗