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Results for “Significance Determination Process”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Histopathological characteristics of PRRS and expression profiles of viral receptors in the piglet immune system

Porcine reproductive and respiratory syndrome (PRRS) is a highly contagious viral disease that causes significant economic losses to the swine industry worldwide. PRRS virus (PRRSV) infection is a receptor-mediated endocytosis and replication process. The purpose of this study was to determine the localization and expression of four important PRRSV receptors in immunological organs of piglets. After piglets were infected with PRRSV, Hematoxylin and Eosin staining, immunofluorescence, and Western blot were used to perform histopathological examination and receptors distribution analysis. The results showed that PRRSV caused severe damage to the piglets’ immune organs, including atrophy of the thymus and swelling of lymph node. Histopathological lesions were mainly observed in the lung and lymph node and were characterized by interstitial pneumonia, collapsed follicles, exhaustion of germinal centers, and extensive hemorrhage. Immunofluorescence staining and Western blot results showed that the receptors of CD163 and NMHCII-A were mainly distributed in the thymus, hilar lymph nodes, and mesenteric lymph nodes. However, Sn and vimentin receptors were expressed at low levels in the immune organs of piglets. The distribution of the four receptors in the immune organs was more concentrated in the cortex but was more scattered in the medulla. Compared to the control group, the relative expression of the four receptors increased significantly in most immune organs after viral infection. In conclusion, our study examined the distribution and expression of four PRRSV receptors in immunological organs. We observed a significant increase in the expression of Sn, CD163, and vimentin following viral infection. These findings may provide potential targets for future antiviral reagent design or vaccine development.

Chen, Hong↗
DOE OSTI2025

𝜂 and 𝜂′ meson production in 𝐽/𝜓 radiative decays from lattice QCD

We report on the computation of amplitudes describing the radiative decay processes 𝐽/𝜓 →𝛾⁢𝜂 and 𝐽/𝜓 →𝛾⁢𝜂′ from first principles via lattice quantum chromodynamics (QCD). Using lattices with two heavier than physical degenerate flavors of light quark where 𝑚 𝜋 ∼391 MeV, and a strange quark tuned to approximately the physical value, we compute three-point correlation functions using optimized meson operators with a range of momenta. The use of optimized operators allows access to the 𝜂′, even though it appears as an excited state, lying above the ground-state 𝜂 in the isoscalar pseudoscalar channel. Statistically precise signals are obtained in this disconnected process by averaging over large numbers of kinematically equivalent correlators. We determine transition form factors as a function of photon virtuality across the timelike region, which describe also the Dalitz processes 𝐽/𝜓 →𝑒 + ⁢𝑒 − ⁢𝜂 (′) . Significantly lower magnitudes of transition form factor for both the 𝜂 and 𝜂′ are found than those extracted from experimental data, and possible explanations for this observation are presented.

form factors↗
DOE OSTI2025

Control of core–shell nanoparticles properties through plasma synthesis: a computational study

The improved properties of core–shell nanoparticles (CSNPs) over homogeneous nanoparticles (NPs) have expanded and diversified the applications of these nanomaterials. However, controlling the properties of CSNPs can be a challenging task. Low temperature plasmas have proven to be an effective method of producing NPs with uniform size and morphology, and high yield. That said, NP transport and growth dynamics are sensitive to LTP properties. We report on a computational investigation of the evolution of Ge–Si CSNP properties as a function of operating conditions through the modeling of a flowing, two-zone inductively coupled plasma (ICP) reactor. Ar/GeH 4 and Ar/SiH 4 gas mixtures were supplied to separate plasma zones at a pressure of 1 Torr to promote growth of Ge cores and Si shells. The negatively charged CSNPs are trapped electrostatically in the vicinity of the antennas where the plasma is generated and where the majority of particle growth occurs. Particles that grow to a critical size are then de-trapped by fluid drag due to neutral gas flow. A two-dimensional hybrid plasma model coupled with a three-dimensional kinetic NP transport model were utilized to resolve plasma chemistry and NP growth processes that take place on distinct timescales. The trends in CSNP properties and trapping mechanisms associated with flow rate, applied ICP power and inlet precursor fraction are discussed. While the spatial distribution of plasma produced radical species can have significant impact on the NP growth process, the NP transport dynamics are what ultimately dictates the growth environment that is unique to each particle and so determines their final dimension and composition. The key to optimizing reactor conditions involves controlling the spatial density of growth species and plasma profile as a means to tailor particle trapping dynamics suitable to produce CSNPs for a specific application.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ultrafast Laser Welding and Terahertz Time-domain Spectroscopy of Soda Lime Silicate Glass

Joining and welding techniques of similar and dissimilar materials have reached their limits due to the inflexibility of adapting dielectric materials, e.g., glasses and ceramics, reproducibility for transparent materials, and cycle process time. The ability to join pieces of glasses using laser irradiation allows rapid processing of vacuum insulating glass (VIG) for a widening range of commercial energy-efficient applications. We have used a 1064-nm laser wavelength with 15 picoseconds pulse width and a 155-kHz repetition rate to weld commercial plate glass pieces. The welded samples were characterized via x-ray fluorescence (XRF), time-of-flight secondary ion mass spectrometry (TOF–SIMS), polarimetry, and terahertz time-domain spectroscopy (THz-TDS) to determine the integrity of the weld and chemical changes in the welded areas. Our data shows no significant changes in glass chemistry and structure on average over nano- to micro-scales occurred from the welding process within the limits of the characterization tools. Our results demonstrate successful welding of glass plates without significant changes in the glass chemistry, structure, or properties in the laser-modified region or strains in the bulk glass.

Matthies, Kathleen [ORNL] (ORCID:0009000213135441)↗
DOE OSTI2025

Inverse kinematics study of the energy levels of 21 Ne populated with the 20 Ne +𝑑 reaction

In recent years there has been significant experimental effort aimed at studying the impact of 16 O neutron poisoning on the weak 𝑠 process in rotating massive stars. Improving the understanding of energy levels in 21 Ne is crucial to reducing uncertainties in the rates of the 𝛼-induced reactions on 17 O that determine the overall efficiency of the weak 𝑠 process. This paper reports on one such experiment: a study of the 20 Ne (𝑑,𝑝)⁢ 21 Ne reaction in inverse kinematics. Deduced spin-parity assignments were made based on adiabatic distorted-wave approximation analysis and neutron partial widths were estimated by comparison with a previous experiment. Of particular significance for nuclear astrophysics is the resulting neutron partial width for the 7820-keV energy level, estimated to be 12 200 ⁢(2900)⁢ eV, and an upper limit of ≤ 9300 eV for that of the 7749-keV energy level. These results are in tension with previous studies and therefore this paper also discusses the current state of the research into the astrophysically relevant energy levels and highlights both areas of agreement and areas of disagreement between this and various other studies that have investigated this nucleus.

direct reactions↗
DOE OSTI2025

Search for η c ( 2 S ) → ω ω and ω ϕ and measurements of χ c J → ω ω and ω ϕ in ψ ( 2 S ) radiative processes

Using ( 2712 ± 14 ) × 10 6 ψ ( 2 S ) events collected with the BESIII detector at the BEPCII collider, we search for the decays η c ( 2 S ) → ω ω and η c ( 2 S ) → ω ϕ via the process ψ ( 2 S ) → γ η c ( 2 S ) . No statistically significant signals are observed. The upper limits of their product branching fractions at the 90% confidence level are determined to be B ( ψ ( 2 S ) → γ η c ( 2 S ) , η c ( 2 S ) → ω ω ) < 1.04 × 10 − 6 and B ( ψ ( 2 S ) → γ η c ( 2 S ) , η c ( 2 S ) → ω ϕ ) < 1.85 × 10 − 7 , respectively. We also update the branching fractions of χ c J → ω ω and χ c J → ω ϕ via the ψ ( 2 S ) → γ χ c J transition. Their branching fractions are determined to be B ( χ c 0 → ω ω ) = ( 10.66 ± 0.11 ± 0.57 ) × 10 − 4 , B ( χ c 1 → ω ω ) = ( 6.43 ± 0.07 ± 0.31 ) × 10 − 4 , B ( χ c 2 → ω ω ) = ( 8.75 ± 0.08 ± 0.42 ) × 10 − 4 , B ( χ c 0 → ω ϕ ) = ( 1.18 ± 0.03 ± 0.07 ) × 10 − 4 , B ( χ c 1 → ω ϕ ) = ( 2.04 ± 0.15 ± 0.11 ) × 10 − 5 , and B ( χ c 2 → ω ϕ ) = ( 9.58 ± 1.07 ± 0.76 ) × 10 − 6 , where the first uncertainties are statistical and the second are systematic. Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2026

TES: Modelling Microbes to Predict Post-Fire Carbon Cycling in the Boreal Forest across Burn Severities (Exploratory Proposal)

Wildfires in boreal ecosystems represent a globally significant ecological process that is expected to be sensitive to changing climate as well as forest management strategies, but is currently insufficiently understood and represented in models. We sought to determine whether linking belowground microbial community composition, size, and activity to aboveground properties of burn severity and plant community composition (upland jack pine and upland spruce) would allow us to better model post-fire soil CO 2 fluxes using the Carbon, Organisms, Rhizosphere and Protection in the Soil Environment (CORPSE) model. We used an integrated modelling experimental approach, with mechanistic laboratory experiments designed to inform models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

The complex reaction network of catalytic biomass conversions often involves hundreds of surface intermediates and thousands of reaction steps, greatly hindering the rational design of metal catalysts for these conversions. Here, we present a framework of machine learning (ML)-accelerated first-principles studies for the hydrodeoxygenation (HDO) of propanoic acid over transition metal surfaces. The microkinetic model (MKM) is initially parametrized by ML-predicted energies and iteratively improved by identifying the rate-determining species and steps (RDS), computing their energies by density functional theory (DFT), and reparameterizing the MKM until all the RDS are computed by DFT. The Gaussian process (GP) model performs significantly better than the linear ridge regression model for predicting both the adsorption free energies and transition state free energies. Parameterized with energies from the GP model, only 5–20% of the full reaction network has to be computed by DFT for the MKM to possess DFT-level accuracy for the TOF and dominant reaction pathway. While the linear ridge regression model performs worse than the GP model, its performance is greatly improved when only transition states are predicted by the regression model and adsorption energies are computed by DFT. Overall, we find that a high accuracy in adsorption free energies is more important for a reliable MKM than a high accuracy in TS free energies. Lastly, based on the GP model with GOH and GCHCHCO as catalyst descriptors, we build two-dimensional volcano plots in activity and selectivity that can help design promising alloy catalysts for HDO reactions of organic acids.

adsorption↗
DOE OSTI2024

Rupture Model of the 5 April 2024 Tewksbury, New Jersey, Earthquake Based on Regional Lg -Wave Data

On 5 April 2024, an earthquake of magnitude 4.8 occurred in Tewksbury, New Jersey. It was the largest instrumentally recorded event since 1900 in New Jersey and southern New York. Millions of people around New York City, ~65 km east–northeast of Tewksbury, felt the shaking from the mainshock, but the epicentral area experienced no known significant property damages. We determine the focal mechanism, which is oblique faulting, and retrieve the Lg–wave relative source time functions (RSTFs) from the stations at regional distances to understand rupture processes and ground motions. Our fault–slip models well explain azimuthal variations of the RSTFs. The models show the rupture propagating toward the east–northeast (~50° to 60°), not along the fault strike. The slip distribution on the nodal plane striking north and dipping to the east shows a slip area of 1.1 km radius with the rupture propagating down–dip. The down–dip rupture may account for the observed lack of strong shaking in the epicentral area.

58 GEOSCIENCES↗
DOE OSTI2024

Development of an Attenuated Total Reflectance–Ultraviolet–Visible Probe for the Online Monitoring of Dark Solutions

Optical spectroscopy is a valuable tool for on-line monitoring of a variety of processes. Ultraviolet-visible (UV-vis) spectroscopy in particular, can monitor the concentration of analytes as well as identify speciation and oxidation state. However, it can be difficult to impossible to employ UV-vis based sensors on chemical systems that are very dark (i.e., high optical density) as exceedingly short pathlengths are required (for transmission approaches) or effective means of backscattering are needed (for reflectance approaches). Examples of processes that would benefit significantly from the use of optical sensors and encounter these challenges include used nuclear fuel recycling and molten salts with high concentrations of dissolved uranium. Utilizing an attenuated total reflectance (ATR) UV-vis approach can overcome these challenges and allow for the measurement of solutions orders of magnitude more concentrated than transmission UV-vis. However, determining ideal sensor specifications for varied processes can be time consuming and expensive. Here, in this study, we evaluate the ability for a novel ATR-UV-vis probe to measure very concentrated solutions of Co(II) and Ni(II) nitrate as well as organic dyes (methylene blue, acid red 1, and crystal violet). This sensor design provides a modular method for exploring possible “pathlengths” by altering the exposed ATR fiber length. Also studied were approaches to loading and measuring the sensor cell. These results are compared to a traditional 1 cm cuvette measured by transmission UV-vis. It was found that the ATR-UV-vis probe was capable of measuring solutions 600 times more concentrated than the 1 cm cuvette. Advanced data analysis in the form of multivariate curve resolution (MCR) was used to analyze the speciation of methylene blue over a large concentration range. The application of this novel ATR-UV-vis probe to the interrogation of dark solutions is a promising avenue for use in on-line monitoring of nuclear processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

DISSOLUTION OF SURROGATE U-Zr FUEL USING ALNIFLEX CONDITIONS

Non-aluminum clad spent nuclear fuel (NASNF) stored in L Basin at the Savannah River Site (SRS) is widely varied in fuel composition, design, packaging, and physical condition. The complexity of the NASNF inventory presents significant challenges, and technology development is necessary for successful disposition. One such fuel in the inventory is metallic uranium-zirconium (U-Zr) alloy fuel, the focus of this study. Electrolytic or nitric acid only dissolution of metallic U-Zr alloy can form insoluble zirconium oxide, which results in up to 52% loss of U to insoluble solids, and can be subject to potentially uncontrolled oxidation reactions [1, 2]. The AlNiflex process was determined to be a viable dissolution flowsheet for the U-Zr alloy fuel. Under a narrow set of solution concentrations, a combination of hydrofluoric acid (HF), nitric acid (HNO3), aluminum nitrate (Al(NO3)3), and hexavalent chromium can safely dissolve U-Zr intermetallic alloys, keep Zr soluble, and not significantly corrode stainless steel (SS) vessels [3, 4.

Gogolski, Jarrod M. [Savannah River National Labor↗
DOE OSTI2024

Search for X ( 1870 ) via the decay J / ψ → ω K + K − η

Using a sample of ( 10087 ± 44 ) × 10 6 J / ψ events collected by the BESIII detector at the BEPCII collider, we search for the decay X ( 1870 ) → K + K − η via the J / ψ → ω K + K − η process for the first time. No significant X ( 1870 ) signal is observed. The upper limit on the branching fraction of the decay J / ψ → ω X ( 1870 ) → ω K + K − η is determined to be 9.55 × 10 − 7 at the 90% confidence level. In addition, the branching faction B ( J / ψ → ω K + K − η ) is measured to be ( 3.33 ± 0.02 ( stat ) ± 0.12 ( syst ) ) × 10 − 4 . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching

Diffusion MRI (dMRI) non-invasively maps brain white matter yet necessitates denoising due to low signal-to-noise ratios. Patch2Self (P2S) employing self-supervised techniques and regression on a Casorati matrix effectively denoises dMRI images and has become the new de-facto standard in this field. P2S however is resource intensive both in terms of running time and memory usage as it uses all voxels (n) from all-but-one held-in volumes (d-1) to learn a linear mapping Phi : \mathbb R ^ n x(d-1) \mapsto \mathbb R ^ n for denoising the held-out volume. The increasing size and dimensionality of higher resolution dMRI acquisitions can make P2S infeasible for large-scale analyses. This work exploits the redundancy imposed by P2S to alleviate its performance issues and inspect regions that influence the noise disproportionately. Specifically this study makes a three-fold contribution: (1) We present Patch2Self2 (P2S2) a method that uses matrix sketching to perform self-supervised denoising. By solving a sub-problem on a smaller sub-space so called coreset we show how P2S2 can yield a significant speedup in training time while using less memory. (2) We present a theoretical analysis of P2S2 focusing on determining the optimal sketch size through rank estimation a key step in achieving a balance between denoising accuracy and computational efficiency. (3) We show how the so-called statistical leverage scores can be used to interpret the denoising of dMRI data a process that was traditionally treated as a black-box. Experimental results on both simulated and real data affirm that P2S2 maintains denoising quality while significantly enhancing speed and memory efficiency achieved by training on a reduced data subset.

Fadnavis, Shreyas↗
DOE OSTI2025

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗
DOE OSTI2024

Non-nuclear Component Signatures for Warhead Dismantlement Confirmation

The verification of warhead dismantlement is expected to be an important component in future arms reduction treaties. Historic approaches developed with future arms control treaty verification in mind often involve intrusive measurements, process monitoring, and/or inspector presence to provide confidence that an authentic warhead has been dismantled. This work explores the possibility of reducing the negative impacts of these invasive approaches while also delivering a method that is more likely to provide non-sensitive data that can be shared with not only other nuclear weapons states but also non-nuclear weapons states partners. This work explores a novel approach for verifying dispositioned non-nuclear weapon components, providing confidence post-dismantlement that a treaty accountable item that was dismantled was in fact a treaty-relevant nuclear weapon system as declared. This method provides an alternative to intrusive inspection processes in nuclear weapons production environments, which would require significant changes to the host’s operational behaviors. It achieves this by identifying intrinsic neutron-induced signatures of non-nuclear components to determine their authenticity and estimate the duration they were exposed within a nuclear weapons system using technologies that are already in use for other national security applications. Intrinsic radiation effects studies are already a part of the stockpile aging and surveillance evaluations. However, none of these technologies and approaches have been previously considered for verification applications of non-nuclear component disposition. In this report, we introduce modeling studies that have been used to identify the most promising candidate parts and materials with signatures that are measurable and actionable. These models have been validated with laboratory measurements of signatures induced by the exposure of candidate materials to neutrons over a range of times. Predictive modeling then demonstrates the methodology for estimating exposure times and/or limits. Laboratory measurements of authentic non-nuclear parts from a dismantled warhead demonstrate the feasibility of employing these signature measurements. And finally, a concept of operations (CONOPS) for the potential use of this methodology is presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Half-life determination of heavy ions in a storage ring considering feeding and depleting background processes

Heavy-ion storage rings have relatively large momentum acceptance which allows for multiple ion species to circulate at the same time. This needs to be considered in radioactive decay measurements of highly charged ions, where atomic charge exchange reactions can significantly alter the intensities of parent and daughter ions. In this study, we investigate this effect using the decay curves of ion numbers in the recent 205 Tl 81+ bound-state beta decay experiment conducted using the Experimental Storage Ring at GSI Darmstadt. To understand the intricate dynamics of ion numbers, we present a set of differential equations that account for various atomic and nuclear reaction processes—bound state beta decay, atomic electron recombination and capture, and electron ionization. By incorporating appropriate boundary conditions, we develop a set of differential equations that accurately simulate the decay curves of various simultaneously stored ions in the storage ring: 205 Tl 81+ , 205 Pb 81+ , 205 Pb 82+ , 200 Hg 79+ , and 200 Hg 80+ . Through a quantitative comparison between simulations and experimental data, we provide insights into the detailed reaction mechanisms governing stored heavy ions within the storage ring. Our approach effectively models charge-changing processes, reduces the complexity of the experimental setup, and provides a simpler method for measuring the decay half-lives of highly charged ions in storage rings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A comparative analysis of residual stresses from friction stir processing of aluminum cast 380 and wrought 7075 alloy sheets: experimental characterization and modeling

Residual stresses are often overlooked in friction stir processing (FSP), but their significant impact on fatigue performance necessitates their consideration in optimizing processing parameters. The first step in this effort is understanding how process conditions influence residual stress distributions, especially across different alloys. This study focuses on determining and explaining the through-thickness residual stress variations and the effect of process temperature on the residual stress magnitude in wrought AA7075 and cast AA380.0 alloys. Additionally, for AA380.0, the impact of a second FSP pass was investigated. To achieve this, hole-drilling electronic speckle pattern interferometry (ESPI) and the thermal pseudo-mechanical (TPM) model within finite element analysis were employed to study the 3D distributions of in-plane residual stresses in processed samples under various conditions. A key finding was the varying impact of process temperatures on residual stress magnitudes. Higher process temperatures reduced stresses in AA380.0 but increased them in AA7075. Additionally, the through-thickness stress distributions differed between the two alloys. Further analysis revealed that yield stresses are crucial in explaining these phenomena and the effects of additional FSP passes. Further, this fundamental understanding will be vital in guiding the efforts to mitigate residual stresses and assess their impact on the performance of FSP aluminum alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An Uncertainty-Informed and High-Fidelity Performance Forecasting Framework for Heliostat Fields

Concentrating Solar Thermal (CST) tower systems employ heliostat fields to direct solar energy to a central receiver, which then transfers the heat either directly to a thermal process (e.g., steam production) or to a thermal energy storage system for future use. Heliostat fields compose a significant proportion of the project costs of a CST tower system and the performance of the heliostats determines a plant's productivity at a given location. While CST characterization tools such as SolarPILOT and System Advisor Model (SAM) include a large collection of inputs that influence the performance of a CST tower system, many are uncertain prior to the development of the project and may have a significant impact on the overall energy delivery and profitability of a project; moreover, the fidelity of these models under default conditions may be insufficient to determine the value of component improvements such as those under development in the Heliostat Consortium. This work introduces a Monte Carlo simulation framework that incorporates uncertainty in key performance parameters to generate confidence intervals and percentile estimates for a CST solar field's energy delivery.

14 SOLAR ENERGY↗