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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Early-time measure in eternal inflation

In a situation like eternal inflation, where our data is replicated at infinitely-many other space-time events, it is necessary to make a prior assumption about our location to extract predictions. The principle of mediocrity entails that we live at asymptotic late times, when the occupational probabilities of vacua has settled to a near-equilibrium distribution. In this paper we further develop the idea that we instead exist during the approach to equilibrium, much earlier than the exponentially-long mixing time. In this case we are most likely to reside in vacua that are easily accessed dynamically. Using first-passage statistics, we prove that vacua that maximize their space-time volume at early times have: 1. maximal ever-hitting probability; 2. minimal mean first-passage time; and 3. minimal decay rate. These requirements are succinctly captured by an early-time measure. The idea that we live at early times is a predictive guiding principle, with many phenomenological implications. First, our vacuum should lie deep in a funneled region, akin to folding energy landscapes of proteins. Second, optimal landscape regions are characterized by relatively short-lived vacua, with lifetime of order the de Sitter Page time. For our vacuum, this lifetime is ~ 10 130 years, which is consistent with the Standard Model estimate due to Higgs metastability. Third, the measure favors vacua with small, positive vacuum energy. This can address the cosmological constant problem, provided there are sufficiently many vacua in the entire ensemble of funnels. As a concrete example, we study the Bousso-Polchinski lattice of flux vacua, and find that the early-time measure favors lattices with the fewest number of flux dimensions. This favors compactifications with a large hierarchy between the lightest modulus and all other Kähler and complex structure moduli.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Dungan, Jennifer L.↗
DOE OSTI2023

Hydrogen Evolution on Electrode‐Supported Pt n Clusters: Ensemble of Hydride States Governs the Size Dependent Reactivity

Abstract We report the size‐dependent activity and stability of supported Pt 1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters outperform polycrystalline Pt in activity, with size‐dependent stability. To understand the size effects, we use DFT calculations to study the structural fluxionality under varying potentials. We show that the clusters can reshape under H coverage and populate an ensemble of states with diverse stoichiometry, structure, and thus reactivity. Both experiment and theory suggest that electrocatalytic species are hydridic states of the clusters (≈2 H/Pt). An ensemble‐based kinetic model reproduces the experimental activity trend and reveals the role of metastable states. The stability trend is rationalized by chemical bonding analysis. Our joint study demonstrates the potential‐ and adsorbate‐coverage‐dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

Zhang, Zisheng↗
DOE OSTI2023

Solution-Phase Synthesis and Photoluminescence of Quaternary Chalcohalide Semiconductors

Mixed-metal chalcohalide semiconductors have emerged as promising candidates for photovoltaic applications. However, preparation of these multinary compounds using solution-phase techniques remains particularly challenging compared to traditional solid-state methods. To fully harness their potential, it is desirable to develop synthetic methods that enable control over both the phase purity and dimensionality of chalcohalides. In this work, we report the solution-phase synthesis of Pb 2 SbS 2 I 3 and Pb 2 BiS 2 I 3 quaternary chalcohalides using readily available precursors. Fine tuning of reaction parameters allows for the isolation of rod-like morphologies with tunable diameters and aspect ratios. The quaternary chalcohalides display photoluminescence as an ensemble as well as at the single particle level, as demonstrated using fluorescence microscopy. We further evaluate the relative stability and band gap of Pb 2 SbS 2 I 3 polymorphs and their coloring patterns using electronic structure calculations. The synthetic methods developed here will motivate the study of ever more complex chalcohalides and other multinary semiconductors for new technological applications.

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

Nanotesla Magnetometry with the Silicon Vacancy in Silicon Carbide

Silicon carbide is a promising host material for spin-defect-based quantum sensors owing to its commercial availability and established techniques for electrical and optical microfabricated device integration. The negatively charged silicon vacancy is one of the leading spin defects studied in silicon carbide owing to its near-telecom photoemission, high spin number, and nearly temperature-independent ground-state zero-field splitting. We report the realization of nanotesla shot-noise-limited ensemble magnetometry based on optically detected magnetic resonance with the silicon vacancy in 4H silicon carbide. By coarsely optimizing the anneal parameters and minimizing power broadening, we achieve a sensitivity of 50 nT/√Hz and a theoretical shot-noise-limited sensitivity of 3.5 nT/√Hz. This is accomplished without utilizing complex photonic engineering, control protocols, or applying excitation powers greater than a watt. This work demonstrates that the silicon vacancy in silicon carbide provides a low-cost and simple approach to quantum sensing of magnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Probabilistic measures for biological adaptation and resilience

This paper introduces an approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from nonequilibrium statistical mechanics, we propose a measure termed “ecological resilience through adaptation,” specifically tailored to noisy, forced systems that undergo physiological adaptation in the face of stressful environmental changes. Randomness plays a key role, accounting for model uncertainty and the inherent variability in the dynamical response among components of biological systems. Our measure of resilience is rooted in the probabilistic description of states within these systems and is defined in terms of the dynamics of the ensemble average of a model-specific observable quantifying success or well-being. Our approach utilizes stochastic linear response theory to compute how the expected success of a system, originally in statistical equilibrium, dynamically changes in response to a environmental perturbation and a subsequent adaptation. Importantly, the resulting mathematical derivations allow for the estimation of resilience in terms of ensemble averages of simulated or experimental data. Finally, through a simple but clear conceptual example, we illustrate how our resilience measure can be interpreted and compared to other existing frameworks in the literature. The methodology is general but inspired by applications in plant systems, with the potential for broader application to complex biological processes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Southern Hemisphere dominates recent decline in global water availability

Global land water underpins livelihoods, socioeconomic development, and ecosystems. It remains unclear how water availability has changed in recent decades. Using an ensemble of observations, we quantified global land water availability over the past two decades. We show that the Southern Hemisphere has dominated the declining trend in global water availability from 2001 to 2020. The significant decrease occurs mainly in South America, southwestern Africa, and northwestern Australia. In the Northern Hemisphere, the complex regional increasing and decreasing trends cancel each other, resulting in a negligible hemispheric trend. The variability and trend in water availability in the Southern Hemisphere are largely driven by precipitation associated with climate modes, particularly the El Niño-Southern Oscillation. Finally, this study highlights their dominant role in controlling global water availability.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Leveraging Existing Mission Tools in a Re-Usable, Component-Based Software Environment

Emerging methods in component-based software development offer significant advantages but may seem incompatible with existing mission operations applications. In this paper we relate our positive experiences integrating existing mission applications into component-based tools we are delivering to three missions. In most operations environments, a number of software applications have been integrated together to form the mission operations software. In contrast, with component-based software development chunks of related functionality and data structures, referred to as components, can be individually delivered, integrated and re-used. With the advent of powerful tools for managing component-based development, complex software systems can potentially see significant benefits in ease of integration, testability and reusability from these techniques. These benefits motivate us to ask how component-based development techniques can be relevant in a mission operations environment, where there is significant investment in software tools that are not component-based and may not be written in languages for which component-based tools even exist. Trusted and complex software tools for sequencing, validation, navigation, and other vital functions cannot simply be re-written or abandoned in order to gain the advantages offered by emerging component-based software techniques. Thus some middle ground must be found. We have faced exactly this issue, and have found several solutions. Ensemble is an open platform for development, integration, and deployment of mission operations software that we are developing. Ensemble itself is an extension of an open source, component-based software development platform called Eclipse. Due to the advantages of component-based development, we have been able to vary rapidly develop mission operations tools for three surface missions by mixing and matching from a common set of mission operation components. We have also had to determine how to integrate existing mission applications for sequence development, sequence validation, and high level activity planning, and other functions into a component-based environment. For each of these, we used a somewhat different technique based upon the structure and usage of the existing application.

Greene, Kevin↗
DOE OSTI2021

Identifying precursors of daily to seasonal hydrological extremes over the USA using deep learning techniques and climate model ensembles

Focal Area(s): We focus on two areas of crosscutting interest for DOE: 1) predictability of extreme precipitation and drought in the USA and 2) the integration of climate models with new AI tools, such as convolutional neural networks (CNN) and methods to understand their output (e.g. layer-wise relevance propagation; LRP). This project fits into focus area 3 of this call for white paper using AI to gain insight from complex data, including explainable AI tools. Science Challenge: Predicting hydrological extremes is important due to their impacts on people, agriculture and infrastructure. This prediction is difficult due to the infrequent occurrence of extremes and their complexity. However, extreme events can be related to more predictable conditions in the ocean, such as El Nino, long-term soil moisture or large scale modes of climate variability, such as the North Atlantic Oscillation (NAO).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Holographic pseudoentanglement and the complexity of the AdS/CFT dictionary

The `quantum gravity in the lab' paradigm suggests that quantum computers might shed light on quantum gravity by simulating the CFT side of the AdS/CFT correspondence and mapping the results to the AdS side. This relies on the assumption that the duality map (the `dictionary') is efficient to compute. In this work, we show that the complexity of the AdS/CFT dictionary is surprisingly subtle: there might be cases in which one can efficiently apply operators to the CFT state (a task we call 'operator reconstruction') without being able to extract basic properties of the dual bulk state such as its geometry (which we call 'geometry reconstruction'). Geometry reconstruction corresponds to the setting where we want to extract properties of a completely unknown bulk dual from a simulated CFT boundary state. We demonstrate that geometry reconstruction may be generically hard due to the connection between geometry and entanglement in holography. In particular we construct ensembles of states whose entanglement approximately obey the Ryu-Takayanagi formula for arbitrary geometries, but which are nevertheless computationally indistinguishable. This suggests that even for states with the special entanglement structure of holographic CFT states, geometry reconstruction might be hard. This result should be compared with existing evidence that operator reconstruction is generically easy in AdS/CFT. A useful analogy for the difference between these two tasks is quantum fully homomorphic encryption (FHE): this encrypts quantum states in such a way that no efficient adversary can learn properties of the state, but operators can be applied efficiently to the encrypted state. We show that quantum FHE can separate the complexity of geometry reconstruction vs operator reconstruction, which raises the question whether FHE could be a useful lens through which to view AdS/CFT.

FOS: Physical sciences↗
DOE OSTI2023

Spontaneous shock waves in pulse-stimulated flocks of Quincke rollers

Active matter demonstrates complex spatiotemporal self-organization not accessible at equilibrium and the emergence of collective behavior. Fluids comprised of microscopic Quincke rollers represent a popular realization of synthetic active matter. Temporal activity modulations, realized by modulated external electric fields, represent an effective tool to expand the variety of accessible dynamic states in active ensembles. Here, we report on the emergence of shockwave patterns composed of coherently moving particles energized by a pulsed electric field. The shockwaves emerge spontaneously and move faster than the average particle speed. Combining experiments, theory, and simulations, we demonstrate that the shockwaves originate from intermittent spontaneous vortex cores due to a vortex meandering instability. They occur when the rollers’ translational and rotational decoherence times, regulated by the electric pulse durations, become comparable. The phenomenon does not rely on the presence of confinement, and multiple shock waves continuously arise and vanish in the system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization

In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantum information and quantum simulation of neutrino physics

In extreme astrophysical environments such as core-collapse supernovae and binary neutron star mergers, neutrinos play a major role in driving various dynamical and microphysical phenomena, such as baryonic matter outflows, the synthesis of heavy elements, and the supernova explosion mechanism itself. The interactions of neutrinos with matter in these environments are flavor-specific, which makes it of paramount importance to understand the flavor evolution of neutrinos. Flavor evolution in these environments can be a highly nontrivial problem thanks to a multitude of collective effects in flavor space, arising due to neutrino-neutrino ($v$-$v$) interactions in regions with high neutrino densities. A neutrino ensemble undergoing flavor oscillations under the influence of significant $v$-$v$ interactions is somewhat analogous to a system of coupled spins with long-range interactions among themselves and with an external field (‘long-range’ in momentum-space in the case of neutrinos). As a result, it becomes pertinent to consider whether these interactions can give rise to significant quantum correlations among the interacting neutrinos, and whether these correlations have any consequences for the flavor evolution of the ensemble. In particular, one may seek to utilize concepts and tools from quantum information science and quantum computing to deepen our understanding of these phenomena. In this article, we attempt to summarize recent work in this field. In conclusion, we also present some new results in a three-flavor setting, considering complex initial states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

DeepONet-Assisted Optimization of Surface Topography for Transition Delay in a Mach 4.5 Boundary Layer

We use deep learning, an ensemble variational technique (EnVar), and direct numerical simulations(DNS) to design an optimal topography for a two-dimensional roughness element that delays the on-set of laminar-turbulent transition in a Mach 4.5 flat-plate boundary layer. Deep operator networks (DeepONets), which have the known ability to learn complex nonlinear operators within dynamical systems, are used for machine learning. For the baseline configuration of a smooth flat plate, the second-mode waves at the DNS inflow cause a quick nonlinear breakdown of the high-speed boundary layer within the computational domain. Results reported in the present study validate the ability of DeepONets to model the transition delay via a given topography of the roughness element. The computing cost to optimize the rough-ness element for minimal skin-friction drag is substantially lowered by the DeepONets-based reduced-order model. In comparison to the baseline method of EnVar optimization based on DNS alone, the DeepONets-based EnVar optimizer is able to delay transition past the outflow boundary of the computational domain while utilizing almost 5–6 times fewer DNS.

Machine Learning↗
DOE OSTI2023

Hydrogen Evolution on Electrode–Supported Ptn Clusters: Ensemble of Hydride States Governs the Size Dependent Reactivity

We report the size-dependent activity and stability of supported Pt1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters outperform polycrystalline Pt in activity, with sizedependent stability. To understand the size effects, we use DFT calculations to study the structural fluxionality under varying potentials. We show that the clusters can reshape under H coverage and populate an ensemble of states with diverse stoichiometry, structure, and thus reactivity. Both experiment and theory suggest that electrocatalytic species are hydridic states of the clusters (~2 H/Pt). An ensemble-based kinetic model reproduces the experimental activity trend and reveals the role of metastable states. Furthermore, the stability trend is rationalized by chemical bonding analysis. Our joint study demonstrates the potential- and adsorbate-coverage-dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

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

Analytical gradient-based optimization of CALPHAD model parameters

The calibration of CALPHAD (CALculation of PHAse Diagrams) models involves the solution of a very challenging high-dimensional multiobjective optimization problem. Traditional approaches to parameter fitting predominantly rely on gradient-free methods, which while robust, are computationally inefficient and often scale poorly with model complexity. In this work, we introduce and demonstrate a generalizable framework for analytic gradient-based optimization of the parameters of the CALPHAD model enabled by the recently formalized Jansson derivative technique. This method allows for efficient evaluation of gradients of thermodynamic properties at equilibrium with respect to model parameters, even in the presence of arbitrarily complex internal degrees of freedom. Leveraging these semi-analytic gradients, we employ the conjugate gradient (CG) method to optimize thermodynamic model parameters for four binary alloy systems: Cu-Mg, Fe-Ni, Cr-Ni, and Cr-Fe. Across all systems, CG achieves comparable or superior optimality relative to Bayesian ensemble Markov Chain Monte Carlo (MCMC) with improvements in computational efficiency ranging from one to three orders of magnitude. Furthermore, our results establish a new paradigm for CALPHAD assessments in which high fidelity data-rich model calibration becomes tractable using deterministic gradient-informed algorithms.

CALPHAD↗
NASA NTRS1999

Investigation of the Influence of Microgravity on Transport Mechanisms in a Virtual Spaceflight Chamber: A Ground Based Program

In January 1992, the IML-1 FES experiment produced a set of classic experimental data and a 40 hour holographic "movie" of an ensemble of spheres in a fluid in microgravity. Because the data are in the form of holograms, we can study the three-dimensional distribution of particles with unprecedented detail by a variety of methods and for a wide variety of interests. The possession of the holographic movie is tantamount to having a complex experiment in space while working in an easily accessible laboratory on earth. The movie contains a vast amount of useful data, including residual g, g-jitter, convection and transport data, and particle fluid interaction data. The information content in the movie is so great that we have scarcely begun to tap into the data that is actually available in the more than 1000 holograms, each containing as much as 1000 megabytes of information. This ground-based project is exploiting this data and the concept of holographic storage of spaceflight data to provide an understanding of the effects of microgravity in materials processing. This paper provides the foundation, objectives, and status of the ground based project. The primary objective of this project is to advance the understanding of microgravity effects on crystal growth, convection in materials processing in the space environment, and complex transport phenomena at low Reynolds numbers. This objective is being achieved both experimentally and theoretically. Experiments are making use of existing holographic data recorded during the IML- I spaceflight. A parallel theoretical effort is providing the models for understanding the particle fields and their physics in the microgravity environment.

Trolinger, James D.↗