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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A deep learning-enhanced framework for multiphysics joint inversion

Joint inversion has drawn considerable attention due to the availability of multiple geophysical data sets, ever-increasing computational resources, the development of advanced algorithms, and its ability to reduce inversion uncertainty. A key issue of joint inversion is to develop effective strategies to link different geophysical data in a unified mathematical framework, in which the information obtained from different models can complement each other. We have developed a deep learning-enhanced joint inversion framework to simultaneously reconstruct different physical models by fusing different types of geophysical data. Traditionally, structure similarity constraints are pursued by joint inversion algorithms using manually crafted formulations (e.g., cross gradient). The constraint is constructed by a deep neural network (DNN) during the learning process. The framework is designed to combine the DNN and a traditional independent inversion workflow and improve the joint inversion result iteratively. The network can be easily extended to incorporate multiphysics without structural changes. Numerical experiments on the joint inversion of 2D DC resistivity data and seismic traveltime are used to validate our method. In addition, this learning-based framework demonstrates excellent generalization abilities when tested on data sets using different geologic structures. It also can handle different sensing configurations and nonconforming discretization.

Geochemistry & Geophysics↗
DOE OSTI2020

Effect of melting processes on the structure and precipitation of a heavy rainstorm in Beijing

Abstract Beijing and its surrounding areas experienced a torrential rainstorm from July 21 to 22, 2012. Previous studies have shown that melting was the main rainwater source in this process. In this paper, melting conversion processes were set to zero (NPMLT test) to analyze the effect of microphysical processes on the structure and precipitation of the convective system. The results showed that without the melting processes, the wind shear at the 700 hPa level decreased, and the wind field in Beijing and its surrounding areas changed. The cold front system moved faster, and the rainfall amount only reached the low rain level, much lower than that during the actual rainstorm. The hydrometeors sources had apparently changed. Though the latent heat release was large and little latent heat absorption occurred in the NPMLT test, the net latent heat did not affect the development of the convective system, and the precipitation was low. Therefore, microphysical processes greatly influence precipitation and convective system.

Guo, Chunwei↗
DOE OSTI2020

Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER

Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO , a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE . The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

4D-STEM of Beam-Sensitive Materials

We report that a scanning electron nanobeam diffraction, or 4D-STEM (four-dimensional scanning transmission electron microscopy), is a flexible and powerful approach to elucidate structure from "soft" materials that are challenging to image in the transmission electron microscope because their structure is easily damaged by the electron beam. In a 4D-STEM experiment, a converged electron beam is scanned across the sample, and a pixelated camera records a diffraction pattern at each scan position. This four-dimensional data set can be mined for various analyses, producing maps of local crystal orientation, structural distortions, crystallinity, or different structural classes. Holding the sample at cryogenic temperatures minimizes diffusion of radicals and the resulting damage and disorder caused by the electron beam. The total fluence of incident electrons can easily be controlled during 4D-STEM experiments by careful use of the beam blanker, steering of the localized electron dose, and by minimizing the fluence in the convergent beam thus minimizing beam damage. This technique can be applied to both organic and inorganic materials that are known to be beam-sensitive; they can be highly crystalline, semicrystalline, mixed phase, or amorphous. One common example is the case for many organic materials that have a π-π stacking of polymer chains or rings on the order of 3.4-4.2 Å separation. If these chains or rings are aligned in some regions, they will produce distinct diffraction spots (as would other crystalline spacings in this range), though they may be weak or diffuse for disordered or weakly scattering materials. We can reconstruct the orientation of the π-π stacking, the degree of π-π stacking in the sample, and the domain size of the aligned regions. This Account summarizes illumination conditions and experimental parameters for 4D-STEM experiments with the goal of producing images of structural features for materials that are beam-sensitive. We will discuss experimental parameters including sample cooling, probe size and shape, fluence, and cameras. 4D-STEM has been applied to a variety of materials, not only as an advanced technique for model systems, but as a technique for the beginning microscopist to answer materials science questions. It is noteworthy that the experimental data acquisition does not require an aberration-corrected TEM but can be produced on a variety of instruments with the right attention to experimental parameters.

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

Probing New Bosons and Nuclear Structure with Ytterbium Isotope Shifts

In this Letter, we present mass-ratio measurements on highly charged Yb 42+ ions with a precision of 4 ×10 -12 and isotope-shift measurements on Yb + on the 2 S 1/2 → 2 D 5/2 and 2 S 1/2 → 2 F 7/2 transitions with a precision of 4 ×10 -9 for the isotopes 168,170,172,174,176 Yb. We present a new method that allows us to extract higher-order changes in the nuclear charge distribution along the Yb isotope chain, benchmarking ab initio nuclear structure calculations. Additionally, we perform a King plot analysis to set bounds on a fifth force in the keV/c 2 to MeV/c 2 range coupling to electrons and neutrons.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exploring 𝛽 decay and 𝛽-delayed neutron emission in exotic 46,47 Cl isotopes

In this paper, 𝛽 − and 𝛽-delayed neutron decays of 46,47 Cl are reported from an experiment carried out at the National Superconducting Cyclotron Laboratory using the Beta Counting System. The half-lives of both 46 Cl and 47 Cl were extracted. Based on the delayed 𝛾-ray transitions observed, the level structure of 𝑁=28 46 Ar was determined. Completely different sets of excited states above the first 2 + state in 46 Ar were populated in the 46 Cl 𝛽⁢0⁢𝑛 and 47 Cl 𝛽⁢1⁢𝑛 decay channels. Two new 𝛾-ray transitions in 47 Ar were identified from the very weak 47 Cl 𝛽⁢0⁢𝑛 decay. Furthermore, 46 Cl 𝛽⁢1⁢𝑛 and 47 Cl 𝛽⁢2⁢𝑛 were also observed to yield different population patterns for levels in 45 Ar, including states of different parities. Here, the experimental results allow us to address some of the open questions related to the delayed neutron emission process. For isotopes with large neutron excess and high 𝑄 𝛽 values, delayed neutron emission remains an important decay mode and can be utilized as a powerful spectroscopic tool. Experimental results were compared with shell-model calculations using the FSU and 𝑉 MU effective interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Method and apparatus for shape-based energy analysis of solids

A computer-readable medium stores instructions including storing a model of a physical structure and defining a mesh for the model. The mesh includes finite elements, each defined by a respective set of edges. The instructions include, for each finite element, identifying a governing differential equation and a set of complementary functions that exactly satisfy the governing differential equation. The instructions include determining an applied physical stimulus for the physical structure. The instructions include generating an energy optimization model that minimizes a difference between internal energy and external energy of the finite elements in response to the applied physical stimulus. The model includes a matrix of respective scalar multipliers for the complementary functions for each finite element. The instructions include transforming the matrix and calculating a physical parameter of interest. The instructions include, in response to the physical parameter not satisfying a design parameter, updating the model of the physical structure.

Spears, Robert E.↗
DOE OSTI2022

Structures of Vanadium-Containing Silicate and Borosilicate Glasses: Vanadium Potential Development and MD Simulations

Vanadium-containing multi-component glasses have been found with widely interests in various applications. However, the complex compositions, thus structures, lead to the challenges in experiments to understand the structural origin of the property change of these glasses. In this work, we developed compatible vanadium-related parameters for a widely used pair wise potential set to enable the simulations of the vanadium-containing multi-component glasses. Various crystal structures and glass compositions (with vanadium in different oxidation states) have been tested using the newly developed parameters, and structural information of cell parameters, pair distribution function, estimated bond distance, and coordination number have been obtained. The results are in good agreement with available experimental data, which indicates the new vanadium parameters can be used to simulate the vanadium-containing multi-component glasses and thus help study those applications with wide interests.

Deng, Lu↗
DOE OSTI2023

Rock Valley Direct Comparison Relocation Working Group Location Results and Recommendations

Work accomplished: Collected and compared historic data for the 1993 Rock Valley earthquake sequence; Compared preliminary and prior location work from different location algorithms, phase pick sets, station constellations, and velocity models; Selected a common set of stations that could be used across all location methods for consistency; Reviewed 8 different sets of phase picks and converged on a single, reviewed set of picks for all common stations; Evaluated four pre-existing regional velocity models and incorporated new and preliminary results for five new velocity models that provide information on the very shallow (< 2km) structure near station RTPP; Compared location results from different methods while using the common sets of picks, stations, and velocity models

58 GEOSCIENCES↗
DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quasi-brittle porous material: Simulated effect of stochastic air void structure on compressive strength

Highlights: • A simulation procedure to study the effect of porosity on the compressive strength of a quasi-brittle material is introduced • Based on the simulated results, the relationship between compressive strength and air void fraction (porosity) is presented. • A linear relationship was achieved between the cubic root of porosity and the simulated compressive strength. The effect of porosity comprised of spherical air voids on the compressive strength of quasi-brittle material was studied via simulations. The simulated porous structures were based on pore size distributions of two mortar samples measured by X-ray microtomography. While the simulation method set practical limits on the size of sample, the base of the statistics was established by simulating 128 small structures generated by sampling from pore structures of two mortars. By studying the application of the classical strength-porosity formulas to the simulated data, a new simple model was formed. A linear relationship was achieved between the cubic root of air void fraction (porosity) and the simulated compressive strength. The reasons for scattering of simulated strength around fitted trend remained unresolved in this study; no clear dependence on pore number or other distribution properties was observed. With the presented simulation approach, the dependence of compressive strength on porosity is achieved independently of disturbances that occur in experimental studies creating understanding of compressional behavior of low porosity materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computational design of closely related proteins that adopt two well-defined but structurally divergent folds

The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum [P.-S. Huang, S. E. Boyken, D. Baker, Nature 537, 320–327 (2016)], and to reengineer natural proteins to alter their dynamics [J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Nat. Chem. Biol.13, 1280–1285 (2017)] or fold [P. A. Alexander, Y. He, Y. Chen, J. Orban, P. N. Bryan, Proc. Natl. Acad. Sci. U.S.A. 106, 21149–21154 (2009)], the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations—one short (~66 Å height) and the other long (~100 Å height)—reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Nearest neighbour distributions: New statistical measures for cosmological clustering

ABSTRACT The use of summary statistics beyond the two-point correlation function to analyse the non-Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying cosmological parameters, is an active field of research in cosmology. In this paper, we explore a set of new summary statistics – the k-Nearest Neighbour Cumulative Distribution Functions (kNN-CDF). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the k-nearest data points, and is sensitive to all connected N-point correlations in the data. The kNN-CDF can be used to measure counts in cell, void probability distributions, and higher N-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets – both discrete points, and the generalization for continuous fields. We use data from a large suite of N-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of kNN-CDF improves the constraints on the cosmological parameters by more than a factor of 2 when applied to the clustering of dark matter in the range of scales between 10 and $40\, h^{-1}\, {\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of haloes in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the kNN-CDF are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data, provided the higher order correlation functions are sensitive to cosmology on the scales of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Real-time gravitational replicas: formalism and a variational principle

This work is the first step in a two-part investigation of real-time replica wormholes. Here we study the associated real-time gravitational path integral and construct the variational principle that will define its saddle-points. We also describe the general structure of the resulting real-time replica wormhole saddles, setting the stage for construction of explicit examples. These saddles necessarily involve complex metrics, and thus are accessed by deforming the original real contour of integration. However, the construction of these saddles need not rely on analytic continuation, and our formulation can be used even in the presence of non-analytic boundary-sources. Furthermore, at least for replica- and CPT-symmetric saddles we show that the metrics may be taken to be real in regions spacelike separated from a so-called ‘splitting surface’. This feature is an important hallmark of unitarity in a field theory dual.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Predicting Fluid Flow Regime, Permeability, and Diffusivity in Mudrocks from Multiscale Pore Characterisation

In geoenergy applications, mudrocks prevent fluids to leak from temporary (H 2 , CH 4 ) or permanent (CO 2 , radioactive waste) storage/disposal sites and serve as a source and reservoir for unconventional oil and gas. Understanding transport properties integrated with dominant fluid flow mechanisms in mudrocks is essential to better predict the performance of mudrocks within these applications. In this study, small-angle neutron scattering (SANS) experiments were conducted on 71 samples from 13 different sets of mudrocks across the globe to capture the pore structure of nearly the full pore size spectrum (2 nm–5 μm). We develop fractal models to predict transport properties (permeability and diffusivity) based on the SANS-derived pore size distributions. The results indicate that transport phenomena in mudrocks are intrinsically pore size-dependent. Depending on hydrostatic pore pressures, transition flow develops in micropores, slip flow in meso- and macropores, and continuum flow in larger macropores. Fluid flow regimes progress towards larger pore sizes during reservoir depletion or smaller pore sizes during fluid storage, so when pressure is decreased or increased, respectively. Capturing the heterogeneity of mudrocks by considering fractal dimension and tortuosity fractal dimension for defined pore size ranges, fractal models integrate apparent permeability with slip flow, Darcy permeability with continuum flow, and gas diffusivity with diffusion flow in the matrix. This new model of pore size-dependent transport and integrated transport properties using fractal models yields a systematic approach that can also inform multiscale multi-physics models to better understand fluid flow and transport phenomena in mudrocks on the reservoir and basin scale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-current-density electrosynthesis of formate from captured CO 2 solution by MOF-derived bismuth nanosheets

Greenhouse gas emissions present a significant challenge to humanity, and utilizing renewable electricity to convert emitted CO 2 into value-added products offers a promising solution; however, traditional CO 2 capture and regeneration processes remain energy-intensive, restricting the overall system efficiency and decarbonization efficacy. In this study, an advanced direct reduction of captured CO 2 with large current densities for formate electrosynthesis was demonstrated without the need for CO 2 regeneration or compression. The bismuth nanosheet (DRM-BiNS) was synthesized by direct reduction of a Bi-based MOF, representing a new class of catalytic materials with a large surface area and interconnected pores, suitable for the direct reduction of captured CO 2 . By seamlessly combining experimentation and simulation, insights into the structure-parameter-performance relation were acquired in a flow cell setting, including critical membrane-electrode distance, cell orientation, and pumping flow rate. Important flow-cell components, such as catholyte volume, electrode substrate, membrane choice, and ionomer type, were also carefully examined to enhance the cell performance. In sharp contrast to prior studies limited to current densities below 20 mA/cm 2 in bicarbonate-based captured CO 2 solutions, this work demonstrates a remarkable current density of 300 mA/cm 2 with an FE to formate comparable to the case with gas-fed CO 2 reduction. Moreover, the process sustained an FE above 50% at a high current density of 500 mA/cm 2 . The DRM-BiNS catalyst exhibited outstanding selectivity, activity, and stability, significantly outperforming oxide-derived bismuth nanosheets (OD-BiNS) in captured CO 2 reduction. Furthermore, these findings offer critical insights into the development of sustainable and scalable CO 2 utilization technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Nanoscopic lipid domains determined by microscopy and neutron scattering

Biological membranes are highly complex supramolecular assemblies, which play central roles in biology. However, their complexity makes them challenging to study their nanoscale structures. To overcome this challenge, model membranes assembled using reduced sets of membrane-associated biomolecules have been found to be both excellent and tractable proxies for biological membranes. Due to their relative simplicity, they have been studied using a range of biophysical characterization techniques. Here, in this review article, we will briefly detail the use of fluorescence and electron microscopies, and X-ray and neutron scattering techniques used over the past few decades to study the nanostructure of biological membranes.

59 BASIC BIOLOGICAL SCIENCES↗