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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessing the Feasibility of Bordered Block Diagonal Reordering in Power System Matrices using Fully Convolutional Network

In electromagnetic transient (EMT) simulations for power systems and inverter-based resources (IBRs), the arrangement of states within the system's linear equations, represented by matrix A in Ax=b, is critical. The state ordering in matrix A can highlight distinct characteristics of the system's graph, and identifying an optimal state ordering is crucial for efficient computation. The choice of state ordering, however, is dependent on the solver used, as each solver may perform optimally with different matrix patterns. With a wide array of matrix reordering algorithms available, selecting the most suitable one becomes challenging without insights into the matrix's ideal configuration. To address this, the paper proposes a fully convolutional network (FCN) to evaluate the reordering potential of the A matrix into a bordered block diagonal (BBD) pattern, which is commonly observed in power system and IBR modeling. The FCN's assessment aims to streamline the solver's operation, which in turn could substantially reduce the computational time required to find a solution.

Xia, Qianxue↗
DOE OSTI2025

Wavelength-dependent photodissociation of iodomethylbutane

Ultrashort XUV pulses of the Free-Electron-LASer in Hamburg (FLASH) were used to investigate laser-induced fragmentation patterns of the prototypical chiral molecule 1-iodo-2-methyl-butane (C 5 H 11 I) in a pump-probe scheme. Ion velocity-map images and mass spectra of optical-laser-induced fragmentation were obtained for subsequent FEL exposure with photon energies of 63 eV and 75 eV. These energies specifically address the iodine 4d edge of neutral and singly charged iodine, respectively. The presented ion spectra for two optical pump-laser wavelengths, i.e., 800 nm and 267 nm, reveal substantially different cationic fragment yields in dependence on the wavelength and intensity. For the case of 800-nm-initiated fragmentation, the molecule dissociates notably slower than for the 267 nm pump. The results underscore the importance of considering optical-laser wavelength and intensity in the dissociation dynamics of this prototypical chiral molecule that is a promising candidate for future studies of its asymmetric nature.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Charge radii and electromagnetic moments of 214−218 Bi : Exploring the “southern” border of the 𝑍 > 82 octupole-deformation region

The changes in the mean-squared charge radii relative to 209 Bi 126 (𝛿⁢⟨𝑟 2 ⟩ 𝑁,126 ) and the magnetic dipole and electric quadrupole moments in 214−218 Bi have been measured using the in-source resonance-ionization spectroscopy technique at ISOLDE (CERN). Magnetic moments of odd-odd bismuth nuclei have been analyzed by the additivity relation. Previous tentative spin-parity and configuration assignments based on the 𝛽-decay feeding patterns have been supported. A normal odd-even staggering in charge radii of bismuth isotopes with 𝑁>126 has been observed. The new data for the 𝛿⁡⟨𝑟 2 ⟩ of bismuth isotopes allow a study of the isotonic dependencies in the charge radii, revealing jumps in 𝛿⁢⟨𝑟 2 ⟩ 132,126 and 𝛿⁢⟨𝑟 2 ⟩ 134,126 at 𝑍 = 84. This pattern could be explained by a sudden onset of octupole deformation at 𝑁 = 132 and 134 when going from polonium (𝑍 = 84) to astatine (𝑍 = 85).

fundamental symmetries↗
DOE OSTI2025

Ratchet effects in cyclic pattern formation systems with competing interactions

Ratchet effects can appear for particles interacting with an asymmetric potential under ac driving or for a thermal system in which a substrate is periodically flashed. Here, we show that a different type of collective ratchet effect can arise for a pattern-forming system coupled to an asymmetric substrate when the interaction potential between the particles is periodically oscillated in order to cycle the system through different patterns. We consider particles with competing short-range attraction and long-range repulsion subjected to time-dependent oscillations of the ratio between the attractive and repulsive interaction terms, which causes the system to cycle periodically between crystal and bubble states. In the presence of the substrate, this system exhibits both a positive and a reversed ratchet effect, and we show that there is a maximum in the ratchet efficiency as a function of interaction strength, ac drive frequency, and particle density. In conclusion, our results could be realized for a variety of pattern-forming systems on asymmetric substrates where the pattern type or particle interactions can be oscillated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Planar Defect Layers Template a High-Pressure InBi Polymorph

The short- and long-range order of III–V materials under high pressure has long been the subject of debate, with advancements in structural characterization leading to significant revisions to the accepted structural models. Despite these revisions, previous high-pressure structural assignments in the In–Bi system include the site-disordered β-Sn structure type, a structure type demonstrated to be nonexistent in analogous III–V systems. While X-ray diffraction is consistent with site disordering in InBi at high pressure, cluster expansion calculations indicate that disordering requires temperatures above 3000 K. Here, we propose InBi as a model material for studying unique high-pressure planar defects due to its highly anisotropic stress-dependent properties and structure. Specifically, we identify two sets of planar defects that mimic the diffraction pattern of a site disordered β-Sn structure type and are compatible with the calculated disorder barrier. We derive these defects by symmetry relations over crystallographic transitions. Density functional theory calculations of the proposed defects suggest that these defects are stabilized by diminishing interlayer separations with pressure. Further, we find that one of the proposed defects closely resembles a bulk high-pressure phase of InBi, InBi-ϵ, and we assert that the proposed defects order upon heating, acting as a template for InBi-ϵ growth. The proposed defects and their electronic structure provide a basis for the trend of superconducting critical temperature with increasing pressure. These methods for identifying defects are generalizable to other materials with reports of site disorder at high pressure, prompting a broader search for related high-pressure defects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of Collimation on Diffraction Signal-to-Background Ratios at a Neutron Diffractometer

High diffraction signal-to-background ratios (SBRs), the ratios of diffraction peak integrated intensity over its background intensity, are desired for a neutron diffractometer to acquire good statistics for diffraction pattern measurements and subsequent data analysis. For a given detector, while the diffraction peak signals primarily depend on the characteristics of neutron beam and sample coherent scattering, the background largely originates from the sample incoherent scattering and the scattering from the instrument space. In this work, we investigated the effect of collimation on neutron diffraction SBRs of Si powder measurements using one high-angle area detector bank coupled with six different collimation configurations in a large and complex instrument space at the engineering materials diffractometer VULCAN, SNS, ORNL. The results revealed that the diffraction SBRs can be significantly improved by a proper coarse collimator that leaves no gap between the detector and the collimator, and the improvement of SBRs by a fine radial collimator was remarkable with a proper coarse collimator in place but not distinguishable without one. It was also found that the diffraction SBRs were not effectively improved by adding neutron absorbing element boron to the fine radial collimator body, which indicates that either the absorption of secondary scattered neutrons by the added boron is insignificant or the collimator base material (resin and ABS) alone attenuates background scattering sufficiently. These findings could serve as a useful reference for diffractometer developers and/or operators to optimize their collimation to achieve higher diffraction SBRs.

Yu, Dunji↗
DOE OSTI2025

Two-Frequency RF Fields Induced Multipactor in Coaxial Transmission Lines

Multipactor is a nonlinear discharge phenomenon that occurs in vacuum RF systems, potentially leading to signal distortion, power loss, and even permanent damage to high-power components. This study presents a detailed investigation of two-surface multipactor in coaxial transmission lines under two-frequency excitation, using one-dimensional (1D) Monte Carlo simulations validated by three-dimensional (3D) Particle-in-Cell (PIC) results and experimental data. Introducing a second carrier mode is shown to suppress multipactor by reshaping and shrinking the susceptibility region, with the extent and location of suppression strongly dependent on the device aspect ratio and the relative phase of the second mode. Distinct suppression patterns emerge across different frequency–gap distance (fd) regimes, and in certain cases, susceptibility expansion is also observed. The study identifies and distinguishes pure and mixed multipactor modes in coaxial geometry, where analytical mode boundaries are not readily defined. Unlike planar systems, pure-mode regions in coaxial structures overlap with mixed-mode domains, complicating classification. Image charge forces are found to have minimal effect on susceptibility thresholds but do influence electron growth rates. These findings provide new insights into waveform-driven control of multipactor in high-power RF systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Nonlinear inductive response of pinned superconducting vortices in artificial pinning sites

Using the time dependent Ginzburg-Landau equations, we simulate the inductive responses of a variety of thin-film systems containing patterned antidots with different sizes and shapes. The results for all shapes show that the kinetic inductance diverges as the applied current approaches a critical current that is below the BCS depairing current. In conclusion, exploiting the similarity of the observed current-voltage behavior to that of Josephson junctions, we obtain an empirical equation that well fits the inductivity curve as a function of the applied current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles

Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes-acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. Further, this study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.

Autonomous vehicles↗
DOE OSTI2026

Enhancing SWAT with mechanistic plant hydraulics: development and application in the Hanjiang River Basin

Plant transpiration plays a critical role in global water and energy cycles, requiring better process understanding as climate change intensifies drought stress and alters plant responses. Most hydrological models such as the widely-used SWAT lack representation of plant hydraulics, the mechanistic processes controlling plant water regulation and transpiration. Here, this study developed SWAT-PHS by integrating a plant hydraulics scheme (PHS) into SWAT hydrological model, enabling explicit simulation of root water uptake, sap flow, storage and transpiration at 30-minute timescales for watershed-scale modeling. In the Hanjiang River Basin, SWAT-PHS mitigated overestimation of runoff during the rainy season and underestimation during the dry season, reducing the overall simulation error by 29% across the entire simulation period. The model can simulate reasonable plant water dynamics, including diurnal transpiration patterns and drought responses showing declining transpiration flux, hydraulic buffering through stem water storage, and depth-dependent root water uptake strategies. Sensitivity analysis shows that SWAT-PHS captured mechanistic relationships between plant hydraulic traits and transpiration, with root distribution and stem capacitance positively affecting annual transpiration while vulnerability parameters showed negative effects. This work provides a pathway for improving hydrologic modeling and water resource management by better representing plant water regulation under climate change and expected intensifying water stress conditions.

China↗
DOE OSTI2026

Breakdown front dynamics of streamer-like discharge in electron-charged polymethyl methacrylate

We present the results of an experimental study of fast breakdown in electron-charged polymethyl methacrylate. We irradiate bulk polymethyl methacrylate disks with diameters up to one meter at different implanted charge densities and measure the discharge current during the forced electrical breakdown of the material. We infer the breakdown dynamics from these current waveforms, including the velocity and time dependence of the electric field driving the breakdown, and compare these results with the physical electrical tree patterns left behind in the material. We find that the dynamics and physical characteristics of the breakdown channels in electron-irradiated solids depart from typical expectations of electrical treeing behavior in solid materials. Thus, we interpret these results as an expression of streamer discharges in dense gases motivated by the existence of trapped gases in the solid due to radiation damage. We show that the dynamics of the breakdown channels in the electron-charged solid dielectric material is well described by applying standard streamer physics to this physical system. The results show that the dynamics of breakdown channels in solid dielectric material is a promising avenue to further understand streamer discharges in different media under extreme conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data

Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.

Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗
DOE OSTI2024

Leveraging BERT and Network-Based Attention Analysis for Identifying Treatment Milestones in EHRs

This study introduces a sophisticated data-driven framework for analyzing Electronic Health Records (EHRs) using transformer-based models to identify and disentangle overlapping treatment contexts. The framework leverages a preprocessing pipeline that transforms structured procedural codes into semantically enriched descriptive text, enabling the use of attention mechanisms to cluster medical events into treatment milestones—cohesive and distinct components of care processes. The methodology is rigorously validated using synthetic datasets derived from the MIMIC-III database, designed to simulate the heterogeneity and overlapping procedural contexts characteristic of real-world EHR scenarios. Quantitative evaluation highlights the framework’s robustness in disentangling concurrent care pathways, with attention metrics and unsupervised clustering approaches demonstrating the ability to preserve intra-context relationships while distinguishing inter-context dependencies. By addressing challenges inherent in data heterogeneity, this approach provides a foundation for uncovering complex treatment patterns, advancing clinical decision-making, and optimizing resource allocation in diverse healthcare environments.

Kim, Minsu [ORNL] (ORCID:0000000224185535)↗
DOE OSTI2025

Fast calculation of diffraction patterns from an ensemble of aligned molecules

We report an algorithm to calculate electron diffraction patterns for molecules with anisotropic angular distribution, which is significantly faster than existing methods. The algorithm uses a transform to convert the molecular orientation distribution, which is a function of three Euler angles, to the atom-pair distribution functions which depend on the polar and azimuthal angles. The diffraction signal can then be calculated from the atom-pair distributions. We demonstrate the computation method numerically by calculating electron diffraction patterns for a symmetric top molecule (trifluoroiodomethane) and an asymmetric top molecule (formaldehyde) and show that it reduces the calculation time by approximately two orders of magnitude compared to the standard brute-force method. Here, the method can also be applied to the calculation of x-ray diffraction patterns.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Probing phonon focusing, thermomechanical behavior, and moiré patterns in van der Waals architectures using surface acoustic waves

Surface acoustic waves (SAWs) propagate along solid-air, solid-liquid, and solid-solid interfaces. Their characteristics depend on the elastic properties of the solid. Combining transmission electron microscopy (TEM) experiments with molecular dynamics (MD) simulations, we probe atomic environments around intrinsic defects that generate SAWs in vertically stacked two-dimensional (2D) bilayers of MoS 2 . Our joint experimental-simulation study provides insights into SAW-induced structural and dynamical changes and thermomechanical responses of MoS 2 bilayers. Using MD simulations, we compute mechanical properties from the SAW velocity and thermal conductivity from thermal diffusion of SAWs. The results for Young’s modulus and thermal conductivity of an MoS 2 monolayer are in good agreement with experiments. The presence of defects, such as nanopores which generate SAWs, reduces the thermal conductivity of 2D-MoS 2 by an order of magnitude. We also observe dramatic changes in moiré patterns, phonon focusing, and cuspidal structures on 2D-MoS 2 layers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗
DOE OSTI2025

Morphologies of dealloying corrosion attack at grain boundaries

Dealloying corrosion at grain boundaries severely compromises the performance of polycrystalline materials across a wide variety of technological applications. The impact of this phenomenon depends upon the morphology and rate of intergranular dealloying, which can range from planar to wormhole-like patterns that rapidly advance into the alloy. Using 2D and 3D multi-phase field simulations, we reveal how diverse microstructures result from a fundamental interplay between alloy composition and a grain boundary migration mechanism that alters diffusional pathways of dealloying. Inside intergranular dealloying channels, corrosion product buildup can spawn new channels that branch into grain interiors, such that alloys can be degraded from the inside out. These processes further lead to an atypical coarsening mode assisted by diffusion in the dealloying agent. We summarize a unifying explanation for dealloying morphology selection in polycrystalline alloys, which provides an important step towards their optimization for dealloying corrosion environments.

Corrosion↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗