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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bi-chromatic intensity squeezing using four-wave mixing in 85 Rb vapor

We experimentally investigate four-wave mixing (FWM) in a diamond interaction scheme using 85 Rb vapor, and identify the optimal conditions for joint amplification and relative intensity squeezing of two optical fields: one near the 85 Rb D1 optical transition (λ = 794.6 nm) and the other in the telecom O-band (λ = 1324 nm). We achieved a reduction of relative intensity noise by up to 2.6 ± 0.4 dB compared with the shot noise level, signifying the non-classical quantum correlations. The observed level of intensity squeezing is primarily limited by the available pump laser power, which constrains the achievable FWM gain. Numerical simulations show good agreement with the experimental results.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2012

Plant Science in Reduced Gravity: Lessons Learned

The effect of gravity on the growth and development of plants has been the subject of scientific investigation for over a century. The results obtained in space to test specific hypotheses on gravitropism, gene expression, seed formation, or growth rate are affected by both the primary effect of the microgravity and secondary effects of the spaceflight environment. The secondary effects of the spaceflight environment include physical effects arising from physical changes, such as the absence of buoyancy driven convective mixing, altered behavior of liquids and gases, and the environmental conditions in the spacecraft atmosphere. Thus, the design of biological experiments (e.g. cells, plants, animals, etc.) conducted in microgravity must account for changes in the physical forces, as well as the environmental conditions, imposed by the specific spaceflight vehicle and experimental hardware. In addition, researchers must become familiar with other aspects of spaceflight experiments: payload integration with hardware developers, safety documentation and crew procedures, and the logistics of conducting flight and ground controls. This report reviews the physical and environmental factors that directly and indirectly affect the results of plant science experiments in microgravity and is intended to serve as a guide in the design and implementation plant experiments in space.

Stutte, Gary W.↗
DOE OSTI2022

Transformation of a ceramic precursor to a biomedical (metallic) alloy: Part I – sinterability of Ta 2 O 5 and TiO 2 mixed oxides

Mixed Ta 2 O 5 – TiO 2 binary system was studied by a combination of differential thermal analysis (DTA), scanning electron microscopy-energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and in situ high temperature X-ray diffraction (HT-XRD) techniques. Different compositions of the mixed oxide powders were fabricated by ball–milling the powdered compositions, pelletizing the homogenized composite powders, and heating the green pellets in air at different temperatures for fixed time intervals. The sintered pellets were evaluated and characterized with respect to porosity, morphology, and phase distribution. DTA runs of the un-sintered powders indicated the onset temperatures for both exothermic and endothermic changes in the binary system. Significant amount of sintering was observed to take place at temperatures higher than 900 °C. Both room and high temperature X-ray diffraction patterns exhibited consistency in phase formation. A ternary compound (TaTiO 4 ) and a ternary solid solution (Ti 0.33 Ta 0.67 O 2 ) were observed to form in both room and high temperatures in addition to the respective binary phases (Ta 2 O 5 and TiO 2 ). A sintering temperature in the range 900–1000 °C was observed to be adequate to achieve the requisite mechanical strength and optimum internal porosity (40–48%) for subsequent electrochemical polarization experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗
DOE OSTI2023

Striking stability of a mixed-valence thallium(III)-thallium(I) complex in some solvents

At the dissolution of solid anhydrous thallium(III) trifluoromethanesulfonate, Tl(CF 3 SO 3 ) 3 , or thallium(III) trifluoroacetate, Tl(CF 3 COO) 3 , in dimethylsulfoxide (dmso) or N,N,N’,N’-tetramethylurea (tmu), intensely red-colored complexes are formed. This red thallium complex is stable for years in dmso, while it is reduced fairly rapidly to thallium(I) in tmu with a half-life time of an hour. At the dissolution of Tl(CF 3 SO 3 ) 3 in N,N-dimethylpropyleneurea (dmpu) an immediate reduction to thallium(I) takes place. A stable colorless aqueous thallium(III) solution is obtained at the dissolution in acidic water. Stable dmso solutions and solid dmso solvates of thallium(III) perchlorate, nitrate and trifluormethanesulfonate can be prepared by adding dmso to concentrated acidic aqueous thallium(III) solutions. These experimental observations conclude that the pure solids Tl(CF 3 SO 3 ) 3 and Tl(CF 3 COO) 3 play an essential role in the formation of the red-colored thallium complexes. 205 Tl NMR data show that the red thallium complex contains equal amounts of thallium(III) and thallium(I). The structure of the red thallium complex in dmso, as determined by EXAFS, has Tl–O bond distances of 2.216(3) and 2.80(2) Å, which are in very close agreement with the bond distances obtained in the pure dmso solvates of the thallium(III) and thallium(I) ions, respectively, and a Tl···Tl distance of 3.49(1) Å bridged by oxygen atoms. From the EXAFS data it is impossible to distinguish if dmso molecules and/or trifluoromethanesulfonate ions act as bridges. DFT calculations could eliminate some structures due to the irrelevant structural parameters or the energetics of the proposed reactions.

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

Towards AI-assisted neutrino flavor theory design

Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A model’s construction typically relies on the intuition of theorists. It also requires considerable effort to identify appropriate symmetry groups, assign field representations, and extract predictions for comparison with experimental data. We develop Autonomous Model Builder (AMBer), a framework in which a reinforcement learning agent interacts with a streamlined physics software pipeline to search these spaces efficiently. AMBer selects symmetry groups, particle content, and group representation assignments to construct models while minimizing the number of free parameters introduced. We validate our approach in well-studied regions of theory space and extend the exploration to a previously unexamined symmetry group. While demonstrated in the context of neutrino flavor theories, this approach of reinforcement learning with physics software feedback may be extended to other theoretical model-building problems in the future.

Baretz, Jason Benjamin↗
DOE OSTI2020

IR dynamics from UV divergences: UV/IR mixing, NCFT, and the hierarchy problem

The persistence of the hierarchy problem points to a violation of effective field theory expectations. A compelling possibility is that this results from a physical breakdown of EFT, which may arise from correlations between ultraviolet (UV) and infrared (IR) physics. To this end, we study noncommutative field theory (NCFT) as a toy model of UV/IR mixing which generates an emergent infrared scale from ultraviolet dynamics. We explore the range of such theories where ultraviolet divergences are transmogrified into infrared scales, focusing particularly on the properties of Yukawa theory, where we identify a new infrared pole accessible in the s-channel of the Lorentzian theory. We further investigate the interplay between UV-finiteness and UV/IR mixing by studying properties of the softly-broken noncommutative Wess-Zumino model as soft terms are varied relative to the cutoff. While the Lorentz violation inherent to noncommutative theories may limit their direct application to the hierarchy problem, these toy models provide general lessons to guide the realization of UV/IR mixing in more realistic theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Neutrino oscillation prospects with a dual-baseline beam from BNL to SNOLAB and SURF

The Electron-Ion Collider (EIC) is a next-generation accelerator primarily designed to study the internal structure of nucleons through high-precision electron-hadron collisions. In this work, we explore the feasibility of employing a 1 MW fraction of the EIC proton beam to generate a high-intensity GeV-scale neutrino beam for long-baseline oscillation studies. We have simulated proton-target interactions and optimize the resulting neutrino fluxes for water-based liquid scintillator (WbLS) detectors located at distinct baselines of 900 km and at 2900 km. Oscillation analyses performed with GLoBES show that extended baselines allow access to multiple oscillation maxima, significantly enhancing sensitivity to leptonic CP violation. The study also examines the interplay between matter effects and the intrinsic CP violating phase in shaping observable asymmetries. We note that simplified systematics and no backgrounds are used in this analysis to establish the baseline physics potential. These results suggest that the EIC proton beam could provide a novel and complementary source for precision neutrino physics, extending the scientific reach of the EIC program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Measurements of differential cross-sections in four-lepton events in 13 TeV proton-proton collisions with the ATLAS detector

Measurements of four-lepton differential and integrated fiducial cross-sections in events with two same-flavour, opposite-charge electron or muon pairs are presented. The data correspond to 139 fb -1 of $ \sqrt{s} $ = 13 TeV proton-proton collisions, collected by the ATLAS detector during Run 2 of the Large Hadron Collider (2015–2018). The final state has contributions from a number of interesting Standard Model processes that dominate in different four-lepton invariant mass regions, including single Z boson production, Higgs boson production and on-shell ZZ production, with a complex mix of interference terms, and possible contributions from physics beyond the Standard Model. The differential cross-sections include the four-lepton invariant mass inclusively, in slices of other kinematic variables, and in different lepton flavour categories. Also measured are dilepton invariant masses, transverse momenta, and angular correlation variables, in four regions of four-lepton invariant mass, each dominated by different processes. The measurements are corrected for detector effects and are compared with state-of-the-art Standard Model calculations, which are found to be consistent with the data. The Z → 4 ℓ branching fraction is extracted, giving a value of (4.41 ± 0.30) × 10 -6 . Constraints on effective field theory parameters and a model based on a spontaneously broken B – L gauge symmetry are also evaluated. Further reinterpretations can be performed with the provided information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The Ghent Hybrid model in NuWro: a new neutrino single-pion production model in the GeV regime

Neutrino-induced single-pion production constitutes an essential interaction channel in modern neutrino oscillation experiments, with its products building up a significant fraction of the observable hadronic final states. Frameworks of oscillation analyses strongly rely on Monte Carlo neutrino event generators, which provide theoretical predictions of neutrino interactions on nuclear targets. Thus, it is crucial to integrate state-of-the-art single-pion production models with Monte Carlo simulations to prepare for the upcoming systematics-dominated landscape of neutrino measurements. In this work, we present the implementation of the Ghent Hybrid model for neutrino-induced single-pion production in the NuWro Monte Carlo event generator. The interaction dynamics includes coherently-added contributions from nucleon resonances and a non-resonant background, merged into the pythia branching predictions in the deep-inelastic regime, as instrumented by NuWro. This neutrino-nucleon interaction model is fully incorporated into the nuclear framework of the generator, allowing it to account for the influence of both initial- and final-state nuclear medium effects. We compare the predictions of this integrated implementation with recent pion production data from accelerator-based neutrino experiments. The results of the novel model show improved agreement of the generator predictions with the data and point to the significance of the refined treatment of the description of pion-production processes beyond the ∆ region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Integration of graphical approaches into optimization-based design of multistage liquid extraction

We propose two optimization models for designing two liquid extraction systems: simple multistage liquid extractors and extractors with extract reflux. Both models are motivated by the concepts of the modified McCabe-Thiele graphical method for multistage extractor design. The operating and equilibrium curves in the McCabe-Thiele method are represented by material balances and piece-wise linearized thermodynamics properties. The use of piece-wise approximations improves computational tractability of both optimization models. In addition, we consider some extensions such as dilute systems, insoluble solvents, and non-ideal stages. In conclusion, the applicability of the proposed models is demonstrated with four illustrative examples.

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

A crisis for the verification and validation of turbulence simulations

Three algorithms have been proposed for solution of the Rayleigh–Taylor turbulent mixing problem. They are based upon three different physical principles governing the Euler equations for fluid flow. The principles serve to select the physically relevant solution from among many nonunique solutions. The admissibility principle is in dispute. The three different algorithms, expressing the three physical admissibility principles can be formulated in terms of the three energy dissipation rates or the entropy production rates, as selected by the size of the sub grid scale coefficients. These have maximal values or less than maximal values. The resulting solutions are markedly different. We find strong validation evidence that supports the maximum rate principle, based on a review of prior results and on new results presented here. We review experimental data used for validation and sufficient to discriminate among the three. We present a new analysis of this data. We show that the hypothesized long wave length perturbations in the initial conditions are not significant, so that validation can be based on this data in a straight forward manner. One of the algorithms is labeled direct numerical simulation, but is not, and as a consequence, the two algorithms with less than maximal SGS coefficients are variants of one another. Finally recommendations for the numerical modeling of the deflagration to detonation transition in type Ia supernova are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Interplay of surface energy and rheology in biopolymer soil enhancement

Biopolymers such as xanthan gum (XG) and locust bean gum (LBG) hold great potential as eco-friendly alternative soil binders. In this work, we investigated the impact of XG/LBG mixtures on the unconfined compressive strength (UCS) of sand. The high strength of dry biopolymer/sand arises from the cohesion between solid polymer films and sand particles which supported by work of adhesion calculation and soil mechanics measurement. LBG exhibits much lower sand reinforcement efficacy because polymers unevenly distributed within sand matrix. The formation of a core-shell structure in LBG/sand is an interplay of surface free energy and viscoelastic properties of polymer solutions. This structure is altered when LBG mixed with XG at varying ratios as those physical properties changed due to the complexity of polymer chains association. By probing these factors, we aim to elucidate the role of surface energies and polymer physics in governing the strength of the sand/polymer network, thereby contributing to a more comprehensive understanding polymer-sand interface. The low strength of gels (G’ ∼10Pa) cannot solely account for the increased UCS of wet sand over 10 kPa. Instead, the high strength of biopolymer/sand is more likely derived from the granular particles with biopolymers as solid glue.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthesis of uranium mixed anion compounds synthesized using the Boron-Chalcogen Mixture method: Ba 6 Co 6 U 0·9 1S 13·5 O 0.5 and Ba 5·47 K 0·53 Zn 6 US 13·5 O 0.5

Mixed anion compounds have exhibited interesting structures and properties that differ from compounds only incorporating a single anion in their composition. Unfortunately, difficulties in the synthetic methods used to obtain these materials has slowed the evolution of this field, prompting investigations into alternate synthetic pathways to these materials. Our recently establish Boron-Chalcogen Mixture (BCM) method, which was originally developed for the synthesis of pure actinide chalcogenides from oxides, has been adapted to achieve the partial oxide to sulfide conversion of Ba 2 MUO 6 (M = Co, Zn) which resulted in two new uranium (IV/V) oxysulfide compounds, Ba 6 Co 6 U 0·91 S 13·5 O 0.5 and Ba 5·47 K 0·53 Zn 6 US 13·5 O 0.5 These compounds crystallize in the tetragonal crystal system adopting the space group I4/mcm. Finally, their syntheses, crystal structures, and trends observed in the pursuit of these new mixed anion compounds are reported.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗