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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

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

Xenon–metal pair formation in UO 2 investigated using DFT + U

A recent experimental study on a spent uranium dioxide (UO 2 ) fuel sample from Belgium Reactor 3 identified a unique pair structure formed by the noble metal phase (NMP) and fission gas [xenon (Xe)] precipitate. However, the fundamental mechanism behind this structure remains unclear. The present study aims to provide an understanding of the interaction between five different metal precipitates [molybdenum (Mo), ruthenium (Ru), palladium (Pd), technetium (Tc), and rhodium (Rh)] and the Xe fission gas atoms in UO 2 , by using density functional theory (DFT) in combination with the Hubbard U correction to compute the formation energies involved. All DFT + U calculations were performed with occupation matrix control to ensure antiferromagnetic ordering of UO 2 . The calculated formation and binding energies of the Xe and solid fission products in the NMP reveal that these metal precipitates form stable pair structures with Xe. Notably, the formation energy of Xe–metal pairs is lower than that of the isolated single defects in all instances, with Pd and Mo showing the most favorable binding energy, likely accounting for the observed pair structure formation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine learning assisted prediction of tungsten heavy alloy plasma facing component performance for fusion energy applications

Tungsten and tungsten heavy alloys (WHAs), known for their remarkably high hardness, durability, and corrosion resistance, play a critical role in the thriving development of nuclear fusion reactors in recent years. However, the exploration in tungsten alloys for the nuclear-related applications has been limited by the difficulty of manufacturing and the complexity of experiments to reproduce the environment of nuclear reaction. Therefore, this project aims to utilize nanoscale simulation methods such as density functional theory (DFT) and molecular dynamics (MD) with the help of machine learning techniques to not only understand the mechanisms of tungsten alloys but also allow us to computationally predict their mechanical behaviors under extreme environments. One critical problem of the application of WHAs in nuclear reactors is the surface melting. In the current design of the SPARC reactor, the WHA, W97Ni2.1Fe0.9 or W97NiFe, is chosen to be the first wall components to confine the plasma where the particles are fiercely moving and colliding into each other to create nuclear fusion reaction. This process will generate extremely high heat flux onto these WHA tiles, leaving high surface temperature that could possibly melt the surface of the WHA tiles, As illustrated in Fig. 1(a). a laser experiment previously done illustrates that a rough surface damage would be made after the surface melting where the matrix area mainly composed of nickel and iron as shown in Fig. 1(b), will first melt and then leave vacancies between these tungsten grains. Unfortunately, these kinds of roughness on the first-wall components could be deadly to the plasma inside a Tokmak reactor because the heat that is supposed to dissipate at a designed ratio through the tiles may in turn be excessively absorbed and accumulated on any uneven area of the surface, which will eventually make the whole nuclear reaction fail. In this project, we will introduce a machine learning potential, Allegro, based on DFT calculation and then build a MD model for W-Ni-Fe alloys.

36 MATERIALS SCIENCE↗

Facile Synthesis of Oxyhydrides by Reaction with NaBH 4 in an Open System

Oxyhydrides are an intriguing class of materials in which there is partial replacement of the oxide ion with hydride ions and oxygen vacancies. Conventional synthesis relies on vacuum sealed ampules, using long reaction times at high temperatures, limiting accessibility. Here, we demonstrate a rapid, ambient-pressure route to oxyhydride formation using NaBH 4 under flowing argon in just 1 h. This approach significantly lowers experimental barriers, enabling broader exploration of these materials. The maximum hydride incorporation, obtained using a reaction temperature of 400 °C, is given by the formula SrTiO 2.945 H 0.049 , where the hydride, oxygen vacancy, and unpaired electron concentrations are determined through thermogravimetric analysis, quantitative solid-state nuclear magnetic resonance (NMR) spectroscopy, and electron paramagnetic resonance (EPR) spectroscopy. Density functional theory simulations of the 1 H NMR shifts for candidate point defects support the assignment of the observed hydride peak, validating the efficacy of the synthetic approach. A combination of in situ and ex situ studies of the reaction pathway reveal that hydride incorporation into the perovskite occurs via direct solid-solid reaction, with higher reaction temperatures favoring NaBH 4 decomposition and H 2 (g) release over oxyhydride formation. The electronic defect structure established from the EPR and NMR studies indicate that, at ambient temperature, anion vacant sites are occupied by single electrons, whereas hydride sites do not trap electrons. As a result, this work establishes a scalable synthesis strategy and provides a computational-experimental framework for understanding defect chemistry in oxyhydrides, opening pathways for their integration into energy and electronic applications.

Anions↗

Lagrangian formulation of nuclear–electronic orbital Ehrenfest dynamics with real-time TDDFT for extended periodic systems

Here, we present a Lagrangian-based implementation of Ehrenfest dynamics with nuclear–electronic orbital (NEO) theory and real-time time-dependent density functional theory for extended periodic systems. In addition to a quantum dynamical treatment of electrons and selected protons, this approach allows for the classical movement of all other nuclei to be taken into account in simulations of condensed matter systems. Furthermore, we introduce a Lagrangian formulation for the traveling proton basis approach and propose new schemes to enhance its application for extended periodic systems. Validation and proof-of-principle applications are performed on electronically excited proton transfer in the o-hydroxybenzaldehyde molecule with explicit solvating water molecules. These simulations demonstrate the importance of solvation dynamics and a quantum treatment of transferring protons. This work broadens the applicability of the NEO Ehrenfest dynamics approach for studying complex heterogeneous systems in the condensed phase.

Calculus of variations↗

An experimental and computational investigation of the structure and spectroscopic signatures of α -UO 3

α-UO 3 is a common intermediate compound found in the nuclear fuel cycle, yet the exact crystal structure of this material has long been debated. Inconsistent computational and experimental data in previous works has led to varying conclusions between authors. Furthermore, to ensure the validity of our results in this work, the structural and spectroscopic signatures of pure phase α-UO 3 are investigated using powder X-ray diffraction and optical vibrational spectroscopy (infrared and Raman). Rietveld refinement of powder X-ray diffraction data on pure phase α-UO 3 collected in this work allows us to propose an alteration to the currently accepted C2mm structure (a = 3.9705 Å, b = 6.8553 Å, c = 4.15955 Å, α = β = γ = 90°) for α-UO 3 with no uranyl [UO 2 2+ ] bonds. Raman spectra collected using two excitation wavelengths (two instruments using 532 nm and one 785 nm) are presented, and differences with recently published results are discussed. Infrared spectra from two instruments used here agree well with recently published results, but the spectral range encompassed in our data extends past what has been reported with modern techniques. Additionally, we provide tentative vibrational mode assignments based on density functional perturbation theory calculations and resulting phonon eigenvector visualizations. Unexpected features in the optical vibrational spectra of α-UO 3 are explained by unique features in the structure we present.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Probing Interfacial Reaction Pathways in Atomic Layer Deposition on Sulfide Superionic Conductors

Sulfide superionic conductors (e.g., argyrodite Li 6 PS 5 Cl, LPSCl) are extremely promising for all solid-state batteries, but poor atmospheric stability and high interfacial reactivity limit widespread adoption. Coating LPSCl powders with ultrathin coatings using atomic layer deposition (ALD) mitigates these problems, protecting against atmospheric degradation and reducing reactivity with Li metal, yielding more stable cycling. Despite significant promise, the ALD mechanism is unknown, hampering the development of new coating chemistries. In this study, we elucidate the mechanism for Al 2 O 3 ALD on LPSCl using trimethyl aluminum (TMA) and H 2 O by combining in situ Fourier transform infrared spectroscopy, ex situ solid-state magic angle spinning nuclear magnetic resonance, UV Raman spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculations. We determine that ALD Al 2 O 3 nucleates promptly via TMA reaction with native —OH, —SH, and PS 3 -OH groups to form transient C–Al–O(S) species that are rapidly hydrolyzed during the subsequent H 2 O exposure. This reversible transformation maintains surface nucleophilicity and prevents sulfide decomposition. The resulting layer-by-layer growth leads to highly conformal Al 2 O 3 coatings on LPSCl that are readily scalable to ≥ 50 g quantities using a rotating drum fixture. This detailed understanding of ALD surface reactions provides critical insights guiding the selection of future ALD chemistries with improved performance.

atomic layer deposition↗

Density functional theory (DFT) study of UF 6 hydrolysis: reaction pathways, spectroscopy, and chemical kinetics

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the gas-phase reaction mechanism and associated chemical kinetics are poorly understood. During the performance period we undertook development of a state-of-the-art ab initio gas-phase chemical kinetics simulation workflow to model the hydrolysis of uranium hexafluroride (UF 6 ). In doing so, we addressed several outstanding issues in the theoretical treatment of uranium-containing systems. At the outset it was unclear how to generate accurate estimates of kinetic and thermodynamic data for U-containing chemical reactions. Generation of such data has been made routine. Prior to our work, the literature associated with UF 6 hydrolysis were disparate and inaccurate. This body of work provides a modern and comprehensive theoretical assessment of the reaction mechanism, molecular clustering towards deposition, and chemical kinetics. New methodological implementations and software integrations resulting from this work are also highlighted. As much as possible, our predictions were validated against experimental data including particle morphologies, vibrational spectroscopy, atomization enthalpies, and kinetic rate constants. Nevertheless, we were unable to reconcile kinetic measurements with high-accuracy simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Single nuclear spin detection and control in a van der Waals material

Optically active spin defects in solids are leading candidates for quantum sensing and quantum networking. Recently, single spin defects were discovered in hexagonal boron nitride (hBN), a layered van der Waals (vdW) material. Owing to its two-dimensional structure, hBN allows spin defects to be positioned closer to target samples than in three-dimensional crystals, making it ideal for atomic-scale quantum sensing, including nuclear magnetic resonance (NMR) of single molecules. However, the chemical structures of these defects remain unknown and detecting a single nuclear spin with a hBN spin defect has been elusive. Here we report the creation of single spin defects in hBN using 13 C ion implantation and the identification of three distinct defect types based on hyperfine interactions. We observed both S = 1/2 and S = 1 spin states within a single hBN spin defect. We demonstrated atomic-scale NMR and coherent control of individual nuclear spins in a vdW material, with a π-gate fidelity up to 99.75% at room temperature. By comparing experimental results with density functional theory (DFT) calculations, we propose chemical structures for these spin defects. Our work advances the understanding of single spin defects in hBN and provides a pathway to enhance quantum sensing using hBN spin defects with nuclear spins as quantum memories.

Quantum metrology↗

Confinement of quasi-atomic structures in Ti 2 N and Ti 3 N 2 MXene electrides

Metal carbides, nitrides, or carbonitrides of early transition metals, better known as MXenes, possess notable structural, electrical, and magnetic properties. Analyzing electronic structures by calculating structural stability, band structure, density of states, Bader charge transfer, and work functions utilizing first principle calculations, we revealed that titanium nitride MXenes, namely Ti 2 N and Ti 3 N 2 , have excess anionic electrons in their lattice voids, making them MXene electrides. Bulk Ti 3 N 2 has competing antiferromagnetic (AFM) and ferromagnetic (FM) configurations with slightly more stable AFM configuration, while the Ti 2 N MXene is nonmagnetic. Although Ti 3 N 2 favors AFM configuration with hexagonal crystal systems having 6/ mmm point group symmetry, Ti 3 N 2 does not support altermagnetism. The monolayer of the Ti 3 N 2 MXene is a ferromagnetic electride. These unique properties of having non-nuclear interstitial anionic electrons in the electronic structure of titanium nitride MXene have not yet been reported in the literature. Density functional theory calculations show TiN is neither an electride, MXene, or magnetic.

Anionic electrons↗

Neutron skins probed in proton knockout from neutron-rich nuclei

Proton-induced quasifree knockout reactions provide a powerful probe of nuclear single-particle structure and reaction dynamics in both stable and neutron-rich nuclei. Here, in this work, we develop a unified theoretical framework for the calculation of inclusive (𝑝, 2⁢𝑝) and sequential (𝑝, 3⁢𝑝) reaction cross sections and fragment momentum distributions at intermediate and relativistic energies. The approach is based on a probabilistic extension of Glauber multiple-scattering theory combined with microscopic nuclear densities obtained from Hartree-Fock-Bogoliubov calculations using Skyrme energy-density functionals. We focus in particular on the sensitivity of total cross sections and longitudinal momentum dispersions to neutron-skin thickness along isotopic chains. Our results indicate that both (𝑝, 2⁢𝑝) and (𝑝, 3⁢𝑝) reactions exhibit a systematic decrease of cross section and momentum width with increasing neutron excess, reflecting enhanced attenuation and surface bias induced by neutron skins. The effect is significantly stronger for two-proton removal, suggesting that (𝑝, 3⁢𝑝) reactions may offer enhanced sensitivity to isovector nuclear structure. These findings establish proton-induced knockout reactions as complementary hadronic probes of neutron skins and the density dependence of the nuclear symmetry energy.

direct reactions↗

Self-Learning Kinetic Monte Carlo Simulations of Radiation Damage in Nuclear Fuels

Understanding how irradiation affects the thermo-physical and mechanical properties of nuclear materials, such as thermal conductivity degradation in fuels and embrittlement of structural components, is critical to the safety and efficiency of nuclear reactors. These effects are largely governed by the formation and evolution of atomic-scale point defects and defect clusters. Due to their small sizes, however, these defects are invisible under high-resolution scanning transmission electron microscopy. This project aims to fill this experimental knowledge gap by integrating density functional theory (DFT), machine learning interatomic potential (MLIP), and kinetic Monte Carlo (KMC) techniques to predict longtime evolution of irradiation-induced defects in nuclear fuels.

36 - MATERIALS SCIENCE↗

Mixed Valence {Ni 2+ Ni 1+ } Clusters as Models of Acetyl Coenzyme A Synthase Intermediates

Acetyl coenzyme A synthase (ACS) catalyzes the formation and deconstruction of the key biological metabolite, acetyl coenzyme A (acetyl-CoA). The active site of ACS features a {NiNi} cluster bridged to a [Fe4S4] n+ cubane known as the A-cluster. The mechanism by which the A-cluster functions is debated, with few model complexes able to replicate the oxidation states, coordination features, or reactivity proposed in the catalytic cycle. In this work, we isolate the first bimetallic models of two hypothesized intermediates on the paramagnetic pathway of the ACS function. The heteroligated {Ni 2+ Ni 1+ } cluster, [K(12-crown-4) 2 ][1], effectively replicates the coordination number and oxidation state of the proposed “A red ” state of the A-cluster. Addition of carbon monoxide to [1] - allows for isolation of a dinuclear {Ni 2+ Ni 1+ (CO)} complex, [K(12-crown-2) n ][2] (n = 1–2), which bears similarity to the “A NiFeC ” enzyme intermediate. Structural and electronic properties of each cluster are elucidated by X-ray diffraction, nuclear magnetic resonance, cyclic voltammetry, and UV/vis and electron paramagnetic resonance spectroscopies, which are supplemented by density functional theory (DFT) calculations. Calculations indicate that the pseudo-T-shaped geometry of the three-coordinate nickel in [1] – is more stable than the Y-conformation by 22 kcal mol –1 , and that binding of CO to Ni 1+ is barrierless and exergonic by 6 kcal mol –1 . UV/vis absorption spectroscopy on [2] - in conjunction with time-dependent DFT calculations indicates that the square-planar nickel site is involved in electron transfer to the CO π*-orbital. Further, we demonstrate that [2] - promotes thioester synthesis in a reaction analogous to the production of acetyl coenzyme A by ACS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reaction mechanisms for electrical doping of organic semiconductors using complex dopants

Electrical doping of organic semiconductors (OSCs) can be achieved using simple one-electron reductants and oxidants as n- and p-dopants, respectively, but for such dopants, increased doping strength is accompanied by increased sensitivity to ambient moisture and/or oxygen. “Indirect” or “complex” dopants—defined here as those that generate OSC radical cations or anions via pathways more complex than a single simple electron transfer, i.e., by multistep reactions—represent a means of circumventing this problem. Further, this review highlights the importance of understanding the reaction mechanisms by which such dopants operate for: (i) ensuring a researcher knows the composition of a doped material; (ii) predicting the thermodynamic feasibility of achieving doping with related dopant:OSC combinations; and (iii) predicting whether thermodynamically feasible doping reactions are likely to be rapid or slow, or to require subsequent activation. The mechanistic information available to date for some of the wide variety of complex n- and p-dopants that have been reported is then reviewed, emphasizing that in many cases our knowledge is far from complete.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isospin composition of fission barriers

We employ a microscopic method to study how isospin affects the fission potential of 240 Pu. Our approach uses constrained Hartree-Fock theory (CHF) which allows us to separately investigate the isoscalar and isovector properties of the nuclear energy density functional (EDF). By analyzing the isoscalar and isovector components of the EDF along the fission path we can assess the isovector contribution to fission barriers. Here, we study this effect for the fully adiabatic path to scission. The isovector component of the fission potential is found to increase in magnitude as the nucleus evolves towards scission, exemplifying the importance of stringent constraints on the isovector sector of the nuclear EDF for reliable predictions of fission properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Inter-Oligomer Interaction Influence on Photoluminescence in Cis-Polyacetylene Semiconductor Materials

Semiconducting conjugated polymers (CPs) are pivotal in advancing organic electronics, offering tunable properties for solar cells and field-effect transistors. Here, we carry out first-principle calculations to study individual cis-polyacetylene (cis-PA) oligomers and their ensembles. The ground electronic structures are obtained using density functional theory (DFT), and excited state dynamics are explored by computing nonadiabatic couplings (NACs) between electronic and nuclear degrees of freedom. We compute the nonradiative relaxation of charge carriers and photoluminescence (PL) using the Redfield theory. Our findings show that electrons relax faster than holes. The ensemble of oligomers shows faster relaxation compared to the single oligomer. The calculated PL spectra show features from both interband and intraband transitions. The ensemble shows broader line widths, redshift of transition energies, and lower intensities compared to the single oligomer. This comparative study suggests that the dispersion forces and orbital hybridizations between chains are the leading contributors to the variation in PL. It provides insights into the fundamental behaviors of CPs and the molecular-level understanding for the design of more efficient optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗