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At least 1,783 records · Page 99

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the geometry of geological features, but the resulting poorly scaled or small grid cells can have a substantial negative impact on simulator accuracy and speed. One way to minimize numerical errors caused by gridding complex structures is to simulate on high-quality Voronoi meshes, which reduce grid orientation effects in fluid flow. This work presents a complete methodology to create Voronoi simulation grids, model fluid flow in complex geological systems, and visualize the results. A recently developed Voronoi meshing method that can automatically generate provably good unstructured meshes that conform to input surfaces creating closed volumes is used. Initially an analytical benchmark simulation is presented to validate the quality of the meshes and simulation results and demonstrate the superiority of simulation results using Voronoi meshes over flexed-hexahedral meshes on a domain with internal features. Next, meshes are created for test structures representing four of the most common geological features in the subsurface: layering, pinch-out, an interior lens that tapers to zero thickness on all sides and a fault with offset. Two benchmark flow simulations are run for each test structure. Finally, a realistic geological example for CO 2 injection into an anticline is simulated. Three realizations of the Voronoi mesh at the same resolution are generated for the simulations. Each mesh is highly refined near the injection wells and coarse in areas of less interest. These three meshes are used to model the CO 2 plume in the subsurface as it migrates to the top of the structure and then fills downward. Simulations on the meshes with randomly generated elements inside the input volumes each give slightly different fingering patterns for the viscous-unstable buoyant gas flow. The results presented in this work show a promising step towards utilizing fully automated Voronoi meshing for subsurface flow simulations in complex geology.

58 GEOSCIENCES↗

Novel self-assembled two-dimensional layered oxide structure incorporated with Au nanoinclusions towards multifunctionalities

Two-dimensional (2D) layered oxides have recently attracted wide attention owing to the strong coupling among charges, spins, lattice, and strain, which allows great flexibility and opportunities in structure designs as well as multifunctionality exploration. In parallel, plasmonic hybrid nanostructures exhibit exotic localized surface plasmon resonance (LSPR) providing a broad range of applications in nanophotonic devices and sensors. A hybrid material platform combining the unique multifunctional 2D layered oxides and plasmonic nanostructures brings optical tuning into the new level. Here, a novel self-assembled Bi 2 MoO 6 (BMO) 2D layered oxide incorporated with plasmonic Au nanoinclusions has been demonstrated via one-step pulsed laser deposition (PLD) technique. Comprehensive microstructural characterizations, including scanning transmission electron microscopy (STEM), differential phase contrast imaging (DPC), and STEM tomography, have demonstrated the high epitaxial quality and particle-in-matrix morphology of the BMO-Au nanocomposite film. DPC-STEM imaging clarifies the magnetic domain structures of BMO matrix. Three different BMO structures including layered supercell (LSC) and superlattices have been revealed which is attributed to the variable strain states throughout the BMO-Au film. Owing to the combination of plasmonic Au and layered structure of BMO, the nanocomposite film exhibits a typical LSPR in visible wavelength region and strong anisotropy in terms of its optical and ferromagnetic properties. This study opens a new avenue for developing novel 2D layered complex oxides incorporated with plasmonic metal or semiconductor phases showing great potential for applications in multifunctional nanoelectronics devices.

36 MATERIALS SCIENCE↗

Improved lithospheric attenuation structure of the Arabian Peninsula through the use of national network data

We characterize the attenuation structure of the Arabian Peninsula through the measurement of regional phase amplitudes. High-resolution is achieved by combining stations from global networks with national network data through the cooperative effort of several countries in the region, including Saudi Arabia, Oman, Iraq, and Kuwait. The result is an improved attenuation model of the crust and upper mantle for a broad frequency band that extends from 0.5 to 10 Hz. The observed attenuation is in accordance with various elements of earth structure, including plate boundary type, style of tectonism, thermo-tectonic age, and temperature. Emerging features from the model include details in the structure along the Red Sea, and improved imaging of the southern Arabian Peninsula extending north from the Gulf of Aden. Finally, the resulting attenuation model can be employed for better magnitude estimates, in isolating tectonic and structural features, and in characterizing strong ground motion in the Arabian Peninsula.

58 GEOSCIENCES↗

Bifurcation Analysis Reveals Solution Structures of Phase Field Models

The phase field method is playing an increasingly important role in understanding and predicting morphological evolution in materials and biological systems. Here, in this study, we develop a new analytical approach based on the bifurcation analysis to explore the mathematical solution structure of phase field models. Revealing such solution structures not only is of great mathematical interest but also may provide guidance to experimentally or computationally uncover new morphological evolution phenomena in materials undergoing electronic and structural phase transitions. To elucidate the idea, we apply this analytical approach to three representative phase field equations: the Allen-Cahn equation, the Cahn-Hilliard equation, and the Allen-Cahn-Ohta-Kawasaki system. The solution structures of these three phase field equations are also verified numerically by the homotopy continuation method.

97 MATHEMATICS AND COMPUTING↗

Recent Advances in X-ray Absorption Near Edge Structure (XANES) Simulation for Catalysis: Theories and Applications

X-ray absorption spectroscopy (XAS) is a powerful spectroscopic technique for characterizing catalytic active sites. In particular, X-ray Absorption Near Edge Structure (XANES) provides insights into the oxidation state and local coordination environment of the absorbing atom, shedding light on the catalytic structure. Computational XANES simulations provide one-on-one correspondence between the molecular structure and their corresponding spectra, making them an effective approach for interpreting experimental XANES features. This work outlines various theories used to simulate XANES spectra and highlights recent advancements in computational XANES applications for homogeneous, heterogeneous, and single-atom catalysts focusing on identifying the active site structures, the site heterogeneity, and the dynamic evolution of catalysts.

Xu, Jiayi↗

Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass

Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.

36 MATERIALS SCIENCE↗

Be Surface Structures on W(110) and W(211): A DFT Study

Beryllium and Tungsten are promising candidates for use as plasma facing materials (PFMs) in upcoming fusion reactors. Many complex and competing phenomena however complicate the understanding and development of materials that operate in the harsh conditions of the reactor. In particular, redeposition of Be onto the W divertor must be considered due to the expected erosion of the Be first wall under exposure to the plasma. It is known that a build up of Be on W allows for the formation of BeW alloys which can harm the longevity and performance of the fusion divertor. In an effort to understand the interaction of Be with W surfaces, a study of Be structures on W(110) and W(211) as a function of Be coverage has been carried out using Density Functional Theory. We have found that both W surfaces develop monolayers of Be characterized by a densely packed hexagonal structure. Below this monolayer coverage, Be structures are found to have two motifs of coverage, a densely packed hexagonal pattern punctuated by areas of low-density coverage. The structures found here produce work function values and trends in good agreement with experimental measurements.

36 MATERIALS SCIENCE↗

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗

Surface and interface structures of epitaxial Sb 2 Se 3 on mica

Sb 2 Se 3 thin film is an emerging photon absorber used in solar cells. We report the study of surface and interface structures of Sb2Se3(1 2 0) film grown on mica substrate by a high-rate vapor transport method. The interface epitaxial relationship between Sb 2 Se 3 and mica examined by the cross- sectional TEM images and diffraction patterns along the [0 0 1] and [10] directions of Sb 2 Se 3 reveal a rectangular structure with lengths of 4.03 ± 0.1 Å and 5.29 ± 0.1 Å, consistent with the [1 2 0] out-of-plane direction of Sb 2 Se 3 bulk lattice parameters. In contrast, the two-dimensional reciprocal space map (2D map) constructed from azimuthal reflection high-energy electron diffraction (ARHEED) patterns from the surface exhibits a decorated hexagonal structure. This surface structure emerges from six epitaxial orientation domains/rods and each domain has a rectangular unit mesh of 3.94 ± 0.09 Å and 26.95 ± 1.16 Å along the [0 0 1] and [10] directions. The 26.95 Å is consistent with the unit mesh of the outermost layer of the Sb 2 Se 3 (1 2 0) domains/rods. Overall, our 2D map reveals surface information that are not easily observed by other diffraction techniques.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Two distinct rotations of bithiazole DNA intercalation revealed by direct comparison of crystal structures of Co(III)•bleomycin A 2 and B 2 bound to duplex 5'-TAGTT sites

Bleomycins constitute a family of anticancer natural products that bind DNA through intercalation of a C-terminal tail/bithiazole moiety and hydrogen-bonding interactions between the remainder of the drug and the minor groove. The clinical utility of the bleomycins is believed to result from single- and double-strand DNA cleavage mediated by the HOO-Fe(III) form of the drug. The bleomycins also serve as a model system to understand the nature of complex drug-DNA interactions that may guide future DNA-targeted drug discovery. In this study, the impact of the C-terminal tail on bleomycin-DNA interactions was investigated. Toward this goal, we determined two crystal structures of HOO-Co(III)•BLMA 2 “green” (a stable structural analogue of the active HOO-Fe(III) drug) bound to duplex DNA containing 5'-TAGTT, one in which the entire drug is bound (fully bound) and a second with only the C-terminal tail/bithiazole bound (partially bound). The structures reported here were captured by soaking HOO-Co(III)•BLMA 2 into preformed host–guest crystals including a preferred DNA-binding site. While the overall structure of DNA-bound BLMA 2 was found to be similar to those reported earlier at the same DNA site for BLMB 2 , the intercalated bithiazole of BLMB 2 is “flipped” 180° relative to DNA-bound BLMA 2 . Further, this finding highlights an unidentified role for the C-terminal tail in directing the intercalation of the bithiazole. In addition, these analyses identified specific bond rotations within the C-terminal domain of the drug that may be relevant for its reorganization and ability to carry out a double-strand DNA cleavage event.

59 BASIC BIOLOGICAL SCIENCES↗

Allosteric prediction via convolutional neural networks and protein structural and dynamical features

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.

Rajeshwar T., Rajitha [Oak Ridge National Laborato↗

Early development of multifilament polyacrylonitrile-derived structural hollow carbon fibers from a segmented arc spinneret

Carbon fiber is a highly desired material for structural applications requiring high strength and stiffness and low weight but has seen only incremental improvements in properties over the last few decades. Further increases in carbon fiber specific properties, including specific strength and specific modulus, would further propel its unique capabilities. One method to produce high specific property carbon fibers for structural applications is the development of hollow carbon fibers. In this work, we report on the early development of polyacrylonitrile-derived structural hollow carbon fibers. Here, multifilament, continuous tow, polyacrylonitrile-based precursor hollow fibers were successfully produced utilizing a segmented arc spinneret approach. When batch oxidized, the hollow precursor fibers demonstrated evidence of oxidation proceeding from both the interior and exterior of the filament. Further results suggested that reducing the precursor hollow fiber wall thickness would allow for complete, homogeneous oxidation, thereby avoiding the skin-core structure often observed in commercial carbon fiber. Here, hollow carbon fibers were as small as 35 µm outer diameter, 22 µm inner diameter (6.5 µm wall thickness). At these diameters, the hollow carbon effective fiber specific strength was 0.54 N/tex and the effective specific modulus was 120 N/tex, approaching the effective specific modulus of T700S at 136 N/tex.

36 MATERIALS SCIENCE↗

Structure and spectroscopy of graphite monofluoride

The structure of graphite monofluoride, (CF) n , has been debated since its discovery in 1934. In this work, we investigate a commercial graphite monofluoride by vibrational spectroscopy (infrared, Raman and the first inelastic neutron scattering spectra of this material). The spectroscopy shows that the material contains unreacted graphite and the partially fluorinated product dicarbon fluoride, (C 2 F) n , We evaluate the previously proposed $P\bar{6}m2$ and $P\bar{3}m1$ structures using computational methods and find F···F contacts render the $P\bar{6}m2$ structure dynamically unstable. We propose two alternative structures, $Cmc2_1$ $P6_3mc$, generated by displacement of one layer relative to another and find that $Cmc2_1$ is also dynamically unstable. The calculations are validated by comparison of calculated and observed INS spectra

Density functional theory↗

Changes in microbial community and network structure precede shrub degradation in a desert ecosystem

Large-scale restoration is intended to promote ecological recovery. Improvements in plant and microbial conditions, however, may slow or even reverse in late succession. To better understand long-term restoration outcomes and underlying drivers of successional pathways, we tracked plant, bacterial and fungal, and soil conditions across a 40-year shrub plantation that was intended to stabilize desertified land in northern China. Here, we found that planted Haloxylon ammodendron shrubs developed and then subsequently became degraded after 30–40 years. Bacterial abundance and α-diversity were much higher than those of fungi, but no significant differences in composition and structure were found in different plantation ages. In contrast, the dominant taxa of fungal communities shifted from symbiotroph and saprotroph species towards pathotroph species with increased soil nutrients in the plantation chronosequence after two decades. The changes in fungal dominant species led to a transition in microbial network structure and function, with an increase in negative linkages among taxa that began in the middle stages of succession. Changes in fungal community structure had direct and indirect negative effects on shrub leaf physiology, root activity, and biomass. Our results highlight the preceding role of a breakdown in soil microbial community composition and network structure on the degradation of shrub performance in long-term desert succession. Our study emphasizes the importance of understanding soil-microbial-plant linkages on restoration outcomes, and mechanisms that can slow or reverse the recovery of ecosystems.

Bacterial and fungal community composition↗

Molecular structure models of amorphous bismuth and cerium carboxylate catalyst precursors

As our societal need for materials and energy has grown, so has our need for catalyst processes in hydrogen production. A major function in these applications, for both homogenous and heterogeneous catalysis processes, is the synthesis of an active metal catalyst. It must first be soluble to control the physical properties of the metal being used. Recent work in metal precursors has begun to turn toward these metal carboxylate types of material. Here, structural models are proposed for bismuth 2-ethylhexanoate and 2,2-dimethyloctanoate and cerium 2-ethylhexanoate. The bismuth compounds have been characterized at different ratios of bismuth to carboxylate as solutions of the free acids. Their structures are most consistent with a Bi 4 (RCO 2 ) 12 motif where the Bi ions are arranged in a flattened tetrahedron with Bi – Bi distances of about 4.3 Å. There is evidence for Bi – O – Bi linkages at low free acid concentrations. The cerium compound is most consistent with a linear tetracerium molecule where the Ce – Ce distances repeat at about 4.3 Å out to 16.4 Å. The models were generated by analogy with known crystal structures and compared to high-energy x-ray scattering data. To further evaluate the models, DFT calculations were made, and the equilibrium geometries were compared. The vibrational spectra calculated from those geometries are presented and compared to the experimental results. Magnetization vs. temperature data was collected on the cerium compound, and its behavior was consistent with the proposed model. A geometrical approach to determining the dimensionality and relative positions of the metal ions in these structures is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystal structures and functional analysis of the ZnF5-WWE1-WWE2 region of PARP13/ZAP define a distinctive mode of engaging poly(ADP-ribose)

PARP13/ZAP (zinc-finger antiviral protein) acts against multiple viruses by promoting degradation of viral mRNA. PARP13 has four N-terminal zinc (Zn) fingers that bind CG-rich nucleotide sequences, a C-terminal ADP ribosyltransferase fold, and a central region with a fifth Zn finger and tandem WWE domains. The central PARP13 region, ZnF5-WWE1-WWE2, is implicated in binding poly(ADP-ribose); however, there are limited insights into its structure and function. We present crystal structures of ZnF5-WWE1-WWE2 from mouse PARP13 in complex with ADP-ribose and in complex with ATP. The crystal structures and binding studies demonstrate that WWE2 interacts with ADP-ribose and ATP, whereas WWE1 does not have a functional binding site. Binding studies with poly(ADP-ribose) ligands indicate that WWE2 serves as an anchor for preferential binding to the terminal end of poly(ADP-ribose) chains. The composite ZnF5-WWE1-WWE2 structure forms an extended surface to engage ADP-ribose chains, representing a distinctive mode of recognition that provides a framework for investigating the impact of poly(ADP-ribose) on PARP13 function.

59 BASIC BIOLOGICAL SCIENCES↗

Structural origin of size effect on piezoelectric performance of Pb(Zr,Ti)O 3

Grain size effect plays a vital role in piezoelectric performance from both scientific and technological view. However, the underlying structural mechanism related to grain size is still unclear. In the present study, the structural mechanism of grain size effect on piezoelectric performance has been revealed in the prototype Pb(Zr, Ti)O 3 system by using in-situ synchrotron X-ray diffraction. The miniaturization of grain size tends to favor the appearance of higher symmetric tetragonal phase, while a single monoclinic phase is determined in the coarse-grained ceramics. The direct structural evidence reveals that both tetragonal and monoclinic phases in the fine-grained ceramics are less sensitive to the electric field, corresponding to the inferior piezoelectric performance, while the single monoclinic phase in the coarse-grained ceramics is more active to be driven by the electric field, generating good piezoelectric behavior. Both domain switching ability and lattice strain are suppressed with decreasing grain size, which directly leads to the deterioration in piezoelectric performance. In conclusion, the current results will benefit the structural understanding of the size effect of piezoelectric and other related systems.

36 MATERIALS SCIENCE↗