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DOE OSTI2024

Superallowed Nuclear Beta Decays and Precision Tests of the Standard Model

For many decades, the main source of information on the top-left corner element of the Cabibbo–Kobayashi–Maskawa quark mixing matrix, V ud , was superallowed nuclear β decays with an impressive 0.01% precision. This precision, apart from experimental data, relies on theoretical calculations in which nuclear structure–dependent effects and uncertainties play a prime role. This review is dedicated to a thorough reassessment of all ingredients that enter the extraction of the value of V ud from experimental data. We try to keep balance between historical retrospect and new developments, many of which occurred in just the past 5 years. They have not yet been reviewed in a complete manner, not least because new results are forthcoming. This review aims to fill this gap and offers an in-depth yet accessible summary of all recent developments.

ab initio methods↗

DOE OSTI2021

TNSL Overview

Thermal neutron scattering law (TNSL) data describe low-energy neutrons scattering off of bound materials, and can have a significant impact on modeling any system with slow neutrons, including nuclear reactors. Previous work to introduce TNSL data to neutron transport codes at LLNL focused on COG and TART [1], with the limitation that these codes require highly specialized data processing and formatting. We have recently increased efforts to process TNSL data with the central LLNL nuclear data processing code FUDGE, to be stored in the generalized nuclear database structure (GNDS) for use in any general transport code with the ability to read GNDS data. The first step in this effort is to verify that the TNSL processing with FUDGE yields results comparable to results obtained using the LANL nuclear data processing code NJOY. The next step is to verify the transport of thermal neutrons in Mercury (a Monte Carlo code) and Ardra (a deterministic code) against one another, as well as against the LANL Monte Carlo neutron transport code MCNP. This verification step has not been completed, due to a number of discrepancies between results obtained using differently processed data. There is ongoing effort to understand differences between FUDGE and NJOY. Finally, we map out our current capability to validate TNSL data against benchmark systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Pseudospin-doublet bands and Gallagher Moszkowski doublet bands in 100 Y

New transitions in neutron-rich 100 Y have been identified in a 9 Be + 238 U experiment with mass and Z gates to provide full fragment identification. These transitions and high spin levels of 100 Y have been investigated by analyzing the high statistics γ–γ–γ and γ–γ–γ–γ coincidence data from the spontaneous fission of 252 Cf at the Gammasphere detector array. Two new bands, 14 new levels, and 23 new transitions have been identified. The K π = 4 + new band decaying to a 1s isomeric state is assigned to be the high-K Gallagher-Moszkowski (GM) partner of the known K π = 1 + band, with the π5/2[522]Ⓧν3/2[411] configuration. This 4 + band is also proposed to be the pseudospin partner of the new K π = 5 + band with a 5 + π5/2[422] Ⓧ ν5/2[413] configuration, to form a π5/2[422] Ⓧ ν[3125/2,3/2] neutron pseudospin doublet. Here, constrained triaxial covariant density-functional theory and quantal particle rotor model calculations have been applied to interpret the band structure and available electromagnetic transition probabilities and are found to be in good agreement with experimental values.

100Y↗

DOE OSTI2021

β-decay feeding intensity distributions for 103,104m Nb

The β decays of 103,104m Nb were studied with the Summing NaI(Tl) (SuN) detector at the National Superconducting Cyclotron Laboratory. The β-decay feeding intensity distribution I β (E) for each isotope was extracted by measuring γ rays in coincidence with an emitted electron. The I β (E) was extracted via the total absorption spectroscopy technique. The I β (E) for each nucleus was compared to predictions made by the quasiparticle random-phase approximation (QRPA) model which is commonly used to calculate β-decay properties for astrophysical applications. The main goal was to provide experimental data for neutron-rich nuclei, relevant to the astrophysical r process. In addition, the extracted β-decay feeding intensity distributions can lead to a better understanding of nuclear structure in a region of rapid structure changes around A = 100. Finally, experimental data for 104m Nb are also of interest to antineutrino studies of nuclear reactors

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Evolution of structure and shapes in Er 158 to ultrahigh spin

Not Available

150 ≤ A ≤ 189↗

DOE OSTI2020

Machine Learning Approaches for Nuclear Material Accounting Data from Irradiation and Reprocessing

We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.

Drescher, Adam↗

DOE OSTI2025

Extraction of ground-state nuclear deformations from ultrarelativistic heavy-ion collisions: Nuclear structure physics context

The collective-flow-assisted nuclear shape-imaging method in ultrarelativistic heavy-ion collisions (UHICs) has recently been used to characterize nuclear collective states. In this paper, we assess the foundations of the shape-imaging technique employed in these studies. We argue that some current UHIC nuclear imaging techniques neglect fundamental aspects of spontaneous symmetry breaking and symmetry restoration in colliding ions and incorrectly infer one-body multipole moments from studies of nucleonic correlations. Therefore, the impact of this approach on nuclear structure research has been overstated. Conversely, efforts to incorporate existing knowledge on nuclear shapes into analysis pipelines can be beneficial for benchmarking tools and calibrating models used to extract information from ultrarelativistic heavy-ion experiments.

Nuclear data analysis & compilation↗

DOE OSTI2022

Signatures of muonic activation in the Majorana Demonstrator

Experiments searching for very rare processes such as neutrinoless double-beta decay require a detailed understanding of all sources of background. Signals from radioactive impurities present in construction and detector materials can be suppressed using a number of well-understood techniques. Background from in situ cosmogenic interactions can be reduced by siting an experiment deep underground. However, the next generation of such experiments have unprecedented sensitivity goals of 10 28 years half-life with background rates of 10 -5 cts/(keV kg yr) in the region of interest. To achieve these goals, the remaining cosmogenic background must be well understood. In the work presented here, Majorana Demonstrator data are used to search for decay signatures of metastable germanium isotopes. Contributions to the region of interest in energy and time are estimated using simulations and compared to Demonstrator data. Correlated time-delayed signals are used to identify decay signatures of isotopes produced in the germanium detectors. A good agreement between expected and measured rate is found and different simulation frameworks are used to estimate the uncertainties of the predictions. The simulation campaign is then extended to characterize the background for the LEGEND experiment, a proposed tonne-scale effort searching for neutrinoless double-beta decay in 76 Ge .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

A Vision for the Science of Rare Isotopes

The field of nuclear science has considerably advanced since its beginning just over a century ago. Today, the science of rare isotopes is on the cusp of a new era with theoretical and computing advances complementing experimental capabilities at new facilities internationally. In this article we present a vision for the science of rare isotope beams (RIBs). We do not attempt to cover the full breadth of the field; rather, we provide a perspective and address a selection of topics that reflect our own interests and expertise. We focus in particular on systems near the drip lines, where one often finds nuclei that are referred to as exotic and where the role of the nuclear continuum is only just starting to be explored. An important aspect of this article is its attempt to highlight the crucial connections between nuclear structure and the nuclear reactions required to fully interpret and leverage the rich data to be collected in the next years at RIB facilities. Further, we connect the efforts in structure and reactions to key questions of nuclear astrophysics.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2022

Impacts of processing decisions on TNSL cross sections and their applications

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Assessing the viability of a new subsize tensile specimen geometry for evaluation of structural nuclear and additively manufactured materials

The use of subsize specimens in nuclear materials testing has been a subject of ongoing interest due to radiation safety concerns and resource conservation needs. It is also of interest in additive manufacturing (AM), also known as 3D-printing, as subsize specimens can more accurately represent the behavior of the small, intricate geometries often produced using AM. A novel, extremely small geometry, called the Subsize Teeny (SST) was recently developed and is of interest for implementation. Given its extraordinarily small size and the complexities associated with subsize specimen testing, adequate vetting of this geometry is necessary to ensure data quality. Here, a variety of unirradiated nuclear structural materials were tested in the SST geometry and compared against the well-established SSJ3 geometry. In addition, two case studies implementing the SST as a screening geometry for AM materials were also conducted. The question of SST viability was found to be highly nuanced and will often be dependent on the context or application in question. It was determined, however, that the SST is a largely invalid geometry for exceptionally coarse-grained materials or in cases where the physical defect volume equals or exceeds 0.1 % or where the specimen machining parameters result in significant surface alterations. On the other hand, it was determined that the SST may be employed with confidence if the test material is nearly or totally free of physical defects, isotropic, demonstrates homogeneous plastic deformation, and possesses a fine-grained, nearly or totally homogeneous microstructure with at least twelve slip systems.

Additive manufacturing↗

DOE OSTI2022

Nuclear Data Sheets for A=242

Here, detailed level schemes, decay schemes, band structure, and the experimental data on which they are based are presented for all nuclei with mass number A=242. The experimental data are evaluated and adopted values are given for level and radiation properties. For references on theory refer to the NSR file at the web site given below under Cutoff Date:. This evaluation replaces the A=242 publication by Y. A. Akovali in Nuclear Data Sheets 96, 177 (2002) (2002Ak06).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Data-driven methods for diffusivity prediction in nuclear fuels

The growth rate of structural defects in nuclear fuels under irradiation is intrinsically related to the diffusion rates of the defects in the fuel lattice. The generation and growth of atomistic structural defects can significantly alter the performance characteristics of the fuel. This alteration of functionality must be accurately captured to qualify a nuclear fuel for use in reactors. Predicting the diffusion coefficients of defects and how they impact macroscale properties such as swelling, gas release, and creep is therefore of significant importance in both the design of new nuclear fuels and the assessment of current fuel types. In this article, we apply data-driven methods focusing on machine learning (ML) to determine various diffusion properties of two nuclear fuels—uranium oxide and uranium nitride. We show that using ML can increase, often significantly, the accuracy of predicting diffusivity in nuclear fuels in comparison to current analytical models. We also illustrate how ML can be used to quickly develop fuel models with parameter dependencies that are more complex and robust than what is currently available in the literature. In conclusion, these results suggest there is potential for ML to accelerate the design, qualification, and implementation of nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Nuclear Data Sheets for A=248

Available information pertaining to the nuclear structure of ground and excited states for all known nuclei with mass numbers A=248 has been compiled and evaluated. Here, the adopted level and decay schemes, as well as the detailed nuclear properties and configuration assignments based on experimental data, are presented for these nuclides. When there are insufficient data, expected values from systematics of nuclear properties and/or theoretical calculations are utilized. Unexpected or discrepant experimental results are also noted. This work supersedes the 2014 evaluation by M.J. Martin (2014Ma86).

Nesaraja, Caroline D. [Oak Ridge National Laborato↗

DOE OSTI2023

Nuclear Data Sheets for A=245

Available information pertaining to the nuclear structure of ground and excited states for all known nuclei with mass numbers A=245 have been compiled and evaluated. In this work, the adopted level and decay schemes, as well as the detailed nuclear properties and configuration assignments based on experimental data, are presented for these nuclides. When there are insufficient data, expected values from systematics of nuclear properties and/or theoretical calculations are utilized. Unexpected or discrepant experimental results are also noted. Since the last evaluation, new rotational bands in 245 Pu have been observed to high spin from transfer reaction 244 Pu( 209 Bi, 208 Biγ) by 2014Ho16. While in 245 Am, the 249 Bk α decay measurements by 2013Ah03 added a new rotational band based on π3/2[521] configuration. The 245 Pu β - decay scheme is basically what was proposed in the late 60's and 47 γ rays have still not been placed. In 245 Cm, precise alpha energies and intensities were measured by 2015Ah03 in 249Cf α decay. Their reported alpha energies of the main α group were about 2 keV lower than in the previous evaluation. The spin and parity of the g.s. of 245 Es is still ambiguous as more detailed information on the decay is needed. With the production of 249 No via fusion evaporation reaction by groups in Dubna and GSI, it's alpha decay was studied and some properties of the daughter 245 Fm were published and included in this evalaution. Information on the other nuclides is scarce and not much has been investigated since the last evaluation. A summary and compilation of the discovery of the various nuclides in this mass region is given in: 2013Fr02 ( 245 Pu, 245 Am, 245 Cm, 245 Bk, 245 Cf), 2011Me01 ( 245 Es), and 2013Th02 ( 245 Md, 245 Fm).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Predicting nucleon-nucleus scattering observables using nuclear structure theory

Developing a predictive capability for inelastic scattering will find applications in multiple areas. Experimental data for neutron-nucleus inelastic scattering is limited and thus one needs a robust theoretical framework to complement it. Charged-particle inelastic scattering can be used as a surrogate for ( n, γ ) reactions to predict capture cross sections for unstable nuclei. Our work uses microscopic nuclear structure calculations for spherical nuclei to obtain nucleon-nucleus scattering potentials and calculate cross sections for these processes. We implement the Jeukenne, Lejeune, Mahaux (JLM) semi-microscopic folding approach, where the medium effects on nuclear interaction are parameterized in nuclear matter to obtain the nucleon-nucleon ( NN ) interaction in a medium at positive energies. We solve for the nuclear ground state using the Hartree-Fock-Bogliubov (HFB) many-body method, assuming the nucleons within the nucleus interact via the Gogny-D1M potential. The vibrational excited states of the target nucleus are calculated using the quasi-particle random phase approximation (QRPA). We demonstrate our approach for spherical nuclei in the medium-mass region, showing scattering results for the 90 Zr nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗

DOE OSTI2021

Potential Foldamers Based on an ortho- Terphenyl Amino Acid

We describe the synthesis and characterization of a new class of oligomers built from a terphenyl-based amino acid. Here, these oligomeric amides are of interest because the adoption of specific conformations could potentially be driven by the coordinated formation of inter-residue hydrogen bonds and aromatic interactions. Although high-resolution structural data have proven inaccessible, circular dichroism and nuclear magnetic resonance studies suggest that the new oligomers fold concomitantly with discrete self-association in chloroform. Molecular simulations find no sign of folding as a monomer, and in fact suggest that hydrogen bond patterning is anti-cooperative, inhibiting longer helices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗