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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 OSTI2019

Balloon-Expandable Biodegradable Stents Versus Self-Expandable Metallic Stents: A Comparison Study of Stent-Induced Tissue Hyperplasia in the Rat Urethra

Purpose: To compare the degrees of stent-induced tissue hyperplasia of balloon-expandable, biodegradable stents (BEBSs) with those of self-expandable metallic stents (SEMSs) in a rat urethral model. Materials and Methods: A total of 20 rats were randomized into two groups. The BEBS group (n = 10) received a poly-l-lactic acid (PLLA) biodegradable stent. The SEMS group (n = 10) received a nitinol bare stent. All rats were killed eight weeks after stent placement. The degree of stent-induced tissue hyperplasia was assessed by comparing the results of retrograde urethrography and histologic examination between the two groups. Results: Stent placement was technically successful in all rats. Two rats in the BEBS group were excluded due to procedure-related death. The mean luminal diameter of stented urethra on urethrograms was not significantly different at 4 and 8 weeks between the two groups. On histologic analysis, the percentage of granulation tissue area (p < 0.001) and the thickness of papillary projection (p < 0.001) were significantly higher in the BEBS group compared with the SEMS group. The inflammatory cell infiltration showed a clear tendency to significance (p = 0.050). There were no statistical differences in the number of epithelial layers and the thickness of submucosal fibrosis between the two groups. Conclusion: Formation of stent-induced tissue hyperplasia was significantly evident in the rat urethra with similar degrees between the BEBS and the SEMS. The BEBS was associated with a thicker papillary projection and larger granulation tissue area resulting from higher inflammation compared with the SEMS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Finite deformation cohesive polygonal finite elements for modeling pervasive fracture

In this work, we introduce a framework for modeling dynamic fracture problems using cohesive polygonal finite elements. Random polygonal meshes provide a robust, efficient method for generating an unbiased network of fracture surfaces. Further, these meshes have more facets per element than standard triangle or quadrilateral meshes, providing more possible facets per element to insert cohesive surfaces. This property of polygonal meshes is advantageous for the modeling of pervasive fracture. We use both Wachspress and maximum entropy shape functions to form a finite element basis over the polygons. Fracture surfaces are captured through dynamically inserted cohesive zone elements at facets between the polygons in the mesh. Contact is enforced through a penalty method that is applied to both closed cohesive surfaces and general interpenetration of two polygonal elements. Finally, several numerical examples are presented that illustrate the capabilities of the method and demonstrate convergence of solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗
DOE OSTI2014

Increased activity of osteocyte autophagy in ovariectomized rats and its correlation with oxidative stress status and bone loss

Highlights: • Examine autophagy level in the proximal tibia of ovariectomized rats. • Investigate whether autophagy level is associated with bone loss. • Investigate whether autophagy level is associated with oxidative stress status. - Abstract: Objectives: The objectives of the present study were to investigate ovariectomy on autophagy level in the bone and to examine whether autophagy level is associated with bone loss and oxidative stress status. Methods: 36 female Sprague–Dawley rats were randomly divided into sham-operated (Sham), and ovariectomized (OVX) rats treated either with vehicle or 17-β-estradiol. At the end of the six-week treatment, bone mineral density (BMD) and bone micro-architecture in proximal tibias were assessed by micro-CT. Serum 17β-estradiol (E2) level were measured. Total antioxidant capacity (T-AOC), superoxide dismutase (SOD) activity, catalase (CAT) activity in proximal tibia was also determined. The osteocyte autophagy in proximal tibias was detected respectively by Transmission Electron Microscopy (TEM), immunofluorescent histochemistry (IH), realtime-PCR and Western blot. In addition, the spearman correlation between bone mass, oxidative stress status, serum E2 and autophagy were analyzed. Results: Ovariectomy increased Atg5, LC3, and Beclin1 mRNA and proteins expressions while decreased p62 expression. Ovariectomy also declined the activities of T-AOC, CAT, and SOD. Treatment with E2 prevented the reduction in bone mass as well as restored the autophagy level. Furthermore, LC3-II expression was inversely correlated with T-AOC, CAT, and SOD activities. A significant inverse correlation between LC3-II expression and BV/TV, Tb.N, BMD in proximal tibias was found. Conclusions: Ovariectomy induced oxidative stress, autophagy and bone loss. Autophagy of osteocyte was inversely correlated with oxidative stress status and bone loss.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A probabilistic creep model incorporating test condition, initial damage, and material property uncertainty

Uncertainty is prevalent in the creep resistance of alloys, where at elevated temperature and low pressure, rupture can range across logarithmic decades. In this study, a probabilistic continuum-damage-mechanics (CDM)-based model is derived to capture the uncertainty of creep resistance. To meet this objective, creep data for alloy 304 Stainless Steel is gathered. A constitutive model, “Sinh”, is calibrated deterministically to determine the statistical variability of the material properties. Three sources of uncertainty are injected into the model: test condition (stress and temperature), initial damage, and material properties. Probabilistic simulations are carried out by (a) calibrating probability distribution functions (pdfs) for each source of uncertainty (b) randomly sampling the pdfs using Monte Carlo methods and (c) executing simulations to replicate the uncertain creep behavior. A sensitivity analysis is performed to evaluate the relative effect of each source of uncertainty. In full probabilistic simulations, the cumulative uncertainty of creep behavior is evaluated. The probabilistic model accurately predicts the creep deformation and rupture of the available experiments. The probabilistic model is validated for interpolation but lacks extrapolation ability. Several future works are proposed to further improve the model.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Yield strength prediction of high-entropy alloys using machine learning

Yield strength at high temperature is an important parameter in the design and application of high entropy alloys (HEAs). However, the experimental measurement of yield strength at high temperature is quite costly, complicated, and time-consuming. Therefore, it is essential to identify and apply a robust method for the accurate prediction of yield strength at high temperature from the available experimental and simulation data. In this study, for the first time, a machine learning (ML) method based on the regression technique of random forest (RF) regressor is used to predict the yield strength of HEAs at the desired temperature. Further, the yield strengths of MoNbTaTiW and HfMoNbTaTiZr at 800 °C and 1200 °C, are predicted using the RF regressor model. We find that the results are consistent with the experimental reports, showing that the RF regressor model predicts the yield strength of HEAs at the desired temperatures with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Investigation of the isoscalar monopole response in the proton-rich nucleus 14 O

Deuteron inelastic scattering on 14 O was measured in inverse kinematics using an active-target time projection chamber and a magnetic spectrograph. The experimental technique enabled precise measurements of deuteron recoiling particles in coincidence with beam-like fragments detected in the spectrograph focal plane. The double differential cross section was reconstructed for scattering angles of 3–6 degrees and excitation energies up to 26 MeV. The monopole strength distribution was obtained from the data using a multipole decomposition analysis. The results were compared to quasiparticle random-phase approximation (QRPA) and generator coordinate method (GCM) calculations. The QRPA calculation accurately describes experimental data in the energy range of 13 to 26 MeV. GCM calculations assuming a 12 C (g . s .) + p + p cluster configuration were used to determine the 0 + strength in 14 O below 13 MeV. The monopole transition strength of these cluster states provides a good description of the experimental distribution in the 9–11 MeV region, while the 0$^{+}_{2}$ state accounts for only a small fraction of the experimental strength around 6 MeV.

Active target↗
DOE OSTI2011

Beyond the crystallization paradigm: Structure determination from diffraction patterns from ensembles of randomly oriented particles

We amplify on the priciples of the method we have recently proposed for recovering an oversampled diffraction pattern of a single particle from measured diffraction patterns from multiple particles in orientations related by rotation about an axis parallel to the incident radiation. We propose an alternative method of phasing a reference resolution ring by means of a non-negativity constraint on the diffraction intensities, point out the need for caution about enantiomeric ambiguities in the reconstruction of a diffraction pattern from its angular correlations, and show that converged correlations may be deduced by appropriate averaging of even very noisy data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

De novo design of high-affinity binders of bioactive helical peptides

Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity to structured proteins. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantum error mitigation by Pauli check sandwiching

Abstract We describe and analyze an error mitigation technique that uses multiple pairs of parity checks to detect the presence of errors. Each pair of checks uses one ancilla qubit to detect a component of the error operator and represents one layer of the technique. We build on the results on extended flag gadgets and put it on a firm theoretical foundation. We prove that this technique can recover the noiseless state under the assumption of noise not affecting the checks. The method does not incur any encoding overhead and instead chooses the checks based on the input circuit. We provide an algorithm for obtaining such checks for an arbitrary target circuit. Since the method applies to any circuit and input state, it can be easily combined with other error mitigation techniques. We evaluate the performance of the proposed methods using extensive numerical simulations on 1850 random input circuits composed of Clifford gates and non-Clifford single-qubit rotations, a class of circuits encompassing most commonly considered variational algorithm circuits. We observe average improvements in fidelity of 34 percentage points with six layers of checks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Star formation rate and stellar mass calibrations based on infrared photometry and their dependence on stellar population age and extinction

The stellar mass (M $\star$ ) and the star formation rate (SFR) are among the most important features that characterize galaxies. Measuring these fundamental properties accurately is critical for understanding the present state of galaxies, their history, and future evolution. Infrared (IR) photometry is widely used to measure the M $\star$ and SFR of galaxies because the near-IR traces the continuum emission of the majority of their stellar populations (SPs), and the mid/far-IR traces the dust emission powered by star-forming activity. This work explores the dependence of the IR emission of galaxies on their extinction, and the age of their SPs. It aims to provide accurate and precise IR-photometry SFR and M $\star$ calibrations that account for SP age and extinction while providing quantification of their scatter. We used the CIGALE spectral energy distribution (SED) fitting code to create model SEDs of galaxies with a wide range of star formation histories, dust content, and interstellar medium properties. We fit the relations between M $\star$ and SFR with IR and optical photometry of the model-galaxy SEDs with the Markov chain Monte Carlo (MCMC) method. As an independent confirmation of the MCMC fitting method, we performed a machine-learning random forest (RF) analysis on the same data set. The RF model yields similar results to the MCMC fits, thus validating the latter. This work provides calibrations for the SFR using a combination of the WISE bands 1 and 3, or the JWST NIR-F200W and MIRI-F2100W. It also provides mass-to-light ratio calibrations based on the WISE band-1, the JWST NIR-F200W, and the optical u - r or g - r colors. These calibrations account for the biases attributed to the SP age, while they are given in the form of extinction-dependent and extinction-independent relations. The proposed calibrations show robust estimations while minimizing the scatter and biases throughout a wide range of SFRs and stellar masses. The SFR calibration offers better results, especially in dust-free or passive galaxies where the contributions of old SPs or biases from the lack of dust are significant. Similarly, the M $\star$ calibration yields significantly better results for dusty and high-SFR galaxies where dust emission can otherwise bias the estimations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A proposed method for addressing large unphysical uncertainties in mubar

Mubar uncertainties in Section MF 34 MT 2 of ENDF/B-VIII.0 data are sometimes too large. Physical limitations of the bounds of mubar limit the maximum uncertainty to be < 1.0 and usually $\ll$ 1.0. Two ad hoc methods are proposed to artificially constrain the randomly sampled values of mubar to allowable values. The application of NJOY’s mubar covariance matrix to the “sandwich rule” is also discussed and a consistent way to apply sensitivity coefficients is described. Mubar uncertainties for the Jezebel k eff were found to be 156 pcm – a value comparable to other evaluated cross section uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Viscosity calculated in simulations of strongly coupled dusty plasmas with gas friction

A two-dimensional strongly coupled dusty plasma is modeled using Langevin and frictionless molecular dynamical simulations. The static viscosity {eta} and the wave-number-dependent viscosity {eta}(k) are calculated from the microscopic shear in the random motion of particles. A recently developed method of calculating the wave-number-dependent viscosity {eta}(k) is validated by comparing the results of {eta}(k) from the two simulations. It is also verified that the Green-Kubo relation can still yield an accurate measure of the static viscosity {eta} in the presence of a modest level of friction as in dusty plasma experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Radio-frequency dispersive detection of donor atoms in a field-effect transistor

Radio-frequency dispersive read-out can provide a useful probe to nano-scale structures, such as nano-wire devices, especially, when the implementation of charge sensing is not straightforward. Here, we demonstrate dispersive “gate-only” read-out of phosphor donors in a silicon nano-scale transistor. The technique enables access to states that are only tunnel-coupled to one contact, which is not easily achievable by other methods. This allows us to locate individual randomly placed donors in the device channel. Furthermore, the setup is naturally compatible with high bandwidth access to the probed donor states and may aid the implementation of a qubit based on coupled donors.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Fluorescent Mueller matrix analysis of a highly scattering turbid media

We report the fluorescent Mueller matrix analysis of a highly scattering, inhomogeneous, and low quantum yield polymeric nanoparticle system. Both the ground and the excited state anisotropy of this turbid system were measured. The excited state anisotropy was found to be higher than ground state anisotropy by inverse polar decomposition analysis. The depolarization coefficients of these polythiophene nanoparticles were experimentally determined by recording Mueller matrices from this complex random medium. This approach provides an alternative method of determining optical characteristics of low quantum efficiency turbid system like fluorescently leveled tissue phantom.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Towards numerically accurate many-body perturbation theory: Short-range correlation effects

The example of the uniform electron gas is used for showing that the short-range electron correlation is difficult to handle numerically, while it noticeably contributes to the self-energy. Nonetheless, in condensed-matter applications studied with advanced methods, such as the GW and random-phase approximations, it is common to neglect contributions due to high-momentum (large q) transfers. Then, the short-range correlation is poorly described, which leads to inaccurate correlation energies and quasiparticle spectra. To circumvent this problem, an accurate extrapolation scheme is proposed. It is based on an analytical derivation for the uniform electron gas presented in this paper, and it provides an explanation why accurate GW quasiparticle spectra are easy to obtain for some compounds and very difficult for others.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Particle shape inhomogeneity and plasmon-band broadening of solar-control LaB{sub 6} nanoparticles

An ensemble inhomogeneity of non-spherical LaB{sub 6} nanoparticles dispersion has been analyzed with Mie theory to account for the observed broad plasmon band. LaB{sub 6} particle shape has been characterized using small-angle X-ray scattering (SAXS) and electron tomography (ET). SAXS scattering intensity is found to vary exponentially with exponent −3.10, indicating the particle shape of disk toward sphere. ET analysis disclosed dually grouped distribution of nanoparticle dispersion; one is large-sized at small aspect ratio and the other is small-sized with scattered high aspect ratio, reflecting the dual fragmentation modes during the milling process. Mie extinction calculations have been integrated for 100 000 particles of varying aspect ratio, which were produced randomly by using the Box-Muller method. The Mie integration method has produced a broad and smooth absorption band expanded towards low energy, in remarkable agreement with experimental profiles by assuming a SAXS- and ET-derived shape distribution, i.e., a majority of disks with a little incorporation of rods and spheres for the ensemble. The analysis envisages a high potential of LaB{sub 6} with further-increased visible transparency and plasmon peak upon controlled particle-shape and its distribution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗