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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear Quadrupole Resonance for Substance Detection

This review paper provides a comprehensive overview of recent advances in nuclear quadrupole resonance (NQR) spectroscopy for substance detection, highlighting its principles, methodologies, and applications. The paper elucidates the fundamental physics underlying NQR spectroscopy, emphasizing the interaction between nuclear quadrupole moments and electric field gradients. It explores the various experimental techniques and instrumentation developments that have enabled the sensitive detection and precise characterization of substances containing quadrupolar nuclei. A significant portion of the survey is dedicated to discussing the diverse applications of NQR spectroscopy, including the detection of explosives, drug pharmaceuticals, and material authentication. Furthermore, the survey examines the challenges and limitations associated with NQR spectroscopy, including issues related to signal-to-noise ratio (SNR), temperature dependency, and substance restrictions. Strategies to overcome these challenges are discussed, offering insights into the future directions of NQR spectroscopy research that includes artificial intelligence (AI), internet of things (IoT) integration, incorporating a cloud database for NQR parameter storage, and multi-modal analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Observation of the distribution of nuclear magnetization in a molecule

Precise experimental control and interrogation of molecules and calculations of their structure are enriching the investigation of nuclear and particle physics phenomena. Molecules containing heavy, octupole-deformed nuclei, such as radium, are of particular interest. Here, we report precision laser spectroscopy measurements and theoretical calculations of the structure of the radioactive radium monofluoride molecule 225 Ra 19 F. Our results reveal fine details of the short-range electron-nucleus interaction, indicating the high sensitivity of this molecule to the distribution of magnetization, within the radium nucleus. Here, these results provide a stringent test of the description of the electronic wave function inside the nuclear volume, highlighting the suitability of these molecules for investigating subatomic phenomena.

Nuclear structure↗
DOE OSTI2024

Probing nuclear structure of heavy ions at energies available at the CERN Large Hadron Collider

We perform high-statistics simulations to study the impacts of nuclear structure on the ratios of anisotropic flow observables in 208 Pb + 208 Pb and 129 Xe + 129 Xe collisions at the Large Hadron Collider. Even with 40% difference in atomic numbers between 208 Pb and 129 Xe nuclei, the ratios of anisotropic flow in the same centrality class between the two collision systems are strongly affected by the nuclear structure inputs in the initial state. The ratios of v 2 ⁡{4}/v 2 ⁡{2} in these collisions are sensitive to the nuclear skin thickness of the colliding nuclei, providing indirect constraints on the nuclei's neutron skin. In conclusion, our model predictions serve as a benchmark to compare with experimental measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Neutrino Theory in the Precision Era

This document summarises discussions on future directions in theoretical neutrino physics, which are the outcome of a neutrino theory workshop held at CERN in February 2025. The starting point is the realisation that neutrino physics offers unique opportunities to address some of the most fundamental questions in physics. This motivates a vigorous experimental programme which the theory community fully supports. \textbf{A strong effort in theoretical neutrino physics is paramount to optimally take advantage of upcoming neutrino experiments and to explore the synergies with other areas of particle, astroparticle, and nuclear physics, as well as cosmology.} Progress on the theory side has the potential to significantly boost the physics reach of experiments, as well as go well beyond their original scope. Strong collaboration between theory and experiment is essential in the precision era. To foster such collaboration, \textbf{we propose to establish a CERN Neutrino Physics Centre.} Taking inspiration from the highly successful LHC Physics Center at Fermilab, the CERN Neutrino Physics Centre would be the European hub of the neutrino community, covering experimental and theoretical activities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Solar fusion III: New data and theory for hydrogen-burning stars

In stars that lie on the main sequence in the Hertzsprung-Russell diagram, like our Sun, hydrogen is fused to helium in a number of nuclear reaction chains and series, such as the proton-proton chain and the carbon-nitrogen-oxygen cycles. Precisely determined thermonuclear rates of these reactions lie at the foundation of the standard solar model. This review, the third decadal evaluation of the nuclear physics of hydrogen-burning stars, is motivated by the great advances made in recent years by solar neutrino observatories, putting experimental knowledge of the proton-proton (𝑝⁢𝑝)-chain neutrino fluxes in the few-percent precision range. The basis of the review is a one-week community meeting held in July 2022 in Berkeley, California, and many subsequent digital meetings and exchanges. The relevant reactions of solar and stellar hydrogen burning are reviewed here from both theoretical and experimental perspectives. Recommendations for the state of the art of the astrophysical 𝑆 factor and its uncertainty are formulated for each of them. Furthermore, several other topics of paramount importance for the solar model are reviewed as well: recent and future neutrino experiments, electron screening, radiative opacities, and current and upcoming experimental facilities. In addition to reaction-specific recommendations, general recommendations are also formed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Data-driven analysis of dipole strength functions using artificial neural networks

Here, we present a data-driven analysis of dipole strength functions across the nuclear chart, employing an artificial neural network to model nuclear dipole responses. We train the network on a dataset of experimentally measured dipole strength functions for 216 different nuclei. To assess its predictive capability, we test the trained model on an additional set of 10 new nuclei, where experimental data exist. We demonstrate that the artificial neural network not only accurately reproduces known data but also identifies potential inconsistencies in experimental datasets, indicating which results may warrant further review or possible rejection. For nuclei where experimental data are sparse or unavailable, the network confirms theoretical calculations, reinforcing its utility as a predictive tool in nuclear physics. Finally, utilizing the predicted electric dipole polarizability, we extract the value of the symmetry energy at saturation density and find it consistent with results from the literature.

artificial neural networks↗
DOE OSTI2025

Experimental search for the chiral magnetic effect in relativistic heavy-ion collisions: A perspective

The chiral magnetic effect (CME) refers to generation of the electric current along a magnetic field in a chirally imbalanced system of quarks. The latter is predicted by quantum chromodynamics to arise from quark interaction with nontrivial topological fluctuations of the vacuum gluonic field. The CME has been actively searched for in relativistic heavy-ion collisions, where such gluonic field fluctuations and a strong magnetic field are believed to be present. The CME-sensitive observables are unfortunately subject to a possibly large non-CME background, and firm conclusions on a CME observation have not yet been reached. In this perspective, we review the experimental status and progress in the CME search, from the initial measurements more than a decade ago to the dedicated program of isobar collisions in 2018 and the release of the isobar blind analysis result in 2022 to intriguing hints of a possible CME signal in Au + Au collisions, and discuss future prospects of a potential CME discovery in the anticipated high-statistic Au + Au collision data at the Relativistic Heavy-Ion Collider by 2025. We hope such a perspective will help sharpening our focus on the fundamental physics of the CME and steer its experimental search.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Scattering Calorimeter FY24 Deliverable Report

A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Efficient simulation of optical spectra via machine learning and physical decomposition of environmental effects

Simulations of optical spectra can provide key insights to aid experimental interpretation of electronic excitation phenomena. For chromophores in the condensed phase, these spectra, which incorporate the coupling between electronic excitation and molecular and solvent nuclear motions, can be simulated using excitation energies obtained from molecular dynamics simulations of the chromophore and solvent. Here, we present a hybrid scheme that exploits machine learning and physically informed spectral densities to show that as few as 25 ground and excited state energetic gradient calculations can be used to construct models that accurately predict environment-influenced vibronic coupling in optical spectra. We demonstrate our approach for the green fluorescent protein chromophore in water and the cresyl violet chromophore in methanol. We show that our hybrid approach, employing a machine learning model for the high-frequency spectral density and an ab initio parameterized Debye spectral density for the low-frequency, results in a systematic improvement of the optical absorption lineshape, leading to a simple machine learning scheme that can be used for the simulation of spectral densities and optical spectra.

Snider, Andrew [Univ. of California, Merced, CA (U↗
DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Discovering nuclear models from symbolic machine learning

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated Symbolic Regression approach that handles symbolic regressions over multiple target observables, accounts for experimental uncertainties and is robust against high-dimensional problems. As a proof of principle, we applied this method to describe the nuclear binding energies and charge radii of light and medium mass nuclei. Our approach identified simple analytical relationships based on the number of protons and neutrons, providing interpretable models with precision comparable to state-of-the-art nuclear models. Additionally, we integrated this ML-discovered model with an existing complementary model to estimate the limits of nuclear stability. These results highlight the potential of symbolic ML to develop accurate nuclear models and guide our description of complex many-body problems.

Nuclear structure↗
DOE OSTI2024

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Development of a New Criticality Safety Training Program for College Students

Nuclear criticality safety (NCS) expertise remains a crucial workforce need within the US Department of Energy (DOE) laboratory complex. To address this challenge, a novel university/laboratory-based nuclear criticality training certificate program is being developed through a collaborative effort between the Georgia Institute of Technology, Texas A&M University, and Oak Ridge National Laboratory. This comprehensive program implements a two-tiered certification approach that combines online theoretical coursework with hands-on experimental training to create a sustainable pipeline of nuclear criticality specialists. The program specifically targets undergraduate and graduate students in engineering, physics, and mathematics disciplines across the United States. Through integration of fundamental nuclear physics principles, practical safety applications, and experiential learning opportunities, this initiative aims to establish a standardized pathway for developing the next generation of NCS professionals.

K-Effective↗
DOE OSTI2025

Preliminary Plan to Inform Testing of a Heat Exchanger Test Article

This report presents a preliminary plan to guide the qualification testing of advanced heat exchanger (HX) components for nuclear-to-industrial heat transfer applications. The objective is to establish a defensible, physics-based methodology that integrates computational modeling, targeted experimentation, and in-service inspection considerations to demonstrate component performance and reliability under representative reactor conditions. The analysis identifies Sodium-cooled Fast Reactor (SFR) and High-Temperature Gas-cooled Reactor (HTGR) systems as reference configurations in terms of temperature, pressure, and chemical environment. Within these operating envelopes, dominant degradation mechanisms— including creep–fatigue interaction, flow-induced vibration, corrosion, and diffusion-bond deterioration—were evaluated to define test requirements. A comprehensive computationalexperimental framework is proposed to support life prediction and qualification activities. The framework couples high-fidelity structural-mechanics, thermal-hydraulic, and fluid-structure interaction models with accelerated degradation testing to produce a traceable linkage between microstructural evolution, mechanical performance, and remaining useful life (RUL). The approach adheres to established Verification, Validation, and Uncertainty Quantification (VVUQ) standards (ASME V&V 10/20; NUREG-2152) and incorporates a digital-twin architecture for continuous model refinement through data assimilation. The plan further outlines testing methodologies, including pre-test analyses, test-loop design parameters, and sensor placement strategies that maximize information yield while maintaining mechanistic fidelity. Complementary sections describe in-service inspection (ISI), on-line monitoring (OLM), and structural-health-monitoring (SHM) techniques applicable to compact HX geometries typical of advanced reactors. Collectively, these activities establish the technical foundation for demonstrating 40-60-year equivalent service life of advanced heat exchangers in support of the U.S. Department of Energy’s Advanced Reactor and Integrated Energy Systems programs. The forthcoming phase will execute the defined pre-test analyses, initiate hardware fabrication, and implement the integrated testing campaign to validate the proposed qualification methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗