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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Emerging tension between isospin symmetry and nuclear deformation at 𝐴 = 78

Since the nuclear interaction is, to first order, isospin independent, simple relationships can be derived for 𝐸⁢2 strengths across isobaric analog states within an isobaric triplet. At the same time, there is a well-known relationship between the 2 + excitation energy and the 𝐵(𝐸⁢2;2 + → 0 + ) transition strength in deformed even-even nuclei. Here, we highlight a tension between these two trends in the 𝐴 = 78 isobaric triplet. Recent level-energy determinations indicate that the proton-rich member of the triplet, 78 Zr, is strongly deformed while recent lifetime measurements in 78 Sr and 78 Y, as extrapolated into 78 Zr, would imply that 78 Zr is weakly deformed. Furthermore, we explore the implications of this apparent contradiction and explore potential solutions.

59 ≤ A ≤ 89↗
DOE OSTI2025

Fingerprints of Triaxiality in the Charge Radii of Neutron-Rich Ruthenium

We present the first measurements with a new collinear laser spectroscopy setup at the Argonne Tandem Linac Accelerator System, utilizing its unique capability to deliver neutron-rich refractory metal isotopes produced by the spontaneous fission of 252 Cf. We measured isotope shifts from optical spectra for nine radioactive ruthenium isotopes 106–114 Ru, reaching deep into the mid-shell region. The extracted charge radii are in excellent agreement with predictions from the Brussels-Skyrme-on-a-Grid models that account for the triaxial deformation of nuclear ground states. We show that triaxial deformation impacts charge radii in models that feature shell effects, in contrast to what could be concluded from a liquid drop analysis. This indicates that this exotic type of deformation should not be neglected in regions where it is known to occur, even if its presence cannot be unambiguously inferred through laser spectroscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Generative deep-learning reveals collective variables of Fermionic systems

Complex processes of fermionic systems ranging from protein folding to nuclear fission often follow a low-dimensional reaction path parametrized in terms of a few collective variables. In nuclear theory, variables related to the shape of the nuclear density in a mean-field picture are key to describing the large amplitude collective motion of the neutrons and protons. Exploring the adiabatic energy landscape spanned by these degrees of freedom reveals the possible reaction channels while simulating the dynamics in this reduced space yields their respective probabilities. Unfortunately, this theoretical framework breaks down whenever the systems encounters a quantum phase transition with respect to the collective variables. Here, in this study, we introduce a novel generative deep-learning algorithm designed to build reaction paths that ensure that the many-fermion wave function stays differentiable with respect to the collective variables. This approach is applicable to any fermionic system described by a coherent state. We use the case of potential energy curves in the 16 O nucleus within the Hartree-Fock theory to illustrate its main features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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

Probing New Bosons and Nuclear Structure with Ytterbium Isotope Shifts

In this Letter, we present mass-ratio measurements on highly charged Yb 42+ ions with a precision of 4 ×10 -12 and isotope-shift measurements on Yb + on the 2 S 1/2 → 2 D 5/2 and 2 S 1/2 → 2 F 7/2 transitions with a precision of 4 ×10 -9 for the isotopes 168,170,172,174,176 Yb. We present a new method that allows us to extract higher-order changes in the nuclear charge distribution along the Yb isotope chain, benchmarking ab initio nuclear structure calculations. Additionally, we perform a King plot analysis to set bounds on a fifth force in the keV/c 2 to MeV/c 2 range coupling to electrons and neutrons.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Accelerator Technologies and Science: Progress and Outlook

For over half a century, high-energy particle accelerators play a key role and shape modern nuclear and particle physics, they are also the instruments at the forefront of research for material science and biology. The physics needs continuously push us to invent novel ways to increase energy and improve the performance of accelerators, reduce their cost and make them more power-efficient. Here we briefly overview the most notable accelerator facilities which recently became operational and are now employed for research in nuclear physics, basic energy sciences, neutrinos, high energy particle frontier. We also present upcoming and planned future facilities and outline their main goals, challenges, and required R&D. Focus will be given to the core accelerator technologies such as magnets, RF acceleration, and targets as we as leading beam physics developments such as beam cooling, colliding beams and plasma acceleration.

Shiltsev, Vladimir D.↗
DOE OSTI2020

The convergence of quadrupole rotational invariants from the nuclear shell model

Nuclei exhibit both single-particle and collective degrees of freedom, with the latter often subdivided into vibrational and rotational motions. Experimentally identifying the relative roles of these collective modes is extremely challenging, particularly in the face of possible shape coexistence. Model-independent, invariant quantities describing the deformation of a nucleus in the intrinsic frame have long been known but their determination potentially requires a large quantity of experimental data to achieve convergence. Through comparison with the nuclear shell model, the question of convergence is addressed. Shell-model calculations performed in the sd- and pf-shell model spaces are used to determine electric-quadrupole matrix elements for a multitude of low-lying states using the first 40 states of the relevant spins. Relative contributions to the rotationally invariant quantities from multiple states can therefore be determined. It is found that, on average, the inclusion of four intermediate states results in the leading-order invariant, $\langle\hat{Q^2}\rangle$, converging to within 10% of its true value and the triaxiality term, cos (3δ), converging to its true value, though some variance remains. Higher-order quantities relating to the softness of the nuclear shape are found to converge more slowly. The convergence of quadrupole rotationally invariant sum rules was quantified in the sd- and pf-shell model spaces and indicates the challenge inherent in a full determination of nuclear shape. The present study is limited to relatively small valence spaces. Finally, larger spaces, such as the rare-earth region, potentially offer faster convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Tasting nuclear pasta made with classical molecular dynamics simulations

Nuclear clusters or voids in the inner crust of neutron stars were predicted to have various shapes collectively nicknamed nuclear pasta. Furthermore, the recent review by López, Dorso and Frank summarized their systematic investigations into properties especially the morphological and thermodynamical phase transitions of the nuclear pasta within a Classical Molecular Dynamics model, providing further stimuli to find more observational evidences of the predicted nuclear pasta in neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

High-resolution infrared spectroscopy of supersonically cooled singlet carbenes: Bromomethylene (HCBr) in the CH stretch region

First high-resolution spectra of cold (~35 K) singlet bromomethylene HCBr in the CH stretching (v 1 ) region from 2770 to 2850 cm-1 are reported using near quantum shot-noise limited laser absorption methods in a slit jet supersonic discharge expansion source. Three rovibrational bands are identified at high S/N (20:1 - 40:1) and rotationally assigned to i) the CH stretch fundamental (v 1 ) band $\tilde{X}$(1,0,0) ← $\tilde{X}$ (0,0,0) and ii) vibrational hot bands ($\tilde{X}$(1,1,0) ← $\tilde{X}$(0,1,0) and $\tilde{X}$(1,0,1) ← $\tilde{X}$(0,0,1)) arising from vibrationally excited HCBr populated in the discharge with single quanta in either the H–C–Br bend (v 2 ) or C–Br stretch (v 3 ) modes. Precision rotational constants are reported for a total of six states, with an experimentally determined CH stretch vibrational frequency (2799.38 cm -1 ) in good agreement with previous low-resolution fluorescence studies. Detailed analysis of the fundamental v 1 band highlights the presence of perturbations in the $\tilde{X}$(1,0,0) level, which we tentatively attribute to arise from the nearby triplet state $\tilde{a}$(0,0,1) through spin-orbit interaction or the multiple quanta $\tilde{X}$(0,2,1) singlet state via c-type Coriolis coupling. Reduced-Doppler resolution (60 MHz) in the slit-jet IR spectrometer permits clear observation of nuclear spin hyperfine structure, with experimental line shapes well reproduced by nuclear quadrupole/spin-rotation coupling constants from microwave studies. Lastly, the a-type to b-type transition intensity ratio for the fundamental CH stretch band is notably larger than predicted by a bond-dipole model, which from high level ab initio quantum calculations (CCSD(T)/PVQZ) can be attributed to vibrationally induced “charge-sloshing” of electron density along the polar C–Br bond.

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

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as “characteristic communities of microorganisms” found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Self-absorption and Phonon Pulse Shape Discrimination in Scintillating Bolometers

In this work, we show that self-absorption of photons in scintillating bolometers can differentiate phonon pulse shapes between α (or nuclear recoil) and β/γ signals. This enables phonon pulse shape discrimination for particle identification. We establish a detector signal model that includes self-absorption and compare the simulated phonon pulse shapes with previously reported experimental results. The model predicts increase in pulse shape difference at higher self-absorption. Based on this result, we propose a new design of scintillating bolometers using 4π light reflectors for maximized self-absorption and only a single phonon readout, instead of light detectors that are typically employed for particle discrimination in scintillating bolometers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Ab initio computations of strongly deformed nuclei near Zr 80

Nuclei around N ≈ Z ≈ 40 are strongly deformed and exhibit coexistence of shapes. These phenomena have challenged nuclear models. Here, we perform ab initio coupled-cluster computations of low-lying collective states and electromagnetic quadrupole transitions of the even-even nuclei 72 Kr, 76,78 Sr, 78,80 Zr, and 84 Mo starting from chiral nucleon-nucleon and three-nucleon forces. Our calculations reproduce the coexistence of oblate and prolate shapes in these nuclei, yield rotational bands and strong electromagnetic transitions, but are not accurate for some observables and nuclei. Finally, these results highlight the advances and challenges of ab initio computations of heavy deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Data-driven approach to Core Power distribution reconstruction in a Nuclear Reactor

This report presents the initial development of a data-driven approach for reconstructing the core power distribution in a nuclear reactor (power shape synthesis) using ex-core sensors. Traditional techniques rely on deploying a large number of detectors throughout the reactor core. However, this approach is not feasible for innovative reactor concepts like Advanced Reactors and Microreactors. First, the tight lattice pitch, designed to maximize power density, limits the space available for sensors. Secondly, the harsh operating conditions are not compatible with commercially available detectors. The method proposed in this work integrates high-fidelity modeling with data-driven techniques to accurately reconstruct power distribution across various reactor types, thereby reducing the reliance on in-core sensors. Purdue University Reactor One (PUR-1) was selected as the test case. The CAD model representing the latest configuration of the PUR-1 core was imported into the OpenMC simulation framework, and the model was built. Additionally, the previously developed MCNP6 model was updated. The two models were assessed against the data collected during an experimental campaign conducted in July 2024. Thirty gold foils were placed in three Irradiation Assemblies in PUR-1 core. Using the measured activity of the irradiated foils, the neutron flux at different core locations was estimated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Exploring nuclear exotica at the limits

The study of nuclear limits has been performed and new physical mechanisms and exotic shapes allowing the extension of nuclear landscape beyond the commonly accepted boundaries have been established. The transition from ellipsoidal to toroidal shapes plays an essential role in potential extension of nuclear landscape to hyperheavy nuclei. Moreover, rotational excitations leading to the birth of particle (proton or neutron) bound rotational bands provide a mechanism for an extension of nuclear landscape beyond spin zero proton and neutron drip lines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗