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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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341 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reversible CO 2 Hydrogenation, Neutron Crystallography, and Hydride Reactivity of a Triiridium Heptahydride Complex

Here, the authors report the structure, reactivity, and catalytic utility of a triiridium complex, [Ir 3 H 6 (μ 3 -H)(PN) 3 ] 2+ (2-H, PN = (2-pyridyl)CH 2 PBu t 2 ). Despite its unusual stability to unsaturated organics, electrophiles, and even CF 3 SO 3 D, they find that complex 2-H catalyzes hydrogenation of CO 2 to formate (TON Ir = 9600) and reverse formic acid dehydrogenation (TON Ir = 54 400). The hydrogenation operates via a reactive intermediate [Ir 3 H 4 (μ-H) 4 (PN) 3 ] + (5). Neutron crystallography and DFT-supported neutron vibrational spectroscopy of 2-H reveal Ir─H bond lengths and elucidate the vibration modes within the Ir 3 H 7 core. Stoichiometric oxidation of 2-H produces four classes of iridium complexes of varied nuclearity and hydride structure: tetra- and pentanuclear clusters [Ir 3 H 6 (μ 3 -AuPPh 3 )(PN) 3 ] 2+ (2-Au) and [Ag{Ir 2 H 4 (μ-OAc)(PN) 2 } 2 ] 3+ (6) are generated using AuPPh 3 + and AgOAc, respectively. Further oxidation to class [Ir 2 H 3 (μ-X) 2 (PN) 2 ] + is possible with AgOAc, Hg(OAc) 2 , or I 2 . Finally, a TEMPO/HCl system completely oxidizes the hydrides and gives [Ir 2 Cl 4 (μ-Cl) 2 (PN) 2 ] (11).

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

Laser beam pointing stabilization using analog position-sensitive diodes

Laser wire scanners have been used for ion beam profile and emittance measurements at the Spallation Neutron Source linear accelerator. Due to propagation distances exceeding 100 m, reliable measurements require laser beam stabilization, previously accomplished with a feedback control loop using a digital camera as a position sensor [Hardin et al., Opt. Express 19, 2874 (2011)]. Here, this paper presents an upgraded pointing stabilization system utilizing analog position-sensitive diodes (PSDs) as the position detector, optimized with an optical diffuser. The new system significantly surpasses the previous system by offering an order-of-magnitude improvement in radiation tolerance and a bandwidth limited only by the burst repetition rate of the laser beam. Operating with a 60-Hz burst mode laser, the new system effectively suppresses laser beam drifts up to 30 Hz, compared to the previous system’s 4 Hz limit. In addition, the amplitude of spectral components below 0.1 Hz was reduced by a factor of more than 100, which is over seven times greater than was achieved by the previous system.

Data acquisition↗
DOE OSTI2025

GA-NIFS and EIGER: A merging quasar host at z = 7 with an overmassive black hole

The James Webb Space Telescope is revolutionising our ability to understand the host galaxies and local environments of high-z quasars. Here we obtain a comprehensive understanding of the host galaxy of the z = 7.08 quasar J1120+0641 by combining NIRSpec integral field spectroscopy with NIRCam photometry of the host continuum emission. Our emission-line maps reveal that this quasar host is undergoing a merger with a bright companion galaxy. The quasar host and the companion have similar dynamical masses of ∼10 10 M ⊙ , suggesting that this is a major galaxy interaction. Through detailed quasar subtraction and SED fitting using the NIRCam data, we obtained an estimate of the host stellar mass of M ∗ = (3.0 −1.4 +2.5 ) × 10 9 M ⊙ , with M ∗ = (2.7 −0.5 +0.5 ) × 10 9 M ⊙ for the companion galaxy. Using the Hβ Balmer line, we estimated a virial black hole mass of M BH = (1.9 −1.1 +2.9 ) × 109 M ⊙ . Thus, J1120+0641 has an extreme black hole–stellar mass ratio of M BH /M ∗ = 0.63 −0.31 +0.54 , which is ∼3 dex larger than expected by the local scaling relations between black hole and stellar mass. J1120+0641 is powered by an overmassive black hole with the highest reported black hole–stellar mass ratio in a quasar host that is currently undergoing a major merger. These new insights highlight the power of JWST for measuring and understanding these extreme first quasars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

SHIVER - Spectroscopy HIstogram Visualizer for Event Reduction

Visualizing data from neutron scattering experiments is the first step in understanding the physics. The program is intended to generate and plot cuts and slices, through the four dimensional single crystal inelastic datasets, measured on direct geometry neutron spectrometers at the Spallation Neutron Source (ARCS, CNCS, HYSPEC, SEQUOIA).

Savici, AndreiT [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

Strong, Yet Split Hydrogen Bonding with Ice Rules in Delafossite (H/D)RhO 2

Despite remaining enigmatic, strong hydrogen bonding provides an advanced design handle for tailoring the properties of functional materials. Here, in this study, 3 R –(H/D)RhO 2 delafossites (prepared by ion exchange of Na + from NaRhO 2 ) contain H/D in linear coordination with O, linking Rh III O 2 layers. Bragg and real-space X-ray and neutron scattering analysis, vibrational and solid-state NMR spectroscopy, and density functional theory (DFT)–based electronic structure calculations have been employed to understand the nature of the hydrogen bonding. Despite short distances between H/D and the two O to which they are bonded, a clear double-minimum corresponding to a shorter and longer (H/D)–O distance is established. The triangular lattices formed by H/D appear to display ice-like disorder, corroborated by low-temperature heat capacity measurements.

NMR spectroscopy↗
DOE OSTI2025

Superadditivity at large charge

The weak gravity conjecture has been invoked to conjecture that the dimensions of charged operators in a CFT should obey a superadditivity relation (sometimes referred to as convexity). In this paper, we study superadditivity of the operator spectrum in theories expanded about the semi-classical saddle point that dominates correlators of large charge operators. We explore this in two contexts. The first is a model with two scalar fields that carry different charges, at a non-trivial Wilson-Fisher fixed point. A careful analysis of the semi-classics for this two field model demonstrates that ‘quantum’ violations of superadditivity (those not forbidden by the conjecture) persist in the large charge regime. We then turn to study the general properties of CFTs at large charge as bottom-up EFTs. By a trial and error procedure we come up with a seemingly consistent family of examples violating the conjecture. In so doing the presence of a genuine dilaton field appears necessary. On the one hand our result demonstrates that the superadditivity conjecture cannot be proven purely on the basis of a bottom-up analysis. On the other hand, the need for a dilaton, with the corresponding infinite fine tuning, indicates the conjecture-violating EFTs are unlikely to be UV completable.

effective field theories↗
DOE OSTI2025

Geometry of soft scalars at one loop

We extend the soft theorems for scattering amplitudes of scalar effective field theories to one-loop order. Our analysis requires carefully accounting for the fact that the soft limit is not guaranteed to commute with evaluating IR-divergent loop integrals; new results for the soft limit of general scalar one-loop integrals are presented. The geometric soft theorem remains unmodified for any derivatively-coupled scalar effective field theory, and we conjecture that this statement holds to all orders. In contrast, the soft theorem receives nontrivial corrections in the presence of potential interactions, analogous to the case of non-Abelian gauge theories. We derive the universal leading-order correction to the scalar soft theorem arising from potential interactions at one loop. Explicit examples are provided that illustrate the general results.

differential and algebraic geometry↗
DOE OSTI2025

Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification

We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variability, through the aid of a simultaneously learnt surrogate model with inputs on this manifold. Our method only relies on model evaluations and does not require the knowledge of gradients. The proposed dimensionality reduction framework can then be applied to assist outer loop many-query tasks in scientific computing, like sensitivity analysis and multifidelity uncertainty propagation. In particular, we prove, both theoretically under idealized conditions, and numerically in challenging test cases, how NeurAM can be used to obtain multifidelity sampling estimators with reduced variance by sampling the models on the discovered low-dimensional and shared manifold among models. Several numerical examples illustrate the main features of the proposed dimensionality reduction strategy and highlight its advantages with respect to existing approaches in the literature.

Autoencoders↗
DOE OSTI2025

Determination of Site Occupancy in the M–Pd–Zn (M = Cu, Ag, and Au) γ-Brass Phase by CALculation of PHAse Diagrams Modeling and Rietveld Refinement

The Pd–Zn γ-brass phase provides exciting opportunities for synthesizing site-isolated catalysts with precisely controlled Pd active site ensembles. Introducing a third metallic element into the γ-brass lattice further perturbs the catalytic active site ensembles. Here, in this work, we introduce coinage metallic elements M (M = Cu, Ag, and Au) into the Pd–Zn γ-brass phase and investigate the site occupation factors of each element in the γ-brass lattice. The CALculation of PHAse Diagrams (CALPHAD) modeling approach supported by energetics predicted by the density functional theory and X-ray and neutron diffraction with Rietveld refinement were used to identify the SOF on each Wyckoff site for various M amounts alloyed into the Pd–Zn γ-brass phase. The present analysis unveils the strong preference for Pd occupying the outer tetrahedral (OT) site in the γ-brass lattice, while the coinage metallic elements tend to substitute for Zn on the octahedral (OH) site. The determination of site occupancy in the bulk M–Pd–Zn γ-brass phase provides opportunities to investigate and tailor potential catalytically active site ensembles in the γ-brass phase materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermal processing to modulate surface chemistry and bulk charge distribution in nickel-rich layered lithium positive electrodes

The broader application of nickel-rich layered oxides as positive electrode materials for lithium-ion batteries has been hindered by their high manufacturing cost and inferior cycling stability. Thermal processing, which is integral to electrode materials manufacturing and fundamental in materials science, has not been fully utilized to design advanced positive electrode materials. Herein, we demonstrate the capability of using quenching heat treatment to regulate Li distribution and modulate electronic structure near particle surface. The resulting materials exhibit less parasitic reactions with the electrolyte and an improved charge distribution homogeneity in secondary particles, leading to more stable cycling performance at high voltages (4.5 V vs Li/Li + ). Our synchrotron X-ray analyses reveal the underlying interplay between surface structure and bulk charge distribution in positive electrode materials particles. While strategies used to stabilize positive electrode materials through compositional control, surface modification, and electrolyte engineering have become mature, thermal processing can be advantageous to further improve positive electrode materials manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Robust errant beam prognostics with conditional modeling for particle accelerators

Abstract Particle accelerators are complex and comprise thousands of components, with many pieces of equipment running at their peak power. Consequently, they can fault and abort operations for numerous reasons, lowering efficiency and science output. To avoid these faults, we apply anomaly detection techniques to predict unusual behavior and perform preemptive actions to improve the total availability. Supervised machine learning (ML) techniques such as siamese neural network models can outperform the often-used unsupervised or semi-supervised approaches for anomaly detection by leveraging the label information. One of the challenges specific to anomaly detection for particle accelerators is the data’s variability due to accelerator configuration changes within a production run of several months. ML models fail at providing accurate predictions when data changes due to changes in the configuration. To address this challenge, we include the configuration settings into our models and training to improve the results. Beam configurations are used as a conditional input for the model to learn any cross-correlation between the data from different conditions and retain its performance. We employ conditional siamese neural network (CSNN) models and conditional variational auto encoder (CVAE) models to predict errant beam pulses at the spallation neutron source under different system configurations and compare their performance. We demonstrate that CSNNs outperform CVAEs in our application.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Outlook towards deployable continual learning for particle accelerators

Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. With recent advancements, machine learning (ML) holds promise to assist in more advance prognostics, optimization, and control. While ML based solutions have been developed for several applications in particle accelerators, only few have reached deployment and even fewer to long term usage, due to particle accelerator data distribution drifts caused by changes in both measurable and non-measurable parameters. In this paper, we identify some of the key areas within particle accelerators where continual learning can allow maintenance of ML model performance with distribution drifts. Particularly, we first discuss existing applications of ML in particle accelerators, and their limitations due to distribution drift. Next, we review existing continual learning techniques and investigate their potential applications to address data distribution drifts in accelerators. By identifying the opportunities and challenges in applying continual learning, this paper seeks to open up the new field and inspire more research efforts towards deployable continual learning for particle accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Interplay Between Time and Energy in Bosonic Noisy Quantum Metrology

Quantum entanglement and coherence often allow for protocols that outperform classical ones in estimating a system’s parameter. When using infinite-dimensional probes (such as a bosonic mode), one could, in principle, obtain infinite precision in a finite time for both classical and quantum protocols, which makes it hard to quantify potential quantum advantage. However, such a situation is unphysical, as it would require infinite resources, so one needs to impose some additional constraint: typically the average energy employed by the probe is finite. Here we treat both energy and time as a resource, showing that, in the presence of noise, there is a nontrivial interplay between the average energy and the time devoted to the estimation. Our results are valid for the most general metrological schemes (e.g., adaptive schemes, which may involve entanglement with external ancillae or any kind of continuous measurement). We apply recently derived precision bounds for all parameters characterizing the paradigmatic case of a bosonic mode, subject to Lindbladian noise. We show how the time employed in the estimation should be partitioned in order to achieve the best possible precision. In most cases, the optimal performance may be obtained without the necessity of adaptivity or entanglement with ancilla. We compare results with classical strategies. Interestingly, for temperature estimation, applying a fast-prepare-and-measure protocol with Fock states provides better scaling with the number of photons than any classical strategy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

gallimgg/Topic_Modeling_Assistant

Topic Modeling Assistant for large literature databases in Scopus system with zettelkasten note exporting tool for use in Obsidian

Gallimore, GrantGregory [Oak Ridge National Labora↗
DOE OSTI2026

NEREIDS

NEREIDS (NEutron REsonance Imaging Diagnostic Suite) is a research-grade toolkit for neutron resonance imaging, providing a Rust physics core, Python bindings, and NeXus/HDF5-compliant data I/O, with a path to fast, standalone GUI workflows for VENUS/MARS.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2020

Place polarized neutron reflectivity data in bins of constant wavevector transfer

Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel. The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data. The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections. A future intention is to create a version of this code that will be one module of many in the data analysis workflow.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗