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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Holographic Imaging of Evolving Laser-Plasma Structures

In the 1870s, English photographer Eadweard Muybridge captured motion pictures within one cycle of a horse’s gallop, which settled a hotly debated question of his time by showing that the horse became temporarily airborne. In the 1940s, Manhattan project photographer Berlin Brixner captured a nuclear blast at a million frames per second, and resolved a dispute about the explosion’s shape and speed. In this project, we developed methods to capture detailed motion pictures of evolving, light-velocity objects created by a laser pulse propagating through matter. These objects include electron density waves used to accelerate charged particles, laser-induced refractive index changes used for micromachining, and ionization tracks used for atmospheric chemical analysis, guide star creation and ranging. Our “movies”, like Muybridge’s and Brixner’s, are obtained in one shot, since the laser-created objects of interest are insufficiently repeatable for accurate stroboscopic imaging. Our high-speed photographs have begun to resolve controversies about how laser-created objects form and evolve, questions that previously could be addressed only by intensive computer simulations based on estimated initial conditions. Resolving such questions helps develop better tabletop particle accelerators, atmospheric ranging devices and many other applications of laser-matter interactions. Our photographic methods all begin by splitting one or more “probe” pulses from the laser pulse that creates the light-speed object. A probe illuminates the object and obtains information about its structure without altering it. We developed three single-shot visualization methods that differ in how the probes interact with the object of interest or are recorded. (1) Frequency-Domain Holography (FDH). In FDH, there are 2 probes, like “object” and “reference” beams in conventional holography. Our “object” probe surrounds the light-speed object, like a fleas swarming around a sprinting animal. The object modifies the probe, imprinting information about its structure. Meanwhile, our “reference” probe co-propagates ahead of the object, free of its influence. After the interaction, object and reference combine to record a hologram. For technical reasons, our recording device is a spectrometer (a frequency-measuring device), hence the name “frequency-domain” holography. We read the hologram electronically to obtain a “snapshot” of the object’s average structure as it transits the medium. Our published work shows numerous snapshots of electron density waves (“laser wakes”) in ionized gas (“plasma”), analogous to a water wake behind a boat. Such waves are the basis of tabletop particle accelerators, in which charged particles surf on the light-speed wave, gaining energy. Comparing our snapshots to computer simulations deepens understanding of laser wakes. FDH takes snapshots of objects that are quasi-static --- i.e. like Muybridge’s horse standing still on a treadmill. If the object changes shape, FDH images blur, as when a subject moves while a camera shutter is open. Many laser-generated objects of interest do evolve as they propagate. To overcome this limit of FDH, we developed .... (2) Frequency-Domain Tomography (FDT). In FDT, 5 to 10 probe pulses are fired simultaneously across the object’s path at different angles, like a crossfire of bullets. The object imprints a “streaked” record of its evolution on each probe, which we record as in FDH, then recover a multi-frame “movie” of the object’s evolving structure using algorithms of computerized tomography. When propagation distance exceeds a few millimeters, reconstructed FDT images distort. This is because the lenses that image probes to detector have limited depth of field, like cameras that cannot focus simultaneously on both nearby and distant objects. But some laser-generated objects of interest propagate over meters. For these applications we developed … (3) Multi-Object-Plane Phase-Contrast Imaging (MOP-PCI). In MOP-PCI, we image FDT-like probes to the detector from multiple “object planes” --- like recording an event simultaneously with several cameras, some focused on nearby, others on distant, objects. To increase sensitivity, we exploit a phase-contrast imaging technique developed by Dutch Nobel laureate Fritz Zernike in the 1930s. Using MOP-PCI we recorded single-shot movies of laser pulse tracks through more than 10 cm of air. We plan to record images of meter-long tracks of electron bunches propagating through plasma in an experiment at the Stanford Linear Accelerator Center (SLAC). This will help SLAC scientists understand, optimize and scale small plasma-based particle accelerators that have applications in medicine, industry, materials science and high-energy physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Final Report on Subcontract B605152. Multigrid Methods for Systems of PDEs

The project team has continued with work on developing aggressive coarsening techniques for AMG methods. Of particular interest is the idea to use aggressive coarsening with polynomial smoothing. Using local Fourier analysis the optimal values for the parameters involved in defining the polynomial smoothers are determined automatically in a way to achieve fast convergence of cycles with aggressive coarsening. Numerical tests have the sharpness of the theoretical results. The methods are highly parallelizable and efficient multigrid algorithms on structured and semistructured grids in two and three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗

Radioactive Decay Computation with a Graph Approach for Solving a Linear Dynamic System

ABSTRACT: This article gives two graph-based algorithms for radioactive decay computation. The first algorithm identifies the connected components of the graph induced from the given radioactive decay dynamics to reduce the size of the problem. The solutions are derived over the precalculated connected components, respectively and independently. The second algorithm utilizes acyclic structure of radioactive decay dynamics. The algorithm evaluates the reachable vertices of the induced system graph from the initially activated vertices and finds the minimal set of starting vertices populating the entire reachable vertices. Then, the decay calculations are performed over the reachable vertices from the identified minimal starting vertices, respectively, with the partitioned initial value over the reachable vertices. A formal argument is given to show that the proposed graph inspired divide and conquer calculation methods perform the intended radioactive decay calculation. Empirical efforts comparing the proposed radioactive decay calculation algorithms are presented.

42 ENGINEERING↗

Vectorization of Random Number Generation and Reproducibility of Concurrent Particle Transport Simulation

Efficient random number generation with high quality statistical properties and exact reproducibility of Monte Carlo simulations are important requirements in many areas of computational science. VecRNG is a package providing pseudo-random number generation (pRNG) in the context of a new library VecMath. This library bundles up several general-purpose mathematical utilities, data structures, and algorithms having both SIMD and SIMT (GPUs) support based on VecCore.~Several state-of-the-art RNG algorithms are implemented as kernels supporting parallel generation of random numbers in scalar, vector, and Cuda workflows. In this report, we will present design considerations, implementation details, and computing performance of parallel pRNG engines on both CPU and GPU. Reproducibility of propagating multiple particles in parallel for HEP event simulation is demonstrated, using GeantV-based examples, for both sequential and fine-grain track-level concurrent simulation wor kflows. Strategies for efficient uses of vectorized pRNG and non-overlapping streams of random number sequences in concurrent computing environments is discussed as well.

Jun, S. Y.↗

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗

High-Level Synthesis of Irregular Applications: A Case Study on Influence Maximization

The Influence Maximization problem is the problem of identifying a small cohort of actors from a broader population that, when initially activated in a diffusion process, are expected to result in a large number of activations in the population. While the problem is known to be NP-hard, several approximation algorithms have been devised by leveraging its submodular structure. While these algorithms are theoretically efficient, they are computationally very expensive in practice. This work advances the current state-of-the-art parallelization scheme for the IMM algorithm by devising the adoption of custom hardware accelerators implemented on FPGAs by leveraging High Level Synthesis from OpenCL. We study the performance of our proposed approach by exploring optimizations tailored at improving the parallel efficiency of the accelerators and highlight their effects and limitations in accelerating complex graph analytic applications. Our experimental evaluation shows that FPGA acceleration can improve the performance of the LT diffusion model up to 1.72x for the entire application and up to 2.90x for its most important kernel with respect to a CPU only parallel execution. The FPGA acceleration of the LT model shows also a 1.54x reduction in energy consumption when compared to a parallel CPU only run.

Neff, Reece W.↗

Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I

All chemical forms of energy and oxygen on Earth are generated via photosynthesis where light energy is converted into redox energy by two photosystems (PS I and PS II). There is an increasing number of PS I 3D structures deposited in the Protein Data Bank (PDB). The Triangular Spatial Relationship (TSR)-based algorithm converts 3D structures into integers (TSR keys). A comprehensive study was conducted, by taking advantage of the PS I 3D structures and the TSR-based algorithm, to answer three questions: (i) Are electron cofactors including P700, A -1 and A 0 , which are chemically identical chlorophylls, structurally different? (ii) There are two electron transfer chains (A and B branches) in PS I. Are the cofactors on both branches structurally different? (iii) Are the amino acids in cofactor binding sites structurally different from those not in cofactor binding sites? The key contributions and important findings include: (i) a novel TSR-based method for representing 3D structures of pigments as well as for quantifying pigment structures was developed; (ii) the results revealed that the redox cofactor, P700, are structurally conserved and different from other redox factors. Similar situations were also observed for both A -1 and A 0 ; (iii) the results demonstrated structural differences between A and B branches for the redox cofactors P700, A -1 , A 0 and A 1 as well as their cofactor binding sites; (iv) the tryptophan residues close to A 0 and A 1 are structurally conserved; (v) The TSR-based method outperforms the Root Mean Square Deviation (RMSD) and the Ultrafast Shape Recognition (USR) methods. The structural analyses of redox cofactors and their binding sites provide a foundation for understanding the unique chemical and physical properties of each redox cofactor in PS I, which are essential for modulating the rate and direction of energy and electron transfers.

59 BASIC BIOLOGICAL SCIENCES↗

A novel imaging technique for measuring kinematics of light-weight flexible structures

A new imaging algorithm is proposed to capture the kinematics of flexible, thin, light structures including frequencies and motion amplitudes for real time analysis. The studied case is a thin flexible beam that is preset at different angles of attack in a wind tunnel. As the angle of attack is increased beyond a critical value, the beam was observed to undergo a static deflection that is ensued by limit cycle oscillations. Imaging analysis of the beam vibrations shows that the motion consists of a superposition of the bending and torsion modes. The proposed algorithm was able to capture the oscillation amplitudes as well as the frequencies of both bending and torsion modes. The analysis results are validated through comparison with measurements from a piezoelectric sensor that is attached to the beam at its root.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗

Identify Structural Flaw Location and Type with an Inverse Algorithm of Resonance Inspection

To evaluate the fitness-for-service of a structural component and to quantify its remaining useful life, aging and service-induced structural flaws must be quantitatively determined in service or during scheduled maintenance shutdowns. Resonance inspection (RI), a non-destructive evaluation (NDE) technique, distinguishes the anomalous parts from the good parts based on changes in the natural frequency spectra. Known for its numerous advantages, i.e., low inspection cost, high testing speed, and broad applicability to complex structures, RI has been widely used in the automobile industry for quality inspection. However, compared to other contemporary direct visualization-based NDE methods, a more widespread application of RI faces a fundamental challenge because such technology is unable to quantify the flaw details, e.g. location, dimensions, and types. In this study, the applicability of a maximum correlation-based inverse RI algorithm developed by the authors is further studied for various flaw cases. It is demonstrated that a variety of common structural flaws, i.e. stiffness degradation, voids, and cracks, can be accurately retrieved by this algorithm even when multiple different types of flaws coexist. The quantitative relations between the damage identification results and the flaw characteristics are also developed to assist the evaluation of the actual state of health of the engineering structures.

non-destructive evaluation, resonance inspection, ↗

ROY Revisited, Again: The Eighth Solved Structure

X-ray powder diffraction and crystal structure prediction (CSP) algorithms were used in synergy to establish the crystal structure of the eighth polymorph of 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (ROY), form R05. R05 crystallizes in the monoclinic space group P2_1 with lattice parameters a = 11.479(4) Å, b = 11.030(1) Å, c = 10.840(6) Å, β = 118.23(1)°. This is both the first acentric ROY polymorph, and the first with Z' > 1. The torsion angles defined by the S-C-N-C atom sequence of each molecule in the asymmetric unit are -34.0° and 44.9°. These angles fall between those previously determined for the red and orange forms of ROY. Hirshfeld surface analysis was employed to understand the crystal packing and intermolecular interactions in R05 and an updated energy stability ranking was determined using computational methods. Finally, although the application of CSP was critical to the structure solution of R05, energy stability rankings determined using a series of DFT vdW-inclusive models substantially deviate from experiment, indicating that ROY polymorphism continues to be a challenge for CSP.

36 MATERIALS SCIENCE↗

Unexpected series of regular frequency spacing of δ Scuti stars in the non-asymptotic regime - I. The methodology

In this study, a sequence search method was developed to search the regular frequency spacing in δ Scuti stars through visual inspection and an algorithmic search. We searched for sequences of quasi-equally spaced frequencies, containing at least four members per sequence, in 90 δ Scuti stars observed by CoRoT. We found an unexpectedly large number of independent series of regular frequency spacing in 77 δ Scuti stars (from one to eight sequences) in the non-asymptotic regime. We introduce the sequence search method presenting the sequences and echelle diagram of CoRoT 102675756 and the structure of the algorithmic search. Four sequences (echelle ridges) were found in the 5–21 d –1 region where the pairs of the sequences are shifted (between 0.5 and 0.59 d –1 ) by twice the value of the estimated rotational splitting frequency (0.269 d –1 ). The general conclusions for the whole sample are also presented in this paper. The statistics of the spacings derived by the sequence search method, by FT (Fourier transform of the frequencies), and the statistics of the shifts are also compared. In many stars more than one almost equally valid spacing appeared. The model frequencies of FG Vir and their rotationally split components were used to formulate the possible explanation that one spacing is the large separation while the other is the sum of the large separation and the rotational frequency. In CoRoT 102675756, the two spacings (2.249 and 1.977 d –1 ) are in better agreement with the sum of a possible 1.710 d –1 large separation and two or one times, respectively, the value of the rotational frequency.

79 ASTRONOMY AND ASTROPHYSICS↗

ExaSP2

ExaSP2 is a reference implementation of typical linear algebra algorithms and workloads for a quantum molecular dynamics (QMD) electronic structure code. The algorithm is based on a recursive second-order Fermi-Operator expansion method (SP2) and is tailored for density functional based tight-binding calculations of material systems.

Negre, Christian↗

Symmetry relation database and its application to ferroelectric materials discovery

To investigate the displacive phase transition at the atomic scale, we have implemented a numerical algorithm to automate the detection of the symmetry relations between any two candidate crystal structures. Using this algorithm, here we systematically screen all possible polar–nonpolar structure pairs from the Materials Project database and establish a library of ~4500 pairs that can be connected through a continuous phase transition with small atomic displacements. From this database, we identify several new ferroelectric materials. In addition, the database may also be used in other areas, such as material structure prediction and new materials discovery.

36 MATERIALS SCIENCE↗

sp3-hybridized framework structure of group-14 elements discovered by genetic algorithm

Group-14 elements, including C, Si, Ge, and Sn, can form various stable and metastable structures. Finding new metastable structures of group-14 elements with desirable physical properties for new technological applications has attracted a lot of interest. Using a genetic algorithm, we discovered a new low-energy metastable distorted sp3-hybridized framework structure of the group-14 elements. It has P42/mnm symmetry with 12 atoms per unit cell. The void volume of this structure is as large as 139.7Å3 for Si P42/mnm, and it can be used for gas or metal-atom encapsulation. Band-structure calculations show that P42/mnm structures of Si and Ge are semiconducting with energy band gaps close to the optimal values for optoelectronic or photovoltaic applications. With metal-atom encapsulation, the P42/mnm structure would also be a candidate for rattling-mediated superconducting or used as thermoelectric materials.

36 MATERIALS SCIENCE↗

HACC: Simulating sky surveys on state-of-the-art supercomputing architectures

Current and future surveys of large-scale cosmic structure are associated with a massive and complex datastream to study, characterize, and ultimately understand the physics behind the two major components of the ‘Dark Universe’, dark energy and dark matter. In addition, the surveys also probe primordial perturbations and carry out fundamental measurements, such as determining the sum of neutrino masses. Large-scale simulations of structure formation in the Universe play a critical role in the interpretation of the data and extraction of the physics of interest. Just as survey instruments continue to grow in size and complexity, so do the supercomputers that enable these simulations. In this paper, we report on HACC (Hardware/Hybrid Accelerated Cosmology Code), a recently developed and evolving cosmology N-body code framework, designed to run efficiently on diverse computing architectures and to scale to millions of cores and beyond. HACC can run on all current supercomputer architectures and supports a variety of programming models and algorithms. It has been demonstrated at scale on Cell- and GPU-accelerated systems, standard multi-core node clusters, and Blue Gene systems. HACC’s design allows for ease of portability, and at the same time, high levels of sustained performance on the fastest supercomputers available. We present a description of the design philosophy of HACC, the underlying algorithms and code structure, and outline implementation details for several specific architectures. We show selected accuracy and performance results from some of the largest high resolution cosmological simulations so far performed, including benchmarks evolving more than 3.6 trillion particles.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning and serving of discrete field theories

A method for machine learning and serving of discrete field theories in physics is developed. The learning algorithm trains a discrete field theory from a set of observational data on a spacetime lattice, and the serving algorithm uses the learned discrete field theory to predict new observations of the field for new boundary and initial conditions. The approach of learning discrete field theories overcomes the difficulties associated with learning continuous theories by artificial intelligence. The serving algorithm of discrete field theories belongs to the family of structure-preserving geometric algorithms, which have been proven to be superior to the conventional algorithms based on discretization of differential equations. The effectiveness of the method and algorithms developed is demonstrated using the examples of nonlinear oscillations and the Kepler problem. In particular, the learning algorithm learns a discrete field theory from a set of data of planetary orbits similar to what Kepler inherited from Tycho Brahe in 1601, and the serving algorithm correctly predicts other planetary orbits, including parabolic and hyperbolic escaping orbits, of the solar system without learning or knowing Newton’s laws of motion and universal gravitation. The proposed algorithms are expected to be applicable when the effects of special relativity and general relativity are important.

97 MATHEMATICS AND COMPUTING↗

Modeling and Algorithmic Approaches to Constitutively-Complex, Micro-structured Fluids

The team for this Project made significant progress on modeling and algorithmic approaches to hydrodynamics of fluids with complex microstructure. Our advances are broken down into modeling and algorithmic approaches. In experiments a driven magnetic bead in a complex fluid accelerates out of the Stokes regime and settles into another apparent linear response regime. The modeling explains the take-off as a deformation of entanglements, and the longtime behavior is a nonlinear, far-from-equilibrium property. Furthermore, the model has predictive value, as we can tune microstructural properties relative to the magnetic force applied to the bead to exhibit all possible behaviors. Wave-theoretic probes of complex fluids have been extended in two significant directions, to small volumes and the nonlinear regime. Heterogeneous stress and strain features that lie beyond experimental capability were studied. It was shown that nonlinear penetration of boundary stress in confined viscoelastic fluids is not monotone, indicating the possibility of interlacing layers of linear and nonlinear behavior, and thus layers of variable viscosity. Models, algorithms, and codes were developed and simulations performed leading to phase diagrams of nanorod dispersion hydrodynamics in parallel shear cells and confined cavities representative of film and membrane processing conditions. Hydrodynamic codes for polymeric fluids are extended to include coupling between microscopic and macroscopic models, and to the strongly nonlinear regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗