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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Variation in supercurrent connectivity and vortex pinning of state-of-the-art pulsed laser deposited RE Ba 2 Cu 3 O 7- x coated conductors

REBa 2 Cu 3 O 7-x (REBCO, RE: rare earth) coated conductors (CCs) suffer from great critical current I c differences between different manufacturers, I c variations within individual manufacturers, and often significant lengthwise fluctuations. The understanding of such variations is complicated by the lack of a direct correlation between I c and the critical current density J c . In fact, although J c is the fundamental property determined by the local vortex pinning landscape, I c is often limited by variable current blocking mechanisms. An important practical complexity is commercial practices of performing J c and I c evaluations based on I c at 77 K and self-field (sf), where connectivity variation dominates over vortex pinning variations. However, at higher fields and lower temperatures, vortex pinning becomes more complex and highly variable, making predictions of I c and J c at arbitrary temperature T, magnetic field H, and field orientation θ, quite uncertain. To address some aspects of this problem, we conducted detailed spool-to-spool performance characterization on recently manufactured REBCO CCs. Despite J c (77 K, sf) varies by only ∼11%, J c (77 K, 1 T) of its minimum and maximum (for H//ab-plane) show variations of ∼21% and ∼32%, respectively. This emphasizes the shortcoming in using J c (77 K, sf) as parameter for evaluating even the low field performance. An even more remarkable spool-to-spool J c variation of ∼68% was observed at 20 K and 15 T for H//ab-plane. To identify the origin of such lack of reproducibility we performed microstructural characterizations, which revealed, within the REBCO layer, large variation in the density of copper oxide (CuO x ) particles ranging from 0.1 to 2 μm in size. We believe that they play a decisive role in reducing the effective cross-section of the REBCO layer by not simply blocking current themselves, but also by nucleating off-axis REBCO grains, whose misoriented grain boundaries adversely impact REBCO grain-to-grain connectivity. The REBCO growth associated with high density CuO x particles also leads to the more disordered spatial arrangement of BaHfO 3 precipitate arrays, which, when self-aligning along the ab-planes, generate stronger pinning enhancing J c (H//ab) at all temperatures. In this way, we established that variations of both connectivity and vortex pinning are thus directly coupled. Our results also explain why the so-called ‘lift-factor’, typically defined by the ratio between I c (T, H) and I c (77 K, sf), frequently turns out to be unreliable.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗
DOE OSTI2020

Electroweak Phase Transition with Spontaneous $Z_2$-Breaking

This work investigates a simple, representative extension of the Standard Model with a real scalar singlet and spontaneous $Z_2$ breaking, which allows for a strongly first-order phase transition, as required by electroweak baryogenesis. We perform analytical and numerical calculations that systematically include one-loop thermal effects, Coleman-Weinberg corrections, and daisy resummation, as well as evaluation of bubble nucleation. We study the rich thermal history and identify the conditions for a strongly first-order electroweak phase transition with nearly degenerate extrema at zero temperature. This requires a light scalar with mass below 50 GeV. Exotic Higgs decays, as well as Higgs coupling precision measurements at the LHC and future collider facilities, will test this model. Additional information may be obtained from future collider constraints on the Higgs self-coupling. Gravitational-wave signals could potentially be probed by future gravitational wave experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The rise and fall of stretched bond errors: Extending the analysis of Perdew–Zunger self-interaction corrections of reaction barrier heights beyond the LSDA

Incorporating self-interaction corrections (SIC) significantly improves chemical reaction barrier height predictions made using density functional theory methods. We present a detailed orbital-by-orbital analysis of these corrections for three semi-local density functional approximations (DFAs) situated on the three lowest rungs of Jacob’s ladder of approximations. The analysis is based on Fermi–Löwdin Orbital Self-Interaction Correction (FLOSIC) calculations performed at several steps along the reaction pathway from the reactants (R) to the transition state (TS) to the products (P) for four representative reactions selected from the BH76 benchmark set. For all three functionals, the major contribution to self-interaction corrections of the barrier heights can be traced to stretched bond orbitals that develop near the TS configuration. The magnitude of the ratio of the self-exchange–correlation energy to the self-Hartree energy (XC/H) for a given orbital is introduced as an indicator of one-electron self-interaction error. XC/H = 1.0 implies that an orbital’s self-exchange–correlation energy exactly cancels its self-Hartree energy and that the orbital, therefore, makes no contribution to the SIC in the FLOSIC scheme. For the practical DFAs studied here, XC/H spans a range of values. Here, the largest values are obtained for stretched or strongly lobed orbitals. We show that significant differences in XC/H for corresponding orbitals in the R, TS, and P configurations can be used to identify the major contributors to the SIC of barrier heights and reaction energies. Based on such comparisons, we suggest that barrier height predictions made using the strongly constrained and appropriately normed meta-generalized gradient approximation may have attained the best accuracy possible for a semi-local functional using the Perdew–Zunger SIC approach.

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

All-loop soft theorem for pions

In this paper we discuss a generalization of the Adler zero to loop integrands in the planar limit of the S U ( N ) nonlinear sigma model (NLSM). The Adler zero for integrands is violated starting at the two-loop order and is only recovered after integration. Here we propose a soft theorem satisfied by loop integrands with any number of loops and legs. This requires a generalization of NLSM integrands to an off shell framework with certain deformed kinematics. Defining an , we identify a simple nonvanishing soft behavior of integrands, which we call the . We find that the proposed soft theorem is satisfied by the “surface” integrand of Arkani-Hamed and Figueiredo [], which is obtained from the shifted Tr φ 3 surfacehedron integrand. Finally, we derive an on shell version of the algebraic soft theorem that takes an interesting form in terms of self-energy factors and lower-loop integrands in a mixed theory of pions and scalars. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
NASA NTRS2011

Panchromatic Observations of the Textbook GRB 110205A: Constraining Physical Mechanisms of Prompt Emission and Afterglow

We present a comprehensive analysis of a bright, long duration (T(sub 90) approx. 257 s) GRB 110205A at redshift z = 2.22. The optical prompt emission was detected by Swift/UVOT, ROTSE-IIIb and BOOTES telescopes when the GRB was still radiating in the gamma-ray band. Thanks to its long duration, nearly 200 s of observations were obtained simultaneously from optical, X-ray to gamma-ray (1 eV - 5 MeV), which makes it one of the exceptional cases to study the broadband spectral energy distribution across 6 orders of magnitude in energy during the prompt emission phase. In particular, by fitting the time resolved prompt spectra, we clearly identify, for the first time, an interesting two-break energy spectrum, roughly consistent with the standard GRB synchrotron emission model in the fast cooling regime. Although the prompt optical emission is brighter than the extrapolation of the best fit X/ -ray spectra, it traces the -ray light curve shape, suggesting a relation to the prompt high energy emission. The synchrotron + synchrotron self-Compton (SSC) scenario is disfavored by the data, but the models invoking a pair of internal shocks or having two emission regions can interpret the data well. Shortly after prompt emission (approx. 1100 s), a bright (R = 14.0) optical emission hump with very steep rise ( alpha approx. 5.5) was observed which we interpret as the emission from the reverse shock. It is the first time that the rising phase of a reverse shock component has been closely observed.

Zheng, W.↗
NASA NTRSDate not supplied

Dynamic Analysis of Reynolds Number Effects on Trailing Edge Transonic Vortex Shedding and Its Impact on Turbine Blade Aerodynamic Performance

In this work, we will discuss observations from images acquired from a time-resolved, high-speed self-aligned focusing Schlieren campaign that was performed at the CW-22 facility at NASA Glenn Research Center to understand the dynamic behavior of thick trailing-edge high-pressure turbine blades simulating a ceramic matrix composite (CMC) construction at high inlet turbulence conditions. For the CMC-9 blade, which has a trailing edge thickness of 9% of the axial chord, we identified a regime where an excessive total pressure loss (loss anomaly) is observed only for a narrow range of Reynolds numbers at a fixed exit Mach number of 0.74. The loss anomaly is qualitatively explained by our images, which were taken at 10 distinct blade Reynolds numbers spanning a factor of 6. The images show a significant increase in energy related to the oscillations due to transonic vortex shedding at the Reynolds numbers related to the high loss conditions. This increased energy leads to the formation of strong acoustic waves that turn into shock waves at the highest loss conditions. From our observations stemming from Spectral POD analysis of the high-speed images, we see the acoustic waves produced by the trailing edge vortex shedding exist in all conditions tested; but the shedding frequency has a very slight trend upwards as the Reynolds number is increased, varying about 6% in the range tested. Considering this variation of shedding frequency as a function of Reynolds number, which is well-established for other bluff-body flows, we stipulate there may be a potential feedback mechanism involving an acoustic information transfer path across neighboring blades that may explain why only a narrow range of Reynolds numbers displays strong, shock-forming vortex shedding. We consider a few feedback paths and examine the timing based on the mean flow field from a high-resolution LES simulation. It appears that all feedback mechanisms are viable, presenting an integer number of delay cycles with respect to disturbances generated at the trailing edge. Most noteworthy, however, is the acoustic/shock-boundary layer interaction mechanism at the blade geometric throat. Based on our analysis, this mechanism likely plays an important role in realistic, curved turbine blade passages.

Aerodynamics↗
DOE OSTI2025

RINO: Renormalization Group Invariance with No Labels

A common challenge with supervised machine learning (ML) in high energy physics (HEP) is the reliance on simulations for labeled data, which can often mismodel the underlying collision or detector response. To help mitigate this problem of domain shift, we propose RINO (Renormalization Group Invariance with No Labels), a self-supervised learning approach that can instead pretrain models directly on collision data, learning embeddings invariant to renormalization group flow scales. In this work, we pretrain a transformer-based model on jets originating from quantum chromodynamic (QCD) interactions from the JetClass dataset, emulating real QCD-dominated experimental data, and then finetune on the JetNet dataset -- emulating simulations -- for the task of identifying jets originating from top quark decays. RINO demonstrates improved generalization from the JetNet training data to JetClass data compared to supervised training on JetNet from scratch, demonstrating the potential for RINO pretraining on real collision data followed by fine-tuning on small, high-quality MC datasets, to improve the robustness of ML models in HEP.

Hao, Zichun [Caltech] (ORCID:0000000256244907)↗
DOE OSTI2025

Exotics with gluonic excitations

That the gluons of quantum chromodynamics self-interact with a strong coupling suggests the possibility of hadrons in which the gluonic field plays an essential role: Glueballs in which gluons stick together to produce a hadron in which no quarks are required, and hybrids in which an excited gluonic field couples to quarks. This chapter presents our contemporary theoretical understanding of such states, and the challenges associated with definitively identifying their presence within the experimental spectrum of hadrons.

Dudek, Jozef [William & Mary] (ORCID:0000000343272↗
DOE OSTI2022

Chiral assemblies of pinwheel superlattices on substrates

The unique topology and physics of chiral superlattices make their self-assembly from nanoparticles highly sought after yet challenging in regard to (meta)materials. In this report we show that tetrahedral gold nanoparticles can transform from a perovskite-like, low-density phase with corner-to-corner connections into pinwheel assemblies with corner-to-edge connections and denser packing. Whereas corner-sharing assemblies are achiral, pinwheel superlattices become strongly mirror asymmetric on solid substrates as demonstrated by chirality measures. Liquid-phase transmission electron microscopy and computational models show that van der Waals and electrostatic interactions between nanoparticles control thermodynamic equilibrium. Variable corner-to-edge connections among tetrahedra enable fine-tuning of chirality. The domains of the bilayer superlattices show strong chiroptical activity as identified by photon-induced near-field electron microscopy and finite-difference time-domain simulations. The simplicity and versatility of substrate-supported chiral superlattices facilitate the manufacture of metastructured coatings with unusual optical, mechanical and electronic characteristics.

42 ENGINEERING↗
DOE OSTI2021

Thermal quench in ITER locked mode disruptions

Simulations and theory are presented of an ITER locked mode thermal quench(TQ). In present experiments, locked mode disruptions have a long precursor phase,followed by a rapid termination and thermal quench, which can be identified with a resistive wall tearing mode (RWTM). In ITER, the RWTM will be slowed by the highly conductive vacuum vessel. Here, the rapid termination might be absent, and the plasma could remain in the precursor phase. If the edge temperature is in the collisional regime, the TQ would proceed on a long timescale, limited by the RWTM to almost100ms. This is an important self mitigating effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Power Electronics Based Self-Monitoring and Diagnosing for Photovoltaics Systems

Self-monitoring and diagnosing technology for photovoltaic (PV) systems is a method to reduce energy production losses. The proposed technology will enable existing panel-level power optimizers and inverters in a PV system to actively perturb the system, measure its response to these small-signal perturbations, and detect any changes in the small-signal impedances. Impedance measurement will be used to identify specific faults and power degradation trends in a PV panel. This information can be used to instantly alert Operations and Maintenance (O&M) personnel of the need for corrective action, thereby reducing energy production losses earlier relative to standard PV systems.

Panchal, Jeet↗
DOE OSTI2023

Tritium Safety: Self-Study Course 11952

Course Overview: Tritium is a radioactive isotope of hydrogen which has characteristics that require workers understand what should be done to work safely and responsibly around it. Tritium is used for defense applications, experimental purposes for general research, and is a byproduct of some of the work that is done at LANL. Practical guidance offered in this training will inform safe handling to minimize negative impacts on personnel, the workspace, and the surrounding environment. This course, Tritium Safety Self-Study (Course 11952), provides information on the physical, chemical, and radioactive properties of tritium; sources of tritium; uses of tritium; biological effects of tritium; radiological control methods for tritium; monitoring methods of tritium; tritium waste minimization and handling; and alarms and proper response to abnormal conditions in a tritium facility. Course Objectives: When you have completed this course, you will be able to: Identify the physical, chemical, and radioactive properties of tritium; Identify the sources of tritium; Identify the uses of tritium; Identify the modes of tritium exposure; Identify the biological effects of tritium; Identify the radiological control methods of tritium; Identify methods used to monitor for tritium; Identify tritium waste minimization and handling techniques; Identify proper response to abnormal conditions in tritium facilities.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1991

Lunar base Controlled Ecological Life Support System (LCELSS): Preliminary conceptual design study

The objective of this study was to develop a conceptual design for a self-sufficient LCELSS. The mission need is for a CELSS with a capacity to supply the life support needs for a nominal crew of 30, and a capability for accommodating a range of crew sizes from 4 to 100 people. The work performed in this study was nominally divided into two parts. In the first part, relevant literature was assembled and reviewed. This review identified LCELSS performance requirements and the constraints and advantages confronting the design. It also collected information on the environment of the lunar surface and identified candidate technologies for the life support subsystems and the systems with which the LCELSS interfaced. Information on the operation and performance of these technologies was collected, along with concepts of how they might be incorporated into the LCELSS conceptual design. The data collected on these technologies was stored for incorporation into the study database. Also during part one, the study database structure was formulated and implemented, and an overall systems engineering methodology was developed for carrying out the study.

Schwartzkopf, Steven H.↗
NASA NTRS1993

Ordered organic thin films self-assembled from the vapor phase

Organic films self-assembled from a liquid phase, as in Langmuir-Blodgett or adsorption from solution, have received much attention in the past decade as techniques to achieve highly oriented-ordered polymeric thin films. Many organic compounds including some of the same fatty acids have been vapor deposited as well. However, organic pigments and dyes comprise a major class of important materials which have very low solubilities yet excellent thermal stabilities, making them ideally suited for film deposition from the vapor phase. Surprisingly, such molecular systems exhibit a significant propensity to self order, a high sensitivity to deposition parameters, and a range of microstructural forms that cannot be duplicated by the less energetic mechanisms associated with solution adsorption processes. Molecular solids such as heterocyclic polynuclear aromatics are excellent candidates for film formation by vacuum deposition means. Over the past decade, our work and that of others investigating a wide variety of perylene and phthalocyanine derivatives identified five deposition parameters that can significantly affect film morphology, physical microstructure, and type and extent of ordering developed in vacuum and vapor transport grown films. These parameters are substrate temperature, deposition rate, substrate chemistry and epitaxy, ambient gas convective flows, and post deposition annealing. Examples of how each of these conditions manifest themselves in the film structure and ordering, most frequently revealed by scanning electron microscopy, reflection absorption infrared spectroscopy (RAIR), and grazing incidence x-ray diffraction (GIX), are presented.

Debe, M. K.↗
NASA NTRSDate not supplied

Advancing xEMU Lunar Dust Mitigation Devices

Fine, electrically charged, glass like dust particles caused significant damage to the Apollo EMU9 during lunar EVAs, identified as one of the greatest challenges to future exploration. Passive Lunar Dust Mitigation Devices (LDMD) were developed, within a SBIR Phase II, to prohibit this dust from interrupting venting space suit component operation. A Computational Fluid-Dynamics and Discrete Element Method (CFD-DEM) Simulation Tool was developed at the University of Colorado, Boulder to predict venting gas flow ability to self-clean adhered dust particles from LDMD surfaces. Lunar dust properties (i.e., adhesion and cohesion strengths) required to complete Simulation Tool analysis are relatively unknown due to considerable differences between the Earth and the Moon (i.e., gravity, humidity) and due to an absence of dust particles in their native state. Analytically determining gas flow velocity, density and direction within the fluid Boundary Layer, microns from LDMD surfaces presented a second challenge. Dusty Plasma Chamber testing is being performed at Auburn University, Auburn to observe electrostatically charged dust behavior as it adheres to LDMD prototypes and specific geometry and is then blown away by metered gas flow. Test articles were developed to offer insight into the impact of different flow geometries, surface roughness and dust removal within the gas Boundary-Layer. Observed dust behavior is currently being developed to support the CFD-DEM analysis. Many Simulation Tool analytical cases have been processed to support the intention of completing sensitivity studies to assess how different dust adherence values and Boundary Layer fluid properties impact LDMD self-cleaning effectivity.

Thomas J Stapleton↗
DOE OSTI2023

DeepNeo: a webserver for predicting immunogenic neoantigens

Abstract Non-self epitopes, whether originated from foreign substances or somatic mutations, trigger immune responses when presented by major histocompatibility complex (MHC) molecules and recognized by T cells. Identification of immunogenically active neoepitopes has significant implications in cancer and virus medicine. However, current methods are mostly limited to predicting physical binding of mutant peptides and MHCs. We previously developed a deep-learning based model, DeepNeo, to identify immunogenic neoepitopes by capturing the structural properties of peptide-MHC pairs with T cell reactivity. Here, we upgraded our DeepNeo model with up-to-date training data. The upgraded model (DeepNeo-v2) was improved in evaluation metrics and showed prediction score distribution that better fits known neoantigen behavior. The immunogenic neoantigen prediction can be conducted at https://deepneo.net.

Kim, Jeong Yeon↗