Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “structural features”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Novel ethylenediamine-gallium phosphate containing 6-fold coordinated gallium atoms with unusual four equatorial Ga–N bonds

A novel ethylenediamine-gallium phosphate, formulated as Ga(H{sub 2}NCH{sub 2}CH{sub 2}NH{sub 2}){sub 2}PO{sub 4}·2H{sub 2}O, was synthesized under hydrothermal conditions. The crystal structure, including hydrogen positions, was determined using single-crystal X-ray diffraction data (monoclinic, a=9.4886(3) Å, b=6.0374(2) Å, c=10.2874(3) Å, and β=104.226(3)°, space group Pc) and the bulk was characterized by chemical (Ga–P–C–H–N) and thermal analysis (TG–MS and DSC), including activation energy data of its thermo-oxidative degradation, powder X-ray diffraction (PXRD), solid-state nuclear magnetic resonance (SS-NMR) measurements, and transmission electron microscopy (TEM, SAED/NBD, and STEM BF-EDX). The crystal structure is built up of infinite zig-zag chains running along the c-axis, formed by vertex-shared (PO{sub 4}) and (GaO{sub 2}N{sub 4}) polyhedra. The new compound is characterized by unusual four equatorial Ga–N bonds coming from two nonequivalent ethylenediamine molecules and exhibits strong blue emission at 430 nm (λ{sub ex}=350 nm) in the solid state at room temperature. - Graphical abstract: Single crystals of a new ethylenediamine-gallium phosphate, Ga(H{sub 2}NCH{sub 2}CH{sub 2}NH{sub 2}){sub 2}PO{sub 4}·2H{sub 2}O, were obtained and the structural features presented. This structure is one of the scarce examples of GaPO with Ga–N bonds reported. - Highlights: • A novel ethylenediamine-gallium phosphate was hydrothermally synthesized. • The new compound is characterized by unusual four equatorial Ga–N bonds. • Void-volume analysis shows cages and channels with sizes ideally suited to accommodate small molecules. • The new compound exhibits strong blue emission.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Facile synthesis of interconnected mesoporous ZnMn2O4 nano-peanuts for Li-storage via distinct structure design

Highlights: • Interconnected mesoporous ZnMn{sub 2}O{sub 4} nano-peanuts were successfully synthesized. SS • Novel ZnMn{sub 2}O{sub 4} have three structural features: special mesoporous structure, high specific surface and interconnected walls. • The interconnected mesoporous structure can buffer volume change and avoid particle aggregation. • The ZnMn{sub 2}O{sub 4} nano-peanuts delivered high stable reversible lithium storage properties. - Abstract: The ZnMn{sub 2}O{sub 4} nano-peanuts with diameters of 16–25 nm have been successfully prepared through a simple one-step surfactant-assisted solvothermal process. The as-synthesized ZnMn{sub 2}O{sub 4} exhibits novel interconnected mesoporous hierarchical architecture, which possesses three advantages: special mesoporous structure, high specific surface and interconnected walls. On one hand, the interconnected structure can provide sufficient surface reaction sites to fully contact Li{sup +} with the electrolyte and improve Li{sup +} diffusion and electron transfer; On the other hand, the mesoporous hierarchical networks can buffer the volume change, accommodate or alleviate the strain during charge-discharge process, thus enhancing the conductivity and stability of the electrodes. Benefiting from the mesoporous design, the interconnected ZnMn{sub 2}O{sub 4} delivers a stable capacity (812 mA h g{sup −1} at 100 mA g{sup −1} after 200 cycles), and maintains a high capacity of 516 mA h g{sup −1} even at 2 A g{sup −1} after 200 cycles, which shows that the nanostructured ZnMn{sub 2}O{sub 4} has excellent cycling stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
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 OSTI2023

Structurally Constrained Evolutionary Algorithm for the Discovery and Design of Metastable Phases

Metastable materials are abundant in nature and technology, showcasing remarkable properties that inspire innovative materials design. However, traditional crystal structure prediction methods, which rely solely on energetic factors to determine a structure’s fitness, are not suitable for predicting the vast number of potentially synthesizable phases that represent a local minimum corresponding to a state in thermodynamic equilibrium. Here, we present a new approach for the prediction of metastable phases with specific structural features, and interface this method with the XTALOPT evolutionary algorithm. Our method relies on structural features that include the local crystalline order (e.g., the coordination number or chemical environment), and symmetry (e.g., Bravais lattice and space group) to filter the breeding pool of an evolutionary crystal structure search. The effectiveness of this approach is benchmarked on three known metastable systems: XeN 8 , with a two-dimensional polymeric nitrogen sublattice, brookite TiO 2 , and a high pressure BaH 4 phase that was recently characterized. Additionally, a newly predicted metastable melaminate salt, P1¯WC 3 N 6 , was found to possess an energy that is lower than two phases proposed in a recent computational study. Here, the method presented here could help in identifying the structures of compounds that have already been synthesized, and developing new synthesis targets with desired properties.

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

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗
DOE OSTI2019

Convergent Structures Illuminate Features for Germline Antibody Binding and Pan-Lassa Virus Neutralization

Lassa virus (LASV) causes hemorrhagic fever and is endemic in West Africa. Protective antibody responses primarily target the LASV surface glycoprotein (GPC), and GPC-B competition group antibodies often show potent neutralizing activity in humans. However, which features confer potent and broadly neutralizing antibody responses is unclear. Here, we compared three crystal structures of LASV GPC complexed with GPC-B antibodies of varying neutralization potency. Each GPC-B antibody recognized an overlapping epitope involved in binding of two adjacent GPC monomers and preserved the prefusion trimeric conformation. Differences among GPC-antibody interactions highlighted specific residues that enhance neutralization. Using structure-guided amino acid substitutions, we increased the neutralization potency and breadth of these antibodies to include all major LASV lineages. The ability to define antibody residues that allow potent and broad neutralizing activity, together with findings from analyses of inferred germline precursors, is critical to develop potent therapeutics and for vaccine design and assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

3D-equivariant graph neural networks for protein model quality assessment

Quality assessment (QA) of predicted protein tertiary structure models plays an important role in ranking and using them. With the recent development of deep learning end-to-end protein structure prediction techniques for generating highly confident tertiary structures for most proteins, it is important to explore corresponding QA strategies to evaluate and select the structural models predicted by them since these models have better quality and different properties than the models predicted by traditional tertiary structure prediction methods. We develop EnQA, a novel graph-based 3D-equivariant neural network method that is equivariant to rotation and translation of 3D objects to estimate the accuracy of protein structural models by leveraging the structural features acquired from the state-of-the-art tertiary structure prediction method—AlphaFold2. We train and test the method on both traditional model datasets (e.g. the datasets of the Critical Assessment of Techniques for Protein Structure Prediction) and a new dataset of high-quality structural models predicted only by AlphaFold2 for the proteins whose experimental structures were released recently. Our approach achieves state-of-the-art performance on protein structural models predicted by both traditional protein structure prediction methods and the latest end-to-end deep learning method—AlphaFold2. It performs even better than the model QA scores provided by AlphaFold2 itself. The results illustrate that the 3D-equivariant graph neural network is a promising approach to the evaluation of protein structural models. Integrating AlphaFold2 features with other complementary sequence and structural features is important for improving protein model QA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Data mining for materials design: A computational study of single molecule magnet

We develop a method that combines data mining and first principles calculation to guide the designing of distorted cubane Mn{sup 4+} Mn {sub 3}{sup 3+} single molecule magnets. The essential idea of the method is a process consisting of sparse regressions and cross-validation for analyzing calculated data of the materials. The method allows us to demonstrate that the exchange coupling between Mn{sup 4+} and Mn{sup 3+} ions can be predicted from the electronegativities of constituent ligands and the structural features of the molecule by a linear regression model with high accuracy. The relations between the structural features and magnetic properties of the materials are quantitatively and consistently evaluated and presented by a graph. We also discuss the properties of the materials and guide the material design basing on the obtained results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Atomic structures of fibrillar segments of hIAPP suggest tightly mated β-sheets are important for cytotoxicity

hIAPP fibrils are associated with Type-II Diabetes, but the link of hIAPP structure to islet cell death remains elusive. Here we observe that hIAPP fibrils are cytotoxic to cultured pancreatic β-cells, leading us to determine the structure and cytotoxicity of protein segments composing the amyloid spine of hIAPP. Using the cryoEM method MicroED, we discover that one segment, 19–29 S20G, forms pairs of β-sheets mated by a dry interface that share structural features with and are similarly cytotoxic to full-length hIAPP fibrils. In contrast, a second segment, 15–25 WT, forms non-toxic labile β-sheets. These segments possess different structures and cytotoxic effects, however, both can seed full-length hIAPP, and cause hIAPP to take on the cytotoxic and structural features of that segment. These results suggest that protein segment structures represent polymorphs of their parent protein and that segment 19–29 S20G may serve as a model for the toxic spine of hIAPP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Interpreting Morphological Adaptations Associated with Viviparity in the Tsetse Fly Glossina morsitans (Westwood) by Three-Dimensional Analysis

Tsetse flies (genus Glossina), the sole vectors of African trypanosomiasis, are distinct from most other insects, due to dramatic morphological and physiological adaptations required to support their unique biology. These adaptations are driven by demands associated with obligate hematophagy and viviparous reproduction. Obligate viviparity entails intrauterine larval development and the provision of maternal nutrients for the developing larvae. The reduced reproductive capacity/rate associated with this biology results in increased inter- and intra-sexual competition. Here, we use phase contrast microcomputed tomography (pcMicroCT) to analyze morphological adaptations associated with viviparous biology. These include (1) modifications facilitating abdominal distention required during blood feeding and pregnancy, (2) abdominal and uterine musculature adaptations for gestation and parturition of developed larvae, (3) reduced ovarian structure and capacity, (4) structural features of the male-derived spermatophore optimizing semen/sperm delivery and inhibition of insemination by competing males and (5) structural features of the milk gland facilitating nutrient incorporation and transfer into the uterus. Three-dimensional analysis of these features provides unprecedented opportunities for examination and discovery of internal morphological features not possible with traditional microscopy techniques and provides new opportunities for comparative morphological analyses over time and between species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structure Based Prediction of Neoantigen Immunogenicity

The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8 + T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations

Vision is the dominant sensory modality in many organisms for foraging, predator avoidance, and social behaviors including mate selection. Vertebrate visual perception is initiated when light strikes rod and cone photoreceptors within the neural retina of the eye. Sensitivity to individual colors, i.e., peak spectral sensitivities (λ max ) of visual pigments, are a function of the type of chromophore and the amino acid sequence of the associated opsin protein in the photoreceptors. Large differences in peak spectral sensitivities can result from minor differences in amino acid sequence of cone opsins. To determine how minor sequence differences could result in large spectral shifts we selected a spectrally-diverse group of 14 teleost Rh2 cone opsins for which sequences and λ max are experimentally known. Classical molecular dynamics simulations were carried out after embedding chromophore-associated homology structures within explicit bilayers and water. These simulations revealed structural features of visual pigments, particularly within the chromophore, that contributed to diverged spectral sensitivities. Statistical tests performed on all the observed structural parameters associated with the chromophore revealed that a two-term, first-order regression model was sufficient to accurately predict λ max over a range of 452–528 nm. The approach was accurate, efficient and simple in that site-by-site molecular modifications or complex quantum mechanics models were not required to predict λ max . These studies identify structural features associated with the chromophore that may explain diverged spectral sensitivities, and provide a platform for future, functionally predictive opsin modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Inorganic anion-dependent assembly of zero-, one-, two- and three-dimensional Cu(II)/Ag(I) complexes under the guidance of the HSAB theory: Synthesis, structure, and magnetic property

To systematically explore the influence of inorganic anions on building coordination complexes, five novel complexes based on 1-(benzotriazole-1-methyl)−2-propylimidazole (bpmi), [Cu(bpmi){sub 2}(Ac){sub 2}]·H{sub 2}O (1), [Cu(bpmi){sub 2}(H{sub 2}O){sub 2}]·2NO{sub 3}·2H{sub 2}O (2), [Cu(bpmi)(N{sub 3}){sub 2}] (3), [Ag(bpmi)(NO{sub 3})] (4) and [Cu{sub 3}(bpmi){sub 2}(SCN){sub 4}(DMF)] (5) (Ac{sup −}=CH{sub 3}COO{sup −}, DMF=N,N-Dimethylformamide) are synthesized through rationally introducing Cu(II) salts and Ag(I) salt with different inorganic anions. X-ray single-crystal analyses reveal that these complexes show interesting structural features from mononuclear (1), one-dimensional (2 and 3), two-dimensional (4) to three-dimensional (5) under the influence of inorganic anions with different basicities. The structural variation can be explained by the hard-soft-acid-base (HSAB) theory. Magnetic susceptibility measurement indicates that complex 3 exhibits an antiferromagnetic coupling between adjacent Cu(II) ions. - Graphical abstract: Five new Cu(II)/Ag(I) complexes show interesting structural features from mononuclear, one-dimension, two-dimension to three-dimension under the influence of inorganic anions. The structural variation can be explained by the HSAB theory. - Highlights: • Five inorganic anion-dependent complexes are synthesized. • Structural variation can be explained by the hard-soft-acid-base (HSAB) theory. • The magnetic property of complex has been studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Soft x-ray ptychography studies of nanoscale magnetic and structural correlations in thin SmCo 5 films

High spatial resolution magnetic x-ray spectromicroscopy at x-ray photon energies near the cobalt L 3 resonance was applied to probe an amorphous 50 nm thin SmCo 5 film prepared by off-axis pulsed laser deposition onto an x-ray transparent 200 nm thin Si 3 N 4 membrane. Alternating gradient magnetometry shows a strong in-plane anisotropy and an only weak perpendicular magnetic anisotropy, which is confirmed by magnetic transmission soft x-ray microscopy images showing over a field of view of 10 μm a primarily stripe-like domain pattern but with local labyrinth-like domains. Soft x-ray ptychography in amplitude and phase contrast was used to identify and characterize local magnetic and structural features over a field of view of 1 μm with a spatial resolution of about 10 nm. There, the magnetic labyrinth domain patterns are accompanied by nanoscale structural inclusions that are primarily located in close proximity to the magnetic domain walls. In conclusion, our analysis suggests that these inclusions are nanocrystalline Sm 2 Co 17 phases with nominally in-plane magnetic anisotropy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Comparative SEM and TEM analyses of apatite phases prepared by a multi-sample loading device

Highlights: • A multi-sample loading device which ultrasonically disperses samples was developed. • Comparative EM analyses on various apatite phases were efficiently carried out. • SEM-EDS data revealed distinctive values of O/P and Ca/P intensity ratios. • TEM-SAED data presented characteristic structural features of apatite phases. • Lattice parameters of bone and fossil apatite were affected by CO{sub 3} content. - Abstract: Comparative chemical and structural characterization of various apatite phases from both synthetic and natural sources were carried out by utilizing a multi-sample loading device developed for scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses. The device is capable of spraying nanoparticles via ultrasonication, and four separate samples were loaded on a single TEM grid by a masking tool to characterize different apatite phases in consistent instrumental and analytical conditions. SEM energy dispersive spectroscopy (EDS) analysis of the apatite samples revealed distinctive values of O/P and Ca/P intensity ratios except for the fossil apatite due to its high proportion of externally originating phases. Selected area electron diffraction (SAED) pattern analysis presented the characteristic lattice parameters of the apatite phases, especially the bone and fossil apatite which had CO{sub 3}in their chemistry. Analyzing distinctive chemical and structural features among varied apatite phases can be efficiently carried out through electron microscopy with multiple samples on a single TEM grid, and such methods can be employed for characterizing a wider range of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bergman-type medium range order in amorphous Zr77Rh23 alloy studied by ab initio molecular dynamics simulations

In recent years, some arguments about the existence of medium-range order (MRO) in the Zr-Rh system have been put forward. However, research on the structural features of the Zr-Rh binary alloy at the atomic level is still lacking. This study uses ab initio molecular dynamics simulations to systematically study the local structures of Zr77Rh23 from the liquid to the glassy states. Pair correlation function (PCF), coordination number (CN), Honeycutt–Anderson(HA) index, bond-angle distribution functions, and the Voronoi tessellation method are used to reveal a clear icosahedral-like configuration in the amorphous Zr77Rh23 alloy. It is noteworthy that the splitting in the second peak of the partial PDF implies the existence of a medium range order (MRO) in the Zr77Rh23 system. We obtain the local order in three-dimensional atomic density distributions by using a new atomistic cluster alignment (ACA) method. Interestingly, a Bergman-type MRO is observed in the glassy Zr77Rh23. Furthermore, the spatial distribution and connections of icosahedral-like clusters are shown to further demonstrate the MRO network. Our findings shed light on the nature of atomic local structures of amorphous Zr77Rh23 alloy and have important implications to understanding the formation of various MROs in metallic glasses.

Guo, Y. R.↗