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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 OSTI2023

Measurement of the top quark-antiquark pair charge asymmetry in events with highly boosted top quarks in proton-proton collisions at 13 TeV with the CMS detector

The top quark is the heaviest elementary particle, making it a unique tool to search for new physics. In this talk, I will present a new measurement of the top quark pair charge asymmetry for highly boosted top quarks decaying to a single lepton, missing transverse momentum and jets. The analysis is performed on 13TeV proton-proton collision data recorded by the CMS experiment during Run 2. We have defined a dedicated phase space that selects top quark-antiquark pairs with invariant mass greater than 750GeV in a semileptonic final state where the lepton is not necessarily isolated. This highly boosted sample is enhanced in valence quark production and thus expected to be more sensitive to deviations in the charge asymmetry caused by BSM processes. Dedicated tagging techniques are used to identify the decay products of hadronic top quarks and W bosons. An unfolding procedure is used to correct for detector resolution and acceptance, and inefficiencies in the event reconstruction. The result is presented in the full phase space at parton level and can be used as input to global EFT interpretations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Transcriptomics (PB-DP3)

The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Sample data was acquired using a Illumina HiSeq sequencer system and processed for RNA sequencing (RNA-Seq) expression analysis. Transcriptomic differential expression analysis revealed coordinated circadian clock-driven adjustment of the cell cycle and rewiring of energy and carbon metabolism. Processed RNA-Seq datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed RNA-seq results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mechanism of Peptide Agonist Binding in CXCR4 Chemokine Receptor

Chemokine receptors are key G-protein-coupled receptors (GPCRs) that control cell migration in immune system responses, development of cardiovascular and central nervous systems, and numerous diseases. In particular, the CXCR4 chemokine receptor promotes metastasis, tumor growth and angiogenesis in cancers. CXCR4 is also used as one of the two co-receptors for T-tropic HIV-1 entry into host cells. Therefore, CXCR4 serves as an important therapeutic target for treating cancers and HIV infection. Apart from the CXCL12 endogenous peptide agonist, previous studies suggested that the first 17 amino acids of CXCL12 are sufficient to activate CXCR4. Two 17-residue peptides with positions 1–4 mutated to RSVM and ASLW functioned as super and partial agonists of CXCR4, respectively. However, the mechanism of peptide agonist binding in CXCR4 remains unclear. Here, we have investigated this mechanism through all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method. The Pep-GaMD simulations have allowed us to explore representative binding conformations of each peptide and identify critical low-energy states of CXCR4 activated by the super versus partial peptide agonists. Our simulations have provided important mechanistic insights into peptide agonist binding in CXCR4, which are expected to facilitate rational design of new peptide modulators of CXCR4 and other chemokine receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Star formation characteristics of CNN-identified post-mergers in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)

ABSTRACT The importance of the post-merger epoch in galaxy evolution has been well documented, but post-mergers are notoriously difficult to identify. While the features induced by mergers can sometimes be distinctive, they are frequently missed by visual inspection. In addition, visual classification efforts are highly inefficient because of the inherent rarity of post-mergers (~1 per cent in the low-redshift Universe), and non-parametric statistical merger selection methods do not account for the diversity of post-mergers or the environments in which they appear. To address these issues, we deploy a convolutional neural network (CNN) that has been trained and evaluated on realistic mock observations of simulated galaxies from the IllustrisTNG simulations, to galaxy images from the Canada France Imaging Survey, which is part of the Ultraviolet Near Infrared Optical Northern Survey. We present the characteristics of the galaxies with the highest CNN-predicted post-merger certainties, as well as a visually confirmed subset of 699 post-mergers. We find that post-mergers with high CNN merger probabilities [p(x) > 0.8] have an average star formation rate that is 0.1 dex higher than a mass- and redshift-matched control sample. The SFR enhancement is even greater in the visually confirmed post-merger sample, a factor of 2 higher than the control sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Containment strategy for subsurface H 2 storage based on time-dependent soft solids

Here, we propose an innovative containment strategy based on time-dependent soft solids, namely 2 wt% Laponite suspensions, to reinforce natural subsurface seals and engineer flow barriers, with an eye toward making H 2 subsurface storage scalable and geographically agnostic. This suspension can be injected at its initial low viscosity and elasticity into a porous medium, allowing for easy pumping and targeted delivery. Once inside the target zone, it matures into a soft solid with much higher viscosity and elasticity, acting as a potential flow barrier. We discuss the rheological properties of the suspensions and demonstrate that hydrogen does not adversely affect their microstructure, but rather increases the suspensions’ viscosity and elasticity. Moreover, the suspensions enhance the rock samples’ compressive strength, while hydrogen exposure increases their stiffness and ductility. The ability of rock samples saturated with the suspensions to contain higher injected gas pressures is enhanced by aging at higher temperatures.

08 HYDROGEN↗
DOE OSTI2020

Effect of Using Regenerated Combined FAU and MOR Zeolites as Catalysts during the Pyrolysis of Kraft Lignin

The SiO 2 /Al 2 O 3 mole ratio, pore size, and acid sites are the key parameters of zeolite’s activity in lignin pyrolysis. In this study, the comparison of individual Y and M zeolites, the combined ‘Y + M’ sample after regeneration, and their effect on lignin pyrolysis were studied in five cycles (regeneration and reuse). The results were explained using Brunauer, Emmet, and Teller (BET), micropore surface area (MSA), and total acid sites (TAS) analyses. In comparison with the individual Y or M zeolite sample, the consistent higher catalytic activities of the combined ‘Y + M’ sample in repeated cycles were observed. Pyrolysis heavy oils were characterized by nuclear magnetic resonance (NMR) spectroscopy and gel permeation chromatography (GPC). The NMR analyses revealed that with increased zeolite regeneration cycles, p-hydroxy phenyl and methoxyl groups increased. Decreases in guaiacyl phenolic hydroxyl were less for the combined ‘Y + M’ sample than the individual Y and M zeolites. Lower weight average (M w ) of heavy oil for the combined ‘Y + M’ sample indicated the enhanced cleavage of lignin structures in pyrolysis. These results support the higher catalytic activity of regenerated zeolites for the combined ‘Y + M’ sample compared with individual Y and M zeolites due to the improved MSA and TAS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Image fusion for neutron tomography of nuclear fuel

Image fusion, the process of combining different images together, can be useful to create a more complete picture. In this work, image fusion is applied to neutron tomography of nuclear fuel with the goal of enhancing the information obtained about the fuel. Different reconstruction methods, such as Feldkamp, Davis and Kress filtered back projection and Simultaneous Reconstruction Technique, were combined to enhance image quality. This methodology was shown to reduce noise and ring artifacts without sacrificing sharp edges, allowing for a more accurate representation of sample geometry. Technique enhancements and future applications for the neutron imaging community are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Whole metagenome sequencing and 16S rRNA gene amplicon analyses reveal the complex microbiome responsible for the success of enhanced in-situ reductive dechlorination (ERD) of a tetrachloroethene-contaminated Superfund site

The North Railroad Avenue Plume (NRAP) Superfund site in New Mexico, USA exemplifies successful chlorinated solvent bioremediation. NRAP was the result of leakage from a dry-cleaning that operated for 37 years. The presence of tetrachloroethene biodegradation byproducts, organohalide respiring genera (OHRG), and reductive dehalogenase (rdh) genes detected in groundwater samples indicated that enhanced reductive dechlorination (ERD) was the remedy of choice. This was achieved through biostimulation by mixing emulsified vegetable oil into the contaminated aquifer. This report combines metagenomic techniques with site monitoring metadata to reveal new details of ERD. DNA extracts from groundwater samples collected prior to and at four, 23 and 39 months after remedy implementation were subjected to whole metagenome sequencing (WMS) and 16S rRNA gene amplicon (16S) analyses. The response of the indigenous NRAP microbiome to ERD protocols is consistent with results obtained from microcosms, dechlorinating consortia, and observations at other contaminated sites. WMS detects three times as many phyla and six times as many genera as 16S. Both techniques reveal abundance changes in Dehalococcoides and Dehalobacter that reflect organohalide form and availability. Methane was not detected before biostimulation but appeared afterwards, corresponding to an increase in methanogenic Archaea. Assembly of WMS reads produced scaffolds containing rdh genes from Dehalococcoides, Dehalobacter, Dehalogenimonas, Desulfocarbo, and Desulfobacula. Anaerobic and aerobic cometabolic organohalide degrading microbes that increase in abundance include methanogenic Archaea, methanotrophs, Dechloromonas, and Xanthobacter, some of which contain hydrolytic dehalogenase genes. Aerobic cometabolism may be supported by oxygen gradients existing in aquifer microenvironments or by microbes that produce O 2 via microbial dismutation. The NRAP model for successful ERD is consistent with the established pathway and identifies new taxa and processes that support this syntrophic process. This project explores the potential of metagenomic tools (MGT) as the next advancement in bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deciphering between enhanced light emission and absorption in multi-mode porphyrin cavity polariton samples

Abstract It remains unclear how the collective strong coupling of cavity-confined photons to the electronic transitions of molecular chromophore leverages the distinct properties of the polaritonic constituents for future technologies. In this study, we design, fabricate, and characterize multiple types of Fabry-Pérot (FP) mirco-resonators containing copper(II) tetraphenyl porphyrin (CuTPP) to show how cavity polariton formation affects radiative relaxation processes in the presence of substantial non-Condon vibronic coupling between two of this molecule’s excited electronic states. Unlike the prototypical enhancement of Q state radiative relaxation of CuTPP in a FP resonator incapable of forming polaritons, we find the light emission processes in multimode cavity polariton samples become enhanced for cavity-exciton energy differences near those of vibrations known to mediate non-Condon vibronic coupling. We propose the value of this detuning is consistent with radiative relaxation of Herzberg-Teller polaritons into collective molecular states coupled to the cavity photon coherently. We contrast the feature stemming from light emission from the HT polariton state with those that occur due to polariton-enhanced light absorption. Our results demonstrate the landscape of molecular and photonic interactions enabled by cavity polariton formation using complex chromophores and how researchers can design resonators to leverage these interactions to characterize and control polaritonic properties.

Odewale, Elizabeth O.↗
DOE OSTI2020

Enhancing superconductivity of Y 5 Rh 6 Sn 18 by atomic disorder

Here, we investigate the effect of enhancement of superconducting transition temperature $T_c$ by nonmagnetic atom disorder in the filled skutterudite-related tetragonal Y 5 Rh 6 Sn 18 compound doped with Ca. We documented experimentally that Y 5 Rh 6 Sn 18 and its Ca-doped alloys are electronically inhomogeneous at the nanoscale, when Ca content is smaller than ~1.5 in the Y 5– x Ca x Rh 6 Sn 18 system, while for $\textit{x}$ ≥ 1.5 much stronger chemical phase inhomogeneity is observed with an about 20% volume fraction of the second 3:4:13 cubic phase, which we interpret as a fluctuation of stoichiometry within the bulk sample. Then the enhancement of $T_c$ vs $\textit{x}$ could be modeled by a mechanism proposed in recent theoretical reports for increasing the mean-field transition temperature $T_c$ in the presence of nonmagnetic disorder. The increase in disorder with doping increases the sample inhomogeneity and causes a systematic increase in $T_c$, while for two-phase $\textit{x}$ ≥ 1.5 samples the critical temperature $T^{\star}_c ≈ 2 × T_c$ rapidly increases. Based on band structure calculations performed under pressure, we demonstrate how the change in density of states would affect $T_c$ of Y 5 Rh 6 Sn 18 . We obtained the Grüneisen parameter $γ_G$ larger for the inhomogeneous phase with respect to $γ_G$ of the bulk $T_c$ phase and attribute the enhancement of $T_c$ to larger stiffening of the high-temperature $T^{\star}_c$ phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Annealing influence on the microstructure of irradiated U-Mo monolithic fuel foils

In this study we compared the microstructure evolution of U-Mo fuel foils produced with and without heat treatment at low burn-up via advanced post-irradiation examination. The aim of this study is to observe after irradiation the ways in which the fabrication processes have influenced fuel behavior at early-stage irradiation, as for very low burn up microstructural studies are lacking. In this work it was observed that the larger grain size detected in the heat-treated samples before irradiation led to decreased grain refinement after irradiation. Grain refinement was associated with the presence of small nano-size bubbles and precipitates. This phenomenon is hypothesized to influence early fuel swelling during reactor irradiation. Grain refinement was also observed to increase in regions where γ-U decomposition was present. Thus, it was enhanced in the samples fabricated without heat treatment. The heat treatment also increased the thickness of the U-Mo/Zr interface, namely of the UZr 2 layer. However, the influence of this layer on fuel performance needs further investigation. On one side, it may contribute to better mechanical bonding; on the other, it may influence swelling and blistering in the interaction layer as porosity increases when this layer is increased. This was observed especially in the presence of increased area containing low Mo concentration, and thus containing a higher fraction of the α-U phase, which is highly susceptible to irradiation induced swelling. Strong evidence of reverse transformation under irradiation (α-U + γ'-U2Mo → bcc γ-U) was observed in these samples. While the precipitates (carbides and oxide) seem to be unaffected by the irradiation at these low burnups. However, further analyses are necessary at higher burn-up to assess the exact impact different heat treatments have on fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Magnetic structure determination of multiple phases in the multiferroic candidate GdCrO 3

Due to their potential applications in low-power consumption and/or multistate memory devices, multiferroic materials have attracted a lot of attention in the condensed matter community. As part of the effort to identify new multiferroic compounds, perovskite-based GdCrO 3 was studied in both bulk and thin film samples. A strong enhancement of the capacitance in a field suggested ferroelectric behaviour but significant leakage and no well developed P–E hysteresis loops were observed. Measurements clearly indicate the existence of a polar phase but only below 2 K (likely connected to Gd ordering). Here the determination of the magnetic structure through neutron diffraction collected on an isotopic 160 GdCrO 3 sample at the WISH diffractometer at ISIS is reported. The presence of three successive magnetic phases as a function of temperature (commensurate, spin re-orientation and incommensurate phases once the Gd order), previously only seen by magnetization, is confirmed. Using the most recent guidelines for reporting the determined structures, we highlight the benefits of using such nomenclature for discussing physical properties and consider possible mechanisms and couplings that led this seemingly rather isotropic system to display the complex structures observed.

incommensurate magnetic structure↗
DOE OSTI2024

Characterization of a LaB6 tip as a thermionically enhanced photoemitter

There is a widespread interest in time-resolved electron spectroscopies such as ultrafast electron diffraction, ultrafast electron microscopy, and ultrafast electron energy loss spectroscopy. These techniques require pulsed electron beams with both high current and brightness. LaB6 is commonly used as a thermionic emitter because of its low work function and high electron yield. However, its use as a pulsed photocathode has not been widely explored. Here, we present measurements of the electron yield from a LaB6 filament exposed to 392 nm UV ultrafast laser pulses under a wide range of filament temperatures. We find that sample heating strongly enhances photoelectron yield, an effect known as thermionically enhanced photoemission. However, it also creates potentially undesirable, continuous thermionic background. We conclude that the ideal optimal operating conditions strongly depend on the type of measurement and require defining and quantifying an appropriate figure of merit.

Physics↗
DOE OSTI2023

Efficient Subset Simulation using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo Methods

The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low probability of failure. If the evaluation of each sample is computationally expensive, the crude Monte Carlo simulation strategy is impracticable. Therefore, subset simulations are used to reduce the required number of evaluations. Subset simulations require a Markov Chain Monte Carlo sampler, such as the random walk Metropolis-Hastings algorithm. The algorithm, however, struggles with sampling in low-probability regions, especially if they are narrow. As a consequence, advanced Markov Chain Monte Carlo simulations have been developed. In particular, the Hamiltonian Monte Carlo method explores the target distribution rapidly. Driven by the idea of Hamiltonian dynamics, this sampler provides a non-random walk through the target distribution. The incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results for reliability analysis. One downside of the Hamiltonian Monte Carlo method is that gradient evaluations are computationally expensive, especially when dealing with high-dimensional problems and evaluating long trajectories. We show that integrating Hamiltonian neural networks in Hamiltonian Monte Carlo simulations significantly speeds up the sampling task. Furthermore, the enhancement of adaptive trajectory length within the Hamiltonian Monte Carlo results in the efficient proposal of the following states. Based on this recent enhancement, we provide a fast sampling strategy for subset simulations using Hamiltonian neural networks to replace the evaluation of the gradient and significantly speed up the Hamiltonian Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗