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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Significant Differences in Solvation Thermodynamics of C1–C3 Oxygenates in Hydrophilic versus Hydrophobic Pores of a Hydrophilic Ti-FAU Zeolite Model

The rates of catalytic reactions have been observed to be dramatically different in zeolites, depending on if they are hydrophobic or hydrophilic. Hypotheses aimed at explaining this behavior have pointed to various solvent molecule and zeolite properties as having influence on entropy. Herein, the influence of various solvent and adsorbate properties on the solvation energies, entropies, and free energies of eleven C1-C3 oxygenates in hydrophobic and hydrophilic pores within a hydrophilic model of Ti-FAU zeolite are tested. The results indicate significant variation in the calculated solvation thermodynamics depending on the adsorbate type, as well as if it is bound within a hydrophobic or hydrophilic pore. Further, while solvation energies are related to solvent-adsorbate interactions, solvation entropies have multiple contributions, and these differ depending on if the adsorbate is in a hydrophobic or hydrophilic pore. Specifically, solvation entropies in hydrophobic pores are related to solvent structural properties, whereas solvation entropies in hydrophilic pores are related to adsorbate polarity. Here, the large range of results obtained from two different pores within one zeolite model with minimal unique adsorption sites suggests that solvation behavior in zeolites is complicated and that the phenomena that control observed performance depend on the zeolite, reaction, and solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Probabilistic Prediction of Geomagnetic Storms and the K p index

Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic index K p in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministic K p predictions using a variety of methods – including empirically-derived functions, physics-based models, and neural networks – but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-ahead K p prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm (K p ≥ 5 – ) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion

Abstract Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high‐resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events – merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time‐steps of simulated and in‐vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds.

McDonald, T.↗
DOE OSTI2023

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

Research & Experimental Medicine↗
DOE OSTI2020

Automated Segmentation of Porous Thermal Spray Material CT Scans with Geometric Uncertainty Estimation

Thermal sprayed metal coatings are used in many industrial applications, and characterizing the structure and performance of these materials is vital to understanding their behavior in the field. X-ray Computed Tomography (CT) machines enable volumetric, nondestructive imaging of these materials, but precise segmentation of this grayscale image data into discrete material phases is necessary to calculate quantities of interest related to material structure. In this work, we present a methodology to automate the CT segmentation process as well as quantify uncertainty in segmentations via deep learning. Neural networks (NNs) are shown to accurately segment full resolution CT scans of thermal sprayed materials and provide maps of uncertainty that conservatively bound the predicted geometry. These bounds are propagated through calculations of material properties such as porosity that may provide an understanding of anticipated behavior in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

N* Physics with CLAS12 at Jefferson Lab

Nucleons are the most fundamental bound three-body systems in Nature. With the CLAS12 spectrometer at Jefferson Lab, the spectrum and the structure of nucleon resonances is explored. This includes studies of exclusive piN, pi+pi-p, KLambda, and KSigma electroproduction reactions and the evolution of the electrocouplings of resonances with photon virtuality Q^2. Such type of studies with CLAS have revealed a complex interplay between a core of dressed quarks and an external meson-baryon cloud inside of the excited nucleon states. With CLAS12, also measurements of N -> N* transitions in the DIS region have been performed, addressing the three-dimensional structure of nucleon resonances through their transition GPDs (generalized parton distributions). In the future, the increase of the CEBAF energy and the upgrade of the CLAS12 spectrometer to study exclusive electroproduction channels at higher luminosities and photon virtualities will offer a unique opportunity to study the nucleon excitation mechanisms.

Achenbach, Patrick↗
DOE OSTI2021

3D optical diagnostics for explosively driven deformation and fragmentation

High-speed, optical imaging diagnostics are presented for three-dimensional (3D) quantification of explosively driven metal fragmentation. At early times after detonation, Digital Image Correlation (DIC) provides non-contact measures of 3D case velocities, strains, and strain rates, while a proposed stereo imaging configuration quantifies in-flight fragment masses and velocities at later times. Experiments are performed using commercially obtained RP-80 detonators from Teledyne RISI, which are shown to create a reproducible fragment field at the benchtop scale. DIC measurements are compared with 3D simulations, which have been ‘leveled’ to match the spatial resolution of DIC. Overall, results demonstrate improved ability to identify predicted quantities-of-interest that fall outside of measurement uncertainty and shot-to-shot variability. Similarly, video measures of fragment trajectories and masses allow rapid experimental repetition and provide correlated fragment size-velocity measurements. Measured and simulated fragment mass distributions are shown to agree within confidence bounds, while some statistically meaningful differences are observed between the measured and predicted conditionally averaged fragment velocities. Together these techniques demonstrate new opportunities to improve future model validation.

42 ENGINEERING↗
DOE OSTI2020

Structural basis for divergent C–H hydroxylation selectivity in two Rieske oxygenases

Biocatalysts that perform C–H hydroxylation exhibit exceptional substrate specificity and site-selectivity, often through the use of high valent oxidants to activate these inert bonds. Rieske oxygenases are examples of enzymes with the ability to perform precise mono- or dioxygenation reactions on a variety of substrates. Understanding the structural features of Rieske oxygenases responsible for control over selectivity is essential to enable the development of this class of enzymes for biocatalytic applications. Decades of research has illuminated the critical features common to Rieske oxygenases, however, structural information for enzymes that functionalize diverse scaffolds is limited. Here, we report the structures of two Rieske monooxygenases involved in the biosynthesis of paralytic shellfish toxins (PSTs), SxtT and GxtA, adding to the short list of structurally characterized Rieske oxygenases. Based on these structures, substrate-bound structures, and mutagenesis experiments, we implicate specific residues in substrate positioning and the divergent reaction selectivity observed in these two enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SpectralFly: Ramanujan Graphs as Flexible and Efficient Interconnection Networks

In recent years, graph theoretic considerations have become increasingly important in the design of HPC interconnection topologies. One approach is to seek optimal or near-optimal families of graphs with respect to a particular graph theoretic property, such as diameter. For example, the SlimFly topology is based on a construction of McKay, Miller, and \v{S}ir\'{a}\v{n} which produces a diameter two graph on a number of nodes approaching the Moore bound, i.e. the largest possible diameter two graph with a fixed radix. Motivated by recent work of Aksoy, Bruillard, Young, and Raugas, we consider topologies which optimize the spectral gap rather than the diameter. In particular, we introduce a novel HPC topology, SpectralFly, designed around the Ramanujan graph construction of Lubotzky, Phillips, and Sarnak (LPS). In this work, we show that the combinatorial properties, such as diameter, bisection bandwidth, average path length, and resilience to link failure, of SpectralFly topologies are better than, or comparable to, similarly constrained DragonFly, SlimFly, and BundleFly topologies. Additionally, we simulate the performance of SpectralFly topologies on a representative sample of physics-inspired HPC workloads using the Structure Simulation Toolkit Macroscale Element Library simulator and demonstrate considerable benefit to using LPS construction as the basis of the SpectralFly topology.

graphs and networks, network topology, interconnec↗
DOE OSTI2025

Measurement of isolated prompt photon production in pp and p–Pb collisions at the LHC

This paper presents the measurement of the isolated prompt photon inclusive production cross section in pp and p–Pb collisions by the ALICE Collaboration at the LHC. The measurement is performed in p–Pb collisions at centre-of-mass energies per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 Te and 8.16 TeV, as well as in pp collisions at $\sqrt{s}$ = 5.02 TeV and 8 TeV. The cross section is obtained at midrapidity (|γ| < 0.7) using a charged-track based isolation momentum p$^{iso,~ch}_{T}$ < 1.5 GeV/c in a cone with radius R = 0.4. The data for both collision systems are well reproduced by perturbative QCD (pQCD) calculations at next-to-leading order (NLO) using recent parton distribution functions for free (PDF) and bound (nPDF) nucleons. Furthermore, the nuclear modification factor R pA for both collision energies is consistent with unity for p T > 20 GeV/c. However, deviations from unity (R pA < 1) of up to 20% are observed for p T < 20 GeV/c with limited significance, indicating the possible presence of nuclear effects in the initial state of the collision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Thermal Radiation Modulation Platform by Emissivity Engineering with Graded Metal–Insulator Transition

Thermal radiation from a black body increases with the fourth power of absolute temperature (T 4 ), an effect known as the Stefan-Boltzmann law. Typical materials radiate heat at a portion of this limit, where the portion, called integrated emissivity (ε int ), is insensitive to temperature (|dε int /dT| ≈ 10 -4 °C -1 ). The resultant radiance bound by the T 4 law limits the ability to regulate radiative heat. Here, an unusual material platform is shown in which ε int can be engineered to decrease in an arbitrary manner near room temperature (|dε int /dT| ≈ 8 × 10 -3 °C -1 ), enabling unprecedented manipulation of infrared radiation. As an example, ε int is programmed to vary with temperature as the inverse of T 4 , precisely counteracting the T 4 dependence; hence, thermal radiance from the surface becomes temperature-independent, allowing the fabrication of flexible and power-free infrared camouflage with unique advantage in performance stability. In this work, the structure is based on thin films of tungsten-doped vanadium dioxide where the tungsten fraction is judiciously graded across a thickness less than the skin depth of electromagnetic screening.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Intruder configurations in 29 Ne at the transition into the island of inversion: Detailed structure study of 28 Ne

Detailed γ-ray spectroscopy of the exotic neon isotope 28 Ne has been performed for the first time using the one-neutron removal reaction from 29 Ne on a liquid hydrogen target at 240 MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for 28 Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder p-wave strength providing evidence of the breakdown of the N=20 and N=28 shell gaps. Only a weak, possible f-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large p-wave and small f-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Incremental Interval Assignment by Integer Linear Algebra with Improvements

Interval Assignment (IA) is the problem of selecting the number of mesh edges (intervals) for each curve for conforming quad and hex meshing. The intervals x is fundamentally integer-valued. Many other approaches perform numerical optimization then convert a floating-point solution into an integer solution, which is slow and error prone. We avoid such steps: we start integer, and stay integer. Incremental Interval Assignment (IIA) uses integer linear algebra (Hermite normal form) to find an initial solution to the meshing constraints, satisfying the integer matrix equation Solving for reduced row echelon form provides integer vectors spanning the nullspace of A. Here we add vectors from the nullspace to improve the initial solution, maintaining Ax = b Heuristics find good integer linear combinations of nullspace vectors that provide strict improvement towards variable bounds or goals. IIA always produces an integer solution if one exists. In practice we usually achieve solutions close to the user goals, but there is no guarantee that the solution is optimal, nor even satisfies variable bounds, e.g. has positive intervals. We describe several algorithmic changes since first publication that tend to improve the final solution. The software is freely available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantum computational phase transition in combinatorial problems

Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers. As there are no algorithmic guarantee possible for QAOA to outperform classical computers, without a proof that bounded-error quantum polynomial time (BQP) ≠ nondeterministic polynomial time (NP), it is necessary to investigate the empirical advantages of QAOA. We identify a computational phase transition of QAOA when solving hard problems such as SAT—random instances are most difficult to train at a critical problem density. We connect the transition to the controllability and the complexity of QAOA circuits. Moreover, we find that the critical problem density in general deviates from the SAT-UNSAT phase transition, where the hardest instances for classical algorithms lies. Then, we show that the high problem density region, which limits QAOA’s performance in hard optimization problems (reachability deficits), is actually a good place to utilize QAOA: its approximation ratio has a much slower decay with the problem density, compared to classical approximate algorithms. Indeed, it is exactly in this region that quantum advantages of QAOA over classical approximate algorithms can be identified.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Managing photoinduced electron transfer in AgInS2–CdS heterostructures

Ternary semiconductors such as AgInS2, with their interesting photocatalytic properties, can serve as building blocks to design light harvesting assemblies. The intraband transitions created by the metal ions extend the absorption well beyond the bandgap transition. The interfacial electron transfer of AgInS2 with surface bound ethyl viologen under bandgap and sub-bandgap irradiation as probed by steady state photolysis and transient absorption spectroscopy offers new insights into the participation of conduction band and trapped electrons. Capping AgInS2 with CdS shifts emission maximum to the blue and increases the emission yield as the surface defects are remediated. CdS capping also promotes charge separation as evident from the efficiency of electron transfer to ethyl viologen, which increased from 14% to 29%. The transient absorption measurements that elucidate the kinetic aspects of electron transfer processes in AgInS2 and CdS capped AgInS2 are presented. The improved performance of CdS capped AgInS2 offers new opportunities to employ them as photocatalysts.

Kipkorir, Anthony↗
DOE OSTI2022

Dependency of optical/UV parameters on X-ray spectral index in AGNs

The study of Active Galactic Nuclei (AGNs) is vital in order to understand their respective nuclei bounded activity primarily triggered by the accretion disk and the associated corona. The hard X-ray emission characterised by the spectral index Γ emitted by these sources in 2-10 keV band ionizes the nearby physical features like disk, BLR, NLR and provides a radiative configuration. However, based on previous studies, there is degeneracy in the evolution of Γ across the redshift, wherein few studies display a systematic trend in the evolution and others rule out the systematic variation. Here, in the present work, we study the evolution of Γ across the redshift for a very large sample and perform further studies on the variation of Γ with optical parameters using SDSS data viz. H β & Mg II and their luminosities. Based on analysis we find that there is no change in Γ across the redshift and it does not show any correlation with the optical parameters. This strongly suggests that the Γ is influenced by the soft excess and/or reflection component and is affecting the disk and BLR region at the same strength across the redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Microporous pentiptycene-based polybenzimidazole membranes for high temperature H 2 /CO 2 separation

Separating H 2 from syngas at elevated temperatures (100–250 °C) have attracted significant attention in recent years as a means to reduce energy consumption and capital costs in precombustion carbon capture processes, such as those following steam reforming of natural gas or coal gasification. Polybenzimidazole (PBI), particularly m-PBI, has been reported as a leading membrane material for high-temperature H 2 /CO 2 separation. However, m-PBI exhibits extremely low H 2 permeability, even at high temperatures, which limits its productivity in H 2 /CO 2 separation applications. Here, to address this limitation, this work introduces a new pentiptycene-based polybenzimidazole (PPBI) featuring significantly enhanced H 2 permeability and attractive high-temperature H 2 /CO 2 separation performance, which stems from the unique configurational free volume elements introduced by pentiptycene moieties. Further tuning of the free volume architecture of PPBI films is achieved via acid doping with phosphoric acid (PA) or trans-aconitic acid (TaA), which introduces crosslinking among PPBI chains. Under mixed-gas environment (50/50 mol% H 2 /CO 2 ) at 180 °C, the acid-doped PPBI films exhibit a ∼230 % increase in H 2 /CO 2 selectivity compared to pristine PPBI film while maintaining high H 2 permeability that is nearly 500 % of m-PBI. These properties approach the predicted upper bound for membrane operating at 180 °C, highlighting its great potential for high-temperature H 2 /CO 2 separation.

Liu, Mengdi [University of Notre Dame, IN (United ↗
DOE OSTI2025

Confinement of Lewis Acid–Base Sites by Microporous Silica Layers on Titania for Enhanced Alkanol Dehydration Reactivity

Alkanol dehydration offers a pathway to upgrade biomass-derived short-chain oxygenates into alkenes, essential chemical building blocks widely used in industrial applications. Transition metal oxides with Lewis acid-base site pairs are attractive catalysts due to their high reactivity and cost-effectiveness. This work demonstrates a synthetic pathway to manipulate local environments around active Lewis acid-base pairs in anatase TiO 2 to enhance their reactivity in alkanol dehydration. Microporous SiO 2 layers with an average pore diameter of ~0.6 nm and a controlled thickness of 0.8-33 nm are deposited on anatase TiO 2 powders by using a molecular templated SiO 2 deposition method. The Lewis acid-base strength of accessible Ti-O pairs remains unchanged, as shown by temperature-programmed surface reactions of surface-bound formic acid-derived species and temperature-programmed desorption of pyridine. However, measured alkanol dehydration rates on confined Ti-O pairs are much higher (by up to 7-fold) than those on TiO 2 . The extent of rate enhancements depends on the reactant size and functional group positioning, suggesting that the rate enhancements reflect the interactions between the guest molecules (reactants and transition states) and the surrounding SiO 2 micropore environments. By providing a detailed synthetic procedure to tailor the local environments around active sites in bulk oxides, this approach offers an additional avenue for enhancing catalytic performance.

09 BIOMASS FUELS↗