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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Lateral Water Structure Connects Metal Oxide Nanoparticle Faces

When a metal oxide surface is immersed in aqueous solution, it has the ability to bind, orient, and order interfacial water, affecting both chemical and physical interactions with the surface. Structured interfacial water thus possesses time-averaged, spatially varying polarization charge and potential that are comparable to those arising due to ion accumulation. It is well established that interfacial water structure propagates from the surface into bulk solution. Here, we show that interfacial water structure also propagates laterally, with important consequences. The constant pH molecular dynamics was used to impose a pH difference between opposite faces of a model goethite (a-FeOOH) nanoparticle and quantify water polarization charge on intervening faces. We find that the structure of water on one face is strongly affected by the structure on nearby surfaces, revealing the importance of long-range lateral hydrogen bonding networks with implications for particle aggregation, oriented attachment, and processes such as dissolution and growth.

Zarzycki, Piotr P.↗
DOE OSTI2018

The crystal structure of P450-TT heme-domain provides the first structural insights into the versatile class VII P450s

Highlights: • The crystal structure of CYP116B45 (P450-TT) from T. thermophilus has been solved. • P450-TT crystal structure is the first example of a class VII P450 structure. • P450-TT adopts the typical P450-fold. • Structural deviation of regions involved in substrate recognition is observed. • Analysis of 96 class VII sequences revealed conservation of active site residues. The first crystal structure of a class VII P450, CYP116B46 from Tepidiphilus thermophilus, has been solved at 1.9 Å resolution. The structure reveals overall conservation of the P450-fold and a water conduit around the I-helix. Active site residues have been identified and sequence comparisons have been made with other class VII enzymes. A structure similarity search demonstrated that the P450-TT structure is similar to enzymes capable of oxy-functionalization of fatty acids, terpenes, macrolides, steroids and statins. The insight gained from solving this structure will provide a guideline for future engineering and modelling studies on this catalytically promiscuous class of enzymes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

A comparative study on the oxidation of two-dimensional Ti 3 C 2 MXene structures in different environments

The oxidation of two-dimensional Ti 3 C 2 MXene structures has been recognized as a promising method for the formation of hybrid structures of carbon supported nanotitania. Here, we studied the oxidation of Ti 3 C 2 MXene structures using reactive force field (ReaxFF) based molecular dynamics simulations. To investigate the effect of oxidizing agent, we used three different environments including dry air (oxygen molecules), wet air (oxygen and water molecules) and hydrogen peroxide (H 2 O 2 molecules). Oxidation simulations were performed at different temperatures of 1000, 1500, 2000, 2500 and 3000 K. We found that by controlling the temperature, carbon supported titania can be formed by diffusion of Ti atoms to the surface of MXene structures during the oxidation. These results were confirmed by the increase in the average bond orders of C–C and Ti–O and decrease in the average bond orders of Ti–C. Moreover, it was revealed that by increasing the temperature, the oxidation rate increases, and the rate depends on the oxidant according to the following order: H 2 O 2 > wet air > dry air. This was validated by heating the MXene in wet air and dry air followed by examining the products using X-ray diffraction and Raman spectroscopy. To investigate the effect of the presence of the oxidant, the MXene structure was also heated under vacuum, and it was found that in this case the MXene structure was converted to cubic TiC. Furthermore, it was indicated that during the heating process of the MXene structure in a vacuum, the average bond orders for C–C, Ti–C and Ti–O do not change significantly due to the lack of oxidants in the environment, leaving room for only topotactic transformation of atoms during the heating. In conclusion, the formation of the TiC structure by heating the MXene in an inert environment was confirmed experimentally as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

R -Nb 2 O 5 has an ‘idealized’ V 2 O 5 structure and Wadsley–Roth-like structural stability during Li-ion battery cycling

The adoption of batteries across diverse applications requires electrode materials with a wider range of performance metrics, such as cost, safety, and material availability. Along the path to discovering new commercially viable materials, a fundamental understanding of chemical and atomic structure features that provide structural stability and effective ion transport is essential. In support of new understanding, we report the cycling behavior of metastable R-Nb 2 O 5 . R-Nb 2 O 5 adopts an ‘idealized’ V 2 O 5 structure, in which [NbO 6 ] octahedra alternate in edge- and corner-sharing resulting in ReO 3 -like slabs, whereas Wadsley–Roth materials have ReO 3 -like blocks, linked through edge-sharing octahedra at intersecting crystallographic shear planes. We find that this slab structure is stable during cycling, with minor atomic structure changes and cycling curves that are symmetric on discharge and charge, resembling the behavior of Wadsley–Roth materials more than other related materials, such as ReO 3 , V 2 O 5 , or Nb 3 O 7 F. Based on our findings, R-Nb 2 O 5 can serve as a ‘structural bridge’ between Wadsley–Roth block structures and V 2 O 5 , through which we can relate inter- and intra-polyhedral structures to cycling behavior and structural stability during cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Crystal structure of an atypical cobalamin riboswitch reveals RNA structural adaptability as basis for promiscuous ligand binding

Cobalamin riboswitches encompass a structurally diverse group of cis-acting, gene regulatory elements found mostly in bacterial messenger RNA and are classified into subtypes based on secondary and tertiary characteristics. An unusual variant of the cobalamin riboswitch with predicted structural features was identified in Bacillus subtilis over a decade ago, but its structure and mechanisms of cobalamin selectivity and translational control have remained unsolved. We present the crystal structure of the aptamer domain of this atypical cobalamin riboswitch and a model for the complete riboswitch, including its expression platform domain. We demonstrate that this riboswitch binds to multiple cobalamin derivatives and correlate its promiscuous behavior to its structure and unique arrangement of peripheral elements. Comparative structural analyses between conventional cobalamin riboswitches and the B. subtilis cobalamin riboswitch reveal that the likely basis for this promiscuous ligand binding is intrinsic structural adaptability encoded in the RNA structure. It suggests that cobalamin selectivity might ultimately be viewed as existing on a spectrum of affinity for each derivative rather than as belonging to distinct types based on ligand specificities. Our work provides an interesting and notable example of functional coupling of ligand-sensing and adaptive folding by a structured RNA molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Click-chemistry compatible structures, click-chemistry functionalized structures, and materials and methods for making the same

According to various embodiments, systems, methods, and computer program products for click-chemistry compatible structures, additive manufacturing resins for forming the same, and method of formation of such structures and resins, as well as techniques for functionalizing click-chemistry compatible structures are disclosed. The inventive structures generally include a plurality of photo polymerized molecules structurally arranged according to a three-dimensional pattern, while surfaces of the structure are functionalized with one or more click-chemistry compatible molecules each having one or more click-chemistry compatible functional groups. The structures may be formed from single- or dual-component resins, each having unique synthetic pathways. The resulting structures may be functionalized for utility in a wide range of applications by leveraging click chemistry to further functionalize the structure with organic additives also compatible with click-chemistry reaction schemes.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Structures of single-layer {beta}-sheet proteins evolved from {beta}-hairpin repeats

Free-standing single-layer beta-sheets are extremely rare in naturally occurring proteins, even though beta-sheet motifs are ubiquitous. Here we report the crystal structures of three homologous, single-layer, anti-parallel beta-sheet proteins, comprised of three or four twisted beta-hairpin repeats. The structures reveal that, in addition to the hydrogen bond network characteristic of beta-sheets, additional hydrophobic interactions mediated by small clusters of residues adjacent to the turns likely play a significant role in the structural stability and compensate for the lack of a compact hydrophobic core. These structures enabled identification of a family of secreted proteins that are broadly distributed in bacteria from the human gut microbiome and are putatively involved in the metabolism of complex carbohydrates. A conserved surface patch, rich in solvent-exposed tyrosine residues, was identified on the concave surface of the beta-sheet. These new modular single-layer beta-sheet proteins may serve as a new model system for studying folding and design of beta-rich proteins.

beta-hairpin repeats↗
DOE OSTI2022

Electron Tomography and Machine Learning for Understanding the Highly Ordered Structure of Leafhopper Brochosomes

Insects known as leafhoppers (Hemiptera: Cicadellidae) produce hierarchically structured nanoparticles known as brochosomes that are exuded and applied to the insect cuticle, thereby providing camouflage and anti-wetting properties to aid insect survival. Although the physical properties of brochosomes are thought to depend on the leafhopper species, the structure–function relationships governing brochosome behavior are not fully understood. Brochosomes have complex hierarchical structures and morphological heterogeneity across species, due to which a multimodal characterization approach is required to effectively elucidate their nanoscale structure and properties. In this work, we study the structural and mechanical properties of brochosomes using a combination of atomic force microscopy (AFM), electron microscopy (EM), electron tomography, and machine learning (ML)-based quantification of large and complex scanning electron microscopy (SEM) image data sets. This suite of techniques allows for the characterization of internal and external brochosome structures, and ML-based image analysis methods of large data sets reveal correlations in the structure across several leafhopper species. Our results show that brochosomes are relatively rigid hollow spheres with characteristic dimensions and morphologies that depend on leafhopper species. Nanomechanical mapping AFM is used to determine a characteristic compression modulus for brochosomes on the order of 1–3 GPa, which is consistent with crystalline proteins. Altogether, this work provides an improved understanding of the structural and mechanical properties of leafhopper brochosomes using a new set of ML-based image classification tools that can be broadly applied to nanostructured biological materials.

Chemical structure↗
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 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↗