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At least 667 records · Page 37

Lowest-energy broad 𝛼-cluster resonances in 19 F

There is strong astrophysical interest in the structure of 19 F states near the α-decay threshold, as their properties are important for understanding the development of α clustering in the 20 Ne region. The emergence of clustered states, and more generally of states that couple strongly to reaction channels near their decay thresholds, is also a topic of current interest in theoretical nuclear physics. In this work, we determine the parameters of broad low-spin states in 19 F near the α-decay threshold and present a theoretical study of these states. The analysis is restricted to ℓ = 0 and 1 resonances in the α + 15 N system close to the α threshold in 19 F. Excitation functions for 15 N(α,α) elastic scattering were measured using the Thick Target Inverse Kinematics (TTIK) method, and these new data, together with older high–energy-resolution measurements, were analyzed within the R-matrix framework. The nuclear structure of 19 F was calculated using configuration-interaction methods with a recently developed effective interaction Hamiltonian. As a result, we identify a sequence of α-cluster resonances in 19 F and map the distribution of clustering strength, which is relevant for astrophysical reaction modeling and for the theoretical understanding of many-body dynamics and the emergence of clustering in loosely bound or unstable nuclei. Furthermore, the work advances theoretical insight into the origins of clustering and highlights open questions for future theoretical and experimental studies.

19F↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

The hTERT core promoter forms three parallel G-quadruplexes

The structure of the 68 nt sequence with G-quadruplex forming potential within the hTERT promoter is disputed. One model features a structure with three stacked parallel G-quadruplex units, while another features an unusual duplex hairpin structure adjoined to two stacked parallel and antiparallel quadruplexes. We report here the results of an integrated structural biology study designed to distinguish between these possibilities. As part of our study, we designed a sequence with an optimized hairpin structure and show that its biophysical and biochemical properties are inconsistent with the structure formed by the hTERT wild-type sequence. By using circular dichroism, thermal denaturation, nuclear magnetic resonance spectroscopy, analytical ultracentrifugation, small-angle X-ray scattering, molecular dynamics simulations and a DNase I cleavage assay we found that the wild type hTERT core promoter folds into a stacked, three-parallel G-quadruplex structure. The hairpin structure is inconsistent with all of our experimental data obtained with the wild-type sequence. All-atom models for both structures were constructed using molecular dynamics simulations. These models accurately predicted the experimental hydrodynamic properties measured for each structure. We found with certainty that the wild-type hTERT promoter sequence does not form a hairpin structure in solution, but rather folds into a compact stacked three-G-quadruplex conformation.

59 BASIC BIOLOGICAL SCIENCES↗

Inelastic Neutron Scattering Study of Magnetic Exchange Pathways in MnS

We report an investigation of the magnetic structure and magnetic exchange pathways in MnS via neutron scattering methods, aided by density functional theory (DFT) modeling. The material has been confirmed to undergo antiferromagnetic (AFM) ordering at 152 K, with the magnetic structure representing AFM stacking of ferromagnetic (FM) (111) planes of Mn magnetic moments. Correspondingly, the magnetic structure is described by a propagation vector k = (1/2, 1/2, 1/2), with the volume of the magnetic unit cell being 8 times larger than the volume of the nuclear unit cell. Analysis of inelastic neutron scattering (INS) data collected on a powder sample of MnS revealed that the next-nearest-neighbor magnetic exchange constant (J 2 ) exceeds the nearest-neighbor exchange constant (J 1 ) by more than 3 times, while in the case of MnO, which exhibits the same nuclear and magnetic structures as MnS, the J 2 /J 1 ratio was reported to be below 1.5. Although for MnO the signs of both J 1 and J 2 indicated AFM exchange interactions, machine-learning INS data analysis in combination with DFT calculations suggests that the INS data collected on MnS are best described with J 1 < 0 and J 2 > 0, corresponding to FM and AFM exchange couplings, respectively. To achieve a satisfactory fit to the experimentally observed data, the Hamiltonian used to model the INS spectra also included the next-next-nearest-neighbor magnetic exchange constant (J 3 ). The best-fit model has been obtained with the values of the exchange constants J 1 = -0.27 meV, J 2 = 1.05 meV, and J 3 = -0.19 meV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗

Computational Materials Design for Ceramic Nuclear Waste Forms Using Machine Learning, First-Principles Calculations, and Kinetics Rate Theory

Ceramic waste forms are designed to immobilize radionuclides for permanent disposal in geological repositories. One of the principal criteria for the effective incorporation of waste elements is their compatibility with the host material. In terms of performance under environmental conditions, the resistance of the waste forms to degradation over long periods of time is a critical concern when they are exposed to natural environments. Due to their unique crystallographic features and behavior in nature environment as exemplified by their natural analogues, ceramic waste forms are capable of incorporating problematic nuclear waste elements while showing promising chemical durability in aqueous environments. Recent studies of apatite- and hollandite-structured waste forms demonstrated an approach that can predict the compositions of ceramic waste forms and their long-term dissolution rate by a combination of computational techniques including machine learning, first-principles thermodynamics calculations, and modeling using kinetic rate equations based on critical laboratory experiments. By integrating the predictions of elemental incorporation and degradation kinetics in a holistic framework, the approach could be promising for the design of advanced ceramic waste forms with optimized incorporation capacity and environmental degradation performance. Such an approach could provide a path for accelerated ceramic waste form development and performance prediction for problematic nuclear waste elements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Landscape of nuclear deformation softness with spherical quasiparticle random-phase approximation

We investigate the stability and softness of nuclei against quadrupole, octupole, and hexadecapole deformation. By applying the spherical Skyrme-force Hartree-Fock Bardeen-Cooper-Schrieffer quasiparticle random phase approximation, we diagnose ground-state deformation when imaginary solutions are obtained, i.e., the spherical ground state collapses. We also calculate the multipole polarizability in spherical nuclei with no collapse, as a measure of softness. This numerically light and theoretically sound method is found able to capture deformation patterns across the nuclide chart. As a result, the connection between the intrinsic shape of nuclei and the dynamics of their low-lying collective states is established and the role of shell structure is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Composite octet baryons in a relativistic mean field description of nuclear and neutron star matter

Here, we examine the properties of composite octet baryons in the nuclear medium and neutron-star matter. The internal quark-diquark structure of the octet baryons and the equations of state of nuclear matter and neutron-star matter in the mean field approximation are described by using the three-flavor Nambu-Jona-Lasinio (NJL) model as an effective quark theory of quantum chromodynamics. After introducing our model, we first discuss the properties of single baryons and their effective meson exchange interactions in symmetric nuclear matter by using concepts of Fermi-liquid theory. Several model-independent implications of this description are derived and illustrated by numerical results obtained in our model. Second, we extend the model description to high baryon densities and investigate the equation of state of neutron-star matter and the resulting star masses. We find that the so-called hyperon puzzle persists also for the case of composite hadrons. To get more information on this point, we also investigate the role of 6-Fermi and 8-Fermi interactions, in addition to the standard 4-Fermi interactions. The strengths of those higher-order Fermi interactions is determined so as not to spoil the saturation properties of nuclear matter. Among them, an interaction characterized by a product of four-quark current operators plays a special role to stabilize the stars over a large region of central baryon densities, although it has little effect on the maximum star masses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermal Hydraulic Modeling of an Advanced Nuclear Reactor using open-source MOOSE tools

The aim of this study is to develop model of a small High Temperature Gas cooled Reactor (HTGR) including the balance of plant. This microreactor produces electricity using the thermal power of the nuclear reaction. This work utilizes the MOOSE Multiphysics simulation tools, which are mainly developed at Idaho National Laboratory (INL, Idaho, United States of America). Its thermal-hydraulics and Heat conduction Modules are used to study the fluids behavior in the primary loop and power conversion system and their interactions with the heating structures. More specifically, one verifies that the temperatures, pressures and mass flow rates of the fluids in both loops are consistent and that, at the same time, all the power transfers occur as expected. Moreover, the various mechanical components characteristics (turbine, compressor, pump) are adapted to the reactor operating conditions. This first analysis is conducted using simplified and one-dimensional model for the core. Ultimately, the obtained results are used to build a higher fidelity core model. This step aims to verify that the initial simplified simulation is consistent with the three-dimensional core modeling. In addition, the calculated material temperatures are checked. This study provides a fairly complete model of the thermal hydraulic phenomena for a particular design of High Temperature Gas cooled Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational Evaluation of Thermal Response of Open-Cell Foam With Circular Pore (Computional Evaluation of Thermal Response of Open-Cell Foam with Circular Pore)

The evaluation of effective material properties in heterogeneous materials (e.g., composites or multicomponent structures) critically relevant to a wide spectrum of applications, including nuclear power, electronic packaging, flame retardants, hypersonics, and gas turbine power. The work described in this paper is centered around the numerical assessment of the thermal behavior of porous materials obtained from finite element thermal modeling and simulation. Here, two-dimensional, steady state analyses were performed on unit cells with centered, circular pores using a second order accurate Galerkin finite element method (FEM). The effective thermal conductivities of the porous systems were examined, encompassing a range of porosities from 4.9% to 60.1%. The geometries of the models were generated based on ordered circular pores for each modeled porosity level. The system response quantity (SRQ) under investigation was the dimensionless effective thermal conductivity across the unit cell. The dimensionless effective thermal conductivity was compared across all simulated cases, producing a trend between porosity and effective thermal conductivity. In the presented investigation, the method of manufactured solutions (MMS) was used to perform code verification, and the grid convergence index (GCI) was employed to estimate discretization uncertainty as solution verification. Code verification concluded an approximately second order accurate Galerkin FEM solver. It was found that the introduction of porosity to the unit cell material structure reduces effective thermal conductivity, as anticipated. Numerical results obtained in this study are compared to an analytical solution and to a sample of empirical data.

36 MATERIALS SCIENCE↗

Hemicellulose Modulates Nanoscale Lignin Architecture in Synthetic Plant Cell Walls

Cellulose, hemicellulose, and lignin─the most abundant biopolymers on Earth─compose the structural matrix of plant biomass, providing renewable resources critical to bioenergy and sustainable materials. Despite their importance, the nanoscale mechanochemical processes underlying lignocellulose assembly during plant secondary cell wall formation remain poorly understood, hindering advancements in biomass conversion technologies. Here, in this study, we synthesize a biomimetic model system comprising cellulose–hemicellulose nanofibrils (CHN) to examine guaiacyl lignin polymerization in a physiologically relevant context. Using advanced nanocharacterization─scattering-type scanning near-field optical microscopy (s-SNOM) with infrared nanospectroscopy coupled to solid-state nuclear magnetic resonance (NMR)─we reveal that hemicellulose presence considerably modulates lignin deposition and alters its interunit bond distribution. Specifically, hemicellulose-rich environments dramatically reduce lignin deposition by approximately 50% and yield highly condensed lignin structures characterized by severely reduced β–O–4′ linkages (<2%) and suppressed β–β′ linkages. Conversely, cellulose-alone scaffolds support notably higher β–O–4′ content (∼10%), resulting in a more uniform nanoscale lignin coating. Our work helps explain how accessible hemicellulose sites, both sterically and chemically, direct radical coupling during lignification, fundamentally reshaping lignin’s nanoscale architecture. These findings deepen our mechanistic understanding of plant cell wall biosynthesis and inform strategies aimed at enhancing biomass deconstruction efficiency for sustainable bioenergy applications.

NMR↗

Thermal neutron scattering cross sections for amorphous carbon

Carbon materials are commonly found in both nuclear reactors and experimental systems. Various carbon structures occur in nuclear applications ranging from crystalline and nuclear graphite to the amorphous carbon seen in next-generation advanced reactor designs. Amorphous carbon is based on a randomized graphite-like structure and offers the unique ability to disperse impurities throughout the bulk composition. A graphite-like amorphous carbon system was modeled using the classical molecular dynamics (MD) code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). An improved version of the temperature-dependent Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used to model the carbon-carbon atomic interactions for the temperature at 300 K along with densities 1.60, 1.70, 1.85, and 2.23 g/cm{sup 3}. From the normalized velocity autocorrelation function (VACF), the phonon density of state (DOS) was then calculated as the Fourier transform of the normalized VACF. This DOS was then used as the primary input for the evaluation of the thermal scattering law (TSL, i.e. S(α,β)) and associated neutron thermal scattering cross sections. The TSL was analyzed using the Full Law Analysis Scattering System Hub (FLASSH). The amorphous structure results in shifts of the phonon DOS to lower energy modes than typically displayed for ideal crystalline graphite. This impact on the DOS is directly reflected in the TSL. Furthermore, the typical optical peak at 0.25 eV for the ideal graphite disappears for amorphous carbon, in good agreement with the expected structure. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Charge radii in covariant density functional theory: A global view

A systematic global investigation of differential charge radii has been performed within the CDFT framework for the first time. Theoretical results obtained with conventional covariant energy density functionals and the separable pairing interaction of Tian et al. [Phys. Lett. B 676, 44 (2009)] are compared with experimental differential charge radii in the regions of the nuclear chart in which available experimental data crosses the neutron shell closures at N=28,50,82, and 126. The analysis of absolute differential radii of different isotopic chains and their relative properties indicate clearly that such properties are reasonably well described in model calculations in the cases when the mean-field approximation is justified. However, while the observed clusterization of differential charge radii of different isotopic chains is well described above the N=50 and N=126 shell closures, it is more difficult to reproduce it above the N=28 and N=82 shell closures because of possible deficiencies in the underlying single-particle structure. The impact of the latter has been evaluated for spherical shapes and it was shown that the relative energies of the single-particle states and the patterns of their occupation with increasing neutron number have an appreciable impact on the evolution of the δ$\langle$r2$\rangle$N,N' values. These factors also limit the predictive power of model calculations in the regions of high densities of the single-particle states of different origin. It is shown that the kinks in the charge radii at neutron shell closures are due to the underlying single-particle structure and due to weakening or collapse of pairing at these closures. The regions of the nuclear chart in which the correlations beyond mean field are expected to have an impact on charge radii are indicated; the analysis shows that the assignment of a calculated excited prolate minimum to the experimental ground state allows us to understand the trends of the evolution of differential charge radii with neutron number in many cases of shape coexistence even at the mean-field level. It is usually assumed that pairing is a dominant contributor to odd-even staggering (OES) in charge radii. Our analysis paints a more complicated picture. It suggests a new mechanism in which the fragmentation of the single-particle content of the ground state in odd-mass nuclei due to particle-vibration coupling provides a significant contribution to OES in charge radii.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laser spectroscopy for the study of exotic nuclei

Investigation into the properties and structure of unstable nuclei far from stability is a key avenue of research in modern nuclear physics. These efforts are motivated by the continual observation of unexpected structure phenomena in nuclei with unusual proton-to-neutron ratios. In recent decades, laser spectroscopy techniques have made significant contributions in our understanding of exotic nuclei in different mass regions encompassing almost the entire nuclear chart. This is achieved through determining multiple fundamental properties of nuclear ground and isomeric states, such as nuclear spins, magnetic dipole and electric quadrupole moments and charge radii, via the measurement of hyperfine structures and isotope shifts in the atomic or ionic spectra of the nuclei of interest. These properties offer prominent tests of recently developed state-of-the-art nuclear theory and help to stimulate new developments in improving the many-body methods and nucleon–nucleon interactions at the core of these models. With the aim of exploring more exotic short-lived nuclei located ever closer to the proton and neutron driplines, laser spectroscopy techniques, with their continuous technological developments towards higher resolution and higher sensitivity, are extensively employed at current- and next-generation radioactive ion beam facilities worldwide. Ongoing efforts in parallel promise to improve the availability of these even more exotic species at next-generation facilities. Very recently, an innovative application of laser spectroscopy on molecules containing short-lived nuclei has been demonstrated offering additional opportunities for several fields of research, e.g. fundamental symmetry studies and astrophysics. Here, in this review, the basic nuclear properties measurable with laser spectroscopy will be introduced. How these observables are associated with nuclear structure and nucleon–nucleon interactions will be discussed. Following this, a general overview of different laser spectroscopy methods will be given with particular emphasis on technical advancements reported in recent years. The main focus of this article is to review the numerous highlights that have resulted from studying exotic nuclei in different mass regions with laser spectroscopy techniques since the last edition in this series. Finally, the challenges facing the field in addition to future opportunities will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

3D structure of anisotropic flow in small collision systems at energies available at the BNL Relativistic Heavy Ion Collider

Here, we present (3 + 1)-dimensional [(3 + 1)D] dynamical simulations of asymmetric nuclear collisions at the BNL Relativistic Heavy Ion Collider (RHIC). Employing a dynamical initial state model coupled to (3 + 1)D viscous relativistic hydrodynamics, we explore the rapidity dependence of anisotropic flow in the RHIC small system scan at 200 GeV center-of-mass energy. We calibrate parameters to describe central 3 He + Au collisions and make extrapolations to d + Au and p + Au collisions. Our calculations demonstrate that approximately 50% of the v 3 (p T ) difference between the measurements by the STAR and PHENIX Collaborations can be explained by the use of reference flow vectors from different rapidity regions. This emphasizes the importance of longitudinal flow decorrelation for anisotropic flow measurements in asymmetric nuclear collisions, and the need for (3 + 1)D simulations. We also present results for the beam energy dependence of particle spectra and anisotropic flow in d + Au collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermal Neutron Scattering Cross Sections for Graphitic Amorphous Carbon

Carbon materials are commonly found in both nuclear reactors and experimental systems. Various carbon structures occur in nuclear applications ranging from crystalline and nuclear graphite to the amorphous carbon seen in next-generation advanced reactor designs. Amorphous carbon is based on a randomized graphite-like structure and offers the unique ability to disperse impurities throughout the bulk composition. A graphite-like amorphous carbon system was modeled using the classical molecular dynamics (MD) code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). An improved version of the temperature-dependent Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used to model the carbon-carbon atomic interactions for the temperature at 300 K along with densities 1.60, 1.70, 1.85, and 2.23 g/cm 3 . From the normalized velocity autocorrelation function (VACF), the phonon density of state (DOS) was then calculated as the Fourier transform of the normalized VACF. This DOS was then used as the primary input for the evaluation of the thermal scattering law (TSL, i.e. S(α,β)) and associated neutron thermal scattering cross sections. The TSL was analyzed using the Full Law Analysis Scattering System Hub (FLASSH). The amorphous structure results in shifts of the phonon DOS to lower energy modes than typically displayed for ideal crystalline graphite. This impact on the DOS is directly reflected in the TSL. Furthermore, the typical features and the optical graphitic peak at 0.25 eV for the ideal graphite DOS disappear for graphite-like amorphous carbon, which shows good agreement with the expected structure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impact of shell structure on the fusion of neutron-rich mid-mass nuclei

The influence of shell effects on fusion of mid-mass nuclei is explored using isotopic chains of K and Ar ions on an oxygen target. Comparison of the reduced excitation functions reveals that the fusion cross section for the open neutron-shell projectile nuclei 41 K and 45 K is systematically larger than for the closed neutron-shell projectiles 39 K and 47 K. Furthermore, the São Paulo fusion model using matter densities from systematics fails to describe the measured excitation functions. Use of more realistic densities from a Dirac-Hartree-Bogoliubov (DHB) approach performs significantly better though it still overpredicts the closed-shell nuclei.

39 ≤ A ≤ 58↗