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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production

Identifying gene targets for enhancing metabolite production in metabolic engineering is challenging due to the vast research literature and the approximation in genome-scale metabolic model (GEM) simulations. Here, to address this, we propose the Gene-Metabolite Association Prediction task, which automates gene discovery for given metabolite-gene pairs, accompanied by a benchmark dataset of 2474 metabolites and 1947 genes for Saccharomyces cerevisiae (SC) and Issatchenkia orientalis (IO). This task is complicated by incomplete metabolic graphs and metabolic heterogeneity. We introduce an Interactive Knowledge Transfer mechanism based on Metabolism Graphs (IKT4Meta) to enhance prediction accuracy by integrating cross-metabolism knowledge. Using Pretrained Language Models (PLMs) to generate inter-graph links mitigates heterogeneity issues, while intra-graph links are propagated via these anchors. Gene-metabolite predictions are then performed on the enriched graphs integrating multiple microorganisms’ knowledge. Experiments show that IKT4Meta outperforms baselines by up to 12.3% in link prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Electron g − 2 foreshadowing discoveries at FCC-ee

A future e + e − circular collider (FCC-ee) may provide a unique probe of the electron Yukawa coupling through Higgs boson production on resonance. Motivated by this exciting possibility, we examine a simple model which can result in O ( 10 ) modifications of the Higgs coupling to electrons. The model can also lead to deviations in the electron anomalous magnetic moment, g e − 2 , which at present shows a + 2.2 σ or − 3.7 σ deviation, implied by differing precision determinations of the electromagnetic fine structure constant. The electron g e − 2 can be a forerunner for FCC-ee discoveries which, as we elucidate, may not be accessible to the high-luminosity LHC measurements. A simple extension of our model can also account for the current deviation in the muon g μ − 2 . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

$t\overline{t}t\overline{t}$ signatures through the lens of color-octet scalars

We reinterpret two recent LHC searches for events containing four top quarks ($t\overline{t}t\overline{t}$) in the context of supersymmetric models with Dirac gauginos and color-octet scalars (sgluons). We explore whether sgluon contributions to the four-top production cross section σ ($pp$ → $t\overline{t}t\overline{t}$) can accommodate an excess of four-top events recently reported by the ATLAS collaboration. We also study constraints on these models from an ATLAS search for new phenomena with high jet multiplicity and significant missing transverse energy ($E^{miss}_{T}$) sensitive to signals with four top quarks. We find that these two analyses provide complementary constraints, with the jets + $E^{miss}_{T}$ search exceeding the four-top cross section measurement in sensitivity for sgluons heavier than about 800 GeV. We ultimately find that either a scalar or a pseudoscalar sgluon can currently fit the ATLAS excess in a range of reasonable benchmark scenarios, though a pseudoscalar in minimal Dirac gaugino models is ruled out. We finally offer sensitivity projections for these analyses at the HL-LHC, mapping the 5σ discovery potential in sgluon parameter space and computing exclusion limits at 95% CL in scenarios where no excess is found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Automated discovery of a robust interatomic potential for aluminum

Machine learning, trained on quantum mechanics (QM) calculations, is a powerful tool for modeling potential energy surfaces. A critical factor is the quality and diversity of the training dataset. Here we present a highly automated approach to dataset construction and demonstrate the method by building a potential for elemental aluminum (ANI-Al). In our active learning scheme, the ML potential under development is used to drive non-equilibrium molecular dynamics simulations with time-varying applied temperatures. Whenever a configuration is reached for which the ML uncertainty is large, new QM data is collected. The ML model is periodically retrained on all available QM data. The final ANI-Al potential makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers. We perform a 1.3M atom shock simulation and show that ANI-Al force predictions shine in their agreement with new reference DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Towards a More Predictive Framework for Laser-Driven Particle Sources through Experimental Data-Informed Models

Laser-driven particle acceleration (LDPA) has emerged as a critical technology for high-energydensity physics applications since its discovery at Lawrence Livermore National Laboratory twenty years ago. However, realizing the full potential of these particle sources requires understanding the fundamental acceleration mechanisms and developing enhanced target designs for improved performance. This research addressed the need for controllable, high-performance laser-driven proton sources through two complementary approaches: experimentally investigating sheath field dynamics in multi-picosecond laser regimes and developing novel three-dimensional printed microstructured targets to achieve enhanced particle acceleration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks

Thermochemical water-splitting (TCH) based on 2-step thermal redox cycles in metal oxides is a promising approach to generating H 2 , but state-of-the-art (SOTA) CeO 2 has several practical limitations, which has motivated continued materials discovery efforts in this field. Here, in this study, we improve upon a SOTA defect graph neural network (dGNN) surrogate model's oxygen vacancy predictions and combine them with materials project phase diagrams to down-select and discover structurally diverse, experimentally known metal oxides whose TCH performance was previously unknown. Amongst twelve candidates selected based on our high-throughput screening and down-selection criteria, we achieved ∼80% accuracy in identifying materials with stable redox cycling and hydrogen production in stagnation flow reactor water-splitting experiments. Closer to 100% accuracy can be achieved if higher-accuracy, hybrid DFT-predicted vacancy formation energies were computed and used in lieu of the most uncertain dGNN-based screening predictions, as they correct false positives to true negatives. Notably, two discovered candidates, Sr 3 PrMn 2 O 8 and Ba 2 Fe 2 O 5 , display hydrogen yields greater than CeO 2 under specific redox conditions. In conclusion, these results demonstrate our ability to computationally predict and experimentally validate promising candidate TCH materials that have the potential to compete with CeO 2 .

08 HYDROGEN↗
DOE OSTI2021

Watershed Workflow

Watershed Workflow aims to lower the bar on leveraging open data products in hyperresolution watershed hydrologic models. Integrated, distributed hydrologic models of watersheds require large amounts and complexity of data including meteorological forcing datasets; land cover datasets; watershed geometry, hydrogography, and elevation datasets; and subsurface soil and rock structural datasets. Increasingly open data products meeting this need are available through U.S. governmental and other agencies via APIs and other electronic means, but are not available in the same format, through the same API, or in the same coordinate system as one another, and present other challenges in manipulations across scales. This product automates the discovery, download, curation, and integration of these types of datasets into a common format for use with hydrologic models.

Coon, EthanT [Oak Ridge National Laboratory] (0000↗
DOE OSTI2025

Deep Koopman operators for causal discovery

Causal discovery aims to identify cause-effect mechanisms for better scientific understanding, explainable decision-making, and more accurate modeling. Standard statistical frameworks, such as Granger causality, lack the ability to quantify causal relationships in nonlinear dynamics due to the presence of complex feedback mechanisms, timescale mixing, and nonstationarity. Thus, applying these methods to study causal dynamics in real-world systems, such as the Earth, is a major challenge. Addressing this shortcoming, we leverage deep learning and a Koopman operator-theoretic formalism to present a class of causal discovery algorithms. Kausal uses deep Koopman operator methods to approximate nonlinear dynamics in a linearized vector space in which traditional causal inference methods such as Granger causality can be more easily applied. Our idealized experiments demonstrate Kausal’s superior ability in discovering and characterizing causal signals compared to existing deep learning and non-deep learning state-of-the-art approaches. Finally, the successful identification of major El Niño and La Niña events in observations showcases Kausal’s skill to handle real-world applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The SPAN512 mid-latitude pulsar survey at the Nançay Radio Telescope

The large number of ongoing surveys for pulsars and transients at various radio observatories is motivated by the science obtained from these sources. Timing and polarisation analysis of relativistic binaries can place strong constraints on theories of gravity. The observation of a growing number of millisecond pulsars (MSPs) spread over the celestial sphere may allow the detection of a stochastic gravitational wave background arising from supermassive black hole binaries. A more complete sample of young pulsars improves our knowledge of neutron star birth and evolution. Transients such as fast radio bursts can serve to probe the intergalactic medium. The SPAN512 pulsar survey covers intermediate Galactic latitudes using the L-band receiver of the Nançay Radio Telescope (NRT). The survey covers 224 sq. deg. of the sky for a total exposure time of 2200 h. Population syntheses predict the discovery of 3 to 19 new normal pulsars and a few MSPs. We present detailed modelling of the NRT beam with its L-band receiver and its sensitivity which we used to precisely assess the expected survey yield. We used the flexible Pulsar Arecibo L-band Feed Array data processing pipeline to search the 47 TB of SPAN512 data for pulsars and transients. The SPAN512 survey discovered two new MSPs and one new middle-aged pulsar. We focus on the analysis of the 2.4-ms spin period pulsar J2205+6012 for which we also report the detection of gamma-ray pulsations. Its narrow pulse width (35µs at an observing frequency of 2.55 GHz) allows for sub-microsecond timing precision over 8 yr, with exciting prospects for pulsar timing array programs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Simulation of MHD instabilities with fluid runaway electron model in M3D- C 1

Runaway electrons are generated in a tokamak during the start up, during normal operation and during a plasma disruption. During a disruption, runaway electrons can be accelerated to high energies, potentially damaging the first wall. To predict the consequences of runaway generation during a disruption, it is necessary to consider resonant interactions of runaways with the bulk plasma. Here we consider the interactions of runaways on low mode number tearing modes. We have developed a fluid runaway electron model for the 3D MHD code M3D-C1[Jardin,et al. J Comput. Sci Discovery 6 014002 (2012)]. To benchmark, we have reproduced the MHD linear tearing mode results (with runaway electrons) in a circular cylinder presented in previous analytic studies[[Helander, P., et al, Phys. Plasmas 14 144102 (2007)] and extended here with a numerical eigenvalue calculation. Furthermore, we find that the low mode number tearing mode has a rotation caused by the MHD - runaways interaction, and the toroidal current scale length is much smaller with runaways than that for without and decreases as the runaway speed increases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

2025 Atmospheric Radiation Measurement (ARM) Annual Report

ARM is a multi-laboratory, U.S. Department of Energy (DOE) Office of Science user facility and a key contributor to atmospheric research efforts. For more than 30 years, ARM has supported the DOE and Office of Science missions by providing atmospheric observations to enable scientific discovery, transform our understanding of the atmosphere, and evaluate and improve the accuracy of atmospheric models. ARM’s cutting-edge capabilities for scientists include continuously operating ground-based observatories, aerial observation platforms, and high performance computing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Searching for Pairs of Higgs Bosons in the LHC Run 2 Dataset

The discovery of the Higgs boson confirms the existence of a scalar sector of the standard model, responsible for electroweak symmetry breaking, but the nature and properties of the potential at the origin of this mechanism are still unknown. By studying the production of pairs of Higgs bosons (HH), physicists can directly measure the coupling of the Higgs boson to itself and thus determine the shape of this potential, which has far-reaching implications on the origin and evolution of our Universe. Because of this deep connection to the foundations of electroweak symmetry breaking, HH production is also an ideal place to search for manifestations of yet-unknown physics, such as modifications of the strength of the self-coupling and of the interaction between pairs of vector bosons and Higgs bosons. In this review article, we summarize the current searches for HH production at ATLAS and CMS, using the LHC Run 2 dataset, discuss the implications of our current constraints on physics beyond the standard model, and briefly review prospect for future HH searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

First Impressions: Early-time Classification of Supernovae Using Host-galaxy Information and Shallow Learning

Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches to this problem have taken advantage of complete phase coverage of an event, limiting their use for triggering rapid follow-up of ongoing phenomena. In this work, we introduce a neural network with a single recurrent layer designed explicitly for early photometric classification of supernovae (SNe). Our algorithm leverages transfer learning to account for model misspecification, host-galaxy photometry to solve the data-scarcity problem soon after discovery, and a custom weighted loss to prioritize accurate early classification. We first train our algorithm using state-of-the-art transient and host-galaxy simulations, then adapt its weights and validate it on the spectroscopically confirmed SNe Ia, SNe II, and SNe Ib/c from the Zwicky Transient Facility Bright Transient Survey. On observed data, our method achieves an overall accuracy of 82% ± 2% within 3 days of an event’s discovery, and an accuracy of 87% ± 5% within 30 days of discovery. At both early and late phases, our method achieves comparable or superior results to the leading classification algorithms with a simpler network architecture. These results help pave the way for rapid photometric and spectroscopic follow-up of scientifically valuable transients discovered in massive synoptic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Search techniques for near-earth asteroids

Knowledge of the near-earth asteroids (Apollo, Amor, and Aten groups) has increased enormously over the last 10 to 15 years. This has been due in large part to the success of programs that have systematically searched for these objects. These programs have been motivated by the apparent relationships of the near-earth asteroids to terrestrial impact cratering, meteorites, and comets, and their relative accessibility for asteroid missions. Discovery of new near-earth asteroids is fundamental to all other studies, from theoretical modeling of their populations to the determination of their physical characteristics by various remote-sensing techniques. The methods that have been used to find these objects are reviewed, and ways in which the search for near-earth asteroids can be expanded are discussed.

Helin, E. F.↗
NASA NTRS1995

Planetary and Primitive Object Strength Measurement and Sampling Apparatus

Support is requested for continuation of a program of dynamic impact (harpoon) coring of planetary, comet, or asteroid surface materials. We have previously demonstrated that good quality cores are obtainable for planetary materials with compressive strengths less than 200 MPa. Since the dynamics of penetration are observable on a Discovery class spacecraft, which images the sampling operation, these data can be used with a model developed under this project, to measure in-situ strength and frictional strength of the crust of the object. During the last year we have developed a detailed analytic model of penetrator mechanics. Progress is reported for the solid penetrators experiments, the CIT penetrator model, and the impact spall sampling apparatus.

Ahrens, Thomas J.↗
NASA NTRS2008

First Science with the Keck Interferometer Nuller High Spatial Resolution N-Band Observations of the Recurrent Nova RS Ophiuchi

We report observations of the nova RS 0phiuchi using the Keck Interferometer Nuller (KIN) taken approximately 3.8 days following the most recent outburst that occurred on 2006 February 12. The KIN operates in N-band from approx. 8 to 12.5 microns in a nulling mode - the sparse aperture equivalent of the conventional coronagraphic technique used in filled aperture te1escopes. In this mode the stellar light is suppressed by a destructive fringe, effectively enhancing the contrast of the circumstellar material located near the star. In a second, constructive-fringe mode, the instrument detects primarily the light from the central, bright source. These are the outer and inner spatial regimes, resprectively. We will describe the capabilities of the KIN, including these unique modes, and outline how they were key in our discovery that dust does not appear to be created in the outburst as in previous models, but instead was created between nova events. We also show how these first results from the KIN are consistent with Spitzer data. The KIN data show evidence of enhanced neutral atomic hydrogen emission and atomic metals including silicon located in the inner spatial regime near the white dwarf (WD) relative to the outer regime. There are also nebular emission lines and evidence of hot silicate dust in the outer spatial region, centered at approximately 17 AU from the WD, that are not found in the inner regime. The KIN and Spitzer data suggest that these emissions were excited by the nova flash in the outer spatial regime before the blast wave reached these regions. We describe the present results in terms of a new model for dust creation in recurrent novae that includes an increase in density in the plane of the orbit of the two stars created by a spiral shock wave caused by the motion of the stars through the cool wind of the red giant star. These data show the power and potential of the nulling technique which has been developed for the detection of Earth-like planets around nearby stars for the Terrestrial Planet Finder and Darwin missions.

Barry, Richard K.↗
NASA NTRS1937

Stability of Castering Wheels for Aircraft Landing Gears, Special Report

In many installations of castering rubber-tired wheels there is a tendency for the wheel to oscillate violently about the spindle axis. This phenomenon, popularly called 'shimmy,' has occurred in some airplane tail wheels and has been corrected in two ways: first by the application of friction in the spindles of the tail wheels; and, second, by locking the wheels while taxiing at high speeds. Shimmy is common with the large wheels used as nose wheels in tricycle landing gears and, since it is impossible to lock the wheels, friction in the nose-wheel spindle has been the sole means of correction. Because the nose wheel is larger than the conventional tail wheel and usually carries a greater load, the larger amounts of spindle friction necessary to prevent shimmy are objectionable. the present paper presents a theoretical and experimental study of the problem of the stability of castering wheels for airplane landing gears. On the basis of simplified assumptions induced from experimental observations, a theoretical study has been made of the shimmy of castering wheels. The theory is based on the discovery of a phenomenon called 'kinematic shimmy' and is compared quantitatively with the results of model experiments. Experimental checks, using a model having low-pressure tires, are reported and the applicability of the results to full scale is discussed. Theoretical methods of estimating the spindle viscous damping and spindle solid friction necessary to avoid shimmy - lateral freedom - is introduced.

Kantrowitz, Arthur↗