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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Terahertz inverse spin Hall effect in spintronic nanostructures with various ferromagnetic materials

Bilayers of ferromagnetic and heavy metal nanolayers excited with femtosecond laser pulses emit subpicosecond bursts of electromagnetic radiation with spectral frequencies up to several THz. We fabricated such spintronic THz emitters containing various ferromagnetic materials with vastly different magnetic remanence, saturation magnetization, and coercive fields. In all cases, the THz amplitude versus magnetic-field dependence follows the independently measured magnetization hysteresis loops and the THz polarization direction is perpendicular to the sample’s magnetization M, both consistent with the inverse spin Hall effect (ISHE) as the physical origin. The mV-level signals of observed THz transient also favor the ISHE over the anomalous Nernst effect (ANE). The M(T) variation governs the temperature dependence of the THz generation. Emitters with weakly remanent ferromagnets are magnetic-field tunable, while moderately and strongly remanent ferromagnets, once magnetized, allow intense THz generation even without an external field, nevertheless exhibiting low susceptibility to magnetic perturbations if the hysteresis loop is square. Hence, exploiting the magnetic properties of the ferromagnetic layer enables tailoring of weakly temperature-dependent spintronic THz emitters. Finally, we explored the applicability of perovskite oxide materials such as La-Sr-Mn-O (LSMO) for THz transient generation. We detected weak (<40-μV amplitude) THz emissions from both LSMO/Au and pure LSMO nanostructures with no sign flip upon the sample reversal. Furthermore, we excluded the ISHE and believe it was likely governed by the ANE in the thick-film regime, although we cannot exclude the transient demagnetization mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impurity gas monitoring using ultrasonic sensing and neural networks: forward and inverse problems

Ultrasonic sensing is a non-invasive technique for monitoring impurity gas composition in various industrial applications where safety and regulatory compliance are crucial. In this study, ultrasonic sensing and neural networks were used to analyze impurity gases (i.e., air and argon) in helium. An experimental platform was established to acquire ultrasonic data. In the forward problem, an artificial neural network (ANN) model was used to forecast the response and time-of-flight (TOF) based on the excitation, and argon and air concentrations. The inverse problem was solved using a convolutional neural network (CNN) to predict the argon and air concentrations given the ultrasonic response and excitation. The results showed that the ANN accurately predicted the ultrasonic response and the change in TOF with concentration. As the air concentration was increased from 0 to 9.8%, the TOF sensitivity to detect argon decreased by 39.8% and 16.1% from ANN and sound speed theory, respectively. The CNN demonstrated high accuracy in predicting concentrations for inputs in the testing dataset. The application of the trained CNN indicated that it over-predicts air concentration while under-predicting the argon concentration. To improve accuracy, the predicted air and argon concentrations should be corrected by -0.992% and 1.027% bias, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Prediction of neutron production and energy spectrum by the inverse kinematic reaction between an incident 7 Li 3+ beam and a proton target in PHITS

A neutron source using the inverse kinematic reaction between lithium and proton, p( 7 Li, n) 7 Be, achieves forward-directed neutrons, potentially enhancing neutron yield in the forward direction. Despite the advantage, no evaluated-cross-section data for this reaction can be used in Monte Carlo simulation codes, such as PHITS. To solve this problem, this study aims to evaluate the applicability of the user-defined cross-section data, Frag data, for p ( 7 Li, n) 7 Be in PHITS. The simulations reproduced collisions between 7 Li 3+ ions and polypropylene targets. The Frag data was edited based on the JENDL-5 by utilizing the two-body collision kinematics. The neutron yield and angular distribution were investigated in the simulation. As a result, the forward neutron convergence with a reasonable neutron yield and energy spectrum was observed. The expected neutron yield in the forward 1-steradian area is 2.46 × 10 10 n/s when lithium-ion energy and current are 16.45 MeV and 0.1 mA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Intruder configurations in 29 Ne at the transition into the island of inversion: Detailed structure study of 28 Ne

Detailed γ-ray spectroscopy of the exotic neon isotope 28 Ne has been performed for the first time using the one-neutron removal reaction from 29 Ne on a liquid hydrogen target at 240 MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for 28 Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder p-wave strength providing evidence of the breakdown of the N=20 and N=28 shell gaps. Only a weak, possible f-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large p-wave and small f-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Revisiting the Temporal Leontief Inverse: New Insights on the Analysis of Regional Technological Economic Change

The current availability of longer series of input-output tables, as well as the release of global input-output databases, has fostered a growing literature analyzing changes in the economic structure and their drivers. In this paper, we take advantage of these time-series by proposing a methodology designed to trace the contribution of different drivers of the change in interindustrial relationships over time. Based on the Temporal Leontief Inverse (TLI), the Extended TLI (ETLI) decomposes the economy-wide effects of changes in direct interindustrial links between years, isolating the impact of different determinants of economic (environmental, energy, etc.) spillovers according to the interests of the researcher. For example, one can explore how the multipliers of a particular industry were affected by changes in technology of other sectors and in the own sector; by changes in trade patterns in specific countries; by indirect changes in intraregional production chains in foreign nations; etc. The ETLI is illustrated by uncovering certain hidden effects not captured in a previous application of the original TLI to the Chicago region between 1980-1997.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Physicochemical Gas–Solid Sorption Properties of Geologic Materials Using Inverse Gas Chromatography

The goal of this study was to determine the physicochemical properties of a variety of geologic materials using inverse gas chromatography (IGC) by varying probe gas selection, temperature, carrier gas flow rate, and humidity. This is accomplished by measuring the level of interaction between the materials of interest and known probe gases. Identifying a material’s physicochemical characteristics can help provide a better understanding of the transport of gaseous compounds in different geologic materials or between different geological layers under various conditions. Our research in this study focused on measuring the enthalpy (heat) of adsorption, Henry’s constant, and diffusion coefficients of a suite of geologic materials, including two soil types (sandy clay-loam and loam), quartz sand, salt, and bentonite clay, with various particle sizes. The reproducibility of IGC measurements for geologic materials, which are inherently heterogeneous, was also assessed in comparison to the reproducibility for more homogeneous synthetic materials. This involved determining the variability of physicochemical measurements obtained from different IGC approaches, instruments, and researchers. For the investigated IGC-determined parameters, the need for standardization became apparent, including the need for application-relevant reference materials. The inherent physical and chemical heterogeneities of soil and many geologic materials can make the prediction of sorption properties difficult. Characterizing the properties of individual organic and inorganic components can help elucidate the primary factors influencing sorption interactions in more complex mixtures. This research examined the capabilities and potential challenges of characterizing the gas sorption properties of geologic materials using IGC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An Inverse-Designed Nanophotonic Interface for Excitons in Atomically Thin Materials

Efficient nanophotonic devices are essential for applications in quantum networking, optical information processing, sensing, and nonlinear optics. Extensive research efforts have focused on integrating two-dimensional (2D) materials into photonic structures, but this integration is often limited by size and material quality. Here, we use hexagonal boron nitride (hBN), a benchmark choice for encapsulating atomically thin materials, as a waveguiding layer while simultaneously improving the optical quality of the embedded films. When combined with a photonic inverse design, it becomes a complete nanophotonic platform to interface with optically active 2D materials. Grating couplers and low-loss waveguides provide optical interfacing and routing, tunable cavities provide a large exciton-photon coupling to transition metal dichalcogenide (TMD) monolayers through Purcell enhancement, and metasurfaces enable the efficient detection of TMD dark excitons. This work paves the way for advanced 2D-material nanophotonic structures for classical and quantum nonlinear optics.

2D materials↗
DOE OSTI2021

Synthesis of High-Performance Lignin-Based Inverse Thermoplastic Vulcanizates with Tailored Morphology and Properties

In this work, we report synthesis of a high-strength renewable phenolic composition with linear large deformation strain without a thermoplastic-like yielding while retaining thermal processability. Small molecule carboxylic acid derivatives with varying molecular architectures act as esterifying crosslinkers in an equal mass mixture of lignin and acrylonitrile–butadiene copolymers in a highly scalable, solvent-free process. These “inverse thermoplastic vulcanizates” (iTPVs)—unique in their approach of crosslinking the rigid lignin phase rather than the soft phase—exhibit ordered self-assembly, tunable nanoscale morphology, and processability. The first of its kind iTPV compositions exhibit engineering stress–strain curves with two- to sixfold linear extensibility, a twofold rise in strength, and an order of magnitude enhanced modulus compared to a simple lignin-rubber blend. Viscoelastic properties correlate well with crosslinker architecture and the resulting morphology, allowing competing properties of toughness and stiffness to be tuned. This research finds a path for identifying the potential of lignin as a sustainable feedstock.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Highly Selective Methane to Methanol Conversion on Inverse SnO 2 /Cu 2 O/Cu(111) Catalysts: Unique Properties of SnO 2 Nanostructures and the Inhibition of the Direct Oxidative Combustion of Methane

Direct methane to methanol (CH 4 → CH 3 OH) conversion in heterogeneous catalysis has been a long-standing challenge due to the difficulties in equalizing the activation of methane and protection of the methanol product at the same reaction conditions. Here, we report an inverse catalyst, consisting of small structures of SnO 2 (0.5-1 nm in size) dispersed on Cu 2 O/Cu(111), for highly selective CH 3 OH production from CH 4 . This system was investigated by combining theoretical [density functional theory calculations (DFT), kinetic Monte Carlo simulations (KMC)] and experimental methods [scanning tunneling microscopy (STM), ambient-pressure X-ray photoelectron spectroscopy (AP-XPS)]. The DFT and AP-XPS studies showed that on SnO 2 /Cu 2 O/Cu(111) the conversion of CH 4 by oxygen (O 2 ) preferred complete combustion to carbon dioxide (CO 2 ). The addition of water (H 2 O) enhanced the production of CH 3 OH to nearly 100% selectivity in KMC simulations. This trend was consistent with results of AP-XPS. The presence of water in the reaction environment rendered an extremely high amount of methoxy species (*CH 3 O), a precursor for CH 3 OH production. Further, the high CH 3 OH selectivity of SnO 2 /Cu 2 O/Cu(111) reflected the unique atomic and electronic structure of the supported SnO 2 nanoparticles. As a result, the O 2 adsorption and dissociation, and thus the full combustion of CH 4 to CO 2 , was completely suppressed; while the H 2 O dissociative adsorption was still feasible, providing active hydroxyl species for a truly selective CH 4 to CH 3 OH conversion.

03 NATURAL GAS↗
DOE OSTI2023

Microscopic Investigation of H 2 Reduced CuO x /Cu(111) and ZnO/CuO x /Cu(111) Inverse Catalysts: STM, AP-XPS, and DFT Studies

Understanding the reduction mechanism of ZnO/CuO x interfaces by hydrogen is of great importance for advancing the performance of industrial catalysts for CO 2 hydrogenation to methanol. Here, the reduction of pristine and ZnO-modified CuO x /Cu(111) by H 2 was investigated using ambient pressure scanning tunnelling microscopy (AP-STM), ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and density functional theory (DFT). The morphological changes and reaction rates seen for the reduction of CuO x /Cu(111) and ZnO/CuO x /Cu(111) are very different. On CuO x /Cu(111), perfect "44" and "29" structures displayed a very low reactivity towards H 2 at room temperature. A long induction period associated with an autocatalytic process was observed to enable the reduction by the removal of chemisorbed non-lattice oxygen initially and lattice oxygen sequentially at the CuO x -Cu interface, which led to formation of oxygen deficient "5-7" hex and honeycomb structures. In the final stages of the reduction process, regions of residual oxygen species and metallic Cu were seen. The addition of ZnO particles to CuO x /Cu(111) opened new reaction channels. On the ZnO sites, the dissociation of H 2 was fast and H adatoms easily migrated to adjacent regions of copper oxide. This hydrogen spillover substantially enhanced the rate of oxygen removal, resulting in the rapid reduction of the copper oxide located in the periphery of the zinc oxide islands with no signs for the reduction of ZnO. The deposited ZnO completely modified the dynamics for H 2 dissociation and hydrogen migration, providing an excellent source for CO 2 hydrogenation processes on the inverse oxide/metal system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Intra-Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data

Understanding plant hydraulic regulation is critical for predicting plant and ecosystem responses to projected increases in drought stress. Plant hydraulic regulation is controlled by observable, diverse plant hydraulic traits that can vary as much across individuals of the same species as they do across different species. Direct measurements of plant hydraulic traits from a range of ecosystems remain limited in comparison to other, more readily measured traits (e.g., specific leaf area). Furthermore, plant hydraulic trait measurements, often made at leaf or branch levels, are not easily scaled to whole-plant values that are typically used to predict plant and ecosystem fluxes. In this study, multiple whole-plant hydraulic parameters are inferred from observations of plant water use (i.e., sap flow), soil properties, and meteorological data. We use a Markov Chain Monte Carlo model inversion approach to obtain the best estimates and uncertainty of plant hydraulic parameters that capture whole-plant effective embolism resistance and stomatal sensitivity to decreasing plant water potential. We then use the inferred values in the model to estimate whole-tree water use and isohydricity. This approach reliably infers whole-plant parameter values with enough specificity to resolve inter- and intra-specific differences, and thus supplements time- and labor-intensive direct measurements of traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating Carbon Dioxide Emissions in Two California Cities Using Bayesian Inversion and Satellite Measurements

NASA's Orbiting Carbon Observatories (OCO-2 and OCO-3) provide measurements of column-averaged carbon dioxide concentrations (XCO 2 ) with sufficient spatial resolution and precision to constrain bottom-up estimates of CO 2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO 2 fluxes in the South Coast Air Basin (SoCAB) which surrounds Los Angeles, and in the San Francisco Bay Area Air Basin (SFBA). We study 2020 to understand the impact of the COVID-19 lockdowns and an active wildfire season. Our results indicated that a 50% (30%) reduction in CO 2 emissions relative to 2015 during the COVID-19 lockdown period was consistent with OCO measurements for SFBA (SoCAB). We find that posterior wildfire emissions differed significantly from the prior at the scale of individual wildfires, though with large uncertainties, and that wildfire emissions in SFBA are significant, attributing 72% of the region's CO 2 emissions during August 2020 to wildfires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Inverse design of cellular structures with the targeted nonlinear mechanical response

Advanced additive manufacturing capabilities have enabled a transformational ability to create sophisticated cellular structures using diverse materials. By altering the topology of the unit cell, the mechanical behavior, such as the stress-strain response during compression, can be modulated. Nevertheless, identifying a printable topology within an enormous design space that would precisely deliver the targeted nonlinear material response is challenging. We propose a data-driven generative framework based on a conditional variational autoencoder (cVAE) architecture that can inverse design the cellular structure based on the intended nonlinear stress-strain response. Trained on a dataset of structure-property pairs, the cVAE learns a compact and expressive latent space that enables efficient mapping from targets to feasible geometries. Two inference modes are explored: (1) decoder-only generation, which enables the exploration of diverse designs conditioned solely on the desired mechanical response, and (2) encoder-decoder generation, which further allows for the incorporation of desired topologies, ensuring the generated structure conforms to both mechanical properties and to desired-topology constraints. The results demonstrate that the model can generate structurally plausible and mechanically accurate designs, with the predicted stress-strain curves closely matching the targets. Even under joint conditioning, the model effectively balances geometric fidelity and functional performance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗
DOE OSTI2022

Inverse design of plasma metamaterial devices with realistic elements

In an expansion of a previous study, we apply inverse design methods to produce two-dimensional plasma metamaterial devices with realistic plasma elements which incorporate quartz envelopes, collisionality (loss), non-uniform density profiles, and resistance to experimental error/perturbation. Finite difference frequency domain simulations are used along with forward-mode differentiation to design waveguides and demultiplexers operating under the transverse magnetic polarization. Additionally, optimal devices with realistic elements are compared to previous devices with idealized elements, and several parameter initialization schemes for the optimization algorithm are explored, yielding a robust procedure for producing such devices. Demultiplexing and waveguiding are demonstrated for microwave-regime devices composed of plasma elements with reasonable space-averaged plasma frequencies ~10GHz and a collision frequency ~1 GHz, allowing for future in-situ training and experimental realization of these designs.

42 ENGINEERING↗
DOE OSTI2021

Acceleration of heavy ions in inverse free electron laser

In conventional linear accelerators, the beam is accelerated with a synchronous harmonic of the radio frequency field where the electric field component is collinear with the beam direction. This approach requires the design of complex accelerating structures, especially for low-energy heavy ions. If the beam motion were sustainably coupled to transverse electromagnetic fields, this could significantly simplify the accelerating structure design, and even allow acceleration with free-space waves. However, despite the long history of the proposed concept for accelerating low-velocity ion beams, it has not found practical application, partially because of the complexity of the technical design. In this paper, we present a practical design approach for this undulator-based accelerator for low-energy heavy-ions, reminiscent of the inverse free electron laser operating principle, but in a different parameter space.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Bayesian inversion and the Tomita–Takesaki modular group

We show that conditional expectations, optimal hypotheses, disintegrations and adjoints of unital completely positive maps are all instances of Bayesian inverses. We study the existence of the latter by means of the Tomita–Takesaki modular group and we provide extensions of a theorem of Takesaki as well as a theorem of Accardi and Cecchini to the setting of not necessarily faithful states on finite-dimensional C* -algebras.

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↗