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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Structural stability, electronic structure and mechanical properties of actinide carbides AnC (An = U, Np)

Ab initio calculations are performed to investigate the structural stability, electronic structure and mechanical properties of actinide carbides AnC (An=U, Np) for three different crystal structures, namely NaCl, CsCl and ZnS. Among the considered structures, NaCl structure is found to be the most stable structure for these carbides at normal pressure. A pressure induced structural phase transition from NaCl to ZnS is observed. The electronic structure reveals that these carbides are metals. The calculated elastic constants indicate that these carbides are mechanically stable at normal pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Electronic Structures and Magnetism of Zr-, Th-, and U-based Metal-Organic Frameworks (MOFs) by Density Functional Theory

Metal-organic frameworks (MOFs) have recently gained wide interest as candidate materials for nuclear waste immobilization. While the fundamental thermodynamic properties, such as the substitution energies determine the favorability of radionuclide sequestration by utilization of a MOF matrix, the studies of MOF electronic structure reveal the role of d-, and/or f-electrons on changes in physical properties of actinide-containing materials. We use density functional theory (DFT) calculations to investigate the electronic structures of Zr-, Th-, and U-MOFs, including their electronic band structures and, where appropriate, their magnetic properties. We employ various DFT methods including DFT+U, collinear spin-polarization, spin-orbit coupling, and different flavors of exchange-correlation functionals to assess the robustness to the specific exchange-correlation functional. Unlike the Zr-, and Th-MOFs, the U-MOF is found to be sensitive to electron localization and spin; hence we explore the magnetic structure of the U-MOF in further detail.

Metal-Organic Framework, MOF, Actinides, DFT↗
DOE OSTI2017

Structure Determination of Mycobacterium tuberculosis Serine Protease Hip1 (Rv2224c)

The Mycobacterium tuberculosis (Mtb) serine protease Hip1 (hydrolase important for pathogenesis; Rv2224c) promotes tuberculosis (TB) pathogenesis by impairing host immune responses through proteolysis of a protein substrate, Mtb GroEL2. The cell surface localization of Hip1 and its immunomodulatory functions make Hip1 a good drug target for new adjunctive immune therapies for TB. Here, we report the crystal structure of Hip1 to a resolution of 2.6 Å and the kinetic studies of the enzyme against model substrates and the protein GroEL2. The structure shows a two-domain protein, one of which contains the catalytic residues that are the signature of a serine protease. Surprisingly, a threonine is located within the active site close enough to hydrogen bond with the catalytic residues Asp463 and His490. Mutation of this residue, Thr466, to alanine established its importance for function. Our studies provide insights into the structure of a member of a novel family of proteases. Knowledge of the Hip1 structure will aid in designing inhibitors that could block Hip1 activity

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Atomic Structure of Pt 3 Ni Nanoframe Electrocatalysts by in Situ X-ray Absorption Spectroscopy

Understanding the atomic structure of a catalyst is crucial to exposing the source of its performance characteristics. It is highly unlikely that a catalyst remains the same under reaction conditions when compared to as-synthesized. Hence, the ideal experiment to study the catalyst structure should be performed in situ. Here, we use X-ray absorption spectroscopy (XAS) as an in situ technique to study Pt3Ni nanoframe particles which have been proven to be an excellent electro catalyst for the oxygen reduction reaction (ORR). The surface characteristics of the nanoframes were probed through electrochemical hydrogen underpotential deposition and carbon monoxide electrooxidation, which showed that nanoframe surfaces with different structure exhibit varying levels of binding strength to adsorbate molecules. It is well-known that Pt-skin formation on Pt-Ni catalysts will enhance ORR activity by weakening the binding energy between the surface and adsorbates. Ex situ and in situ XAS results reveal that nanoframes which bind adsorbates more strongly have a rougher Pt surface caused by insufficient segregation of Pt to the surface and consequent Ni dissolution. In contrast, nanoframes which exhibit extremely high ORR activity simultaneously demonstrate more significant segregation of Pt over Ni-rich subsurface layers, allowing better formation of the critical Pt-skin. This work demonstrates that the high ORR activity of the Pt3Ni hollow nanoframes depends on successful formation of the Pt-skin surface structure.

Becknell, Nigel↗
DOE OSTI2016

Ab initio electronic structure of quasi-two-dimensional materials: A “native” Gaussian–plane wave approach

Ab initio electronic structure calculations of two-dimensional layered structures are typically performed using codes that were developed for three-dimensional structures, which are periodic in all three directions. The introduction of a periodicity in the third direction (perpendicular to the layer) is completely artificial and may lead in some cases to spurious results and to difficulties in treating the action of external fields. In this paper we develop a new approach, which is “native” to quasi-2D materials, making use of basis function that are periodic in the plane, but atomic-like in the perpendicular direction. We show how some of the basic tools of ab initio electronic structure theory — density functional theory, GW approximation and Bethe-Salpeter equation — are implemented in the new basis. We argue that the new approach will be preferable to the conventional one in treating the peculiarities of layered materials, including the long range of the unscreened Coulomb interaction in insulators, and the effects of strain, corrugations, and external fields.

Trevisanutto, Paolo E.↗
DOE OSTI2017

Experimental evidence for pressure-induced first order transition in cerium nitride from B1 to B10 structure type

Here, the crystal structure of CeN was investigated up to pressures of 82 GPa, using diamond anvil cell powder X-ray diffraction in two experiments with He and Si-oil as the pressure transmitting media. In contrast to previous reports, we do not observe the B2 (CsCl type) structure at high pressure. Instead, the structural phase transition, starting at 65 GPa, from the ambient rock salt B1 structure results in a distorted CsCl-like B10 structure, irrespective of the pressure medium. Our result unambiguously confirms two recent density functional theory (DFT) studies predicting the B10 phase to be stable at these pressures, rather than the B2 (CsCl type) phase previously reported. The B10 structure appears to approach the B2 structure as pressure is increased further, but DFT calculations indicate that an L1 0 structure (AuCu type) is energetically favored

36 MATERIALS SCIENCE↗
DOE OSTI2017

Modeling adsorption properties of structurally deformed metal–organic frameworks using structure–property map

Structural deformation and collapse in metal-organic frameworks (MOFs) can lead to loss of long-range order, making it a challenge to model these amorphous materials using conventional computational methods. In this work, we show that a structure–property map consisting of simulated data for crystalline MOFs can be used to indirectly obtain adsorption properties of structurally deformed MOFs. The structure–property map (with dimensions such as Henry coefficient, heat of adsorption, and pore volume) was constructed using a large data set of over 12000 crystalline MOFs from molecular simulations. By mapping the experimental data points of deformed SNU-200, MOF-5, and Ni-MOF-74 onto this structure–property map, we show that the experimentally deformed MOFs share similar adsorption properties with their nearest neighbor crystalline structures. Furthermore, once the nearest neighbor crystalline MOFs for a deformed MOF are selected from a structure–property map at a specific condition, then the adsorption properties of these MOFs can be successfully transformed onto the degraded MOFs, leading to a new way to obtain properties of materials whose structural information is lost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems

Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.

Algorithms↗
DOE OSTI2023

RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins

Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data.

3D visualization↗
DOE OSTI2018

A Two-Fold Structural Classification Method for Determining the Accurate Ensemble of Protein Structures

Atomic-level structural characterization of flexible proteins, such as intrinsically disordered proteins and multi-domain proteins connected by flexible linkers, is challenging as they possess distinct conformations in physiological conditions. Significant efforts have been made to develop integrated approaches by combining small angle neutron/X-ray scattering experiments with molecular simulations to reveal the distinct atomic structures and the corresponding populations for these flexible proteins. One widely used method, the basis-set supported ensemble method, classifies the simulation-generated protein conformations into a set of structural basis and then derives the corresponding populations by fitting to the experimental data. This method makes an implicit assumption that protein conformations of similar structures have similar small angle scattering profiles.The present work demonstrates that, for various protein systems ranging from compact globular proteins and flexible multidomain proteins through to intrinsically disordered proteins, this method provides inaccurate assessment of the structural ensemble of the protein molecules due to the breakdown of the assumption made. To alleviate this problem, a two-fold-clustering method is developed to cluster the simulation-generated protein structures using information on both 3D structure and scattering profiles. As benchmarked by both simulation and experimental results, this new method yields much more accurate populations of structural basis of protein molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A quantitative study of the structure-activity relationship in hierarchical zeolites using liquid-phase reactions

Micro/meso/macroporous (hierarchical) zeolites show remarkable catalytic performance for reactions involving bulky reactants. However, quantitative assessment of the microstructural characteristics contributing to the observed performance remains elusive. Here, structure–activity relationships are established for a set of micro/mesoporous self-pillared pentasil (SPP) zeolites using two parallel liquid-phase reactions (benzyl alcohol alkylation and self-etherification) based on analysis of mass transport and reaction kinetics. A reaction–diffusion mathematical model is developed that quantitatively assigns the catalytic contributions of the external surface and micropores of SPP zeolites for these reactions. In addition, the effect of the zeolite external surface structure on the corresponding catalytic activity is quantitatively assessed by comparing SPP zeolites (with MFI structure) with MCM-22 (with MWW structure). This work demonstrates that reaction–diffusion modeling allows quantitative description of the catalytic performance of hierarchical zeolites and provides a model reaction to assess nm-sized characteristic diffusion lengths in MFI.

bio-inspired↗
DOE OSTI2021

Global Optimization of Chemical Cluster Structures: Methods, Applications, and Challenges

Chemical clusters are relevant to many applications in catalysis, separations, materials, and energy sciences. Experimentally, the structure of clusters is difficult to determine, but it is very important in understanding their chemistry and properties. Computational methods can be used to examine cluster structure, however finding the most stable structure is not simple, particularly as the cluster size increases. Global optimization techniques have long been used to tackle the problem of the most stable structure, but such approaches would have to look for a global minimum, while sampling local minima over the whole potential energy surface as well. In this review, the state-of-the-art theory of global optimization theory is summarized. First, the definition, significance, relation to experiments, and a brief history of global optimization is presented. We then discuss, in more detail, three versatile global optimization methods: the basin hopping, the artificial bee colony algorithm, and the genetic algorithm. We close with some representative application examples of global optimization of clusters since 2016 and the challenges, open questions and opportunities in this field.

Global optimization, Chemical clusters, Artificial↗
DOE OSTI2016

Application of micro X-ray diffraction to investigate the reaction products formed by the alkali–silica reaction in concrete structures

Alkali–silica reaction (ASR) is one of the most important deterioration mechanisms in concrete leading to substantial damages of structures worldwide. Synchrotron-based micro-X-ray diffraction (micro-XRD) was employed to characterize the mineral phases formed in micro-cracks of concrete aggregates as a consequence of ASR. This high spatial resolution technique enables to directly gain structural information on ASR products formed in a 40-year old motorway bridge damaged due to ASR. Micro-X-ray-fluorescence was applied on thin sections to locate the reaction products formed in veins within concrete aggregates. Micro-XRD pattern were collected at selected points of interest along a vein by rotating the sample. Rietveld refinement determined the structure of the ASR product consisting of a new layered framework similar to mountainite and rhodesite. It is conceivable that understanding the structure of the ASR product may help developing new technical treatments inhibiting ASR.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Monte Carlo Simulation of Borosilicate Glass Dissolution using Molecular Dynamics-Generated Glass Structures

Atomic-scale insights into the dissolution mechanisms of borosilicate glasses are critical to the development of the waste form corrosion models that inform performance assessments of nuclear waste disposal facilities. Monte Carlo (MC) simulations have been instrumental in advancing the state of knowledge of borosilicate glass dissolution; however, all such simulations to date have relied on lattices to represent the amorphous glass structure, thereby potentially introducing artifacts. Therefore, a new approach, referred to as the amorphous MC approach, has been developed whereby glass structures generated from molecular dynamics simulations are used as starting points for MC simulations of glass dissolution. MC simulations of sodium borosilicate glasses that covered a wide compositional range were performed and revealed correlations between dissolution rate and structural features of the glasses. Notably, the lattice MC approach predicted the fraction of tetrahedral boron to have a lesser influence on the dissolution rate than computed with the amorphous MC approach. The lattice MC simulations also overestimated the dissolution rate for a given glass composition. These findings highlight the importance of using truly amorphous structures in MC simulations of glass corrosion.

Kerisit, Sebastien N.↗
DOE OSTI2016

Competing Pathways for Nucleation of the Double Perovskite Structure in the Epitaxial Synthesis of La 2 MnNiO 6

Over the past decades a confluence of advanced synthesis techniques, data-driven characterization, and rapid increases in computing power has sparked a renaissance in materials engineering. The emerging “materials-by-design” approach, while radically transforming the development of multicomponent systems, has tended to overlook the complex kinetic pathways that define materials synthesis. Although we are able to envision almost limitless materials combinations, we are unable to synthesize all of them in practice, since existing characterization and modeling approaches often fail to capture the inherent complexity of such systems. There is currently a disconnect between highly local structural characterization and macroscale properties measurements, resulting in oversimplified or incomplete structure-property models. Here we describe a multi-technique approach that combines aberration-corrected transmission electron microscopy with emerging oxide atom probe tomography to measure chemical ordering and extended defects in the model complex oxide, La2MnNiO6. We visualize cation ordering, as well as a three-dimensional network of secondary phases, which we describe in terms of ab initio structure calculations. We propose a defect model in which these phases alter their surrounding octahedral environment, severely disrupting cation superexchange. Through this array of experimental and theoretical techniques, we uncover fundamental structure-property relationships and illustrate a new approach to engineer complex, multicomponent systems.

atom probe tomography↗