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At least 991 records · Page 55

Participation In The AXAF Program As Interdisciplinary Scientist

We have supported the Advanced X-ray Astrophysics Facility (AXAF) project through specific studies and research in X-ray astronomy. Our research in X-ray astronomy has been concentrated in three projects: the ROSAT Deep Survey, the ROSAT All-sky Cluster Survey, and the study of moderate to high redshift clusters discovered serendipitously in long ROSAT pointings utilizing the wavelet transform. We have continued to develop the techniques and catalogues described in the publications listed below. The PI continued to participate in the SWG and attended its meetings except where conflicts existed. The Co-I supported the PI and attended all meetings in order to provide continuity. A post-doctoral fellow (Rosati) was hired to fully develop the techniques described above and make them applicable to the AXAF program. The results are described in the publications below. We continued to provide analysis of scientific and technical issues to the project scientist as appropriate. We made detailed simulations of the AXAF deep survey program and have made this available to the project and the ASC. The principal scientific results, discussed in great detail in the publications listed below, are as follows: (1) The wavelet transform is now a fine working tool for the analysis of faint X-ray sources especially clusters. (2) The analysis of the ROSAT DEEP CLUSTER SURVEY has given important constraints on cosmology particularly on the matter content of the universe and the amplitude of the fluctuations that created the galaxies and clusters. (3) The ROSAT DEEP SURVEY in the Lockman Hole has given an important'deep survey in the X-ray band that gives vital data on the distribution and evolution of X-ray sources. It is an important and complementary data base to compare with the AXAF deep fields. (4) The Northern ROSAT All Sky Cluster Survey now has a complete catalog and is again important and complementary to AXAF/ Chandra studies of clusters which are deeper but in a narrower area. These projects have had a significant impact on the whole field and have set up some excellent experiments to be undertaken with the AXAF/Chandra telescope such as the Chandra Deep Field South.

Giacconi, Riccardo↗

Dimensionally Aligned Signal Projection Algorithms Library

Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. This work seeks to provide an effective open-source implementation of the DASP algorithms proposed by Vann et al. (2018) as well as functionality to help explore and test how these algorithms work with an interactive dashboard and signal-generation tool. The DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. The HASP algorithms are variations of the algorithms originally presented by Vann et al. (2018). For consistency, FASP, which is the terminology used for the short-time Fourier transform (STFT), has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals. Finally, the library provides multiple interactive visualizations, each of which is implemented using IPyWidgets and works in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as for the artifical signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.

harmonics↗

Probing Thermal Stability of Li-Ion Battery Ni-Rich Layered Oxide Cathodes by means of Operando Gas Analysis and Neutron Diffraction

Thermal stability is a crucial parameter that must be considered within the overall performance metrics of Ni-rich layered oxide cathodes. While the intrinsic structural stability of the cathode materials under thermal conditions is important, it is also critical to consider their reaction with electrolytes. In this study, operando gas analysis, ex situ neutron diffraction, and differential scanning calorimetry were combined to give a broader picture of the thermal stability of Ni-rich NMC cathodes. Li 1– x Ni 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) composite materials with four different states of charge were investigated with and without the presence of an electrolyte. It has been found that electrolyte can greatly accelerate both the structural and thermal decomposition of the cathode materials. A higher state of charge will also make cathode materials more susceptible to thermal shock. Without an electrolyte, O 2 release inducing a structural change from layered to rock salt was the major observation during thermal runaway. However, all samples retained some levels of layered structure after annealing up to 300 °C without the electrolyte. In comparison, almost all the O3-type layered phase transformed to the rock-salt phase for the cathode materials heated with the electrolyte at the same experimental conditions. Moreover, the amount of CO 2 increased by nearly two orders of magnitude when annealing cathode materials with electrolyte in operando gas analysis experiments. More delithiated NMC811 samples released larger amounts of CO 2 at earlier onset temperatures, resonating well with the differential scanning calorimetry (DSC) results showing that more delithiated samples release more heat during thermal shock.

25 ENERGY STORAGE↗

Revealing and Engineering Assembly Pathways of 3D DNA Origami Crystals

Recent developments in nanomaterial self-assembly demonstrate the capability to create tailored nanostructures by engineering both the binding coordination and specificity of interactions between material subunits. DNA origami frames allow for the design and fabrication of a broad variety of ordered 3D nanoscale architectures through self-assembly, facilitated by frame-to-frame bonds with designable strength and specificity. While the bond design is critical to lattice formation, the assembly process itself is often dependent on a thermal pathway. Highly ordered nanoscale frameworks, assembled from DNA frames, are predominantly crystallized through thermal annealing pathways that typically follow a “slow” cooling approach, with experiments on the time scale of days yielding DNA origami crystals in the range of 1−10 μm. This extended assembly time scale hinders the study of crystal formation pathways, necessitating a deeper understanding of factors governing successful annealing. Lack of insight into time scale also presents a practical limitation for material fabrication. Here, we investigate key factors affecting lattice assembly pathways and demonstrate that precise engineering of assembly conditions greatly reduces assembly times by up to nearly 2 orders of magnitude. We evaluate the nucleation and growth of crystals via optical and electron microscopy, and small-angle X-ray scattering techniques, mapping the time−temperature-transformation of superlattices from the melt through single-crystal optical tracking. The results show that origami frame assembly can be described by classical nucleation and growth theory, which can, in turn, be used to prescribe the growth of the crystals. Lastly, these findings are applied to demonstrate thermal pathway-dependent assembly, forming distinct assemblies based on different thermal annealing profiles.

36 MATERIALS SCIENCE↗

Emergence of spin singlets with inhomogeneous gaps in the kagome lattice Heisenberg antiferromagnets Zn-barlowite and herbertsmithite

The kagome Heisenberg antiferromagnet formed by frustrated spins arranged in a lattice of corner-sharing triangles is a prime candidate for hosting a quantum spin liquid (QSL) ground state consisting of entangled spin singlets. However, the existence of various competing states makes a convincing theoretical prediction of the QSL ground state difficult, calling for experimental clues from model materials. The kagome lattice materials Zn-barlowite (ZnCu 3 (OD) 6 FBr) and herbertsmithite (ZnCu 3 (OD) 6 Cl 2 ) do not exhibit long-range order and are considered the best realizations of the kagome Heisenberg antiferromagnet known so far. In this study, we use 63 Cu nuclear quadrupole resonance combined with the inverse Laplace transform to locally probe the inhomogeneity of delicate quantum ground states affected by disorder. We present direct evidence for the gradual emergence of spin singlets with spatially varying excitation gaps, but even at temperatures far below the super-exchange energy scale their fraction is limited to ~60% of the total spins. Theoretical models need to incorporate the role of disorder to account for the observed inhomogeneously gapped behaviour.

36 MATERIALS SCIENCE↗

Non-covalent planarizing interactions yield highly ordered and thermotropic liquid crystalline conjugated polymers

Controlling the multi-level assembly and morphological properties of conjugated polymers through structural manipulation has contributed significantly to the advancement of organic electronics. In this work, a redox active conjugated polymer, TPT–TT, composed of alternating 1,4-(2-thienyl)-2,5-dialkoxyphenylene (TPT) and thienothiophene (TT) units is reported with non-covalent intramolecular S⋯O and S⋯H–C interactions that induce controlled main-chain planarity and solid-state order. As confirmed by density functional theory (DFT) calculations, these intramolecular interactions influence the main chain conformation, promoting backbone planarization, while still allowing dihedral rotations at higher kinetic energies (higher temperature), and give rise to temperature-dependent aggregation properties. Thermotropic liquid crystalline (LC) behavior is confirmed by cross-polarized optical microscopy (CPOM) and closely correlated with multiple thermal transitions observed by differential scanning calorimetry (DSC). This LC behavior allows us to develop and utilize a thermal annealing treatment that results in thin films with notable long-range order, as shown by grazing-incidence X-ray diffraction (GIXD). Specifically, we identified a first LC phase, ranging from 218 °C to 107 °C, as a nematic phase featuring preferential face-on π–π stacking and edge-on lamellar stacking exhibiting a large extent of disorder and broad orientation distribution. A second LC phase is observed from 107 °C to 48 °C, as a smectic A phase featuring sharp, highly ordered out-of-plane lamellar stacking features and sharp tilted backbone stacking peaks, while the structure of a third LC phase with a transition at 48 °C remains unclear, but resembles that of the solid state at ambient temperature. Furthermore, the significance of thermal annealing is evident in the ∼3-fold enhancement of the electrical conductivity of ferric tosylate-doped annealed films reaching 55 S cm −1 . More importantly, thermally annealed TPT–TT films exhibit both a narrow distribution of charge-carrier mobilities (1.4 ± 0.1) × 10 −2 cm 2 V −1 s −1 along with a remarkable device yield of 100% in an organic field-effect transistor (OFET) configuration. This molecular design approach to obtain highly ordered conjugated polymers in the solid state affords a deeper understanding of how intramolecular interactions and repeat-unit symmetry impact liquid crystallinity, solution aggregation, solution to solid-state transformation, solid-state morphology, and ultimately device applications.

Chemistry↗

Negative linear compressibility and complex phase behaviour in 7 Li 2 CO 3

We present a combination of neutron powder-diffraction measurements demonstrating negative linear compressibility and irregular thermal expansion in 7 Li 2 CO 3 . This is shown to be due to an interplay between the tilting of the rigid carbonate group and the shear strain in the unit cell, which leads to a first-order transition from monoclinic to hexagonal symmetry. The phase evolution is shown to be highly sensitive to the level of hydrostaticity in the sample. Under hydrostatic conditions, the sample begins transformation at 8.5 GPa leading to a change from tetrahedral to octahedral Li coordination. Symmetry adapted basis mode analysis, combined with density functional theoretical (DFT) calculations and Raman spectroscopy, is used to show that this transition is reverse proper ferroelastic in nature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Blue Horizontal Branch Stars with Multimodal Fusion

Blue Horizontal Branch stars (BHBs) are ideal tracers to probe the global structure of the milky Way (MW), and the increased size of the BHB star sample could be helpful to accurately calculate the MW's enclosed mass and kinematics. Large survey telescopes have produced an increasing number of astronomical images and spectra. However, traditional methods of identifying BHBs are limited in dealing with the large scale of astronomical data. A fast and efficient way of identifying BHBs can provide a more significant sample for further analysis and research. Therefore, in order to fully use the various data observed and further improve the identification accuracy of BHBs, we have innovatively proposed and implemented a Bi-level attention mechanism-based Transformer multimodal fusion model, called Bi-level Attention in the Transformer with Multimodality (BATMM). The model consists of a spectrum encoder, an image encoder, and a Transformer multimodal fusion module. The Transformer enables the effective fusion of data from two modalities, namely image and spectrum, by using the proposed Bi-level attention mechanism, including cross-attention and self-attention. As a result, the information from the different modalities complements each other, thus improving the accuracy of the identification of BHBs. The experimental results show that the F1 score of the proposed BATMM is 94.78%, which is 21.77% and 2.76% higher than the image and spectral unimodality, respectively. It is therefore demonstrated that higher identification accuracy of BHBs can be achieved by means of using data from multiple modalities and employing an efficient data fusion strategy.

79 ASTRONOMY AND ASTROPHYSICS↗

Crystallographic map: A general lattice and basis formalism enabling efficient and discretized exploration of crystallographic phase space

Three-dimensional lattices are fundamental to solid-state physics. The description of a lattice with an atomic basis constitutes the necessary information to predict solid phase properties and evolution. Here, we present an algorithm for systematically exploring crystallographic phase space. Further, coupled with ab initio techniques, such as density functional theory, this algorithm offers an approach for exploring and tuning materials behavior, with a broad range of potential applications: particularly martensitic phase transformations and materials stability.

36 MATERIALS SCIENCE↗

On two nucleons near unitarity with perturbative pions

We explore the impact of perturbative pions on the Unitarity Expansion in the two-nucleon S-waves of Chiral Effective Field Theory at next-to-next-to leading order (N 2 LO). Pion exchange explicitly breaks the nontrivial fixed point’s universality, i.e. invariance of S waves under both conformal and Wigner’s combined SU(4) spin–isospin transformations. On the other hand, Unitarity explicitly breaks chiral symmetry. The two seem incompatible in their respective exact-symmetry limits. χEFT with Perturbative Pions in the Unitarity Expansion resolves the apparent conflict in the Unitarity Window (phase shifts 45° ≲ δ(k) ≲ 135°), i.e. around momenta most relevant for low-energy nuclear systems. Its only LO scale is the scattering momentum; NLO adds only scattering length, effective range and non-iterated one-pion exchange (OPE); and N 2 LO only once-iterated OPE. Agreement in the 1 S 0 channel is very good.

Chiral symmetry↗

Foundations of Molecular 'Isotomics'

The naturally occurring rare isotopes are versions of common elements, such as hydrogen, carbon and oxygen, that contain a larger than usual number of neutrons in their atomic nuclei and therefore are higher in mass than the common atoms of that element. Isotopes exist for most elements and are found in most natural and synthetic materials, but are uneven in their distribution because chemical and physical processes are isotope-selective (e.g., a chemical reaction may proceed more rapidly for one isotope than for another). For this reason, abundances of isotopes in a material of interest can provide a record, or ‘signature’ of various features of that material’s origin and history. These signatures have been used in the geo, life, chemical and physical sciences in a wide variety of ways over close to 8 decades. However, many such applications struggle to reach unique interpretations of isotopic data because multiple factors combine to control a given sample’s overall isotopic content. That is, the factors controlling isotopic content are too numerous and complex to fully constrain from a simple measurement of a material’s isotope abundances. However, the distribution of isotopes within materials, at molecular scales potentially provides a vastly larger number and diversity of constraints on the chemical and physical processes that comprise a material’s history. The rare isotopes may be concentrated into one atomic position in a molecule relative to another, some proportion of molecules in a sample may contain two or more rare isotopes, and those multiply-isotope-substituted forms of molecules may also have uneven distributions of those isotopes across individual atomic sites. For these reasons, even small, seemingly simple molecules, such as sugars, amino acids or drug compounds, actually exist in a vast number of isotopically unique forms (often millions or more), and each one of those forms is in some sense an independent ‘vote’ on that sample’s history. This project has focused on opening this rich archive of information by enabling the creation of routinely and widely applicable ways of measuring and interpreting isotopic structures of molecules. This work has included the development of core technologies and analytical methods, advancing fundamental understanding of the physical and chemical properties of isotopic versions of molecules, and conducting proof of concept studies of illustrative geochemical, cosmochemical and forensic problems in order to show how these technologies, methods and principles come together to solve problems in new ways. A key to the success of this project was the adaptation of ‘Fourier transform mass spectrometry’ (FTMS) to the task of precisely measuring proportions of the rare, naturally occurring isotopic forms of molecules. FTMS is a highly specialized form of mass spectrometry that traps ions within magnetic or electrostatic cavities and, effectively, ‘listens’ (through registering of subtle electrical signals) to the harmonic signals they make while rapidly orbiting within those cavities. These signals have periods that are a function of their mass and strength (or ‘loudness’) that is proportional to their abundances. Thus, these signals constrain relative amounts of molecules that differ in their mass due to various isotopic substitutions. This technology has been essential to the identification of organic molecules in the life, chemical and environmental sciences for over 4 decades, but generally has lacked the control, stability and precision to meaningfully measure rare isotope forms of molecules. This project’s most fundamental contribution has been to modify FTMS, both in terms of hardware and methods, to enable such measurements. The raw data of molecular isotopic structure is tremendously voluminous and complex, so another important activity of this project has been developing the theoretical and data-science tools needed to interpret the data generated by this new form of isotopic measurement. A particularly challenging part of this task has been predicting molecular isotopic structure, as only through the comparison of measurements with predictions can we make progress on hypothesis driven research questions. We have attacked this this prediction task through a combination of first-principles chemical-physics models of the effects of isotope substitution on molecule properties and data-science models that permit us to generalize that chemical physics to cases that have not yet been studied by detailed chemical physics theory. The proof of concept applications we have pursued over the course of this study include biological reactions of amino acids and other biomolecules, non-biological synthesis of organic molecules in extra-terrestrial settings such as meteorites, petroleum geoscience questions concerning the origin and evolution of natural gas, oil and kerogen compounds, and forensic questions such as the sourcing of chemical weapons. The successes of these applications have laid the groundwork for the next phase of this field’s development, which will include larger scale and more ambitious studies of molecular isotopic structure as a means of diagnosing human diseases, such as cancer, and reconstructing detailed interpretations of the origin and evolution of organic molecules in modern and geological environments.

Cesar, Jaime↗

Transformer Analysis with ANSYS Maxwell and COMSOL

This is an extension of work described by Rodriguez et al . (2021). It continues analyses of a generic transformer design by Wes Greenwood. In this report, we summarize that work and add comparable results using the ANSYS Maxwell software (henceforward, “ANSYS”), and with COMSOL . We found the ANSYS and COMSOL calculations of inductance agreed well with previous results for simplified coils in air, and with a ferromagnetic core. We then describe the ANSYS and COMSOL approach and show results for a full transformer model based on magnetic field analyses. Finally, we present electrostatic analyses of E field enhancement, once again resolving individual wires. The purpose is to assess the electrostatic fields in order to locate where electric breakdown is likely to originate. We found the maximum enhancement between the secondary and either the primary or the tertiary at the end of the windings with a large potential difference.

42 ENGINEERING↗

Simulation of multicorrelated random processes using the FFT algorithm

A technique for the digital simulation of multicorrelated Gaussian random processes is described. This technique is based upon generating discrete frequency functions which correspond to the Fourier transform of the desired random processes, and then using the fast Fourier transform (FFT) algorithm to obtain the actual random processes. The main advantage of this method of simulation over other methods is computation time; it appears to be more than an order of magnitude faster than present methods of simulation. One of the main uses of multicorrelated simulated random processes is in solving nonlinear random vibration problems by numerical integration of the governing differential equations. The response of a nonlinear string to a distributed noise input is presented as an example.

Wittig, L. E.↗

Non-isothermal elastoviscoplastic analysis of planar curved beams

The development of a general mathematical model and solution methodologies, to examine the behavior of thin structural elements such as beams, rings, and arches, subjected to large nonisothermal elastoviscoplastic deformations is presented. Thus, geometric as well as material type nonlinearities of higher order are present in the analysis. For this purpose a complete true abinito rate theory of kinematics and kinetics for thin bodies, without any restriction on the magnitude of the transformation is presented. A previously formulated elasto-thermo-viscoplastic material constitutive law is employed in the analysis. The methodology is demonstrated through three different straight and curved beams problems.

Simitses, G. J.↗

Application of an improved Nelson-Nguyen analysis to eccentric, arbitrary profile liquid annular seals

An improved dynamic analysis for liquid annular seals with arbitrary profile based on a method, first proposed by Nelson and Nguyen, is presented. An improved first order solution that incorporates a continuous interpolation of perturbed quantities in the circumferential direction, is presented. The original method uses an approximation scheme for circumferential gradients, based on Fast Fourier Transforms (FFT). A simpler scheme based on cubic splines is found to be computationally more efficient with better convergence at higher eccentricities. A new approach of computing dynamic coefficients based on external specified load is introduced. This improved analysis is extended to account for arbitrarily varying seal profile in both axial and circumferential directions. An example case of an elliptical seal with varying degrees of axial curvature is analyzed. A case study based on actual operating clearances of an interstage seal of the Space Shuttle Main Engine High Pressure Oxygen Turbopump is presented.

Padavala, Satyasrinivas↗

Theory of the Lattice Boltzmann Equation: Symmetry properties of Discrete Velocity Sets

In the lattice Boltzmann equation, continuous particle velocity space is replaced by a finite dimensional discrete set. The number of linearly independent velocity moments in a lattice Boltzmann model cannot exceed the number of discrete velocities. Thus, finite dimensionality introduces linear dependencies among the moments that do not exist in the exact continuous theory. Given a discrete velocity set, it is important to know to exactly what order moments are free of these dependencies. Elementary group theory is applied to the solution of this problem. It is found that by decomposing the velocity set into subsets that transform among themselves under an appropriate symmetry group, it becomes relatively straightforward to assess the behavior of moments in the theory. The construction of some standard two- and three-dimensional models is reviewed from this viewpoint, and procedures for constructing some new higher dimensional models are suggested.

Rubinstein, Robert↗

How to Extend the Capabilities of Space Systems for Long Duration Space Exploration Systems

For sustainable Exploration Missions the need exists to assemble systems-of-systems in space, on the Moon or on other planetary surfaces. To fulfill this need new and innovative system architectures must be developed to be modularized and launched with the present lift capability of existing rocket technology. To enable long duration missions with minimal redundancy and mass, system software and hardware must be reconfigurable. This will enable increased functionality and multiple use of launched assets while providing the capability to quickly overcome components failures. Additional required capability includes the ability to dynamically demate and reassemble individual system elements during a mission in order to recover from failed hardware or to adapt to changes in mission requirements. To meet the Space Exploration goals of Interoperability and Reconfigurability, many challenges must be addressed to transform the traditional static avionics architectures into architectures with dynamic capabilities. The objective of this paper is to introduce concepts associated with reconfigurable computer systems; to review the various needs and challenges associated with reconfigurable avionics space systems; to provide an operational example that illustrates the application to both the Crew Exploration Vehicle and a collection of 'Habot-like' mobile surface elements; to summarize the approaches that address key challenges to the acceptance of a Flexible, Intelligent, Modular, Affordable and Reconfigurable avionics space system.

space assembly↗

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation

High fidelity simulations of grain formation in alloys are an indispensable tool for process-to-mechanical-properties characterization. Such simulations, however, can be computationally expensive as they require fine spatial and temporal discretizations. Their cost becomes an obstacle to parametric studies and ensemble runs and ultimately makes downstream tasks like optimal control and uncertainty quantification challenging. To enable such downstream tasks, we introduce GrainNN, an efficient and accurate reduced-order model for epitaxial grain growth in additive manufacturing conditions. GrainNN is a sequence-to-sequence long-short-term-memory (LSTM) deep neural network that evolves the dynamics of manually crafted features. Its innovations are (1) an attention mechanism with grain-microstructure-specific transformer architecture; and (2) an overlapping combination of several clones of the network to generalize to grain configurations that are different from those used for training. This design enables GrainNN to predict grain formation for unseen physical parameters, grain number, domain size and geometry. Furthermore, GrainNN not only reconstructs the quantities of interest but also can be pointwise accurate. In our numerical experiments, we use a polycrystalline phase field method to both generate the training data and assess GrainNN. For multiparametric, ensemble simulations with many grains, GrainNN can be orders of magnitude faster than phase field simulations, while delivering 5%–15% pointwise error. Additionally, this speedup includes the cost of the phase field simulations for generating training data.

36 MATERIALS SCIENCE↗