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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Impact of LHC precision measurements of inclusive jet and dijet production on the CTEQ-TEA global PDF fit

In this study, we investigate the impact of new Large Hadron Collider (LHC) inclusive jet and dijet measurements on parton distribution functions (PDFs) that describe the proton structure, with a particular focus on the gluon distribution at large momentum fraction, x , and the corresponding partonic luminosities. We assess constraints from these datasets using next-to-next-to-leading-order (NNLO) theoretical predictions, accounting for a range of uncertainties from scale dependence and numerical integration. From the scale choices available for the calculations, our analysis shows that the central predictions for inclusive jet production show a smaller scale dependence than dijet production. We examine the relative constraints on the gluon distribution provided by the inclusive jet and dijet distributions, and also explore the phenomenological implications for inclusive H , t t ¯ , and t t ¯ H production at the LHC at 14 TeV. Published by the American Physical Society 2025

Ablat, Alim (ORCID:0009000519877755)↗
DOE OSTI2026

A Review of Advanced Characterization Methods and Techniques for Amorphous and Poorly Crystalline Materials Applicable to Cementitious Waste Forms

This review covers advanced characterization methods of cementitious materials. The particular focus is to understand cementitious compositions with amorphous content because conventional techniques such as X-ray diffraction are more applicable to materials with long range order. Also of interest is advanced characterization that provides deeper insights into properties such as porosity. There are five groups of characterization methods discussed in this review which are: electron beam/microscopy, X-ray, neutron diffraction and scattering, nuclear magnetic resonance, and optical techniques. The techniques can be further grouped by the categories of nanoscale structural understanding (transmission electron microscopy and pair distribution function), microscale structural understanding (focused ion beam and x-ray tomography), microscopic elemental distributions (energy dispersive spectroscopy and X-ray fluorescence), and chemical binding information (electron energy loss spectroscopy, x-ray absorption spectroscopy, nuclear magnetic resonance, Raman spectroscopy, and infrared spectroscopy), with advantages and disadvantages of each method discussed. The recommendation for further research is to begin with techniques that are easier to prepare samples for, measure, and analyze, such as the optical techniques of Raman and infrared spectroscopy. If more information is needed, pursue collaborations, other techniques, or proposals for beam time at the synchrotron sources.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Small-𝑥 asymptotics of the leading-twist flavor-singlet quark TMDs

In this paper, we investigate the small-𝑥 behavior of the flavor-singlet, leading-twist quark transverse-momentum-dependent parton distribution functions (TMDs) using the light-cone operator treatment. This formalism allows us to express TMD operators at small 𝑥 in terms of polarized dipole amplitudes, enabling a systematic approach to their small-𝑥 evolution. We derive the evolution equations for these TMDs and solve them within the large-𝑁 𝑐 approximation under the linearized, double-logarithmic approximation, where 𝑁 𝑐 represents the number of quark colors. Expanding on previous work on unpolarized and helicity TMDs, we present the small-𝑥 asymptotics for a comprehensive set of TMDs, including the Sivers function, helicity worm-gear, transversity, pretzelosity, Boer-Mulders, and transversity worm-gear distributions. Our results provide a complete picture of the small-𝑥 asymptotic behavior for all leading-twist flavor-singlet quark TMDs. We also discuss the implications of our findings for phenomenological applications and outline potential avenues for further research, particularly in understanding nonlinear effects and extending beyond the double-logarithmic approximation and large-𝑁 𝑐 approximations.

Adamiak, Daniel [Thomas Jefferson National Acceler↗
DOE OSTI2024

Large-scale Linear Magnetic Holes with Magnetic Mirror Properties in Hybrid Simulations of Solar Wind Turbulence

Magnetic holes (MHs) are coherent magnetic field dips whose size ranges from fluid to kinetic scale, ubiquitously observed in the heliosphere and in planetary environments. Despite the long-standing effort in interpreting the abundance of observations, the origin and properties of MHs are still debated. In this Letter, we investigate the interplay between plasma turbulence and MHs, using a 2D hybrid simulation initialized with solar wind parameters. We show that fully developed turbulence exhibits localized elongated magnetic depressions, whose properties are consistent with linear MHs frequently encountered in space. The observed MHs develop self-consistently from the initial magnetic field perturbations by trapping hot ions with large pitch angles. Ion trapping produces an enhanced perpendicular temperature anisotropy that makes MHs stable for hundreds of ion gyroperiods, despite the surrounding turbulence. We introduce a new quantity, based on local magnetic field and ion temperature values, to measure the efficiency of ion trapping, with potential applications to the detection of MHs in satellite measurements. We complement this method by analyzing the ion velocity distribution functions inside MHs. Our diagnostics reveal the presence of trapped gyrotropic ion populations, whose velocity distribution is consistent with a loss cone, as expected for the motion of particles inside a magnetic mirror. Our results have potential implications for the theoretical and numerical modeling of MHs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory

Risk-sensitive reinforcement learning (RL) has garnered significant attention in recent years due to the growing interest in deploying RL agents in real-world scenarios. A critical aspect of risk awareness involves modelling highly rare risk events (rewards) that could potentially lead to catastrophic outcomes. These infrequent occurrences present a formidable challenge for data-driven methods aiming to capture such risky events accurately. While risk-aware RL techniques do exist, they suffer from high variance estimation due to the inherent data scarcity. Our work proposes to enhance the resilience of RL agents when faced with very rare and risky events by focusing on refining the predictions of the extreme values predicted by the state-action value distribution. To achieve this, we formulate the extreme values of the state-action value function distribution as parameterized distributions, drawing inspiration from the principles of extreme value theory (EVT). We propose an extreme value theory based actor-critic approach, namely, Extreme Valued Actor-Critic (EVAC) which effectively addresses the issue of infrequent occurrence by leveraging EVT-based parameterization. Importantly, we theoretically demonstrate the advantages of employing these parameterized distributions in contrast to other risk-averse algorithms. Our evaluations show that the proposed method outperforms other risk averse RL algorithms on a diverse range of benchmark tasks, each encompassing distinct risk scenarios.

Wang, Yu↗
DOE OSTI2024

3D Lead-Organoselenide-Halide Perovskites and their Mixed-Chalcogenide and Mixed-Halide Alloys

Here, we incorporate Se into the 3D halide perovskite framework using the zwitterionic ligand: SeCYS ( + NH 3 (CH 2 ) 2 Se - ), which occupies both the X - and A + sites in the prototypical ABX 3 perovskite. The new organoselenide-halide perovskites: (SeCYS)PbX 2 (X=Cl, Br) expand upon the recently discovered organosulfide-halide perovskites. Single-crystal X-ray diffraction and pair distribution function analysis reveal the average structures of the organoselenide-halide perovskites, whereas the local lead coordination environments and their distributions were probed through solid-state 77 Se and 207 Pb NMR, complemented by theoretical simulations. Density functional theory calculations illustrate that the band structures of (SeCYS)PbX 2 largely resemble those of their S analogs, with similar band dispersion patterns, yet with a considerable band gap decrease. Optical absorbance measurements indeed show band gaps of 2.07 and 1.86 eV for (SeCYS)PbX 2 with X=Cl and Br, respectively. We further demonstrate routes to alloying the halides (Cl, Br) and chalcogenides (S, Se) continuously tuning the band gap from 1.86 to 2.31 eV–straddling the ideal range for tandem solar cells or visible-light photocatalysis. The comprehensive description of the average and local structures, and how they can fine-tune the band gap and potential trap states, respectively, establishes the foundation for understanding this new perovskite family, which combines solid-state and organo-main-group chemistry.

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

Temperature and density dependent pair potential for deuterium under shock

Large-scale classical molecular dynamics (CMD) simulations naturally include the microscopic physics necessary for atomistic modeling of shock release at the ablator-fuel interface in an inertial confinement fusion (ICF) capsule. Here, the multi-megabar shocks utilized in ICF experiments can drive the deuterium fuel from ambient to electron volt temperatures (T) and multi-fold compression. Modeling interatomic interactions over such an extreme range of conditions is challenging for empirical bond order potentials. We generate a pair potential for deuterium with explicit temperature and mass density dependence from ab initio density functional theory molecular dynamics using the iterative Boltzmann inversion method. This potential accurately reproduces the radial distribution functions and pressures from DFT in CMD equilibrium simulations across a wide range of thermodynamic conditions, yet fails to return the expected Hugoniot relations when used in direct CMD shock simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Global QCD analysis of spin PDFs in the proton with high-𝑥 and lattice constraints

We perform a comprehensive global QCD analysis of spin-dependent parton distribution functions (PDFs), combining all available data on inclusive and semi-inclusive deep-inelastic scattering (DIS), as well as inclusive weak boson and jet production in polarized 𝑝⁢𝑝 collisions, simultaneously extracting spin-averaged PDFs and fragmentation functions. Including recent Jefferson Lab DIS data at high 𝑥, together with subleading power corrections to the leading-twist framework, allows us to verify the stability of the PDFs for 𝑊 2 ≥ 4 GeV 2 and quantify the uncertainties on the spin structure functions more reliably. We explore the use of new lattice QCD data on gluonic pseudo-Ioffe time distributions, which, together with jet production and high-𝑥 DIS data, improve the constraints on the polarized gluon PDF. The expanded kinematic reach afforded by the data into the high-𝑥 region allows us to refine the bounds on higher-twist contributions to the spin structure functions, and test the validity of the Bjorken sum rule.

Perturbative QCD↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2024

Highly efficient semi-hydrogenation in strained ultrathin PdCu shell and the atomic deciphering for the unlocking of activity-selectivity

Excellent ethylene selectivity in acetylene semi-hydrogenation is often obtained at the expense of activity. To break the activity-selectivity trade-off, precise control and in-depth understanding of the three-dimensional atomic structure of surfacial active sites are crucial. Here, we designed a novel Au@PdCu core–shell nanocatalyst featuring diluted and stretched Pd sites on the ultrathin shell (1.6 nm), which showed excellent reactivity and selectivity, with 100% acetylene conversion and 92.4% ethylene selectivity at 122 °C, and the corresponding activity was 3.3 times higher than that of the PdCu alloy. The atomic three-dimensional decoding for the activity-selectivity balance was revealed by combining pair distribution function (PDF) and reverse Monte Carlo simulation (RMC). The results demonstrate that a large number of active sites with a low coordination number of Pd–Pd pairs and an average 3.25% tensile strain are distributed on the surface of the nanocatalyst, which perform a pivotal function in the simultaneous improvement of hydrogenation activity and ethylene selectivity. Our work not only develops a novel strategy for unlocking the linear scaling relation in heterogeneous catalysis but also provides a paradigm for atomic 3D understanding of lattice strain in core–shell nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Blocky Selective Postpolymerization C–H Functionalization of Polyolefins

C–H functionalization of commodity polyolefins affords functional materials derived from a high-volume, low-cost resource. However, current postpolymerization modification strategies result in randomly distributed functionalization along the length of the polymer backbone, which has a negative impact on the crystallinity of the resultant polymers, and thus the thermomechanical properties. Here, we demonstrate an amidyl radical mediated C–H functionalization of polyolefins to access blocky microstructures, which exhibit a higher crystalline fraction, larger crystallite size, and improved mechanical properties compared to their randomly functionalized analogues. Taking inspiration from the site-selective C–H functionalization of small molecules, we leverage the steric protection provided by crystallites and target polymer functionalization to amorphous domains in a semicrystalline polyolefin gel. The beneficial outcomes of blocky functionalization are independent of the identity of the pendant functional group that is installed through functionalization. Here, the decoupling of functional group incorporation and crystallinity highlights the promise in accessing nonrandom microstructures through selective functionalization to circumvent traditional tradeoffs in postpolymerization modification, with potential impact in advanced materials and upcycling plastic waste.

Neidhart, Eliza K. [The University of North Caroli↗
DOE OSTI2024

Observation of Kolmogorov turbulence due to multiscale vortices in dusty plasma experiments

We report the experimental observation of fully developed Kolmogorov turbulence originating from self-excited vortex flows in a three-dimensional (3D) dust cloud. The characteristic -5/3 scaling of 3D Kolmogorov turbulence is consistent in both the spatial and temporal energy spectra within a statistical variation of experimental data. Additionally, the 2/3 scaling in the second-order structure function further supports the presence of Kolmogorov turbulence. We also identified a slight deviation in the tails of the probability distribution functions for velocity gradients, a reflection of intermittency. The experiment showed the formation of a dust cloud in the diffused plasma region away from the electrodes. The dust rotation was observed in multiple experimental campaigns under different discharge conditions at different spatial locations and background plasma environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A comparison of the dielectric function for p-point water models

We compute the longitudinal dielectric function ɛl(k) for p-point water models, p = 3 (SPC/E, TIP3P), p = 4 (TIP4P-EW, OPC), and p = 5 (TIP5P-E) from the charge–charge fluctuation function SZZ(k), obtained from two methods: average of the charge in k-space (method:sum) and from the pair distribution function in Fourier space (method:integral). The latter requires a continuation to small k-values, which we thoroughly discuss. We conclude with a detailed comparison of the longitudinal dielectric function for the different p-point models and its main characteristics: small k and large k limits, position of the poles, and its (complex) zeros.

Shevy, Noah [Ames National Laboratory, Department ↗
DOE OSTI2025

Approximating the particle distribution in rotating and tandem mirror traps

Steady-state distribution functions can be used to calculate stability conditions for modes, radiation energy losses and particle loss rates. Heuristic analytic approximations to these distributions can capture key behaviors of the true distributions such as the relative speeds of different transport processes while possessing computational advantages over their numerical counterparts. In this paper, we motivate and present a closed-form ana- lytic model for a distribution of particles in a centrifugal or tandem mirror. We find that our model outperforms other known models in approximating numerical steady- state simulations outside of a narrow range of low confining potentials. We demonstrate the model’s suitability in the high confining potential regime for applications such as loss-cone stability thresholds, fusion yields and available energy.

Li, G.X.↗
DOE OSTI2025

Approximating the particle distribution in rotating and tandem mirror traps

Steady-state distribution functions can be used to calculate stability conditions for modes, radiation energy losses and particle loss rates. Heuristic analytic approximations to these distributions can capture key behaviors of the true distributions such as the relative speeds of different transport processes while possessing computational advantages over their numerical counterparts. In this paper, we motivate and present a closed-form analytic model for a distribution of particles in a centrifugal or tandem mirror. We find that our model outperforms other known models in approximating numerical steady-state simulations outside of a narrow range of low confining potentials. We demonstrate the model’s suitability in the high confining potential regime for applications such as loss-cone stability thresholds, fusion yields and available energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine learning based unfolding of x-ray spectra from filter stack spectrometer data

We demonstrate the application of neural networks to perform x-ray spectra unfolding from data collected by filter stack spectrometers. A filter stack spectrometer consists of a series of filter-detector pairs, where the detectors behind each filter measure the energy deposition through each layer as photo-stimulated luminescence (PSL). The network is trained on synthetic data, assuming x-rays of energies < 1 MeV and of two different distribution functions (Maxwellian and Gaussian) and the corresponding measured PSL values obtained from five different filter stack spectrometer designs. Predicted unfolds of single distributions are near identical reproductions of the ground truth spectra, with differences in the values lower than 20% at the higher energy end in some cases. The neural network has also demonstrated robustness to experimental measurement errors of < 5% and some capability of performing unfolds for linear combinations of the two distributions without previous training. The network can perform unfolds at rates > 1 Hz, ideal for application to some high-repetition-rate systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

TMD factorisation for diffractive jets in photon-nucleus interactions

Abstract Using the colour dipole picture and the colour glass condensate effective theory, we study the diffractive production of two or three jets via coherent photon-nucleus interactions at high energy. We consider the hard regime where the photon virtuality and/or the transverse momenta of the produced jets are much larger than the saturation momentumQ s of the nuclear target. We show that, despite this hardness, the leading-twist contributions are controlled by relatively large parton configurations, with transverse sizesR~ 1/Q s , which undergo strong scattering and probe gluon saturation. We demonstrate that these leading-twist contributions admit transverse-momentum dependent (TMD) factorisation, in terms of quark and gluon diffractive TMD distribution functions, for which we obtain explicit expressions from first principles. We go beyond our previous work by evaluating the contributions involving the quark diffractive distributions and by establishing that their DGLAP evolution emerges via controlled calculations within the colour dipole picture. We find the same expression for the quark diffractive TMD in two different processes (semi-inclusive diffraction and the diffractive production of quark-gluon dijets), thus demonstrating its universality.

Physics↗
DOE OSTI2024

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗