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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nonconservation of Lepton Numbers in the Neutrino Sector Could Change the Prospects for Core Collapse Supernova Explosions

We show that interactions violating the conservation of lepton numbers in the neutrino sector could significantly alter the standard low entropy picture for the presupernova collapsing core of a massive star. A rapid neutrino-antineutrino equilibration leads to entropy generation and enhanced electron capture and, hence, a lower electron fraction than in the standard model. This would affect the downstream core evolution, the prospects for a supernova explosion, and the emergent neutrino signal. If realized by lepton-number-violating neutrino self-interactions (LNV 𝜈⁢SI), the relevant mediator mass and coupling ranges can be probed by future accelerator-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Regularizing INR with Diffusion Prior for Self-Supervised 3D Reconstruction OF Neutron Computed Tomography Data

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as fast and lightweight inverse imaging solvers that are amenable to hybrid approaches that combine learned priors with traditional inverse problem formulations. In this paper, we present a diffusive computed tomography (CT) inversion framework for regularizing INRs called Diffusive INR (DINR), designed to enable high-quality reconstruction from sparse-view neutron CT. Pretrained purely on synthetic data, DINR is evaluated on simulated and experimentally obtained observations of concrete microstructures, where traditional reconstruction methods suffer substantial degradation when the number of views is reduced. Our approach delivers superior performance, reduces reconstruction artifacts, and achieves gains in PSNR and SSIM, enabling accurate micro-structural characterization even under extreme data limitations compared to state-of-the-art sparse-view reconstruction techniques.

Hossain, Maliha [ORNL]↗
DOE OSTI2022

Peripheral Nerve Magnetoneurography With Optically Pumped Magnetometers

Electrodiagnosis is routinely integrated into clinical neurophysiology practice for peripheral nerve disease diagnoses, such as neuropathy, demyelinating disorders, nerve entrapment/impingement, plexopathy, or radiculopathy. Measured with conventional surface electrodes, the propagation of peripheral nerve action potentials along a nerve is the result of ionic current flow which, according to Ampere’s Law, generates a small magnetic field that is also detected as an “action current” by magnetometers, such as superconducting quantum interference device (SQUID) Magnetoencephalography (MEG) systems. Optically pumped magnetometers (OPMs) are an emerging class of quantum magnetic sensors with a demonstrated sensitivity at the 1 fT/√Hz level, capable of cortical action current detection. But OPMs were ostensibly constrained to low bandwidth therefore precluding their use in peripheral nerve electrodiagnosis. With careful OPM bandwidth characterization, we hypothesized OPMs may also detect compound action current signatures consistent with both Sensory Nerve Action Potential (SNAP) and the Hoffmann Reflex (H-Reflex). In as much, our work confirms OPMs enabled with expanded bandwidth can detect the magnetic signature of both the SNAP and H-Reflex. Taken together, OPMs now show potential as an emerging electrodiagnostic tool.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Double-Helical Tiled Chain Structure of the Twist-Bend Liquid Crystal Phase in CB7CB

The twist-bend nematic liquid crystal phase is a three-dimensional fluid in which achiral bent molecules spontaneously form an orientationally ordered, macroscopically chiral, heliconical winding of a ten nanometer-scale pitch in the absence of positional ordering. Here, the structure of the twist-bend phase of the bent dimer CB7CB and its mixtures with 5CB is characterized, revealing a hidden invariance of the self-assembly of the twist-bend structure of CB7CB, such that over a wide range of concentrations and temperatures, the helix pitch and cone angle change as if the ground state for a pitch of the TB helix is an inextensible heliconical ribbon along the contour formed by following the local molecular long axis (the director). Remarkably, the distance along the length for a single turn of this helix is given by 2πR mol , where R mol is the radius of bend curvature of a single all-trans CB7CB molecule. This relationship emerges from frustrated steric packing due to the bent molecular shape: space in the fluid that is hard to fill attracts the most flexible molecular subcomponents, a theme of nanosegregation that generates self-assembled, oligomer-like correlations of interlocking bent molecules in the form of a brickwork-like tiling of pairs of molecular strands into duplex double-helical chains. At higher temperatures in the twist-bend phase, the cone angle is small, the director contour is nearly along the helix axis z, and the duplex chains are sequences of biaxial elements formed by overlapping half-molecule pairs, with an approximately 45° rotation of the biaxis between each such element along the chain.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantifying Background Magnetic Fields at Marine Energy Sites: Challenges and Recommendations

Unknowns around the environmental effects of marine renewable energy have slowed the deployment of this emerging technology worldwide. Established testing methods are necessary to safely permit and develop marine energy devices. Magnetic fields are one potential cause of environmental effects and are created when electricity is generated and transmitted to shore. Further, the existing variation of the background magnetic field at sites that may be developed for marine energy is largely unknown, making it difficult to assess how much additional stress or impact the anthropogenic magnetic field may have. This study investigates two instruments for their ability to characterize the background magnetic fields at a potential marine energy site in Sequim Bay, WA. Based on this evaluation, this study recommends an Overhauser magnetomer for assessing the background magnetic field and demonstrates the use of this sensor at a potential marine energy site.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Distributed Real-time Plume Monitoring for Deep Sea Mineral Extraction​

In the emerging industry of deep-sea mining for minerals and deposits (e.g. polymetallic nodules for nickel, cobalt, copper, and manganese), more data is required to understand the effects of sediment plume generation and predict the distribution of disturbed sediment. There are two main sources of plume generation, the first being at the active mining site where the “collector” directly removes the top layer of the sea floor. The other is the “midwater plume” consisting of unwanted sediment that was collected during extraction that is pumped back into the aphotic zone. The vast majority of plume generation is caused by the collector, causing detrimental and long-lasting impacts on seafloor ecosystems due to the lack of wave activity or strong currents at the sea floor. Therefore, it is crucial to invest in the infrastructure to support the study and constant monitoring over a large area of the sea floor where plume generation is present. Due to the limited number of usable channels and power requirements, current subsea wireless communications technologies are not well suited to instrumenting the large areas of the sea floor needed to monitor plume migration. The scope of this effort is to transition experimental demonstrations of high-bandwidth, full-duplex scalable underwater laser communications to the seafloor in an open ocean environment. Specifically tackling challenges associated with the dynamic nature of the subsea world, including but not limited to, deployment logistics, sustainability, and range. The goal is to enable the internet of underwater things for deep sea industries by broadening the capabilities of subsea communications. By using high-precision laser transmitters, many of the challenges current subsea optical systems face can be circumvented, such as power consumption, interference, and bandwidth limitations. This approach lends itself to wireless interlinking multi-node networks, in series or parallel, facilitating the implementation of a wide array of sensor types. This interlinking allows all the data gathered from the network to be processed through a single hardline uplink to the surface, lowering the complexity required for near real-time data processing. Additionally, the laser control systems produce metadata that can be used to help characterize the water column between the nodes. Combining data from various sensors such as turbidity, temperature, current velocity with metadata such as beam attenuation and deflection can produce a high-resolution model of sea floor conditions around an active mining zone. The resulting near real-time model can be used to optimize location and flow rate of the mining operation to minimize and quantify the environmental impact.

Mons, Ishan↗
DOE OSTI2022

Qualification of Continuous Fiber Reinforced 3D Printed Material for use in Hot Cell Environments

The ability to employ additively manufactured polymers in highly radioactive environments facilitates rapid prototyping as well as emergency replacement of various equipment components contained in-cell. A technical evaluation (TEV) exists seeking to qualify 3D printed polymers and carbon reinforcements for use in-cell, the data generated in this project seeks to support the TEV. The goal of the study is to determine if the loss in mechanical properties is low enough to justify semi-permanent use in-cell.

3D printing↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

In real-world applications like spectrum management and interference detection, dealing with unseen electromagnetic waveforms is critical. Although some methods attempt to simulate open set data using generator models, they face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. This results in difficulties capturing distinctive features across classes, especially in dynamic scenarios where new classes emerge. To detect unseen waveforms, we propose combining time and frequency domain features with cosine similarity loss to enhance feature distinctiveness and enabling more accurate predictions. This approach efficiently captures more comprehensive information than single-domain representations or approaches without cosine loss. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10\% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Benefits and risks of lead halide perovskite photovoltaics

Photovoltaics (PV) do not emit anything during operation, but, over their life-cycle, emissions are generated from the use of fossil-fuels in the extraction and production of materials and in the manufacturing and installation of PV components and systems. Nonetheless, these emissions are always very small compared to those from conventional combustion-based generators of electricity. The case for CO2 emissions has been well documented; over their lifetime, they range from 10 g CO2-eq / kWh for CdTe PV system installed in high-irradiation (2300 kWh/(m2-yr) locations to 80 g CO2-eq / kWh for Chinese single-crystalline silicon PV systems installed in low-irradiation (1000 kWh/(m2-yr) locations,1 compared to ~1000 g CO2-eq/kWh for electricity from coal. However, in the case of the rapidly emerging lead halide perovskite PV (LHP-PV) technology, concerns are raised regarding the potential of emissions of lead from the life-cycles of LHP-PV, including at their end of life. This warranted an evaluation of lead emissions from PV and comparisons with emissions in other power generation life-cycles.

Perovskites, PV, Lead, Risks↗
DOE OSTI2020

Vendor-Independent Design Requirements for a Boiling Water Reactor Safety System Upgrade

This Vendor-Independent License Amendment Request (LAR) Framework Document is a research product developed for the Idaho National Laboratory Light Water Reactor Sustainability (LWRS) Program. It was developed by MPR Associates, Inc. with technical input from LWRS and Exelon Generation personnel. To accomplish the purpose of this research, an operating plant (Limerick Generating Station [LGS]) was used as a reference to provide a concrete example and to present a "top-down" view of design concepts consistent with functional requirements baseline documents (references X and Y) also developed for this research. While this document is written in a framework to support a complete LAR submittal, its purpose is to communicate research concepts and provide an example of how to present digital information necessary to address expectations with regard to leveraging the Alternate Review Process as provided in Digital Instrumentation and Controls Interim Staff Guidance #06, Revision 2, Licensing Process. To leverage that process, this research document presupposes that a utility would select a vendor platform which has been prequalified for safety-related by the United States Nuclear Regulatory Commission. While this document is written using the Exelon Generation Limerick Generating Station (LGS) Units 1 and 2 as a baseline, this document is a research product. This document contains no commitments and makes no binding design decisions for Exelon Generation. Exelon Generation is leveraging this research to support their in-progress LGS Plant Protection System (PPS) upgrade efforts and plans to leverage it for their Redundant Reactor Control System (RRCS) replacement. The LWRS Program appreciates the research support provided by Exelon Generation in the generation of this document.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Density Functional Tight-Binding Enables Tractable Studies of Quantum Plasmonics

Routine investigations of plasmonic phenomena at the quantum level present a formidable computational challenge due to the large system sizes and ultrafast time scales involved. This Feature Article highlights the use of density functional tight-binding (DFTB), particularly its real-time time-dependent formulation (RT-TDDFTB), as a tractable approach to study plasmonic nanostructures from a quantum mechanical purview. We begin by outlining the theoretical framework and limitations of DFTB, emphasizing its efficiency in modeling systems with thousands of atoms over picosecond time scales. Applications of RT-TDDFTB are then explored in the context of optical absorption, nonlinear harmonic generation, and plasmon-mediated photocatalysis. We demonstrate how DFTB can reconcile classical and quantum descriptions of plasmonic behavior, capturing key phenomena such as size-dependent plasmon shifts and plasmon coupling in nanoparticle assemblies. Lastly, we showcase DFTB’s ability to model hot carrier generation and reaction dynamics in plasmon-driven H2 dissociation, underscoring its potential to model photocatalytic processes. Collectively, these studies establish DFTB as a powerful, yet computationally efficient tool to probe the emergent physics of materials at the limits of space and time.

Electrical energy↗
DOE OSTI2022

Representing Socio‐Economic Uncertainty in Human System Models

Abstract Socio‐economic development pathways and their implications for the environment are highly uncertain, and energy transitions will involve complex interactions among sectors. Here, traditional Monte Carlo analysis is paired with scenario discovery techniques to provide a richer portrait of these complexities. Modeled uncertain input variables include costs of advanced energy technologies, energy efficiency trends, fossil fuel resource availability, elasticities of substitution for labor, capital, and energy across economic sectors, population growth, and labor and capital productivity. The sampled values are simulated through a multi‐sector, multi‐region, recursively dynamic model of the world economy to explore a range of possible future outcomes. We find that many patterns of energy and technology development are possible for various long‐term environmental pathways and that sectoral output for most sectors is little affected through 2050 by the long‐term temperature target, but with tight constraints on emissions, emission intensities must fall much more rapidly. Scenario discovery techniques are applied to the large uncertainty ensembles to explore if there are prevailing storylines behind outcomes of interest. An illustrative investigation focused on different levels of economic growth shows many combinations of pathways and no single storyline emerging for a given economic outcome. This method can be extended to other outcomes of interest, exploring the nature of scenarios with both tail and median outcomes. Sampling from a Monte Carlo generated ensemble provides a rich set of scenarios to investigate, and potentially aids in avoiding heuristic biases in less structured scenario approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Influence of monsoon low pressure systems on South Asian disasters and implications for disaster prediction

Transient atmospheric vortices called monsoon low pressure systems (LPS) generate a large fraction of total rainfall over South Asia and often produce extreme precipitation. Here, we assess the influence of these storms on the occurrence of disasters, using information from the Emergency Events Database (EM-DAT) that we geocoded and then associated with LPS tracks. We show that more than half of hydro-meteorological disasters over South Asia during summer are associated with these LPS events. Weaker LPS (which are called monsoon lows) occur more frequently than stronger LPS (called monsoon depressions), but the stronger LPS produce a larger number of disasters. Furthermore, although many prior studies have shown that the peak rainfall in LPS falls southwest of the vortex centre, the disasters are concentrated on the northern edge of the LPS tracks, along the Himalayas and upper basins of the Ganga and Brahmaputra rivers. Observations show a sharp peak in rainfall on the day of disasters, confirming the physical link between LPS and these hydro-meteorological disasters. A similar peak in rainfall is found in weather forecasts made up to five days before the disaster, suggesting that short-term precipitation forecasts can be useful in disaster preparation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Where Is the Provenance? Ethical Replicability and Reproducibility in GIScience and Its Critical Applications

As replicability and reproducibility (R&R) crises develop within emerging convergent inquiry, ethical use of provenance information is central to the establishment and preservation of trust in critical applications of GIScience and geospatial technologies. Today large volumes of geospatial data are generated at high velocity from satellite sensors and unmanned aircraft systems, citizen sensors, geolocation-based data services, global navigation satellite systems, and so on. The extensive use of these data for applications such as disaster and humanitarian response raises the issue of R&R from competing perspectives of location privacy and geospatial data quality. Although geospatial data can be integrated and linked with contextual information to identify individuals’ movements, steps taken to ensure privacy can complicate the multiuser development of high-quality geospatial workflows. Provenance information as digital records of historical (retrospective) and potential future (prospective) geospatial processes is often overlooked, misunderstood, or inadequately addressed. We explore the relationship between provenance information, location privacy, and geospatial data quality in the context of R&R with a focus on disaster analytics. Here, we argue that in the era of big data and deep learning, GIScientists and associated institutions bear greater responsibility both for geospatial workflow quality and for location privacy. Given vastly heterogenous computational landscapes, we provide practical recommendations for ethically driven provenance and R&R research and development within the GIScience community and beyond.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Development and experimental qualification of novel disruption prevention techniques on DIII-D

Novel disruption prevention solutions spanning a range of control regimes are being developed and tested on DIII-D to enable ITER success. First, a new real-time control algorithm has been developed and tested for regulating nearness to stability limits and maintaining safety-margins. Its first application has been for reliable prevention of vertical displacement events (VDEs) by adjusting plasma elongation (κ) and the inner-gap between the plasma and inner-wall in response to real- time open-loop VDE growth rate (γ) estimators. VDEs were robustly prevented up to average open-loop growth rates of 800 rad/s with initial tunings, with only applying shape modification when near safety limits. Second, the disruption risk during fast, emergency shutdown after large tearing and locked modes can be significantly improved by transitioning to a limited topology during shutdown. More than 50% of emergency limited shutdowns after locked modes reach a final normalized current I_N < 0.3 before terminating, scaling to the 3 MA ITER requirement. Furthermore, this is in contrast to diverted shutdowns, the majority of which disrupt at I_N > 0.8. Despite improvements, these results highlight the critical importance of early prevention. Third, a novel emergency shut down method has been developed which excites instabilities to form a warm, helical core post-thermal quench. The current quench extends to ~100ms and avoids VDEs and runaway electron generation. Novel real-time machine learning disruption prediction has been integrated with the DIII-D proximity controller, and a real- time compatible multi-mode MHD spectroscopy technique has been developed. Results presented here were enabled by a focused effort, the Disruption Free Protocol, in DIII-D’s 2019-20 campaign to complement disruption prevention experiments with a large piggy-back program. In addition to testing novel techniques, it is estimated to have helped avoid 32 potential disruptions in piggyback operations with rapid, early shutdowns after large rotating n=1 or locked modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗