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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Stretchable electrochemical energy storage devices

The increasingly intimate contact between electronics and the human body necessitates the development of stretchable energy storage devices that can conform and adapt to the skin. Therefore, the development of stretchable batteries and supercapacitors has received significant attention in recent years. This review provides an overview of the general operating principles of batteries and supercapacitors and the requirements to make these devices stretchable. The following sections provide an in-depth analysis of different strategies to convert the conventionally rigid electrochemical energy storage materials into stretchable form factors. Namely, the strategies of strain engineering, rigid island geometry, fiber-like geometry, and intrinsic stretchability are discussed. A wide range of materials are covered for each strategy, including polymers, metals, and ceramics. By comparing the achieved electrochemical performance and strain capability of these different materials strategies, we allow for a side-by-side comparison of the most promising strategies for enabling stretchable electrochemical energy storage. The final section consists of an outlook for future developments and challenges for stretchable supercapacitors and batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Achieving record hot spot energies with large HDC implosions on NIF in HYBRID-E

HYBRID-E is an inertial confinement fusion implosion design that increases energy coupled to the hot spot by increasing the capsule scale in cylindrical hohlraums while operating within the current experimental limits of the National Ignition Facility. HYBRID-E reduces the hohlraum scale at a fixed capsule size compared to previous HYBRID designs, thereby increasing the hohlraum efficiency and energy coupled to the capsule, and uses the cross-beam energy transfer (CBET) to control the implosion symmetry by operating the inner (23° and 30°) and outer (44° and 50°) laser beams at different wavelengths (Δλ> 0). Small case to capsule ratio designs can suffer from insufficient drive at the waist of the hohlraum. We show that only a small amount of wavelength separation between the inner and outer beams (Δλ1-2 Å) is required to control the symmetry in low-gas-filled hohlraums (0.3 mg/cm3 He) with enough drive at the waist of the hohlraum to symmetrically drive capsules 1180 μm in outer radius. This campaign is the first to use the CBET to control the symmetry in 0.3 mg/cm3 He-filled hohlraums, the lowest gas fill density yet fielded with Δλ> 0. We find a stronger sensitivity of hot spot P2 in μm per Angstrom (40–50 μm/Å wavelength separation) than observed in high-gas-filled hohlraums and previous longer pulse designs that used a hohlraum gas fill density of 0.6 mg/cm3. There is currently no indication of transfer roll-off with increasing Δλ, indicating that even longer pulses or larger capsules could be driven using the CBET in cylindrical hohlraums. We show that the radiation flux symmetry is well controlled during the foot of the pulse, and that the entire implosion can be tuned symmetrically in the presence of the CBET in this system, with low levels of laser backscatter out of the hohlraum and low levels of hot electron production from intense laser–plasma interactions. Radiation hydrodynamic simulations can accurately represent the early shock symmetry and be used as a design tool, but cannot predict the late-time radiation flux symmetry during the peak of the pulse, and semi-empirical models are used to design the experiments. Deuterium–tritium (DT)-layered tests of 1100 μm inner radius implosions showed performance close to expectations from simulations at velocities up to ~360 km/s, and record yields at this velocity, when increasing the DT fuel layer thickness to mitigate hydrodynamic mixing of the ablator into the hot spot as a result of defects in the ablator. However, when the implosion velocity was increased, mixing due to these defects impacted performance. The ratio of measured to simulated yield for these experiments was directly correlated with the level of observed mixing. These simulations suggest that reducing the mixing, e.g., by improving the capsule defects, could result in higher performance. In addition, future experiments are planned to reduce the coast time at this scale, delay between the peak compression and the end of the laser, to increase the hot spot convergence and pressure. To reduce the coast time by several hundred ps compared to the 1100 μm inner radius implosions, HYBRID-E has also fielded 1050 μm inner radius capsules, which resulted in higher hot spot pressure and a fusion energy yield of ~170 kJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Simulation of divertor heat flux width on EAST by BOUT++ transport code

The BOUT++ edge plasma transport code is applied to study the effects of neutral recycling, drifts and heating scheme on edge plasma profiles and the divertor heat flux width of two discharges of the experimental advanced superconducting tokamak (EAST) steady-state H-mode plasmas heated by low hybrid wave (LHW) and neutral beam (NB), respectively. Neutral recycling seems to have played an important role in the plasma density profile. The edge plasma density drops dramatically for the case w/o neutral recycling, while it can be sustained for the case w/ neutral recycling. Drifts are found to have significant influences on edge plasma profiles. Both the amplitude and width of the divertor heat flux are found to have increased a lot due to drifts. The simulated heat flux width w/ drifts for the two discharges shows reasonable agreement with the experiments. However, the width from the simulation and experiment for the LHW heated discharge is much larger than that of the NB heated discharge. Comparison with Goldston's drift-based model and more detailed analysis on the heat flux contributions from drifts versus turbulence show that drifts are the dominant factor in edge plasma transport for both LHW and NB heated discharges, while turbulence may have played a more important role in determining the heat flux width in LHW heated discharges than that in NB heated discharges. This may account for the larger heat flux width in the LHW heated discharge. The magnetic topology and the equilibrium change by the LHW power may also be a potential reason for the larger heat flux width in the LHW heated discharges, which still needs more evidence and studies to support it. Finally, additional SOLPS simulation w/o drifts for the two discharges show reasonable agreement with the counterpart from the BOUT++ simulation, suggesting the two are both suitable codes for EAST edge plasma simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

"BAAE" instabilities observed without fast ion drive

The instability that was previously identified as a fast-ion driven beta-induced Alfv´en-acoustic eigenmode (BAAE) in DIII-D was misidentified. In a dedicated experiment, low frequency modes (LFM) with characteristic “Christmas light” patterns of brief instability linked to the safety factor evolution occur in plasmas with electron temperature T e ≳ 2.1 keV but modest beta. To isolate the importance of different driving gradients on these modes, the electron cyclotron heating power and 80 keV, sub-Alfv´enic neutral beams are altered for 50-100 ms durations in reproducible discharges. Although beta-induced Alfv´en eigenmodes and reversed-shear Alfv´en eigenmodes stabilize when beam injection ceases (as expected for a fast-ion driven instability), the low frequency modes that were called BAAEs persist. Data mining reveals that characteristic LFM instabilities can occur in discharges with no beam heating but strong electron cyclotron heating. A large database of over 1000 discharges shows that LFMs are only unstable in plasmas with hot electrons but modest overall beta. The experimental LFMs have low frequencies (comparable to diamagnetic drift frequencies) in the plasma frame, occur near the minimum of the safety factor q min , and appear when q min is close to rational values. In conclusion, theoretical analysis suggests that the LFMs are a low frequency reactive instability of predominately Alfv´enic polarization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Statistical relationships across epigenomes using large-scale hierarchical clustering

Recent advances in genomics and sequencing platforms have revolutionized our ability to create immense data sets, particularly for studying epigenetic regulation of gene expression. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given nonlinear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3000 epigenomes of uninfected individuals and provide a framework to characterize the relationships among epigenetic modifiers, their modifiers, genetic loci, and specific immune cell types across all chromosomes using hierarchical clustering. Hierarchical clustering of epigenomic data revealed consistent epigenetic patterns across chromosomes, demonstrating that variation due to epigenetic modifiers is greater than variation between cell types. Gene Ontology and KEGG pathway analyses indicated significant enrichment of genes involved in chromatin remodeling, mRNA splicing, immune responses, and the regulation of microRNAs and snoRNAs. Epigenetic modifiers frequently formed biologically relevant clusters, including the cohesin complex, RNA Polymerase II transcription factors, and PRC2 complex members. These clustering behaviors remained consistent across all chromosomes, supported by entropy analysis and high Adjusted Rand Index scores, indicating robust cross-chromosomal similarity. Co-occurrence analysis further revealed specific sets of modifiers that consistently appeared together within clusters, reflecting shared biological functions and interactions. Validation using another dataset confirmed the reproducibility of these clustering patterns and modifier co-occurrence relationships, underscoring the reliability and generalizability of the methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improved measurement of the decays η ′ → π + π − π + ( 0 ) π − ( 0 ) and search for the rare decay η ′ → 4 π 0

Using a sample of 10 billion J / ψ events collected with the BESIII detector, the decays η ′ → π + π − π + π − , η ′ → π + π − π 0 π 0 and η ′ → 4 π 0 are studied via the process J / ψ → γ η ′ . The branching fractions of η ′ → π + π − π + π − and η ′ → π + π − π 0 π 0 are measured to be ( 8.56 ± 0.25 ( stat ) ± 0.23 ( syst ) ) × 10 − 5 and ( 2.12 ± 0.12 ( stat ) ± 0.10 ( syst ) ) × 10 − 4 , respectively, which are consistent with previous measurements but with improved precision. No significant η ′ → 4 π 0 signal is observed, and the upper limit on the branching fraction of this decay is determined to be less than 1.24 × 10 − 5 at the 90% confidence level. In addition, an amplitude analysis of η ′ → π + π − π + π − is performed to extract the doubly virtual isovector form factor α for the first time. The measured value of α = 1.22 ± 0.33 ( stat ) ± 0.04 ( syst ) , is in agreement with the prediction of the vector meson dominance model. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Measurement of the 13 C(α, n 0 ) 16 O Differential Cross Section from 0.8 to 6.5 MeV

The cross section of the 13 C(α, n 0 ) 16 O reaction is needed for nuclear astrophysics and applications to a precision of 10% or better, yet inconsistencies among 50 years of experimental studies currently lead to an uncertainty of ≈15%. Here, using a state-of-the-art neutron detection array, we have performed a high resolution differential cross section study covering a broad energy range. These measurements result in a dramatic improvement in the extrapolation of the cross section to stellar energies potentially reducing the uncertainty to ≈5% and resolving long standing discrepancies in higher energy data.

6 ≤ A ≤ 19↗
DOE OSTI2025

Observation of D + → η ′ μ + ν μ and First Experimental Study of D + → η ′ ℓ + ν ℓ Decay Dynamics

Using 20.3 fb − 1 of e + e − collision data collected at the center-of-mass energy 3.773 GeV with the BESIII detector, we report the first observation of the semileptonic decay D + → η ′ μ + ν μ with significance of 8.6 σ including systematic uncertainties, and an improved measurement of D + → η ′ e + ν e . The branching fractions of D + → η ′ μ + ν μ and D + → η ′ e + ν e are determined to be ( 1.92 ± 0.2 8 stat ± 0.0 8 syst ) × 10 − 4 and ( 1.79 ± 0.1 9 stat ± 0.0 7 syst ) × 10 − 4 , respectively. The ratio of the two branching fractions is determined to be R μ / e = 1.07 ± 0.1 9 stat ± 0.0 3 syst , which agrees with the theoretical expectation of lepton flavor universality within the standard model. From an analysis of the D + → η ′ ℓ + ν ℓ decay dynamics, the product of the hadronic form factor f + η ′ ( 0 ) and the Cabibbo-Kobayashi-Maskawa matrix element | V c d | is measured for the first time, giving f + η ′ ( 0 ) | V c d | = ( 5.92 ± 0.5 6 stat ± 0.1 3 syst ) × 10 − 2 . The η − η ′ mixing angle in the quark flavor basis is determined to be ϕ P = ( 39.8 ± 0.8 stat ± 0.3 syst ) ° . Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2023

Interpretable Data-Driven Probabilistic Power System Load Margin Assessment with Uncertain Renewable Energy and Loads

The increasing uncertainties caused by the high-penetration of stochastic renewable generation resources poses a significant threat to the power system voltage stability. To address this issue, this paper proposes a probabilistic deep kernel learning enabled surrogate model to extract the hidden relationship between uncertain sources, i.e., wind power and loads, and load margin for probabilistic load margin assessment (PLMA). Unlike other deep learning approaches, a kernel SHAP provides the sensitivity analysis as well as interpretability of the inputs to outputs influences. This allows identifying the critical factors that affect load margin so that corrective control can be initiated for stability enhancement. Numerical results carried out on the IEEE 118-bus power system demonstrate the accuracy and efficiency of the proposed data-driven PLMA scheme.

deep kernel learning↗
DOE OSTI2021

Ribbon Wrinkling Origin and Its Effect on Tape-Wound Core Shape

Improved understanding of advanced manufacturing techniques is needed to fabricate next- generation soft magnetic tape-wound cores. These utilize metal amorphous nano-composites (MANCs) in the form of long thin ribbons. MANCs exhibit attractive soft magnetic properties for use in high frequency and high power density magnetic components. Of particular interest here, the permeability and hysteresis of MANC ribbons can be tuned in a strain annealing process. An unexpected consequence is that wider ribbons develop longitudinal wrinkle patterns. This can substantially reduce the tape-wound core stacking factor. However, when winding a wrinkled ribbon into a toroidal core, the wrinkles can completely flatten, or crinkle. By this phenomenon, the stacking factor can be recovered. To understand the crinkling effect we have developed analytical and finite element analysis (FEA) models. Experiments with known boundary conditions demonstrate the transition from wrinkled to crinkled versus winding curvature. The models utilize an elastic modulus measured via ribbon tensile testing and a ribbon thickness value measurement made by profilometry. The analytical model provides insight into the crinkling effect but cannot explain the length of the transition region from wrinkling to crinkling. With FEA, we successfully predict the transition region and depending on wrinkling amplitude can determine when a ribbon will wind into a useable core. Such mechanics-based insight provides critical feedback for allowable processing parameters in the strain annealing process.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Feasibility Study of Developing Alternative Common-Cause Failure Model for Event Assessment

This report is a revision of the original report, INL/LTD-14-33376. The original report, which was a limited distribution to the Nuclear Regulatory Commission (NRC) only and not available to the public, was revised as this report for public distribution. The report presents the feasibility study of alternative common-cause failure (CCF) models that could be used for event assessment in the Standardized Plant Analysis Risk (SPAR) models. The current CCF model used by the SPAR models is the alpha factor model. The proposed alternative CCF models are the partial alpha factor model and general dependency model. These alternative CCF models are reviewed and compared to the current alpha factor model, with the partial alpha factor model being identified as the preferred CCF model that could be used for event assessment in the SPAR models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Use Attainability Analysis Aquatic Life Uses for Perennial Reach of Sandia Canyon [Slides]

The following information will be presented during the February 23, 2022 Accord Pueblos Technical Meeting. The purpose of the study is to determine if natural thermal conditions are preventing the attainment of Coldwater Aquatic Life Use in the perennial reach of the upper Sandia Canyon Assessment Unit (Sandia AU). The New Mexico Water Quality Standards allow for a change in the designated use if a Use Attainability Analysis (UAA) demonstrates that the use is not attainable due to one or more of six factors listed in 40 CFR 131.10(g), including naturally occurring pollutant concentrations. The Sandia AU is located in a perennial reach of upper Sandia Canyon between Sigma Canyon and NPDES Outfall 001. The classified Segment 20.6.4.126 NMAC comprises perennial waters within Los Alamos National Laboratory boundaries and includes the Sandia AU. Persistent surface flows originate from NPDES permitted effluent releases. These releases have occurred since the early 1950’s and continue today. The UAA examines several lines of evidence. NMED’s Air-Water Temperature Correlation (AWTC) model is used for identifying appropriate stream classifications and attainable aquatic life use subcategories. The model correlates between July average air temperatures (ATEMP) and maximum weekly average stream temperatures. Air temperatures are obtained from PRISM and LANL Meteorological Towers and used to derive ATEMP. Thermographs were placed in the Sandia AU to obtain measured stream temperatures during summer months when stream temperatures are the highest. Measured data is used with AWTC modeled data to determine if the Sandia AU is meeting its natural air temperature driven thermal condition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancing Site Screening for Underground Hydrogen Storage: Qualitative Site Quality Assessment - SHASTA: Subsurface Hydrogen Assessment, Storage, and Technology Acceleration Project

The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.

08 HYDROGEN↗
DOE OSTI2024

Enhancing Site Screening for Underground Hydrogen Storage: Qualitative Site Quality Assessment - SHASTA: Subsurface Hydrogen Assessment, Storage, and Technology Acceleration Project

The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.

08 HYDROGEN↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

A Preferential Growth Channel for Supermassive Black Holes in Elliptical Galaxies at z ≲ 2

The assembly of stellar and supermassive black hole (SMBH) mass in elliptical galaxies since z ~ 1 can help to diagnose the origins of locally observed correlations between SMBH mass and stellar mass. We therefore construct three samples of elliptical galaxies, one at z ~ 0 and two at 0.7 ≲ z ≲ 2.5, and quantify their relative positions in the M BH -M * plane. Using a Bayesian analysis framework, we find evidence for translational offsets in both stellar mass and SMBH mass between the local sample and both higher-redshift samples. The offsets in stellar mass are small, and consistent with measurement bias, but the offsets in SMBH mass are much larger, reaching a factor of 7 between z ~ 1 and z ~ 0. The magnitude of the SMBH offset may also depend on redshift, reaching a factor of ~20 at z ~ 2. The result is robust against variation in the high- and low-redshift samples and changes in the analysis approach. The magnitude and redshift evolution of the offset are challenging to explain in terms of selection and measurement biases. We conclude that either there is a physical mechanism that preferentially grows SMBHs in elliptical galaxies at z ≲ 2, or that selection and measurement biases are both underestimated, and depend on redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Exploring for Superhot Geothermal Targets in Magmatic Settings: Developing a Methodology

This paper presents preliminary results from a subset of work carried out as part of a multinational research project entitled DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN). One objective of DEEPEN is to develop a customized approach to exploration for superhot geothermal plays in magmatic systems. This paper summarizes key geologic components, risk factors, and exploration methods for geothermal plays in magmatic settings based on a review and comparative analysis of international training sites. As part of a Play Fairway Analysis (PFA) approach to exploring for multiple play types in a single magmatic system, training data were compiled and weights assigned to various evidence layers. Two different approaches for weighting exploration datasets are described in this paper - one based on expert opinions and the other using statistical learning. Weights produced by both approaches will be input into a 3D PFA workflow that combines multiple exploration datasets to generate 3D geothermal favorability models, which will be applied to two international demonstration sites.

GEOTHERMAL ENERGY↗