Structural Consequences of Cutting a Binding Loop: Two Circularly Permuted Variants of Streptavidin
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CHEM↗
SEARCH · Engineering Papers
Results for “structural complexity”
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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Time-dependent local and average structural evolution of δ-phase 239 Pu-Ga alloys
Here, plutonium metal is a very unusual element, exhibiting six allotropes at ambient pressure, between room temperature and its melting point, a complicated phase diagram, and a complex electronic structure. Many phases of plutonium metal are unstable with changes in temperature, pressure, chemical additions, or time. This strongly affects structure and properties, and becomes of high importance, particularly when considering effects on structural integrity over long periods of time [1]. This paper presents a time-dependent neutron total scattering study of the local and average structure of naturally aging δ-phase 239 Pu-Ga alloys, together with preliminary results on neutron tomography characterization.
36 MATERIALS SCIENCE↗
Topological Data Analysis for Particulate Gels
Soft gels, formed via the self-assembly of particulate materials, exhibit intricate multiscale structures that provide them with flexibility and resilience when subjected to external stresses. Here, this work combines particle simulations and topological data analysis (TDA) to characterize the complex multiscale structure of soft gels. Our TDA analysis focuses on the use of the Euler characteristic, which is an interpretable and computationally scalable topological descriptor that is combined with filtration operations to obtain information on the geometric (local) and topological (global) structure of soft gels. We reduce the topological information obtained with TDA using principal component analysis (PCA) and show that this provides an informative low-dimensional representation of the gel structure. We use the proposed computational framework to investigate the influence of gel preparation (e.g., quench rate, volume fraction) on soft gel structure and to explore dynamic deformations that emerge under oscillatory shear in various response regimes (linear, nonlinear, and flow). Our analysis provides evidence of the existence of hierarchical structures in soft gels, which are not easily identifiable otherwise. Moreover, our analysis reveals direct correlations between topological changes of the gel structure under deformation and mechanical phenomena distinctive of gel materials, such as stiffening and yielding. In summary, we show that TDA facilitates the mathematical representation, quantification, and analysis of soft gel structures, extending traditional network analysis methods to capture both local and global organization.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Basic Research of Intrinsic Tamper indication Markings and Patterns defined by Pulsed Laser Irradiation
With our previous research, it was found that surface asperities or roughness must be present to create periodic surface structures upon laser exposure. In particular, an initial rough surface morphology (such as that found with a machined surface) provides multiple sites for light scattering, which underlies the formation of periodic ripple morphologies. Light scattering from a random surface creates patterns of periodic structures (with complex orientations) that could be used as intrinsic markings for tagging materials and equipment. Despite these initial findings, the fundamental mechanisms that give rise to periodic surface structures and their characteristic shapes were not identified in prior research.
36 MATERIALS SCIENCE↗
Mapping 3D grain and precipitate structure during in situ mechanical testing of open-cell metal foam using micro-computed tomography and high-energy X-ray diffraction microscopy
Open-cell metal foams are ultra-low-density cellular metals with complex hierarchical structures that span bulk, cell, ligament, and sub-ligament scales and give rise to desirable properties such as high strength-to-weight ratio and excellent energy absorption. Although literature suggests that intrinsic material structures at sub-ligament length scales (e.g., grains and precipitates) play an important role in mechanical behavior of open-cell metal foams, there are very few experimental measurements of such structures in three dimensions and for meaningful volumes of foam. This study seeks to map and track the three-dimensional (3D) grain and precipitate structures of an intact volume of open-cell aluminum foam by advancing microstructural characterization techniques that leverage X-ray micro-computed tomography (μCT) and far-field high-energy X-ray diffraction microscopy (FF-HEDM). A 6%-relative-density aluminum foam sample was mechanically tested in compression while μCT and FF-HEDM measurements were collected at interrupted loading states at beamline 1-ID of the Advanced Photon Source. Further, a new scanning strategy and reconstruction algorithm were established to enable characterization of a foam volume with diameter approximately four times wider than the nominal width of the X-ray beam. The result is a set of maps that detail both the 3D grain and precipitate structures throughout the foam volume at successive strain steps. A novel grain tracking procedure was developed to track individual grains within the foam volume by accounting for the large rigid-body motions that individual ligaments can undergo during mechanical loading. The ability to track grains and precipitate structures in three dimensions throughout large bulk deformation of ultra-low-density polycrystalline materials enables new possibilities for validating numerical models and investigating local failure mechanisms. Furthermore, the methods and procedures developed in this study could be applied to other ultra-low-density structures, such as additively manufactured lattices.
36 MATERIALS SCIENCE↗
Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning
Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.
Naghshnejad, Pegah [Department of Chemical Enginee↗
Spin state solvomorphism in a series of rare S = 1 manganese(III) complexes
We present that structural, magnetic and spectroscopic data of four complex salts, [Mn(napsal 2 323)]NTf 2 , 1 ,[Mn(napsal 2 323)]ClO 4 , 2 , [Mn(napsal 2 323)]BF 4 , 3 and [Mn(napsal 2 323)]NO 3 , 4 , of the [Mn(napsal 2 323)] + complex cation indicate that the Mn 3+ ion is stabilized in the rare S = 1 spin triplet form in this ligand sphere. Zero-field splitting values of D = +19.6 cm -1 and | E | = 2.02 cm -1 for complex 1 were obtained by High Field Electron Paramagnetic Resonance (HFEPR) measurements conducted over a range of frequencies. Structural and magnetic data also indicate that co-crystallization of complexes 2 and 3 with 0.5 equivalents of ethanol yields the high spin S = 2 forms of the perchlorate and tetrafluoroborate solvates [Mn(napsal 2 323)]ClO 4 ·0.5(C 2 H 5 OH), 2·0.5EtOH and [Mn(napsal 2 323)]BF 4 ·0.5(C 2 H 5 OH), 3·0.5EtOH .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach
Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel meta-algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local space-time dependencies to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. For causal discovery, CaStLe flexibly accepts any appropriately adapted time series causal discovery algorithm to recover local causal structures. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. Regularities in local space-time dependencies are transformed into informative spatial replicates, which actually improve CaStLe's performance when applied to ever-larger spatial grids. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We provide validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of geophysics-inspired benchmarks while identifying the method's limitations and domains where its assumptions may not hold.
Nichol, J. Jake [Univ. of New Mexico, Albuquerque,↗
The benefits of using time-frequency analysis with synthetic aperture focusing technique
Improvements in detection and resolution are always desired and needed. There are various instruments available for the inspection of concrete structures that can be used with confidence for detecting different defects. However, more often than not that confidence is heavily dependent on the experience of the operator rather than the clear, objective discernibility of the output of the instrument. The challenge of objective discernment is amplified when the concrete structures contain multiple layers of reinforcement, are of significant thickness, or both, such as concrete structures in nuclear power plants. We seek to improve and extend the usefulness of results produced using the synthetic aperture focusing technique (SAFT) on data collected from thick, complex concrete structures. A secondary goal is to improve existing SAFT results, with regards to repeatedly and objectively identifying defects and/or internal structure of concrete structures. Towards these goals, we are applying the time-frequency technique of wavelet packet decomposition and reconstruction using a mother wavelet that possesses the exact reconstruction property. However, instead of analyzing the coefficients of each decomposition node, we select and reconstruct specific nodes based on the frequency band it contains to produce a frequency band specific time-series representation. SAFT is then applied to these frequency specific reconstructions allowing SAFT to be used to visualize the reflectivity of a frequency band and that band's interaction with the contents of the concrete structure. We apply our technique to data sets collected using a commercial, ultrasonic linear array (MIRA) from two 1.5m × 2m × 25cm concrete test specimens. One specimen contains multiple layers of rebar. The other contains honeycomb, crack, and rebar bonding defect analogs. This approach opens up a multitude of possibilities for improved detection, readability, and overall improved objectivity. We will focus on improved defect/reinforcement isolation in thick and multilayered reinforcement environments. Additionally, the ability to empirically explore the possibility of a frequency-band-defect-type relationship or sensitivity becomes available.
36 MATERIALS SCIENCE↗
Glucan Binding Protein C of Streptococcus mutans Mediates both Sucrose-Independent and Sucrose-Dependent Adherence
The high-resolution structure of glucan binding protein C (GbpC) at 1.14 Å, a sucrose-dependent virulence factor of the dental caries pathogen Streptococcus mutans , has been determined. GbpC shares not only structural similarities with the V regions of AgI/II and SspB but also functional adherence to salivary agglutinin (SAG) and its scavenger receptor cysteine-rich domains (SRCRs). This is not only a newly identified function for GbpC but also an additional fail-safe binding mechanism for S. mutans . Despite the structural similarities with S. mutans antigen I/II (AgI/II) and SspB of Streptococcus gordonii , GbpC remains unique among these surface proteins in its propensity to adhere to dextran/glucans. The complex crystal structure of GbpC with dextrose (β- d -glucose; Protein Data Bank ligand BGC) highlights exclusive structural features that facilitate this interaction with dextran. Targeted deletion mutant studies on GbpC's divergent loop region in the vicinity of a highly conserved calcium binding site confirm its role in biofilm formation. Finally, we present a model for adherence to dextran. The structure of GbpC highlights how artfully microbes have engineered the lectin-like folds to broaden their functional adherence repertoire.
Mieher, Joshua L.↗
The Benefits of Using Time-Frequency Analysis with Synthetic Aperture Focusing Technique
Improvements in detection and resolution are always desired and needed. There are various instruments available for the inspection of concrete structures that can be used with confidence for detecting different defects. However, more often than not that confidence is heavily dependent on the experience of the operator rather than the clear, objective discernibility of the output of the instrument. The challenge of objective discernment is amplified when the concrete structures contain multiple layers of reinforcement, are of significant thickness, or both, such as concrete structures in nuclear power plants. We seek to improve and extend the usefulness of results produced using the synthetic aperture focusing technique (SAFT) on data collected from thick, complex concrete structures. A secondary goal is to improve existing SAFT results, with regards to repeatedly and objectively identifying defects and/or internal structure of concrete structures. Towards these goals, we are applying the time-frequency technique of wavelet packet decomposition and reconstruction using a mother wavelet that possesses the exact reconstruction property. However, instead of analyzing the coefficients of each decomposition node, we select and reconstruct specific nodes based on the frequency band it contains to produce a frequency band specific time-series representation. SAFT is then applied to these frequency specific reconstructions allowing SAFT to be used to visualize the reflectivity of a frequency band and that band s interaction with the contents of the concrete structure. We apply our technique to data sets collected using a commercial, ultrasonic linear array (MIRA) from two 1.5m x 2m x 25cm concrete test specimens. One specimen contains multiple layers of rebar. The other contains honeycomb, crack, and rebar bonding defect analogs. This approach opens up a multitude of possibilities for improved detection, readability, and overall improved objectivity. We will focus on improved defect/reinforcement isolation in thick and multilayered reinforcement environments. Additionally, the ability to empirically explore the possibility of a frequency-band-defect-type relationship or sensitivity becomes available.
concrete NDE↗
Linking morphology with activity through the lifetime of pretreated PtNi nanostructured thin film catalysts
In this study, the nanoscale morphology of highly active Pt 3 Ni 7 nanostructured thin film fuel cell catalysts is linked with catalyst surface area and activity following catalyst pretreatments, conditioning and potential cycling. The significant role of fuel cell conditioning on the structure and composition of these extended surface catalysts is demonstrated by high resolution imaging, elemental mapping and tomography. The dissolution of Ni during fuel cell conditioning leads to highly complex, porous structures which were visualized in 3D by electron tomography. Quantification of the rendered surfaces following catalyst pretreatment, conditioning, and cycling shows the important role pore structure plays in surface area, activity, and durability.
30 DIRECT ENERGY CONVERSION↗
Structural Characterization of Native Proteins and Protein Complexes by Electron Ionization Dissociation-Mass Spectrometry
Mass spectrometry (MS) has played an increasingly important role in the identification and structural and functional characterization of proteins. In particular, the use of tandem mass spectrometry has afforded one of the most versatile methods to acquire structural information for proteins and protein complexes. The unique nature of electron capture dissociation (ECD) for cleaving protein backbone bonds while preserving non-covalent interactions has made it especially suitable for the study of native protein structures. However, the intra- and inter-molecular interactions stabilized by hydrogen bonds and salt bridges can hinder the separation of fragments even with pre-activation, which has become particularly problematic for the study of large macromolecular proteins and protein complexes. Here, we describe the capabilities of another activation method, 30 eV electron ionization dissociation (EID), for the top-down MS characterization of native protein-ligand and protein-protein complexes. Rich structural information that cannot be delivered by ECD can be generated by EID. EID allowed for the comparison of the gas-phase and the solution-phase structural stability and unfolding process of human carbonic anhydrase I (HCA-I). In addition, the EID fragmentation patterns reflect the structural similarities and differences among apo-, Zn-, and Cu,Zn-superoxide dismutase (SOD1) dimers. In particular, the structural changes due to Cu-binding and a point mutation (G41D) were revealed by EID-MS. The performance of EID was also compared to that of 193 nm ultraviolet photodissociation (UVPD), which allowed us to explore their qualitative similarities and differences as potential valuable tools for the MS study of native proteins and protein complexes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Characterizing vertical upper ocean temperature structures in the European Arctic through unsupervised machine learning
In-situ observations of subsurface ocean temperatures are, in many regions, inconsistently distributed in time and space. These spatio-temporal inconsistencies in the observational network lead to difficulties in utilizing those observations effectively for ocean model evaluation or understanding larger-scale ocean characteristics. Model accuracy of subsurface ocean characteristics is especially important within regions that contain complex ocean structures. One such region is the European Arctic which not only contains several types of water masses with unique characteristics, but also wintertime sea ice coverage and complex bathymetry. This study presents an unsupervised neural networking technique that can be used in combination with traditional ocean model evaluation techniques to provide additional information on the accuracy of modeled vertical ocean temperature profiles. Self-organizing maps is an unsupervised machine learning technique that we apply to approximately twenty thousand Argo and CTD temperature profiles from 2012 to 2020 in the European Arctic to categorize the observed vertical ocean temperature structures in the top 150 m. The observed ocean profile categories, or neurons, defined by the self-organizing map show strong spatial and temporal dependencies. We then use the neuron weights, or the learned temperature profile structure of each neuron, to validate the spatial and temporal variability of modeled vertical temperature structures. This analysis gives us new insights about the model’s capabilities to reproduce specific vertical structures of the top-most ocean layer within different regions and seasons. Mapping modeled ocean temperature profiles onto the neuron-space of the observationally-defined self organized map highlights the potential of this method to advance our understanding of model deficiencies in that region.
54 ENVIRONMENTAL SCIENCES↗
Mixed cerium-platinum oxides: Electronic structure of [CeO]Pt{sub n} (n = 1, 2) and [CeO{sub 2}]Pt complex anions and neutrals
The electronic structures of several small Ce–Pt oxide complexes were explored using a combination of anion photoelectron (PE) spectroscopy and density functional theory calculations. Pt and Pt{sub 2} both accept electron density from CeO diatomic molecules, in which the cerium atom is in a lower-than-bulk oxidation state (+2 versus bulk +4). Neutral [CeO]Pt and [CeO]Pt{sub 2} complexes are therefore ionic, with electronic structures described qualitatively as [CeO{sup +2}]Pt{sup −2} and [CeO{sup +}]Pt{sub 2}{sup −}, respectively. The associated anions are described qualitatively as [CeO{sup +}]Pt{sup −2} and [CeO{sup +}]Pt{sub 2}{sup −2}, respectively. In both neutrals and anions, the most stable molecular structures determined by calculations feature a distinct CeO moiety, with the positively charged Ce center pointing toward the electron rich Pt or Pt{sub 2} moiety. Spectral simulations based on calculated spectroscopic parameters are in fair agreement with the spectra, validating the computationally determined structures. In contrast, when Pt is coupled with CeO{sub 2}, which has no Ce-localized electrons that can readily be donated to Pt, the anion is described as [CeO{sub 2}]Pt{sup −}. The molecular structure predicted computationally suggests that it is governed by charge-dipole interactions. The neutral [CeO{sub 2}]Pt complex lacks charge-dipole stabilizing interactions, and is predicted to be structurally very different from the anion, featuring a single Pt–O–Ce bridge bond. The PE spectra of several of the complexes exhibit evidence of photodissociation with Pt{sup −} daughter ion formation. The electronic structures of these complexes are related to local interactions in Pt-ceria catalyst-support systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Molecular Dynamics Simulation on the Effect of MgO/Al{sub 2}O{sub 3} Ratio on Structure and Properties of Blast Furnace Slag Under Different Basicity Conditions
The SiO{sub 2}-Al{sub 2}O{sub 3}-CaO-MgO is the basic structural system of blast furnace slag and the composition directly affects the performance of the slag. Molecular dynamics simulations were carried out to analyze the local structure, structural unit, bond angle, transport properties, and enthalpy of the slag with the increase of MgO/Al{sub 2}O{sub 3} mass ratio under different basicity conditions. It was found that the change of MgO/Al{sub 2}O{sub 3} ratio does not affect the short-range order structure, but it will reduce the overall stability of the network structure. Through the analysis of the structural unit of the slag, it was found that the polymerization degree of the system decreases with the increase of MgO/Al{sub 2}O{sub 3} ratio, indicating that the complex network structure of the system is partially depolymerized. Besides, the self-diffusion coefficients of each ion were concluded and the magnitudes were observed to be in the following order: Mg{sup 2+}>Ca{sup 2+}>Al{sup 3+}>O{sup 2-}>Si{sup 4+}. The diffusivity of the slag increases with the increase of MgO/Al{sub 2}O{sub 3} ratio and the corresponding viscosity decreases. And the enthalpy of the slag is increased with the increase of MgO/Al{sub 2}O{sub 3} ratio or basicity, therefore the fuel consumption should also be properly adjusted during the operation of blast furnace to ensure the target temperature.
36 MATERIALS SCIENCE↗
Controlling Extraction of Rare Earth Elements Using Functionalized Aryl-vinyl Phosphonic Acid Esters
Ligands that can discriminate between individual rare earth elements are important for production of these critical elements. A set of aryl-vinyl phosphonic acid ligands for extracting rare earth elements were designed and synthesized under the hypothesis that the strength of the rare earth-ligand interactions could be tuned by changing the dipole moment of the ligand. The ligands were synthesized via a two-step reaction procedure using a Heck coupling reaction to functionalize vinyl phosphonic acid, followed by Steglich esterification to obtain high-purity styryl phosphonic acid monoesters with varying dipole moments along the P-C bond. The metal binding strength and composition of the rare earth complexes formed with these styryl phosphonic acid monoesters were experimentally studied by liquid-liquid extraction techniques, while DFT calculations were performed to determine the dipole moments of the free and complexed ligands and the electronic structure of the complexes formed. All three prepared ligands were much stronger extracting agents for europium(III) than the dialkylphosphonic acids usually used for this separation. However, the order of increasing extraction strength was found to match the order of the decreasing calculated dipole moment along the P-C bond of the three styryl-based ligands, rather than correlating with increasing ligand basicity, as reflected by the pK a of the ligands. Finally, these findings suggest that this approach can be used to systematically alter the extraction strength of aromatic phosphonic monoesters for rare earth element purification.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗