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At least 109 records · Page 6

Efficient identification of critical stresses in structures subject to dynamic loads

Optimum structural design problems generally employ constraints which are parametric in terms of space and time variables. A parametric constraint may be replaced by equivalent critical point constraints at its local minima for optimization applications. In complex structures, accurate identification of such critical points is computationally expensive due to the cost of finite element analyses. Three techniques are described for efficiently and accurately identifying critical points for space- and time-dependent parametric constraints. An adaptive search technique and a spline interpolation technique are developed for exactly known response. A least squares spline approximation is suggested for noisy behavior. A helicopter tail-boom structure subjected to transient loading is used as an example to demonstrate the techniques described. All three techniques are shown to be computationally efficient for critical point identification and the least squares approximation also removes noise from the data. The case of multiple constraints per element is shown to be particularly suited to the use of spline techniques.

Haftka, R. T.↗

Optical Microscopy-Guided Laser Ablation Electrospray Ionization Ion Mobility Mass Spectrometry: Ambient Single Cell Metabolomics with Increased Confidence in Molecular Identification

Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data

Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.

Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗

Characterizing Nanophase Materials on Mars: Spectroscopic Studies of Allophane and Imogolite

Allophane is an amorphous or poorly crystalline hydrous aluminosilicate material. Allophane's chemical structure represents a hollow nanosphere, 5-6 nm in diameter with 4-7 large pores in the structure. Identification of allophane and other amorphous and nanophase minerals on Mars has provided clues about the aqueous geochemical environment there. These materials likely represent partially altered or leached basaltic ash and therefore, could represent a geologic marker for where water was present on the Martian surface; as well as indicate regions of climate change, where surface water was not present long enough or sufficiently warm to form clays. Characterization of these materials is important for increasing spectral recognition capabilities using visible/near-infrared (VNIR) and thermal infrared (TIR) spectra of Mars. A suite of synthetic allophane samples was created using a method that has been modified to produce allophane with Fe isomorphically substituted for Al in octahedral coordination. Compositions of the materials range from high-Si allophane (molar Al:Si = 1:2) to protoimogolite (Al:Si = 2:1), with Fe(3+) and Fe(2+) isomorphically substituted for Al from 0-10 mol% of total Al. These compositions span the range observed in natural terrestrial allophanes. Fe K-edge X-ray absorption spectroscopy provided information on the speciation and electrochemical and structural position of Fe in the framework. Fourier transform infrared spectroscopy confirmed syntheses and demonstrated changes in infrared spectroscopic signature with Fe substitution. VNIR reflectance spectra and TIR Thermal infrared emissivity spectra were also collected for direct comparison to Martian data. By increasing spectral recognition capacities of nanophase materials, more accurate estimates can be made on the aqueous geochemical environment of Mars.

Jeute, Thomas↗

RNA-Puzzles Round V: blind predictions of 23 RNA structures

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson–Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.

59 BASIC BIOLOGICAL SCIENCES↗

New Constraints on the Melting Temperature and Phase Stability of Shocked Iron up to 270 GPa Probed by Ultrafast X-Ray Absorption Spectroscopy

Studying the properties and phase diagram of iron at high-pressure and high-temperature conditions has relevant implications for Earth’s inner structure and dynamics and the temperature of the inner core boundary (ICB) at 330 GPa. Also, a hexagonal-closed packed to body-centered cubic (bcc) phase transition has been predicted by many theoretical works but observed only in a few experiments. The recent coupling of high-power laser with advanced x-ray sources from synchrotrons allows for novel approaches to address these issues. Here, we present a study on shock compressed iron up to 270 GPa and 5800 K probed by single-pulse (100 ps FWHM) x-ray absorption spectroscopy (XAS). Based on the analysis of the XAS spectra, we provide structural identification and bulk temperature measurements along the Hugoniot up to the melting. These results rule out the predicted transition to a high-temperature bcc phase and allow one to discriminate among existing equations of state models and melting curves. In particular, we report the first bulk temperature measurement in shock compressed iron on the melting plateau at 240(20) GPa and 5345(600) K. The melting curve resulting from our work extrapolates to a temperature of 6202(514) K at 330 GPa and represents a refined upper bound for the ICB temperature. Published by the American Physical Society 2024

Balugani, S.↗

2D Polyhedral Template Matching for Atomic Resolution Microscopy

SAND2024-13879O The 2D Polyhedral Template Matching for Atomic Resolution Microscopy is a suite of functions for analyzing atomic resolution electron microscopy images using the 2D polyhedral template matching (2D-PTM) method. This software analyzes atomic resolution microscopy data from electron microscopic imaging or scanning probe microscopies. The primary application is for identifying different crystal phases, crystal orientations, and defect structures obtained in such atomic resolution images. Written in MATLAB and starting from an atomic resolution image, the code identifies the positions of atomic intensity peaks. It then matches predefined structural templates to the local atomic environments. Outputs include the local structural identification, the template scaling factor and rotation angle, root-mean-squared deviation (RMSD), and centrosymmetry parameter.

Medlin, Douglas↗

What Is the Limit of Quantification for the Minor Phase in Time-of-Flight Neutron Diffraction? A Case Study on Fe and Ni Powder Mixtures at VULCAN

A phase present in small quantities within materials may not simply serve as a secondary component; it can play a crucial role in determining the integrity, properties, and performance of the material. These minor but important phases usually draw attention in material design and processing for fundamental understanding as well as material quality control. Accurately quantifying a minor phase amid a majority phase, especially at extremely low fractions, remains a challenging task. Time-of-flight neutron diffraction, coupled with advanced pattern analysis techniques like Rietveld refinement, is a powerful tool for crystal structure identification and phase quantification. The deep penetrating capability of neutrons enables the detection and quantification of trace phases within materials. In this study, the quantification limits of time-of-flight neutron diffraction were explored using the VULCAN diffractometer at the Spallation Neutron Source, using Fe–Ni powder mixtures as a sample system. By comparing the refinement results to the known weighed values, it was determined that the reliable quantification of a minor Ni phase is achievable down to about 0.1 wt% while a Ni fraction as low as 0.02 wt% is difficult to trace. Effective control of the refinement parameters, especially the profile function parameters, are found to significantly influence the convergence of fittings and the accuracy of phase quantification.

Rietveld refinement↗

Exploration for fossil and nuclear fuels from orbital altitudes

The paper discusses the application of remotely sensed data from orbital satellites to the exploration for fossil and nuclear fuels. Geological applications of Landsat data are described including map editing, lithologic identification, structural geology, and mineral exploration. Specific results in fuel exploration are reviewed and a series of related Landsat images is included.

Short, N. M.↗

Proceedings of the Flat-plate Solar Array Project Research Forum on High-efficiency Crystalline Silicon Solar Cells

The high-efficiency crystalline silicon solar cells research forum addressed high-efficiency concepts, surface-interface effects, bulk effects, modeling and device processing. The topics were arranged into six interactive sessions, which focused on the state-of-the-art of device structures, identification of barriers to achieve high-efficiency cells and potential ways to overcome these barriers.

Kachare, R.↗

An overview of the essential differences and similarities of system identification techniques

Information is given in the form of outlines, graphs, tables and charts. Topics include system identification, Bayesian statistical decision theory, Maximum Likelihood Estimation, identification methods, structural mode identification using a stochastic realization algorithm, and identification results regarding membrane simulations and X-29 flutter flight test data.

Mehra, Raman K.↗

Model based estimation of image depth and displacement

Passive depth and displacement map determinations have become an important part of computer vision processing. Applications that make use of this type of information include autonomous navigation, robotic assembly, image sequence compression, structure identification, and 3-D motion estimation. With the reliance of such systems on visual image characteristics, a need to overcome image degradations, such as random image-capture noise, motion, and quantization effects, is clearly necessary. Many depth and displacement estimation algorithms also introduce additional distortions due to the gradient operations performed on the noisy intensity images. These degradations can limit the accuracy and reliability of the displacement or depth information extracted from such sequences. Recognizing the previously stated conditions, a new method to model and estimate a restored depth or displacement field is presented. Once a model has been established, the field can be filtered using currently established multidimensional algorithms. In particular, the reduced order model Kalman filter (ROMKF), which has been shown to be an effective tool in the reduction of image intensity distortions, was applied to the computed displacement fields. Results of the application of this model show significant improvements on the restored field. Previous attempts at restoring the depth or displacement fields assumed homogeneous characteristics which resulted in the smoothing of discontinuities. In these situations, edges were lost. An adaptive model parameter selection method is provided that maintains sharp edge boundaries in the restored field. This has been successfully applied to images representative of robotic scenarios. In order to accommodate image sequences, the standard 2-D ROMKF model is extended into 3-D by the incorporation of a deterministic component based on previously restored fields. The inclusion of past depth and displacement fields allows a means of incorporating the temporal information into the restoration process. A summary on the conditions that indicate which type of filtering should be applied to a field is provided.

Damour, Kevin T.↗

A comparison of refined models for flexible subassemblies

Interactions between structure response and control of large flexible space systems have challenged current modeling techniques and have prompted development of new techniques for model improvement. Due to the geometric complexity of envisioned large flexible space structures, finite element models (FEM's) will be used to predict the dynamic characteristics of structural components. It is widely accepted that these models must be experimentally 'validated' before their acceptance as the basis for final design analysis. However, predictions of modal properties (natural frequencies, mode shapes, and damping ratios) are often in error when compared to those obtained from Experimental Modal Analysis (EMA). Recent research efforts have resulted in the development of algorithmic approaches for model improvement, also referred to as system or structure identification.

Smith, Suzanne Weaver↗

Applications of multiple-constraint matrix updates to the optimal control of large structures

Low-authority control or vibration suppression in large, flexible space structures can be formulated as a linear feedback control problem requiring computation of displacement and velocity feedback gain matrices. To ensure stability in the uncontrolled modes, these gain matrices must be symmetric and positive definite. In this paper, efficient computation of symmetric, positive-definite feedback gain matrices is accomplished through the use of multiple-constraint matrix update techniques originally developed for structural identification applications. Two systems were used to illustrate the application: a simple spring-mass system and a planar truss. From these demonstrations, use of this multiple-constraint technique is seen to provide a straightforward approach for computing the low-authority gains.

Smith, S. W.↗

Laboratory Investigation of the Growth and Crystal Structure of Nitric Acid Hydrates by Transmission Electron Microscopy (TEM)

A great deal of recent laboratory work has focussed on the characterization of the nitric acid hydrates, thought to be present in type I Polar Stratospheric Clouds (PSCs). Phase relationships and vapor pressure measurements (1-3) and infrared characterizations (4-5) have been made. However, the observed properties of crystalline solids (composition, melting point, vapor pressure, surface reactivity, thermodynamic stability, extent of solid solution with other components, etc.) are controlled by their crystal structure. The only means of unequivocal structural identification for crystalline solids is diffraction (using electrons, X-rays, neutrons, etc.). Other observed properties of crystalline solids, such as their infrared spectra, their vapor pressure as a function of temperature, etc. yield only indirect information about what phases are present, their relative proportions, or whether they are crystalline or amorphous.

Blake, David F.↗

Juggling Act: Re-Planning and Building on Observatory...Simultaneously!

SOFIA (Stratospheric Observatory for Infrared Astronomy) is a major SMD program that has been required to meet several requirements and implement major planning and business initiatives overthe past 1 1/2 years, in the midst of system development and flight test phases. The program was required to implementing JCL and EVM simultaneously, as well as undergo a major replan and Standing Review Board - and all without impacting technical schedule progress. The team developed innovative processes that met all the requirements, and improved Program Management process toolsets. The SOFIA team, being subject to all the typical budget constraints, found ways to leverage existing roles in new ways to meet the requirements without creating unmanageable overhead. The team developed strategies and value added processes - such as improved risk identification, structured reserves management, cost/risk integration - so that the effort expended resulted in a positive return to the program.

Zavala, Eddie↗