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Results for “range prediction”

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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A search for dark matter produced in association with a dark Higgs boson decaying into a Higgs boson pair in 3b or 4b final states using pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

A search is performed for dark matter particles produced in association with a resonant pair of Higgs bosons using 140 fb −1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. This signature is expected in some extensions of the Standard Model predicting the production of dark matter particles, and is interpreted in terms of a dark Higgs model containing a Z′ mediator in which the dark Higgs boson s decays into a pair of Higgs bosons. The dark Higgs boson is reconstructed through final states with at least three b-tagged jets, produced by the pair of Higgs boson decays, in events with significant missing transverse momentum consistent with the presence of dark matter. The observed data are found to be in good agreement with Standard Model predictions, constraining scenarios with dark Higgs boson masses within the range of 250 to 400 GeV and Z′ mediators up to 2.3 TeV.

Dark Energy and Dark Matter↗
DOE OSTI2020

Microparticle impact-bonding modes for mismatched metals: From co-deformation to splatting and penetration

In this paper we present a comprehensive experimental campaign of high-velocity microparticle impacts with different combinations of particle and substrate materials to identify possible deformation regimes. Based on experimental observations of the impact sites, we identify three typical modes of behavior, namely, splatting, co-deformation, and penetration. We develop a theoretical framework to predict the operative bonding regime for a given particle/substrate combination, ranging from splatting and penetration at two extremes of a spectrum, and co-deformation in the center. We propose an impact ratio based on the materials’ properties, which can successfully quantify the spectrum. Co-deformation is expected when the ratio is around unity, while much larger or smaller ratios give rise to penetration and splatting, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An experimental investigation of flame and autoignition behavior of propane

We report autoignition delay time data are one important means to develop, quantify, and validate fundamental understanding of combustion chemistry at low temperatures (T<1200 K). However, low-temperature chemistry often has higher uncertainties and scatter in the experimental data compared with high-temperature ignition data (T>1200 K). In this study, autoignition properties of propane and oxygen mixtures were investigated using the University of Michigan rapid compression facility in order to understand the effects of ignition regimes on low-temperature ignition data. For the first time for propane, autoignition delay times were determined from pressure histories, and autoignition characteristics were simultaneously recorded using highspeed imaging of the test section through a transparent end-wall. Propane mixtures with fuel-to-O 2 equivalence ratios of φ = 0.25 and φ = 0.5 and O 2 -to-inert gas molar ratios of 1:3.76 were studied over the pressure range of 8.9 to 11.3 atm and the temperature range of 930 – 1070 K. The results showed homogeneous or strong autoignition occurred for all φ = 0.25 experiments, and inhomogeneous or mixed autoignition occurred for all φ = 0.5 experiments. While a limited temperature range is covered in the study, importantly the data span predicted transitions in autoignition behavior, allowing validation of autoignition regime hypotheses. Specifically, the results agree well with strong-autoignition limits proposed based on the Sankaran Criterion. The autoignition delay time data at the strong-ignition conditions are in excellent agreement with predictions using a well-validated detailed reaction mechanism from the literature and a zerodimensional modeling assumption. However, the experimental data at the mixed autoignition conditions were systematically faster than the model predictions, particularly at lower temperatures (T< ~970 K). The results are an important addition to the growing body of data in the literature that show mixed autoignition phenomena are important sources of the higher scatter observed in the low-temperature autoignition data for propane and other fuels. The results are discussed in terms of different methods to capture the effects of pre-autoignition heat release associated with mixed autoignition conditions and thereby address some of the discrepancies between kinetic modeling and experimental measurements.

42 ENGINEERING↗
DOE OSTI2026

High-throughput oxidation screening and down-selection of refractory high entropy alloys in the Al-Cr-Mo-Nb-Ta-Ti system

Rapid experimentation and characterization are ever-present needs in the discovery of high entropy alloys. High entropy alloy systems are difficult to survey with systematic composition sweeps using traditional synthesis methods. The number of distinct compositions in even a four-element system is experimentally intractable. Exploration of these, and higher-element systems, necessitates thermodynamic prediction coupled with an automated sample creation method and a rapid screening methodology to effectively down-select alloys with targeted properties. As a result, a high-throughput method for evaluating the oxidation performance of refractory high entropy alloys was developed and tested. The six-element system of aluminum, chromium, molybdenum, niobium, tantalum, and titanium was evaluated for single phase stability and short-duration oxidation resistance. Target compositions were initially determined via thermodynamic predictions of single-phase stability across a wide temperature range. A twenty-five-sample build plate was produced using directed energy deposition additive manufacturing. After fabrication, the twenty-five 1 cm 3 samples were heat treated and characterized for composition and phase identification. The build plate was exposed to a high temperature oxidizing environment at 1000 °C for three hours. After oxidation, the composition, morphology, and chemistry of the oxides formed were characterized. Of the twenty-five samples produced, nine exhibited a favorable oxidation response, from which a single-phase BCC alloy at a composition of Al 13 Cr 7 Mo 19 Nb 18 Ta 26 Ti 17 was identified as the alloy with the most protective oxidation coating with a thin, adherent oxide scale. Finally, the complete experimental down-selection—from machine setup to final alloy identification—required approximately 45 labor hours, demonstrating a rapid validation for alloy discovery.

Additive manufacturing↗
DOE OSTI2025

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

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

Accuracy in Resolving the First Hydration Layer on a Transition-Metal Oxide Surface: Experiment (AP-XPS) and Theory

Understanding the equilibrium conditions at the metal oxide/aqueous interface is a key component toward visualizing the structure of water in confined environments and differentiating the catalytic activity of transition-metal oxides. While ambient pressure X-ray photoelectron spectroscopy (AP-XPS) has been the primary technique to investigate the formation of a hydration layer on many surfaces, results over the extended relative humidity (RH) range accessible experimentally have not been compared quantitatively to theoretical predictions. With the use of first-principles theoretical methods and accumulated knowledge of AP-XPS spectral analysis, we do so here for a model surface, TiO 2 -terminated undoped SrTiO 3 (100) (STO). The measured distribution of OH and H 2 O coverages from vacuum up to the first hydration layer is in good agreement with a static density functional theory (DFT) configuration involving partial dissociation of H 2 O per Ti-atom mediated by H-bonding. Furthermore, ab initio molecular dynamics (AIMD) simulations at 300 K for select coverages (1/4, 1/2, and 1 ML) test the role of fluctuations and entropy in the competition between adsorption and dissociation with coverage. This comparison between theory and experiment for OH and H 2 O coverages on STO provides a foundation for a more quantitative assessment of the first hydration layer and associated competition between adsorption, dissociation, and H-bonding on transition-metal oxide surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process for Polyethylene-Based Composite Radiation Shielding Material

Polyethylene (PE) is one of the best shielding materials for primary space radiation due to its high hydrogen content. For effective secondary neutron shielding, boron-rich fillers are incorporated to enhance performance. The semicrystalline nature and high thermal expansion coefficient of PE impede its adoption for in situ additive manufacture in space via the fused deposition modeling (FDM) 3D printing. Here, we developed an optimized PE blend to mitigate the effects of under-extrusion and warpage. Guided by studies on extrusion and warpage, we developed an optimal set of printing parameters for the proposed PE blend. The optimum PE blend─both in its pure form and when doped with fillers─has been tested on different FDM printers. The printed structures exhibit high and uniform density, smooth surfaces, no warpage, and competitive mechanical properties. The FDM-printed plates demonstrate efficient shielding from thermal neutrons, predicted via modeling and confirmed experimentally using extended Q-range small-angle neutron scattering.

additive manufacturing↗
DOE OSTI2020

A near-explicit mechanistic evaluation of Isoprene photochemical seecondary organic aerosol formation and evolution: simulations of multiple chamber experiments with and without added NOx

Experimentally determined yields of secondary organic aerosol (SOA) from the photochemical oxidation of isoprene in the absence of aqueous acidic aerosol vary substantially, both within a given experiment and across different environmental chamber conditions. The underlying mechanisms driving this variation remain poorly evaluated, leading to significant uncertainty in how to extrapolate laboratory chamber results to the atmosphere. Herein, we compare SOA predictions from a near-explicit gas-phase chemical mechanism of isoprene oxidation by the hydroxyl radical (OH) in the presence and absence of nitrogen oxide radicals (NOx), to multiple chamber experiments on non-aqueous isoprene photochemical SOA (ipSOA) conducted by different groups in different chambers. SOA is predicted by volatility-driven gas-particle partitioning of hundreds of individual reaction products. The mechanism includes simplified descriptions of particle-phase organic chemistry, including organic hydroperoxide photolysis, and organic nitrate hydrolysis and accretion reactions. The model has good skill (mean normalized bias typically within 25%) at predicting the observed formation and evolution of ipSOA across a range of chambers and conditions at low NOx. The model has much less skill at describing the observed non-linear response of ipSOA to elevated NOx. Organic nitrate hydrolysis is unable to explain significant ipSOA at high NOx, whereas particle-phase accretion reactions of tertiary nitrates may play a role. Uncertainties in the chamber radical environment and fate of key organic peroxy radicals (RO2) remain as or even more important than vapor losses to chamber walls in determining how best to extrapolate chamber-based yields to the atmosphere. Implications for likely atmospheric yields of ipSOA and recommendations for future chamber experiments are discussed.

Thornton, Joel A.↗
DOE OSTI2025

Approach to Evaluating Reorganization Energies of Interfacial Electrochemical Reactions

Reaction rate coefficients for electron-transfer processes at the electrode–electrolyte interface are commonly estimated by using the Butler–Volmer equation, but their values are inaccurate beyond a few tenths of volts of overpotential. The Marcus–Hush–Chidsey (MHC) formalism yields correct asymptotic behavior of the rate coefficients vs applied overpotential but has complex dependencies on the redox system’s intrinsic parameters, which can be difficult to model or measure. In this work, we bridge the two kinetics formalisms to estimate the reorganization energy, one of the important parameters for the MHC formalism, and investigate its dependence on other intrinsic parameters such as activation barriers, electronic coupling strength, and the density of states of the electrode surface. We examine the sensitivity of the reorganization energy to these parameters, establish some general relationships for accurately predicting rate coefficients using the MHC formalism over a wide range of applied overpotentials, and compare this approach to calculating MHC rate constants with other empirical approaches for the mechanisms of CO 2 reduction on different metal electrode surfaces.

Butler−Volmer↗
DOE OSTI2023

Combined First-Principles and Experimental Investigation into the Reactivity of Codeposited Chromium–Carbon under Pressure

High-pressure synthesis in the diamond anvil cell suffers from the lack of a general approach for the control of precursor stoichiometry and homogeneity. Here, we present results from a new method we have developed that uses magnetron cosputtering to prepare stoichiometrically precise and atomically mixed amorphous films of Cr:C. Laser-heated diamond anvil cell experiments carried out on a flake of this sample at pressures between 13.5 and 24.3 GPa lead to the observation of Cr 3 C (Pnma) over the entire pressure range–in good agreement with our in-house theoretical predictions–but also reveal two other metastable phases that were not expected: a novel monoclinic chromium carbide phase and the NaCl-type CrC (Fm3̅m) phase. The unexpected stability of CrC is investigated by using first-principles methods, revealing a large stabilizing effect tied to substoichiometry at the carbon site. These results offer an important case study into the current limitations of crystal structure prediction methods with regard to phase complexity and bolster the growing need for advanced theoretical approaches that can more completely survey experimentally unexplored phase space.

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

J -Resolved Molecular Fingerprinting by Parahydrogen Hyperpolarized Low-Field NMR

A J-resolved spectroscopy that depends on homonuclear scalar coupling in the strong-coupling regime and heteronuclear coupling in the weak regime expands complex peak patterns to a second axis. Hyperpolarization by Signal Amplification by Reversible Exchange (SABRE) enables the spectroscopy at a low magnetic field of 0.82 mT. Overlapping peaks of molecules such as 3-fluoropyridine and 3,5-difluoropyridine are resolved. Density matrix simulations of the 1 H and 19 F spins indicate a strong dependence on the signs and values of the J-coupling constants, including the homonuclear couplings that are not directly observable. The best matching peak positions and intensities predict coupling constants, including couplings between chemically equivalent nuclear spins, ranging in magnitude from 0.4 to 9.0 Hz for the two molecules. Simulations of other spin systems show unique patterns for molecules containing 1 H and 19 F or 13 C. The dependence of the J-resolved peak patterns on all coupling constants in a spin system presents a new modality for portable and inexpensive identification of molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ecosystem Water‐Saving Timescale Varies Spatially With Typical Drydown Length

Abstract Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale ( τ ) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of τ to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of τ that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to τ are measures of the average number of dry days between rainfall events. Values of τ are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem‐level water use strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Elucidating gene expression adaptation of phylogenetically divergent coral holobionts under heat stress

As coral reefs struggle to survive under climate change, it is crucial to know whether they have the capacity to withstand changing conditions, particularly increasing seawater temperatures. Thermal tolerance requires the integrative response of the different components of the coral holobiont (coral host, algal photosymbiont, and associated microbiome). Here, using a controlled thermal stress experiment across three divergent Caribbean coral species, we attempt to dissect holobiont member metatranscriptome responses from coral taxa with different sensitivities to heat stress and use phylogenetic ANOVA to study the evolution of gene expression adaptation. We show that coral response to heat stress is a complex trait derived from multiple interactions among holobiont members. We identify host and photosymbiont genes that exhibit lineage-specific expression level adaptation and uncover potential roles for bacterial associates in supplementing the metabolic needs of the coral-photosymbiont duo during heat stress. Our results stress the importance of integrative and comparative approaches across a wide range of species to better understand coral survival under the predicted rise in sea surface temperatures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems

Abstract Predicting complex dynamics in physical applications governed by partial differential equations in real-time is nearly impossible with traditional numerical simulations due to high computational cost. Neural operators offer a solution by approximating mappings between infinite-dimensional Banach spaces, yet their performance degrades with system size and complexity. We propose an approach for learning neural operators in latent spaces, facilitating real-time predictions for highly nonlinear and multiscale systems on high-dimensional domains. Our method utilizes the deep operator network architecture on a low-dimensional latent space to efficiently approximate underlying operators. Demonstrations on material fracture, fluid flow prediction, and climate modeling highlight superior prediction accuracy and computational efficiency compared to existing methods. Notably, our approach enables approximating large-scale atmospheric flows with millions of degrees, enhancing weather and climate forecasts. Here we show that the proposed approach enables real-time predictions that can facilitate decision-making for a wide range of applications in science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Study of the GeV to TeV morphology of the γ Cygni SNR (G 78.2+2.1) with MAGIC and Fermi-LAT

Context: Diffusive shock acceleration (DSA) is the most promising mechanism that accelerates Galactic cosmic rays (CRs) in the shocks of supernova remnants (SNRs). It is based on particles scattering caused by turbulence ahead and behind the shock. The turbulence upstream is supposedly generated by the CRs, but this process is not well understood. The dominant mechanism may depend on the evolutionary state of the shock and can be studied via the CRs escaping upstream into the interstellar medium (ISM). Aims: Previous observations of the γ Cygni SNR showed a difference in morphology between GeV and TeV energies. Since this SNR has the right age and is at the evolutionary stage for a significant fraction of CRs to escape, our aim is to understand γ-ray emission in the vicinity of the γ Cygni SNR. Methods: We observed the region of the γ Cygni SNR with the MAGIC Imaging Atmospheric Cherenkov telescopes between 2015 May and 2017 September recording 87 h of good-quality data. Additionally, we analysed Fermi-LAT data to study the energy dependence of the morphology as well as the energy spectrum in the GeV to TeV range. The energy spectra and morphology were compared against theoretical predictions, which include a detailed derivation of the CR escape process and their γ-ray generation. Results: The MAGIC and Fermi-LAT data allowed us to identify three emission regions that can be associated with the SNR and that dominate at different energies. Our hadronic emission model accounts well for the morphology and energy spectrum of all source components. It constrains the time-dependence of the maximum energy of the CRs at the shock, the time-dependence of the level of turbulence, and the diffusion coefficient immediately outside the SNR shock. Further, while in agreement with the standard picture of DSA, the time-dependence of the maximum energy was found to be steeper than predicted, and the level of turbulence was found to change over the lifetime of the SNR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Preliminary searches for spin-dependent interactions using sidebands of nuclear spin-precession signals

Various theories beyond the Standard Model predict new particles with masses in the sub-eV range with very weak couplings to ordinary matter. A new P-odd and T-odd interaction between polarized and unpolarized nucleons proportional to s⃗⋅r̂ is one such possibility, where r⃗=rr̂ is the spatial vector connecting the nucleons, and s⃗ is the spin of the polarized nucleon. Such an interaction involving a scalar coupling gsN at one vertex and a pseudoscalar coupling gpn at the polarized nucleon vertex can be induced by the exchange of spin-0 pseudoscalar bosons. We describe a new technique to search for interactions of this form and present the first measurements of this type. We show that future improvements to this technique can improve the laboratory upper bound on the product gsNgpn by two orders of magnitude for interaction ranges at the 100 micron scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Evolution of the Kondo lattice electronic structure above the transport coherence temperature

Significance The temperature ( T )-dependent evolution of the Kondo lattice electronic structure is a long-standing topic of theoretical and experimental investigation, still lacking a truly microscopic theory that agrees with a full experimental characterization. Here multiple characteristic T scales of the interaction of localized f moments with conduction electrons in the Kondo lattice CeCo I n 5 are identified and investigated using angle-resolved photoemission measurements that substantiate dynamical mean-field theory which newly includes the full realism of crystalline electric-field (CEF) f splittings. Thereby errors in the itinerant versus localized f -state classification from standard density functional theory are corrected, microscopic insight into the broad T -range crossover of f -hybridization effects is gained, and a prediction of CEF degeneracy crossover below the lattice coherence T is made.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗