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At least 289 records · Page 16

Disentangling Planets from Photoelectric Instability in Gas-rich Optically Thin Dusty Disks

Structures in circumstellar disks such as gaps and rings are often attributed to planets. This connection has been difficult to show unequivocally, as other processes may also produce these features. In particular, a photoelectric instability (PEI) has been proposed, operating in gas-rich optically thin disks, that generates structures predicted by planet–disk interactions. We examine the question of how to disentangle the planetary effects on disk structure from the effects of the PEI. We use the Pencil Code to perform 2D global hydrodynamical models of the dynamics of gas and dust in a thin disk with and without planetary perturbers. Photoelectric heating is modeled with an equation of state where pressure is proportional to dust surface density. The drag force on grains and its backreaction on the gas are included. Analyzing the situation without PEI, we find that gas–dust interactions alter the shape of the planetary gap from the dust-free case when the local dust-to-gas ratio ε approaches unity. This result also applies to primordial disks, because dust drifting inward accumulates at the edge of the planetary gap, and any initial dust-to-gas ratio eventually achieves ε = 1 if the dust reservoir is sufficient. We find a result particular to high dust-to-gas ratio disks as well: as dust drifts inward, the dust front becomes a sharp transition, and the backreaction triggers the Rossby wave instability. When PEI is included, we find that it obscures structures induced by planets unless the planet's mass is sufficiently large to carve a noticeable gap. Specifically, the instability generates arcs and rings of regular spacing: a planet is discernible when it carves a dust gap wider than the wavelength of the PEI.

Areli Castrejon↗

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observations of structure in the interstellar polarization curve Preliminary results

We have measured the wavelength dependence of the interstellar polarization curve with higher wavelength resolution than has generally been used before. Our data show structure which has been previously unknown, and which may have important implications with respect to the composition of the interstellar grains. It is similar in general form to structure predicted on the basis of a theoretical model designed by us to give a detailed match to the extinction structure.

Mavko, G. E.↗

Structure of Soot-Containing Laminar Jet Diffusion Flames

The structure and soot properties of nonbuoyant and weakly-buoyant round jet diffusion flames were studied, considering ethylene, propane and acetylene burning in air at pressures of 0.125-2.0 atm. Measurements of flame structure included radiative heat loss fractions, flame shape and temperature distributions in the fuel-lean (overfire) region. These measurements were used to evaluate flame structure predictions based on the conserved-scalar formalism in conjunction with the laminar flamelet concept, finding good agreement betweem predictions and measurements. Soot property measurements included laminar smoke points, soot volume function distributions using laser extinction, and soot structure using thermophoretic sampling and analysis by transmission electron microscopy. Nonbuoyant flames were found to exhibit laminar smoke points like buoyant flames but their properties are very different; in particular, nonbuoyant flames have laminar smoke point flame lengths and residence times that are shorter and longer, respectively, than buoyant flames.

Mortazavi, S.↗

Structural-acoustic coupling in aircraft fuselage structures

Results of analytical and experimental investigations of structural-acoustic coupling phenomenon in an aircraft fuselage are described. The structural and acoustic cavity modes of DC-9 fuselage were determined using a finite element approach to vibration analysis. Predicted structural and acoustic dispersion curves were used to determine possible occurrences of structural-acoustic coupling for the fuselage. An aft section of DC-9 aircraft fuselage, housed in an anechoic chamber, was used for experimental investigations. The test fuselage was excited by a shaker and vibration response and interior sound field were measured using accelerometer and microphone arrays. The wavenumber-frequency structural and cavity response maps were generated from the measured data. Analysis and interpretation of the spatial plots and wavenumber maps provided the required information on modal characteristics, fuselage response and structural-acoustic coupling.

Mathur, Gopal P.↗

Current-driven resistive ballooning modes in axially bounded solar flare plasmas

The most unstable current-driven resistive modes of an axially bounded coronal loop are found in computer simulations to exhibit the spatial structure of ballooning modes. The observed modes are not confined to mode rational surfaces, but instead have broad radial extent. A theory assuming ballooning mode spatial structure predicts that a minimum current should be required for linear instability, and that, when the mode is unstable, the linear growth rate scales linearly with the resistivity eta below a critical resistivity, and scales as cu root of eta for larger resistivities. Both predictions are borne out by simulation results. Both theory and simulation analyses of the mode suggest that the strong radial structure of the mode near the ends of the system is the primary contributing factor to the instability of the mode. A helical current sheet is formed in the nonlinear evolution of the mode near the edge of the current channel and is accompanied by a strong radial gradient in the current and partial current reversal.

Otani, Niels F.↗

Quiet High-Speed Fan

A calibration of the acoustic and aerodynamic prediction methods was performed and a baseline fan definition was established and evaluated to support the quiet high speed fan program. A computational fluid dynamic analysis of the NASA QF-12 Fan rotor, using the DAWES flow simulation program was performed to demonstrate and verify the causes of the relatively poor aerodynamic performance observed during the fan test. In addition, the rotor flowfield characteristics were qualitatively compared to the acoustic measurements to identify the key acoustic characteristics of the flow. The V072 turbofan source noise prediction code was used to generate noise predictions for the TFE731-60 fan at three operating conditions and compared to experimental data. V072 results were also used in the Acoustic Radiation Code to generate far field noise for the TFE731-60 nacelle at three speed points for the blade passage tone. A full 3-D viscous flow simulation of the current production TFE731-60 fan rotor was performed with the DAWES flow analysis program. The DAWES analysis was used to estimate the onset of multiple pure tone noise, based on predictions of inlet shock position as a function of the rotor tip speed. Finally, the TFE731-60 fan rotor wake structure predicted by the DAWES program was used to define a redesigned stator with the leading edge configured to minimize the acoustic effects of rotor wake / stator interaction, without appreciably degrading performance.

Lieber, Lysbeth↗

Integrated Modeling Tools for Thermal Analysis and Applications

Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.

Milman, Mark H.↗

Novel fold of rotavirus glycan-binding domain predicted by AlphaFold2 and determined by X-ray crystallography

The VP8* domain of spike protein VP4 in group A and C rotaviruses, which cause epidemic gastroenteritis in children, exhibits a conserved galectin-like fold for recognizing glycans during cell entry. In group B rotavirus, which causes significant diarrheal outbreaks in adults, the VP8* domain (VP8*B) surprisingly lacks sequence similarity with VP8* of group A or group C rotavirus. Here, by using the recently developed AlphaFold2 for ab initio structure prediction and validating the predicted model by determining a 1.3-Å crystal structure, we show that VP8*B exhibits a novel fold distinct from the galectin fold. This fold with a β-sheet clasping an α-helix represents a new fold for glycan recognition based on glycan array screening, which shows that VP8*B recognizes glycans containing N-acetyllactosamine moiety. Although uncommon, our study illustrates how evolution can incorporate structurally distinct folds with similar functionality in a homologous protein within the same virus genus.

59 BASIC BIOLOGICAL SCIENCES↗

A Surface Exposed, Two-Domain Lipoprotein Cargo of a Type XI Secretion System Promotes Colonization of Host Intestinal Epithelia Expressing Glycans

The only known required component of the newly described Type XI secretion system (TXISS) is an outer membrane protein (OMP) of the DUF560 family. TXISS OMPs are broadly distributed across proteobacteria, but properties of the cargo proteins they secrete are largely unexplored. We report biophysical, histochemical, and phenotypic evidence that Xenorhabdus nematophila NilC is surface exposed. Biophysical data and structure predictions indicate that NilC is a two-domain protein with a C-terminal, 8-stranded β-barrel. This structure has been noted as a common feature of TXISS effectors and may be important for interactions with the TXISS OMP . The NilC N-terminal domain is more enigmatic, but our results indicate it is ordered and forms a β-sheet structure, and bioinformatics suggest structural similarities to carbohydrate-binding proteins. X. nematophila NilC and its presumptive TXISS OMP partner NilB are required for colonizing the anterior intestine of Steinernema carpocapsae nematodes: the receptacle of free-living, infective juveniles and the anterior intestinal cecum (AIC) in juveniles and adults. We show that, in adult nematodes, the AIC expresses a Wheat Germ Agglutinin (WGA)-reactive material, indicating the presence of N-acetylglucosamine or N-acetylneuraminic acid sugars on the AIC surface. A role for this material in colonization is supported by the fact that exogenous addition of WGA can inhibit AIC colonization by X. nematophila. Conversely, the addition of exogenous purified NilC increases the frequency with which X. nematophila is observed at the AIC, demonstrating that abundant extracellular NilC can enhance colonization. NilC may facilitate X. nematophila adherence to the nematode intestinal surface by binding to host glycans, it might support X. nematophila nutrition by cleaving sugars from the host surface, or it might help protect X. nematophila from nematode host immunity. Proteomic and metabolomic analyses of wild type X. nematophila compared to those lacking nilB and nilC revealed differences in cell wall and secreted polysaccharide metabolic pathways. Additionally, purified NilC is capable of binding peptidoglycan, suggesting that periplasmic NilC may interact with the bacterial cell wall. Overall, these findings support a model that NilB-regulated surface exposure of NilC mediates interactions between X. nematophila and host surface glycans during colonization. This is a previously unknown function for a TXISS.

59 BASIC BIOLOGICAL SCIENCES↗

Ex Machina Determination of Structural Correlation Functions

Determining the structural properties of condensed-phase systems is a fundamental problem in theoretical statistical mechanics. In this study, we present a machine learning method that is able to predict structural correlation functions with significantly improved accuracy in comparison with traditional approaches. The usefulness of this ex machina (from the machine) approach is illustrated by predicting the radial distribution functions of two paradigmatic condensed-phase systems, a Lennard-Jones fluid and a hard-sphere fluid, and then comparing those results to the results obtained using both integral equation methods and empirically motivated analytical functions. We find that application of the developed ex machina method typically decreases the predictive error by more than an order of magnitude in comparison with traditional theoretical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RCSB protein data Bank: Next‐generation advanced search for exploration of experimental structures and computed structure models

Abstract The Protein Data Bank (PDB), established in 1971, is the primary global, open‐access archive for experimentally determined 3D macromolecular structures (proteins, RNA, DNA). The research‐focused RCSB.org web‐portal provides access to these data alongside more than one million machine‐learning‐predicted structure models, greatly expanding the available structural landscape. Rapid growth of both experimental and computational structures has increased the need for powerful yet accessible search tools that serve a broad and diverse scientific community. Herein, we describe a redesigned RCSB Protein Data Bank RCSB.org Advanced Search capability that supports intuitive discovery of 3D structures through a unified interface. This interface integrates annotation‐, sequence‐, and 3D structure‐based searches, embeds an interactive 3D viewer, and incorporates curated biological knowledge, such as catalytic site definitions from Mechanism and Catalytic Site Atlas and ligand‐guided structural motifs, for constructing geometry‐driven queries. A new Chemical Search tool allows definition of chemical queries via an integrated drawing tool or standard identifiers, seamlessly combining them with annotation filters. By allowing query definition directly within spatial and chemical contexts, these search interfaces reduce the need for detailed knowledge of residue numbering, chain identifiers, or external cheminformatics software. This capability enables efficient exploration of structures, chemical diversity, and structure–function relationships across all life domains. The redesigned interfaces can be accessed directly at rcsb.org/search/advanced for Advanced Search and rcsb.org/search/chemical for Chemical Search.

Rose, Yana [Research Collaboratory for Structural ↗

On the nature of the interaction between structures and proof-mass actuators

This paper presents an analysis of the interaction between a structure, an actuator used to control the vibration of the structure, and the control law to be implemented by the actuator. The control hardware used is a proof-mass actuator with experimentally verified dynamics capable of being used in a space structure configuration. A local rate-feedback control law is used. The control of two different structures is presented. The first structure is a cantilevered beam constructed of a quasi-isotropic composite material that is controlled by a single actuator forming the experimental component of the investigation. The second structure is a finite-element model of a truss system controlled by a single actuator. Models of both structures predict the presence of potential instabilities in system performance if proper consideration is not given to interactions between the control law, the structure, and the actuator.

Zimmerman, David C.↗

Design Rules for Two–Dimensional Organic Semiconductor–Incorporated Perovskites (OSiP) Gleaned from Thousands of Simulated Structures

Two-dimensional (2D) halide perovskites are an attractive class of hybrid perovskites that have additional optoelectronic tunability due to their accommodation of relatively large organic ligands. Nevertheless, contemporary ligand design depends on either expensive trial-and-error testing of whether a ligand can be integrated within the lattice or conservative heuristics that unduly limit the scope of ligand chemistries. Here, the structural determinants of stable ligand incorporation within Ruddlesden-Popper (RP) phase perovskites are established by molecular dynamics (MD) simulations of over ten-thousand RP-phase perovskites and training of machine learning classifiers capable of predicting structural stability based solely on generalizable ligand features. The simulation results show near-perfect predictions of positive and negative literature examples, predict trade-offs between several ligand features and stability, and ultimately predict an inexhaustibly large 2D-compatible ligand design-space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Design, analysis, and testing of a hybrid scale structural dynamic model of a Space Station

The impracticality of testing the fully-assembled on-orbit configurations of future large erectable space platforms fosters an increased reliance on other means for verifying predicted structural dynamic performance. One option is scale modeling. This paper discusses the design of a hybrid scale dynamic test model of the Freedom Space Station and its associated suspension system. Hybrid scaling laws are reviewed, followed by scale factor trades, component design examples, and an analytical evaluation of the overall model fidelity. Component and subassembly test results from a six-bay hybrid scale model truss are presented. Potential interactions of gravity and the suspension system with the free-free dynamics of the scale model are investigated. Suspension system design parameters, such as the number, location, mass, and stiffness of the suspension devices are traded to minimize undesirable interactions and form the basis for an overall suspension system concept for the scale model.

Gronet, Marc J.↗

Unraveling the Molecular Origin of Prey-Wrapping Spider Silk's Unique Mechanical Properties and Assembly Process Using NMR

Prey wrapping spider silk's unique mechanical properties are investigated confirming the silk's high degree of extensibility and superior toughness compared to other types of spider silk. For the first time, the pre-spinning dope phase is studied in isotope-enriched intact aciniform (AC) silk glands using solution NMR that reveals a combination of α-helical domains linked by disordered random coil chains consistent with previously proposed “beads-on-a-string” models. The model is further refined through the AlphaFold2 protein structure prediction tool. Finally, extensive magic angle spinning (MAS) solid-state (SS) NMR data for isotopically-enriched fibers is used to refine the structural model for AC silk from two species, A. aurantia and A. argentata. The SSNMR data shows that the AC silk fibers are highly α-helical, coiled-coil in structure but, also exhibit significant β-sheet components that can be traced back to the Gly-rich disordered linker regions in the pre-spinning dope phase that are converted to β-sheet structures during fiber formation. This combination of mechanical and structural characterization enhances the understanding of AC silk's liquid-to-solid transition and structure-mechanics relationship. In conclusion, these prey wrap silk results and models will provide the basis for the design of biomimetic materials inspired by the AC spider silk system.

36 MATERIALS SCIENCE↗