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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Upper limit on the chiral magnetic effect in isobar collisions at the Relativistic Heavy-Ion Collider

The chiral magnetic effect (CME) is a phenomenon that arises from the QCD anomaly in the presence of an external magnetic field. The experimental search for its evidence has been one of the key goals of the physics program of the Relativistic Heavy-Ion Collider. The STAR Collaboration has previously presented the results of a blind analysis of isobar collisions ( Ru 44 96 + Ru 44 96 , Zr 40 96 + Zr 40 96 ) in the search for the CME. The isobar ratio ( Y ) of CME-sensitive observable, charge separation scaled by elliptic anisotropy, is close to but systematically larger than the inverse multiplicity ratio, the naive background baseline. This indicates the potential existence of a CME signal and the presence of remaining nonflow background due to two- and three-particle correlations, which are different between the isobars. In this postblind analysis, we estimate the contributions from those nonflow correlations as a background baseline to Y , utilizing the isobar data as well as Heavy Ion Jet Interaction Generator simulations. This baseline is found consistent with the isobar ratio measurement, and an upper limit of 10% at 95% confidence level is extracted for the CME fraction in the charge separation measurement in isobar collisions at s NN = 200 GeV. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

On the possibility of negative activation energies in bimolecular reactions

The temperature dependence of the rate constants for model reacting systems was studied to understand some recent experimental measurements which imply the existence of negative activation energies. A collision theory model and classical trajectory calculations are used to demonstrate that the reaction probability can vary inversely with collision energy for bimolecular reactions occurring on attractive potential energy surfaces. However, this is not a sufficient condition to ensure that the rate constant has a negative temperature dependence. On the basis of these calculations, it seems unlikely that a true bimolecular reaction between neutral molecules will have a negative activation energy.

Jaffe, R. L.↗
NASA NTRS1992

Meteorological overview of the Arctic Boundary Layer Expedition (ABLE 3A) flight series

A meteorological overview of the Arctic Boundary Layer Expedition (ABLE 3A) flight series is presented. Synoptic analyses of mid-tropospheric circulation patterns are combined with isentropic back trajectory calculations to describe the long-range (400-3000 km) atmospheric transport mechanisms and pathways of air masses to the Arctic and sub-Arctic regions of North America during July and August 1988. Siberia and the northern Pacific Ocean were found to be the two most likely source areas for 3-day transport to the study areas in Alaska. Transport to the Barrow region was frequently influenced by polar vortices and associated short-wave troughs over the Arctic Ocean, while the Bethel area was most often affected by lows migrating across the Bering Sea and the Gulf of Alaska, as well as ridges of high pressure which built into interior Alaska. July 1988 was warmer and dryer than normal over much of Alaska. As a result, the 1988 Alaska fire season was one of the most active of the past decade. Airborne lidar measurements verified the presence of biomass burning plumes on many flights, often trapped in thin subsidence layer temperature inversions. Several cases of stratosphere/troposphere exchange were noted, based upon potential vorticity analyses and aircraft lidar data, especially in the Barrow region and during transit flights to and from Alaska.

Shipham, Mark C.↗
NASA NTRS2002

Coronal Element Abundances of the Post-Common Envelope Binary V471 Tauri with ASCA

We report on ASCA observations of the coronally active companion star in the post-common envelope binary V471 Tau. While it would be prudent to check the following results with grating spectroscopy, we find that a single-temperature plasma model does not fit the data. Two temperature models with variable abundances indicate that Fe is underabundant compared to the Hyades photospheric mean, whereas, the high first ionization potential element Ne is overabundant. This is indicative of the inverse first ionization effect, believed to result from the fractionation of ionized material by the magnetic field in the upper atmosphere of the star. Evolutionary calculations indicate that there should be no peculiar abundances on the companion star resulting from the common envelope epoch. Indeed, we find no evidence for peculiar abundances, although uncertainties are high.

Still, Martin↗
NASA NTRS1972

Population inversion calculations using near resonant charge exchange as a pumping mechanism

Near resonance charge exchange between ions of a large ionization potential gas such as helium or neon and vapors of metals such as zinc, cadmium, selenium, or tellurium has produced laser action in the metal ion gas. The possibility of obtaining population inversions in near resonant charge exchange systems (Xe-Ca, Xe-Mg, Xe-Sr, Xe-Ba, Ar-Mg, N-Ca) was investigated. The analysis is an initial value problem that utilizes rate equations for the densities of relevant levels of the laser gas (Ca, Ba, Mg, or Sr) and an electron energy equation. Electron excitation rates are calculated using the Bohr-Thomson approximation for the cross section. Approximations to experimental values of the electron ionization cross section and the ion-atom charge exchange cross section are used. Preliminary results have been obtained for the Ca-Xe system and show that it is possible to obtain gains greater than 10 to the 14th power/m with inversion times up to 8x10 to the minus 7th power second. A possible charge exchange laser system using a MPD arc plasma accelerator is also described.

Chubb, D. L.↗
NASA NTRS1994

Directional and polarimetric effects in the optical domain

Papers focused on land surface, atmospheric, and ocean properties are reported. Specific comments pertaining to polarization, models and inversion, and measurements, are given. Recommendations are: continued research into the application potential of the BRDF (Bidirectional Reflectance Distribution Function) and polarization properties of ground surface and atmospheric targets; three dimensional models, which account for the statistical behavior of remotely sensed data, should be extended and inverted in order to support analysis of data potentially covering rolling terrain such that pixels represent heterogeneous mixtures of surface cover types and project ground footprints with sizes between 10 to 6 km, the ground pixel sizes of planned future sensors; available reflectance models should be further validated by means of multi dimensional (directional, spectral, temporal) field data and existing models should be intercompared in more depth to evaluate their performance and limitations; existing methods for model inversion should be validated in more depth in order to quantify the practical limitations and the expected accuracy of the parameters retrieved and new approaches should be developed based upon apriori knowledge of plant canopy development and spectral BRDF properties; there is a need to establish a protocol of validation and intercomparison of the indices and compositing techniques which have been proposed during these last years.

Vanderbilt, V. C.↗
DOE OSTI2022

Deep Generative Models for Materials Discovery and Machine Learning-Accelerated Innovation

Machine learning and artificial intelligence (AI/ML) methods are beginning to have significant impact in chemistry and condensed matter physics. For example, deep learning methods have demonstrated new capabilities for high-throughput virtual screening, and global optimization approaches for inverse design of materials. Recently, a relatively new branch of AI/ML, deep generative models (GMs), provide additional promise as they encode material structure and/or properties into a latent space, and through exploration and manipulation of the latent space can generate new materials. These approaches learn representations of a material structure and its corresponding chemistry or physics to accelerate materials discovery, which differs from traditional AI/ML methods that use statistical and combinatorial screening of existing materials via distinct structure-property relationships. However, application of GMs to inorganic materials has been notably harder than organic molecules because inorganic structure is often more complex to encode. In this work we review recent innovations that have enabled GMs to accelerate inorganic materials discovery. We focus on different representations of material structure, their impact on inverse design strategies using variational autoencoders or generative adversarial networks, and highlight the potential of these approaches for discovering materials with targeted properties needed for technological innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. I. Inverse Lagrangian analysis

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. Here, to this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ±1.2%; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K 0 = 270.3 ± 3.8 GPa, pressure derivative K$^{'}_{0}$= 5.66 ± 0.10, and correlation coefficient $R_{K_{0},K^{'}_{0}}$= –0.843.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Inversion, chemical complexity, and interstitial transport in spinels

Abstract Spinels with the generic chemical formula AB 2 O 4 have potential applications in nuclear energy and batteries. In both cases, their functionality is related to mass transport through the crystal. Here, using long‐time atomistic simulations, we examine the impact of the cation structure on interstitial transport in two spinel chemistries, inverse MgGa 2 O 4 and double MgAlGaO 4 . We emphasize two aspects of the transport properties: the unit mechanisms that are described by individual barriers, for which we introduce pole‐figure‐like plots, and the aggregate behavior of those unit mechanisms. Compared to previous work on normal spinels, we find that inversion significantly reduces the rate of interstitial transport in these structures and has an impact on the stability of defects as they move through the lattice. In particular, B cation interstitials are found to be kinetically stable only in the inverse MgGa 2 O 4 . These results provide new insight into relationship between structure, chemistry, and transport in spinels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning

Abstract One of the critical components in Industrial Gas Turbines (IGT) is the turbine blade. Design of turbine blades needs to consider multiple aspects like aerodynamic efficiency, durability, safety and manufacturing, which make the design process sequential and iterative. The sequential nature of these iterations forces a long design cycle time, ranging from several months to years. Due to the reactionary nature of these iterations, little effort has been made to accumulate data in a manner that allows for deep exploration and understanding of the total design space. This is exemplified in the process of designing the individual components of the IGT resulting in a potential unrealized efficiency. To overcome the aforementioned challenges, we demonstrate a probabilistic inverse design machine learning framework, namely PMI (PMI), to carry out an explicit inverse design. PMI calculates the design explicitly without costly iteration and overcomes the challenges associated with ill-posed inverse problems. In this work the framework will be demonstrated on inverse aerodynamic design of three-dimensional turbine blades.

Engineering↗
NASA NTRS1990

An improved Newton iteration for the generalized inverse of a matrix, with applications

The purpose here is to clarify and illustrate the potential for the use of variants of Newton's method of solving problems of practical interest on highly personal computers. The authors show how to accelerate the method substantially and how to modify it successfully to cope with ill-conditioned matrices. The authors conclude that Newton's method can be of value for some interesting computations, especially in parallel and other computing environments in which matrix products are especially easy to work with.

Pan, Victor↗
DOE OSTI2025

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗
NASA NTRS1973

Quasi-steady plasma acceleration.

A coaxial plasma accelerator driven by protracted pulses of current in the range of 10,000 to 100,000 A and synchronized mass flows from 1.0 to 36 g/sec argon attains, after some tens of microseconds, a stable magnetoplasmadynamic acceleration mode. This 'quasi-steady' discharge form is characterized by constant terminal voltage and current, a diffuse, fixed current distribution within the discharge, and a steady plasma efflux at velocities of approximately 20 km/sec. Measured potential distributions reveal that the bulk of the arc voltage gradient, exclusive of the electrode falls, occurs within two diameters of the cathode, and is normal to it. The anode fall voltage varies inversely with local current density, implying substantially lower anode losses at higher power arc operation. Spectroscopic, potential, and velocity measurements indicate the existence of a characteristic mass flow rate for a given current, below which arc operation becomes erratic.

Jahn, R. G.↗
DOE OSTI2022

A mixed, unified forward/inverse framework for earthquake problems: fault implementation and coseismic slip estimate

SUMMARY We introduce a new finite-element (FE) based computational framework to solve forward and inverse elastic deformation problems for earthquake faulting via the adjoint method. Based on two advanced computational libraries, FEniCS and hIPPYlib for the forward and inverse problems, respectively, this framework is flexible, transparent and easily extensible. We represent a fault discontinuity through a mixed FE elasticity formulation, which approximates the stress with higher order accuracy and exposes the prescribed slip explicitly in the variational form without using conventional split node and decomposition discrete approaches. This also allows the first order optimality condition, that is the vanishing of the gradient, to be expressed in continuous form, which leads to consistent discretizations of all field variables, including the slip. We show comparisons with the standard, pure displacement formulation and a model containing an in-plane mode II crack, whose slip is prescribed via the split node technique. We demonstrate the potential of this new computational framework by performing a linear coseismic slip inversion through adjoint-based optimization methods, without requiring computation of elastic Green’s functions. Specifically, we consider a penalized least squares formulation, which in a Bayesian setting—under the assumption of Gaussian noise and prior—reflects the negative log of the posterior distribution. The comparison of the inversion results with a standard, linear inverse theory approach based on Okada’s solutions shows analogous results. Preliminary uncertainties are estimated via eigenvalue analysis of the Hessian of the penalized least squares objective function. Our implementation is fully open-source and Jupyter notebooks to reproduce our results are provided. The extension to a fully Bayesian framework for detailed uncertainty quantification and non-linear inversions, including for heterogeneous media earthquake problems, will be analysed in a forthcoming paper.

58 GEOSCIENCES↗
DOE OSTI2022

Physics constrained learning for data-driven inverse modeling from sparse observations

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that measures the discrepancy between predictions and observations in some chosen norm. This loss function often includes the PDE constraints as a penalty term when only sparse observations are available. As a result, the PDE is only satisfied approximately by the solution. However, the penalty term typically slows down the convergence of the optimizer for stiff problems. We present a new approach that trains the embedded DNNs while numerically satisfying the PDE constraints. We develop an algorithm that enables differentiating both explicit and implicit numerical solvers in reverse-mode automatic differentiation. This allows the gradients of the DNNs and the PDE solvers to be computed in a unified framework. We demonstrate that our approach enjoys faster convergence and better stability in relatively stiff problems compared to the penalty method. Furthermore, our approach allows for the potential to solve and accelerate a wide range of data-driven inverse modeling, where the physical constraints are described by PDEs and need to be satisfied accurately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Inverse Method for Noninvasive Material Discrimination with Multienergy X-Ray Radiography

Active x-ray inspections have great potential for noninvasive detection of illicit materials. Dual-energy x-ray radiography, in particular, has been used to determine material composition by utilizing the energy-dependence of the x-ray attenuation coefficients. However, current implementations of this method are limited in their ability to determine the material composition of composite objects. Here, in this paper, we present an inverse algorithm that uses multienergy x-ray radiography data to noninvasively reconstruct the contents of a container. A critical feature of the current contribution is that material identification can be performed using conventional detectors and x-ray spectra with different endpoint energies produced by varying nothing more than the tube voltage. Adaptive regularization is used to increase the accuracy of material estimations from multienergy data sets. The utility of these methods is demonstrated with experimentally acquired radiographs obtained using a tunable x-ray source that produces spectra with endpoint energies of 100–450 keV. The object inspected is a scale model of a nuclear materials storage container composed of three-dimensional printed plastic and stainless-steel spheres inside a thin-walled steel container. Reconstructions of the steel sphere thicknesses are within a root-mean-square error of 0.37 cm.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Light-induced electronic polarization in antiferromagnetic Cr 2 O 3

In a solid, the electronic subsystem can exhibit incipient order with lower point group symmetry than the crystal lattice. Ultrafast external fields that couple exclusively to electronic order parameters have rarely been investigated, however, despite their potential importance in inducing exotic effects. Here we show that when inversion symmetry is broken by the antiferromagnetic order in Cr 2 O 3 , transmitting a linearly polarized light pulse through the crystal gives rise to an in-plane rotational symmetry-breaking (from C 3 to C 1 ) via optical rectification. Using interferometric time-resolved second harmonic generation, we show that the ultrafast timescale of the symmetry reduction is indicative of a purely electronic response; the underlying spin and crystal structures remain unaffected. The symmetry-broken state exhibits a dipole moment, and its polar axis can be controlled with the incident light. Furthermore, our results establish a coherent nonlinear optical protocol by which to break electronic symmetries and produce unconventional electronic effects in solids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Na-functionalized Ir Te 2 monolayer: Suppressed charge ordering and electric field tuned topological phase transition

Two-dimensional materials with atomic thickness usually possess superior tunability by surface adsorption than their bulk counterparts, showing great promise for novel nanotechnologies. In layered transition-metal dichalcogenide IrTe 2 there exhibits complex structural distortions induced by charge ordering, resulting in difficulties for the applications of its corresponding monolayer material. Here, using first-principles calculations, we demonstrate that depositing Na on the surface of the IrTe 2 monolayer can suppress the structural distortion to form a stable NaIrTe 2 sheet. It naturally breaks the inversion symmetry to enable a Rashba-type spin splitting for potential spintronic applications. In addition, the introduced empty Na s band and the valence band of the IrTe 2 monolayer can be inverted by the application of a perpendicular electric field, achieving a quantum phase transition from normal to topological insulator. Such an electric field-controlled topological phase transition is promising for the realization of topological field-effect transistors. Furthermore, these findings not only provide a feasible approach to stabilizing the IrTe 2 monolayer, but also broaden its applications in spintronics and low-dissipation topoelectronics.

36 MATERIALS SCIENCE↗