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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ductility mechanisms in complex concentrated refractory alloys from atomistic fracture simulations

The striking variation in damage tolerance among refractory complex concentrated alloys is examined through the analysis of atomistic fracture simulations, contrasting behavior in elemental Nb with that in brittle NbMoTaW and ductile Nb45Ta25Ti15Hf15. We employ machine-learning interatomic potentials (MLIPs), including a new MLIP developed for NbTaTiHf, in atomistic simulations of crack tip extension mechanisms based on analyses of atomistic fracture resistance curves. While the initial behavior of sharp cracks shows good correspondence with the Rice theory, fracture resistance curves reveal marked changes in fracture modes for the complex alloys as crack extension proceeds. In NbMoTaW, compositional complexity appears to promote dislocation nucleation relative to pure Nb, despite theoretical predictions that the alloy should be relatively more brittle. In Nb45Ta25Ti15Hf15, alloying alters the fracture mode compared to elemental Nb, promoting crack tip blunting and enhancing resistance to crack propagation.

Computational methods↗
DOE OSTI2024

Electronic structure analysis and DFT benchmarking of Rydberg-type alkali-metal-crown ether, -cryptand, and -adamanzane complexes

Density functional theory (DFT) and electron propagator theory (EPT) calculations were performed to study ground and excited electronic structures of alkali-metal (M) coordinated 9-crown-3, 24-crown-8, [2.1.1]cryptand, o-Me 2 -1.1.1, and 3 6 Adamanzane complexes. Each complex bears an expanded electron in the periphery and occupies diffuse 1p-, 1d-, 1f-type molecular orbitals (or superatomic 1P, 1D, 1F orbitals) in excited electronic states. The calculated superatomic shell model of the M(9-crown-3) 2 is 1S, 1P, 1D, 1F, 2S, 2P, 2D, 1G and it is held by all other complexes up to the studied 1F level. Due to the highly diffuse nature of the electron, the ionization energies of these complexes are significantly lower (1.6–2.0 eV) and hence these complexes belong to the superalkali category. Further, the ab initio EPT ionization energy and the excitation energies of the Li(9-crown-3) 2 were used to evaluate DFT errors associated with a series of exchange correlation functionals that span multiple rungs of Jacob's ladder (i.e., GGA, meta-GGA, global GGA hybrid, meta-GGA hybrid, range-separated hybrid, double-hybrid). Among these, the best performing functional is the range-separated hybrid CAM-B3LYP and the errors are within 6% of high-level ab initio EPT results. The accuracy of CAM-B3LYP is indeed transferable to similar complexes and hence the findings are expected to accelerate the progression of studies of Rydberg-type systems.

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

Time delay lens modelling challenge

ABSTRACT In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant H0. However, published state-of-the-art analyses require of order 1 yr of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge, we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated data sets. The results in Rungs 1 and 2 show that methods that use only the point source positions tend to have lower precision ($10\!-\!20{{\ \rm per\ cent}}$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic data sets can recover H0 within the target accuracy (|A| < 2 per cent) and precision (<6 per cent per system), even in the presence of a poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.

Ding, X.↗
DOE OSTI2025

Modal Analysis and Testing of a Cantilever Beam: Results and Guide

This report discusses modal analysis and testing of a cantilever beam including an introduction to modal testing, simulation, analysis, and a comparison of results. An accompanying presentation can be found from the LLNL CASIS website. Modal testing and analysis are essential for characterizing the response of a structure during vibration environments. Determining natural frequencies and mode shapes helps determine whether resonances will be reached during operations and if so, how the structure will respond and how the response can be tuned. The goal of this work is to convey the basics of modal testing and analysis through a simple project. This can be applied later to more complex, applicable structures. This includes a variety of work including data collection, finite element analysis and data processing. For this project a cantilever beam was chosen because it is a simple, well-characterized structure.

42 ENGINEERING↗
DOE OSTI2021

Sensitivity Analysis of Particle-In-Cell Modeling Parameters in Settling Bed, Bubbling Fluidized Bed and Circulating Fluidized Bed

The objective of the work presented is to perform a preliminary sensitivity analysis of particle-in-cell (PIC) model parameters when applied to settling bed, bubbling fluidized bed, and circulating fluidized bed simulations. These examples correspond to widely different flow conditions commonly seen in chemical engineering applications. Simulations were performed using the PIC method in the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). As part of the non-intrusive uncertainty quantification (UQ) analysis, simulation campaigns were generated using Nodeworks. Sampling locations or settings for PIC model parameters were determined using the Latin Hypercube method. Response surfaces were created using radial basis functions (RBF), and Sobol’ indices were estimated to quantify the influence of model parameters on the quantities of interest (QoI). This study marks a first step towards systematically determining optimal ranges for model parameters used in MFiX-PIC. Based on limited experience, it is expected that these values would depend strongly on flow conditions. Given the complexity of the multiphase flow systems under analysis, a non-intrusive UQ based approach is used to identify the most influential parameters in each case. This prior knowledge will help in proposing an effective design of experiments (DoE) and determine optimal parameters through techniques such as deterministic or Bayesian calibration, which will be pursued in the future.

42 ENGINEERING↗
DOE OSTI2023

The AXEAP2 program for K β X-ray emission spectra analysis using artificial intelligence

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant K β XES of 3 d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 ( AXEAP2 ), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3 d electron spin state, 3 d –3 p electron exchange force and K β emission core-hole lifetime.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Active conformation of the p97-p47 unfoldase complex

The p97 AAA+ATPase is an essential and abundant regulator of protein homeostasis that plays a central role in unfolding ubiquitylated substrates. Here we report two cryo-EM structures of human p97 in complex with its p47 adaptor. One of the conformations is six-fold symmetric, corresponds to previously reported structures of p97, and lacks bound substrate. The other structure adopts a helical conformation, displays substrate running in an extended conformation through the pore of the p97 hexamer, and resembles structures reported for other AAA unfoldases. These findings support the model that p97 utilizes a “hand-over-hand” mechanism in which two residues of the substrate are translocated for hydrolysis of two ATPs, one in each of the two p97 AAA ATPase rings. Proteomics analysis supports the model that one p97 complex can bind multiple substrate adaptors or binding partners, and can process substrates with multiple types of ubiquitin modification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Progress Towards Microcalorimeter Gamma Spectroscopy Analysis for Nuclear Fuel Separations

The High Efficiency and Resolution Microcalorimeter Spectrometer, 400 pixels (HERMES-400) is an ultra-high resolution gamma-ray spectrometer at Idaho National Laboratory’s Materials and Fuels Complex. HERMES-400 is intended to enable precise nondestructive analysis of advanced fuel cycle materials. Key upgrades and repairs of the instrument were performed this year to improve performance. First, the fourth and final microcalorimeter detector module was installed, meeting the milestone for its integration into the system. Operation with all four modules enables higher detector efficiency than any previous microcalorimeter gamma-ray system. Second, a thinner magnetic shield was installed. This shields the sensitive microcalorimeter pixels from stray magnetic fields while allowing transmission of lower-energy gamma rays, which are important to isotopic analysis. Finally, the cryostat, which provides cooling of the modules to their operating temperature, was found to have a helium coolant leak, which was repaired. HERMES-400 is in a stable state to perform repeated, long-term gamma-ray measurements with good detector efficiency and energy resolution. In FY25, irradiated TRISO fuel and salts from advanced electrochemical recycling techniques are candidates for microcalorimeter measurements. A final upgrade of the magnetic shielding and vibration damping of the system is also planned to maximize the system performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.

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

Visual‐Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning

Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real‐world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision‐makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically developed tools for scenario analysis rigorously quantify the combined effects of multiple sources of uncertainty, but the practical application of these models is limited by the challenges of information visualization and communication of results. In short, municipal water supply planners lack access to planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user‐friendly visual and interactive tools to enhance user accessibility. In this work, we fill this gap by proposing Visual‐Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. Santa Barbara faces multiple uncertainties from pending state and federal regulations to changing hydrology and water demand. The city seeks to increase its water portfolio robustness by expanding its seawater desalination plant, but must decide how much capacity to add. We introduce computational tools that assess uncertainty across nine uncertain drivers identified with the help of water planners in SB. To allow public participation in the desalination expansion decision, we develop interactive visual‐analytics to aid decision‐makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness and aim to enhance participation and uncertainty characterization of urban water planning efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Hydride and Seek: Comparing Crystallographic Hydride Placement Techniques with an Open-Shell Cobalt Complex

Locating hydrides is crucial in organometallic chemistry but difficult to do accurately using X-ray diffraction. Electron diffraction has been proposed as a way to overcome this problem but has not been systematically compared to neutron diffraction and to quantum crystallography (Hirshfeld atom refinement, HAR) to test this hypothesis. Here, we present a comparative analysis of methods for a terminal cobalt hydride complex by comparing a single-crystal neutron diffraction reference structure to results from single-crystal X-ray diffraction with and without Hirshfeld atom refinement (HAR, NoSpherA2), density functional theory (DFT), and electron diffraction (3D-ED/MicroED) refined under kinematical and dynamical formalisms. Conventional X-ray diffraction gives lower precision than neutron diffraction as expected. Despite expected improvements, HAR gives systematic deviation from the neutron benchmark. Interestingly, optimized DFT equilibrium geometries are closer to the neutron value than the value from HAR. On the other hand, electron diffraction with a high-quality data set coupled with dynamical refinement localizes the hydride in difference maps and gives excellent agreement with the neutron data. Dynamical refinement is crucial, as kinematical refinement does not allow assignment of a hydride peak. This cross-modal comparison defines the conditions under which 3D-ED/MicroED delivers high-precision metal–hydride distances for this open-shell cobalt hydride.

anions↗
DOE OSTI2021

The multi-faceted inverted harmonic oscillator: Chaos and complexity

The harmonic oscillator is the paragon of physical models; conceptually and computationally simple, yet rich enough to teach us about physics on scales that span classical mechanics to quantum field theory. This multifaceted nature extends also to its inverted counterpart, in which the oscillator frequency is analytically continued to pure imaginary values. In this article we probe the inverted harmonic oscillator (IHO) with recently developed quantum chaos diagnostics such as the out-of-time-order correlator (OTOC) and the circuit complexity. In particular, we study the OTOC for the displacement operator of the IHO with and without a non-Gaussian cubic perturbation to explore genuine and quasi scrambling respectively. In addition, we compute the full quantum Lyapunov spectrum for the inverted oscillator, finding a paired structure among the Lyapunov exponents. We also use the Heisenberg group to compute the complexity for the time evolved displacement operator, which displays chaotic behaviour. Finally, we extended our analysis to N-inverted harmonic oscillators to study the behaviour of complexity at the different timescales encoded in dissipation, scrambling and asymptotic regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Weather-Driven Resilience for Distribution Systems

With increasing billion dollar disasters due to weather events, it is of utmost priority for utility and grid operators to maintain and enhance the resilience of distribution grid. Traditionally, such analysis were conducted with reliability metrics alone. However, with increasing complexity of distribution grid and advancements in grid edge resources, evaluating grid resilience is challenging and involves multi-faceted analysis of the impact of weather events on the distribution grid. This presentation provides background, details, and future works in the field of weather-driven resilience for power distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Design principles and physical properties of two-dimensional heterostructured borides

Principles of design to create dynamically stable transition metal-, lanthanide-, and actinide-based low-dimensional borides are presented. A charge transfer analysis of donor metal atoms to electron deficient honeycombed B lattices allows to predict complex covalent heterostructures hosting Dirac states. The applicable guidelines are supported with the analysis of phonon spectra computed with first-principles calculations to demonstrate the physical stability of nanometer-thick heterostructures. Similar or dissimilar layered borides can be stacked on top of each other in a layer-by-layer fashion creating compounds that can be fundamentally different from the individual layers, opening a rich playground to explore novel physical properties and new materials. Functionalities such as multiple Dirac states, highly dispersive electronic bands, and decoupled acoustic-optical phonon branches are studied. The combination of appealing electronic properties and physical realization makes of predicted layered borides promising materials to integrate a new generation of two-dimensional materials.

2-dimensional systems↗
DOE OSTI2021

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part I - Analysis with a Small Sample Size

Computer simulations, especially of complex phenomena, can be expensive, requiring high-performance computing resources. Often, to understand a phenomenon, multiple simulations are run, each with a different set of simulation input parameters. These data are then used to create an interpolant, or surrogate, relating the simulation outputs to the corresponding inputs. When the inputs and outputs are scalars, a simple machine learning model can suffice. However, when the simulation outputs are vector valued, available at locations in two or three spatial dimensions, often with a temporal component, creating a surrogate is more challenging. In this report, we use a two-dimensional problem of a jet interacting with high explosives to understand how we can build high-quality surrogates. The characteristics of our data set are unique - the vector-valued outputs from each simulation are available at over two million spatial locations; each simulation is run for a relatively small number of time steps; the size of the computational domain varies with each simulation; and resource constraints limit the number of simulations we can run. We show how we analyze these extremely large data-sets, set the parameters for the algorithms used in the analysis, and use simple ways to improve the accuracy of the spatio-temporal surrogates without substantially increasing the number of simulations required.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Dinitrogen Binding and Functionalization from a Low-Coordinate Alkynyliron Complex

Alkynyl complexes of low-coordinate transition metals offer a sterically open environment and interesting bonding opportunities. Here, in this work, we explore the capacity of iron(I) alkynyl complexes to bind N 2 and isolate a N 2 complex including its X-ray crystal structure. Silylation of the N 2 complex gives an isolable, formally iron(IV) complex with a disilylhydrazido(2−) ligand, but natural bond orbital analysis indicates that an iron(II) formulation is preferable. The structure of this compound is similar to an earlier reported phenyl complex in which phenyl migration forms a new N–C bond, but the alkynyl group does not migrate. DFT calculations are used to test the possible reasons why the alkynyl is resistant to migration, and these show that the large Fe–C bond energy in the alkynyl complex is a factor that could contribute to the lack of migration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗