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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

The Effects of Normal Metal Stripes on TES Performance

Exploring the effects of size and geometry of normal metal features on the transition shapes and performance of transition-edge sensor microcalorimeters. The spectral resolution of transition-edge sensor (TES) microcalorimeters is very sensitive to the specific dependencies of the resistance R in the superconducting transition on the current I, magnetic field B, and temperature T. In particular, it has been shown that transitions that are very steep in (R,T) space lead to a significant noise term, in excess of conventional expectations. This so-called unexplained noise is known to be reduced by the addition of normal metal stripes across the TES perpendicular to the direction of current flow. These normal metal stripes have been shown to drastically alter the oscillatory patterns seen in measurements of the critical current as a function of magnetic field. However, there are many remaining questions about the exact impact of the stripes on current distributions within the TES, the Fraunhofer pattern and, therefore, the shape of the R(I, B, T) surface. Through measurements of the resistance under DC bias of TES devices of various sizes, with different stripe patterns and dimensions, we will discuss how these stripes can affect the R(I, B, T) surface. In addition, using measurements and analysis of the noise spectra of various devices we will present how these changes to the stripe pattern may affect the performance of the TES. In particular, we will discuss strategies to reduce the presence of localized discontinuities in the derivative of R, associated with increased noise, while maintaining the globally low levels of unexplained noise currently achieved with conventional metal stripe patterns. Implementing these strategies is a path towards producing large arrays with highly uniform transitions and high spectral resolution. These large uniform arrays will be required for future x-ray astronomy applications, such as the X-IFU on ATHENA.

TES↗
NASA NTRS2020

230Th Normalization: New Insights on an Essential Tool for Quantifying Sedimentary Fluxes in the Modern and Quaternary Ocean

230Th normalization is a valuable paleoceanographic tool for reconstructing high‐resolution sediment fluxes during the late Pleistocene (last ~500,000 years). As its application has expanded to ever more diverse marine environments, the nuances of 230Th systematics, with regard to particle type, particle size, lateral advective/diffusive redistribution, and other processes, have emerged. We synthesized over 1000 sedimentary records of 230Th from across the global ocean at two time slices, the late Holocene (0–5,000 years ago, or 0–5 ka) and the Last Glacial Maximum (18.5–23.5 ka), and investigated the spatial structure of 230Th‐normalized mass fluxes. On a global scale, sedimentary mass fluxes were significantly higher during the Last Glacial Maximum (1.79–2.17 g/sq.cmkyr, 95% confidence) relative to the Holocene (1.48–1.68 g/sq.cmkyr, 95% confidence). We then examined the potential confounding influences of boundary scavenging, nepheloid layers, hydrothermal scavenging, size‐dependent sediment fractionation, and carbonate dissolution on the efficacy of 230Th as a constant flux proxy. Anomalous 230Th behavior is sometimes observed proximal to hydrothermal ridges and in continental margins where high particle fluxes and steep continental slopes can lead to the combined effects of boundary scavenging and nepheloid interference. Notwithstanding these limitations, we found that 230Th normalization is a robust tool for determining sediment mass accumulation rates in the majority of pelagic marine settings (>1,000 m water depth).

Costa, Kassandra M.↗
NASA NTRS2020

Studies in Astronomical Time Series Analysis: VII. An Enquiry Concerning Non-Linearity, the RMS-Mean Flux Relation, and log-Normal Flux Distributions

A broad and widely used class of stationary, linear, additive time series models can have statistical properties which many authors have asserted imply that the underlying process must be non-linear, non-stationary, multiplicative, or inconsistent with shot noise. This result is demonstrated with exact and numerical evaluation of the model flux distribution function and dependence of flux standard deviation on mean flux (here and in the literature called the rms-flux relation). These models can: (1) exhibit normal, log-normal or other flux distributions; (2) show linear or slightly non-linear rms-mean flux dependencies; as well as (3) match arbitrary second order statistics of the time series data. Accordingly the above assertions cannot be made on the basis of statistical time series analysis alone. Also idscussed are ambiguities in the meaning of terms relevant to this study – linear, stationary and multiplicative – and functions that can transform observed fluxes to a normal distribution as well or better than the logarithm.

Jeffrey D Scargle↗
DOE OSTI2025

High-Temperature Neutron Diffraction Study of Vanadium and Vanadium–Niobium Null-Matrix Alloy for Spectrum Normalization

This study systematically evaluates a vanadium–niobium (V 94.1 Nb 5.9 ) null-matrix alloy as a reference material for neutron spectrum normalization and compares its performance with that of pure vanadium under identical experimental conditions. Neutron diffraction experiments are conducted on the VULCAN Engineering Materials Diffractometer at the Spallation Neutron Source, Oak Ridge National Laboratory, over a temperature range from room temperature to 1200 °C under vacuum. Pure vanadium exhibited distinct Bragg peaks across all temperatures, with its diffraction behavior influenced by both sample orientation and temperature. As the temperature increased, the diffraction peaks shifted to larger d-spacings and decreased in intensity, while spectral deviation near d ≈ 2.8 Å exceeded 10% at 1200 °C. In contrast, the V–Nb alloy produced a nearly featureless spectrum over the full d-spacing range, confirming near-complete cancellation of coherent scattering over the wide temperature range. Its spectra were insensitive to sample orientation, temperature, and microstructural evolution, with spectral deviation around d ≈ 2.8 Å exceeded 5% at 1200 °C. In conclusion, these results demonstrate that the V–Nb null-matrix alloy provides a thermally stable, efficient, and reliable normalization standard for time-of-flight diffractometers or other instrument where it is needed, enabling reduced data acquisition time and improved data quality in high-temperature neutron diffraction experiments.

Alloys↗
DOE OSTI2024

Generative machine learning for detector response modeling with a conditional normalizing flow

In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

i- flow: High-dimensional integration and sampling with normalizing flows

In many fields of science, high-dimensional integration is required. Numerical methods have been developed to evaluate these complex integrals. We introduce the code i-flow, a python package that performs high-dimensional numerical integration utilizing normalizing flows. Normalizing flows are machine-learned, bijective mappings between two distributions. i-flow can also be used to sample random points according to complicated distributions in high dimensions. We compare i-flow to other algorithms for high-dimensional numerical integration and show that i-flow outperforms them for high dimensional correlated integrals. The i-flow code is publicly available on gitlab at https://gitlab.com/i-flow/i-flow.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Determination of asymptotic normalization coefficients for the channel 16 O→ α+ 12 C: excited state 16 O(0 + ; 6.05 MeV)

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In the present paper, we treat the ANC C for the virtual decay 16 O(0 + ; 6.05 MeV)→ α+ 12 C(g.s.), the known values of which are characterized by a large spread (0.29 - 1.65) × 10 3 fm -1/2 . The ANC C is found by analytic continuation in energy of the α 12 C s-wave scattering amplitude, known from the phase-shift analysis of experimental data, to the pole corresponding to the 16O bound state and lying in the unphysical region of negative energies. To determine C, two different methods of analytic continuation are used. In the first method, the scattering data are approximated by the sum of polynomials in energy in the physical region and then extrapolated to the pole. The best way of extrapolation is chosen on the basis of the exactly solvable model. Within the second approach, the ANC C is found by solving the Schrödinger equation for the two-body α 12 C potential, the parameters of which are selected from the requirement of the best description of the phase-shift analysis data at a fixed experimental binding energy of 16 O(0 + ; 6.05 MeV) in the α+ 12 C channel. The values of the ANC C obtained within these two methods lie in the interval (886–1139) fm -1/2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows

We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a working example, we consider the DarkMachines challenge dataset. We show how different design choices (e.g., event representations, anomaly score definitions, network architectures) affect the result on specific benchmark new physics models. Once a baseline is established, we discuss how to improve the anomaly detection accuracy by exploiting normalizing flow layers in the latent space of the variational autoencoder.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2018

Airplane Capabilities: Translating Non-Normal Information for Operational Decision-Making

We consider how a jet transport airplane interface supports the flight crew in managing airplane system failures (or non-normals) for continued safe flight and landing. The existing state of the art starts with a list of airplane system component failures and asks the flight crew to determine, with the help of non-normal procedures, the operational consequences of those failures. As airplane systems become more complex and interconnected, the flight crew's ability to determine operational consequences will become inadequate. We describe an approach that attempts to translate airplane system failures directly into airplane "capabilities," which is a set of basic airplane functions, such as the ability to stop after landing. This paper describes the overall framework for supporting flight crews in operational decision making and the initial efforts to develop a language and display concepts.

managing airplane system non-normals↗
NASA NTRS2021

Vegetation Monitoring Optimization with Normalized Difference Vegetation Index and Evapotranspiration Using Remote Sensing Measurements and Land Surface Models Over East Africa

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration(ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.

triple collocation↗
DOE OSTI2023

Boson star normal modes

Boson stars are gravitationally bound objects that arise in ultralight dark matter models and form in the centers of galactic halos or axion miniclusters. We systematically study the excitations of a boson star, taking into account the mixing between positive and negative frequencies introduced by gravity. We show that the spectrum contains zero-energy modes in the monopole and dipole sectors resulting from spontaneous symmetry breaking by the boson star background. We analyze the general properties of the eigenmodes and derive their orthogonality and completeness conditions which have non-standard form due to the positive-negative frequency mixing. The eigenvalue problem is solved numerically for the first few energy levels in different multipole sectors and the results are compared to the solutions of the Schrödinger equation in fixed boson star gravitational potential. The two solutions differ significantly for the lowest modes, but get close for higher levels. We further confirm the normal mode spectrum in 3D wave simulations where we inject perturbations with different multipoles. As an application of the normal mode solutions, we compute the matrix element entering the evaporation rate of a boson star immersed in a hot axion gas. The computation combines the use of exact wavefunctions for the low-lying bound states and of the Schrödinger approximation for the high-energy excitations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Preclinical Risk Evaluation of Normal Tissue Injury With Novel Radiosensitizers

Genotoxic damage induced by radiation triggers a highly coordinated DNA damage response, and molecular inhibitors of key nodes within this complex response network can profoundly enhance the antitumor efficacy of radiation. This is especially true for drugs targeting the catalytic subunit of DNA-dependent protein kinase, which is a core component of the nonhomologous end-joining DNA repair pathway, and ataxia telangiectasia mutated, which coordinates cell cycle arrest, apoptosis, and DNA repair functionalities after radiation exposure. Unlike the more modest in vitro radiosensitizing effects seen with classic sensitizing agents such as cisplatin, 5-fluorouracil, or taxanes, DNA-dependent protein kinase or ataxia telangiectasia mutated inhibitors provide much more robust sensitizing effects in vitro, as might be anticipated from targeting these key DNA repair modulators. However, patients with homozygous inactivating mutations of ataxia telangiectasia mutated or mice with homozygous defects in DNA-dependent protein kinase (severe combined immunodeficiency) have profoundly enhanced acute normal tissue radiation reactions. Therefore, there is significant potential that the combination of small molecule inhibitors of these kinases with radiation could cause similar dose-limiting acute normal tissue toxicities. Similarly, although less understood, inhibition of these DNA repair response pathways could markedly increase the risk of late radiation toxicities. Because these potent radiosensitizers could be highly useful to improve local control of otherwise radiation-resistant tumors, understanding the potential for elevated risks of radiation injury is essential for optimizing therapeutic ratio and developing safe and informative clinical trials. In this review, we will discuss 2 straightforward models to assess the potential for enhanced mucosal toxicity in the oral cavity and small intestine established in our laboratories. We also will discuss similar strategies for evaluating potential drug–radiation interactions with regard to increased risks of debilitating late effects.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Target normal single-spin asymmetry in inclusive electron-nucleon scattering with two-photon exchange: Analysis using 1/$N_c$ expansion

We calculate the target normal single-spin asymmetry caused by two-photon exchange in inclusive electron-nucleon scattering in the resonance region. Our analysis uses the 1/$N_c$ expansion of low-energy QCD and combines $\textit{N}$ and Δ intermediate and final states using the contracted $\textit{SU}$(4) spin-flavor symmetry. The normal spin asymmetry obtained in leading-order accuracy in 1/$N_c$ has magnitude ~10 -2 and different sign in $\textit{ep}$ and $\textit{en}$ scattering. It can be measured in electron scattering at lab energies ~0.5-1.5 GeV and provides a clean probe of two-photon exchange dynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Decellularized ECM derived from normal bone involved in the viability and chemo-sensitivity in multiple myeloma cells

Multiple myeloma (MM) is an incurable plasma cell malignancy. The progression of MM is closely related to the bone microenvironment. Bone matrix proteins are remodeled and manipulated to govern cancer growth during the process of MM. However the role of normal bone extracellular matrix in MM is still unclear. In this study the decellularized extracellular matrix derived from normal SD rats’ skulls (N-dECM) was prepared by decellularization technology. The CCK 8 assay and the dead-live cell kit assay were used to determine the viability of MM cells and the sensitivity to bortezomib. The Realtime PCR and Western blot assay were used to assay the mRNA and protein related to MM. Under the treatment of N-dECM, we found that the viability of MM cells was inhibited and the sensitivity of MM cells to bortezomib was increased. Additionally, the expression levels of APRIL and TACI, which participated in the progression of MM, were significantly decreased in MM cells. It suggested that N-dECM might inhibit the development of MM via APRIL-TACI axis, and our study may provide a novel and potential biomaterial for MM therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

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

Elucidating Compositional Differences in Halide Perovskites for Normal and Inverted Perovskite Solar Cells

Over the recent few years, extensive research efforts have shifted from normal (n-i-p) to inverted (p-i-n) perovskite solar cells (PSCs), owing to their promising efficiency and operational stability, enabled by low-temperature processing. Despite a fundamentally identical operation principle (only structurally inverted), the optimized perovskite compositions for normal and inverted PSCs differ significantly across the literature, suggesting an underlying design principle for perovskite composition. Here, we unveil the role of cesium cation in enhancing interfacial contact between the perovskite layer and the underlying hole-transporting layer (HTL) in inverted PSCs. Comprehensive in situ and device characterization reveal that cesium incorporation promotes the formation of initial nucleation seeds for heterogeneous nucleation at the perovskite/hydrophobic HTL interface, thereby improving their contact. The resulting compositional heterogeneity explains the focus of recent studies on resolving this issue. This study provides mechanistic insight into designing perovskite compositions to further enhance the performance and longevity of PSCs.

Park, Keonwoo↗