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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Influence of alveolar mixing and multiple breaths of aerosol intake on particle deposition in the human lungs

Predictive dosimetry models play an important role in assessing health effect of inhaled particulate matter and in optimizing delivery of inhaled pharmaceutical aerosols. Here, in this study, the commonly used 1D Multiple-Path Particle Dosimetry model (MPPD) was improved by including a mechanistically based model component for alveolar mixing of particles and by extending the model capabilities to account for multiple breaths of aerosol intake. These modifications increased the retained fraction of particles and consequently particle deposition predictions in the deep lung during tidal breathing. Comparison with an existing dataset (J. Aerosol Sci., 99:27-39, 2016) obtained under two breathing conditions referred to as slow and fast breathing showed significant differences in 1 µm particle deposition between predictions (slow: 30±1%, fast: 21±1%) and measurements (slow: 43±9%, fast: 30±5%) when the prior version of MPPD (single breath and no mixing, J. Aerosol Sci., 151:105647, 2021) was used. Adding a mixing model and multiple breaths moved the predictions (slow: 34±2%, fast:25±2%) closer to the range of deposition measurements. For 2.9 µm particles, predictions from both the original (slow: 70±2%, fast: 57±2%) and the revised MPPD model (slow: 71±2%, fast: 59±3%) compared well with experiments (slow: 67±8%, fast: 58±10%). This was expected as suspended fraction of 2.9 µm particles was small and thus the addition of alveolar mixing and multi breath capability only slightly increased the retained fraction for particles of this size and greater. The revised 1D model improves dose predictions in the deep lung and support human risk assessment from exposure to airborne particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Projected network performance for multiple isotopes using next-generation xenon monitoring systems

Since about 2000 (Bowyer et al., 1998), radioxenon monitoring systems have been under development and testing for the verification of the Comprehensive Nuclear Test-Ban Treaty (CTBT). Operation of the systems since then has resulted in development of a next-generation of systems that are nearly ready for operational deployment. By 2010, the need to screen out civilian sources was well known (Auer et al., 2010; Saey, 2009), and isotopic ratio approaches were soon considered (Kalinowski et al., 2014) to identify specific sources. New generation systems are expected to improve the ability to verify the absence of nuclear tests by using isotopic ratios when multiple isotopes are detected. In this work, thousands of releases were simulated to compute the global detection probability of 131m Xe, 133m Xe, 133 Xe, and 135 Xe at 39 noble gas systems in the International Monitoring System (IMS) for both current and next-generation systems. Three release scenarios are defined at 1 h, 1 d, and 10 d past a 1 kt TNT equivalent 235U explosion event. Multiple cases using from one part in a million to the complete release of the xenon isotopic activity are evaluated for each scenario. Coverage maps and global integrals comparing current and next-generation monitoring systems are presented showing that next-generation noble gas systems will create measurable improvements in the IMS. The global detection probability for 133 Xe is shown to be strong in all scenarios, but only modestly improved by next-generation equipment. However, the detection probability for 131m Xe and 133m Xe increased to about 50% in different scenarios, providing a second detectable isotope for many events. As anticipated from shorter sampling intervals, the expected number of detecting samples roughly doubled and the expected number of detecting stations rose by approximately 50% for all release scenarios. Thus, it might be anticipated that future events would consist of multiple 133 Xe detections and one or more second isotope detections. In conclusion, signals of this nature should increase detection confidence, tighten release location estimates, improve rejection of civilian signals, and lessen the impacts from individual systems being offline for maintenance or repair reasons.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Multiplicity dependence of ϒ production at forward rapidity in pp collisions at $\sqrt{s}$ = 13 TeV

The measurement of ϒ(1S), ϒ(2S), and ϒ(3S) yields as a function of the charged-particle multiplicity density, d N ch /d η , using the ALICE experiment at the LHC, is reported in pp collisions at √s = 13 TeV. The Υ meson yields are measured at forward rapidity (2.5 < y < 4) in the dimuon decay channel, whereas the charged-particle multiplicity is defined at central rapidity (| η | <1). Both quantities are divided by their average value in minimum bias events to compute the self-normalized quantities. The increase of the self-normalized ϒ(1S), ϒ(2S), and ϒ(3S) yields is found to be compatible with a linear scaling with the self-normalized d N ch /d η , within the uncertainties. The self-normalized yield ratios of excited-to-ground ϒ states are compatible with unity within uncertainties. Similarly, the measured double ratio of the self-normalized ϒ(1S) to the self-normalized J/ ψ yields, both measured at forward rapidity, is compatible with unity for self-normalized charged-particle multiplicities beyond one. The measurements are compared with theoretical predictions incorporating initial or final state effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Accessing subnuclear fluctuations and saturation with multiplicity dependent J/ψ production in p+p and p+Pb collisions

We study the production of J/ψ vector mesons as a function of charged hadron multiplicity in p+p and p+Pb collisions at LHC energies. We employ the color glass condensate framework, using running coupling Balitsky-Kovchegov evolved dipole amplitudes, to compute gluon and cc¯-pair production. We use fragmentation functions to obtain charged hadrons, and explore two different hadronization schemes for the J/ψ: non-relativistic quantum chromodynamics and the improved color evaporation model. In our framework, event-by-event multiplicity fluctuations of both hadrons and J/ψ are driven by geometric and saturation scale normalization fluctuations. Studying the correlation between J/ψ and hadron multiplicity, we show that the characteristic difference between forward and backward rapidity in p+Pb collisions is a result of different degrees of saturation probed at different rapidities. We demonstrate that experimental data on heavy-flavor production as a function of event activity provide stringent constraints on the fluctuating proton structure

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Energy dependence of prompt fissions neutron multiplicity in the 239 Pu(n, ƒ) reaction

Accurate multiplicities of prompt fission neutrons emitted in neutron-induced fission on a large energy range are essential for fundamental and applied nuclear physics. Measuring them to high precision for radioactive fissioning nuclides remains, however, an experimental challenge. In this work, the average prompt-neutron multiplicity emitted in the 239 Pu(n, ƒ) reaction was extracted as a function of the incident-neutron energy, over the range 1-700 MeV, with a novel technique, which allowed to minimize and correct for the main sources of bias and thus achieve unprecedented precision. At low energies, our data validate for the first time the ENDF/B-VIII.0 nuclear data evaluation with an independent measurement and reduce the evaluated uncertainty by up to 60%. This work opens up the possibility of precisely measuring prompt fission neutron multiplicities on highly radioactive nuclei relevant for an essential component of energy production world-wide.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Multiplicity dependence of charged-particle production in pp, p–Pb, Xe–Xe and Pb–Pb collisions at the LHC

Multiplicity (N ch ) distributions and transverse momentum (p T ) spectra of inclusive primary charged particles in the kinematic range of |η| < 0.8 and 0.15 GeV/c < p T < 10 GeV/c are reported for pp, p–Pb, Xe–Xe and Pb–Pb collisions at centre-of-mass energies per nucleon pair ranging from $\sqrt{s_{NN}}$ = 2.76 TeV up to 13 TeV. A sequential two-dimensional unfolding procedure is used to extract the correlation between the transverse momentum of primary charged particles and the charged-particle multiplicity of the corresponding collision. This correlation sharply characterises important features of the final state of a collision and, therefore, can be used as a stringent test of theoretical models. The multiplicity distributions as well as the mean and standard deviation derived from the p T spectra are compared to state-of-the-art model predictions. Providing these fundamental observables of bulk particle production consistently across a wide range of collision energies and system sizes can serve as an important input for tuning Monte Carlo event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A legacy of fire emerges from multiple disturbances to most shape microbial and nitrogen dynamics in a deciduous forest

Healthy forests are vital components of terrestrial ecosystems for their raw materials, high biodiversity, cycling of nutrients, and potential to sequester carbon. However, these ecosystems are sensitive to disturbances, and anthropogenic activities pose a serious threat to forest ecosystems globally. For example, human activities have dramatically altered multiple historical disturbance regimes in forests, including suppressing fire, increasing the density of large herbivores, and reducing the size of canopy gaps, among other disturbances. Such disturbances can have dramatic impacts on microbially-mediated forest soil functions, but more research is needed to determine the collective impacts of these disturbances. In this study, we investigated the interactive effects of disturbances, namely the legacies of fire, large herbivore densities, and canopy gap creation, in a deciduous forest soil. We determined that forest floor and mineral soil carbon and nitrogen pools were shaped by multiple disturbances, but fire was more influential than the other disturbances. The abundance of several functionally-relevant microbial taxa were significantly impacted by fire, and the effect was more pronounced in the mineral soil than in the forest floor. Together, these findings demonstrate that multiple disturbances, especially a legacy of fire, exerts long-term control over soil carbon, nitrogen and microbial dynamics in a deciduous forest system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Automatic fitting of multiple-field solid-state NMR spectra

The NMR lineshapes produced by half-integer quadrupolar nuclei are sensitive to 11 distinct fit parameters per inequivalent site. To date, automatic fitting routines have failed to replace manual parameter insertion and evaluation due to the importance of local minima and the need for fitting multiple-field magic-angle spinning (MAS) and static spectra simultaneously. Herein we introduce a new tool, AMES-Fit (Automatic Multiple Experiment Simulation and Fitting), to automatically find the global best-fit simulation parameters for a series of multiple-field NMR lineshapes. AMES-Fit uses an adaptive step size random search algorithm to dynamically probe parameter space and requires minimal human input. Importantly, the best fits are obtained in a few minutes of computation time that would otherwise have required several person-hours of work. The program is freely available and open-source.

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

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗
DOE OSTI2020

Ion Solvation Engineering: How to Manipulate the Multiplicity of the Coordination Environment of Multivalent Ions

During free energy analysis of solvation structures of free divalent cations, their ion pairs, and neutral aggregates in low dielectric solvents reveals the multiplicity of thermodynamically stable cation solvation configurations and identifies the micro- and macroscopic factors responsible for this phenomenon. Specifically, we show the role of ion-solvent interactions and solvent mixtures in determining the cation solvation free energy landscapes. We show that it is the entropic contribution of solvent degrees of freedom that is responsible for the solvation multiplicity, and the mutual balance between enthalpic and entropic forces or their concerted contributions is what ultimately defines the most stable ion solvation configuration and creates new ones. We show general consequences of ion solvation multiplicity on thermodynamics of complex electrolytes, specifically in the context of homogeneous or interfacial charge transfer. Identified factors and their interplay provide a pathway to formulation of solvation design rules that can be used to control bulk solvation, interfacial chemistry, and charge transfer. Our findings also suggest experimentally testable predictions.

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

Fault Slip and Fluid Flow: Seismic Source Analysis to Assess Role of Multiple Slip Patches in Fault Permeability

The relationship between fault reactivation, microearthquakes (MEQs), and permeability evolution during fluid injection plays a critical role in energy harvesting and waste disposal. Recent studies have demonstrated the possibility of predicting fault permeability using cumulative seismic moments of MEQs quantitatively. To understand the underlying physical processes, we conduct fault reactivation experiments using Utah FORGE granitoid and analyze acoustic emission (AE) signals generated during stepwise increases in fluid injection pressure. Frequency analysis of thousands of calibrated AE signals reveals that fault reactivation produces multiple AE source patches with millimeter-scale radii—smaller than the sample fault radius. The cumulative area of the reactivated patches covers the fault multiple times over (∼10x–50x area) for each pressure step. These findings provide mechanistic insight that measured permeability enhancement is not driven by a single large slip event, but by the sequential and interacting activation of multiple slip patches that create a continuous flow pathway.

Nurshal, M. E. M. [Pennsylvania State University, ↗
DOE OSTI2021

Multiple fermion scattering in the weakly coupled spin-chain compound YbAlO 3

The Heisenberg antiferromagnetic spin-1/2 chain, originally introduced almost a century ago, is one of the best studied models in quantum mechanics due to its exact solution, but nevertheless it continues to present new discoveries. Its low-energy physics is described by the Tomonaga-Luttinger liquid of spinless fermions, similar to the conduction electrons in one-dimensional metals. In this work we investigate the Heisenberg spin-chain compound YbAlO3 and show that the weak interchain coupling causes Umklapp scattering between the left- and right-moving fermions and stabilizes an incommensurate spin-density wave order at q = 2k F under finite magnetic fields. These Umklapp processes open a route to multiple coherent scattering of fermions, which results in the formation of satellites at integer multiples of the incommensurate fundamental wavevector Q = nq. Our work provides surprising and profound insight into bandstructure control for emergent fermions in quantum materials, and shows how neutron diffraction can be applied to investigate the phenomenon of coherent multiple scattering in metals through the proxy of quantum magnetic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Extreme terahertz magnon multiplication induced by resonant magnetic pulse pairs

Nonlinear interactions of spin-waves and their quanta, magnons, have emerged as prominent candidates for interference-based technology, ranging from quantum transduction to antiferromagnetic spintronics. Yet magnon multiplication in the terahertz (THz) spectral region represents a major challenge. Intense, resonant magnetic fields from THz pulse-pairs with controllable phases and amplitudes enable high order THz magnon multiplication, distinct from non-resonant nonlinearities such as the high harmonic generation by below-band gap electric fields. Here, we demonstrate exceptionally high-order THz nonlinear magnonics. It manifests as 7th-order spin-wave-mixing and 6th harmonic magnon generation in an antiferromagnetic orthoferrite. We use THz two-dimensional coherent spectroscopy to achieve high-sensitivity detection of nonlinear magnon interactions up to six-magnon quanta in strongly-driven many-magnon correlated states. The high-order magnon multiplication, supported by classical and quantum spin simulations, elucidates the significance of four-fold magnetic anisotropy and Dzyaloshinskii-Moriya symmetry breaking. Moreover, our results shed light on the potential quantum fluctuation properties inherent in nonlinear magnons.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiple elements of soil biodiversity drive ecosystem functions across biomes

The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Furthermore, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multiple freezing–melting pathways of high-density ice through ice XXI phase at room temperature

Various metastable ice phases and their complicated transition pathways have been found by pressurization at low temperatures at which slow kinetics and high metastability are easily achieved. By contrast, such diversity is less expected at room or elevated temperatures. Here, using a combination of a dynamic diamond anvil cell and X-ray free electron laser techniques, we demonstrate that supercompressed water transforms into ice VI through multiple freezing–melting pathways at room temperature, hidden within the pressure region of ice VI. These multiple transition pathways occur via a metastable ice (more specifically, ice XXI with body-centred tetragonal structure ($I\bar{4}2d$)) discovered in this study and a metastable ice VII that exists within the pressure range of ice VI. We find that supercompressed water structurally evolves from high-density water to very-high-density water, causing multiple transition pathways. These findings provide an insight to find more metastable ice phases and their transition pathways at elevated temperatures.

Lee, Yun-Hee [Korea Research Institute of Standard↗
DOE OSTI2020

Splitting of multiple hydrogen molecules by bioinspired diniobium metal complexes: a DFT study

Splitting of molecular hydrogen (H 2 ) into bridging and terminal hydrides is a common step in transition metal chemistry. In this paper, we propose a novel organometallic platform for cleavage of multiple H 2 molecules, which combines metal centers capable of stabilizing multiple oxidation states, and ligands bearing positioned pendant basic groups. Using quantum chemical modeling, we show that low-valent, early transition metal diniobium(II) complexes with diphosphine ligands featuring pendant amines can favorably uptake up to 8 hydrogen atoms, and that the energetics are favored by the formation of intramolecular dihydrogen bonds. This result suggests new possible strategies for the development of hydrogen scavenger molecules that are able to perform reversible splitting of multiple H 2 molecules.

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

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗