Search NASA⌕ Search

SEARCH · Search NASA

Results for “set of small ordered structures”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Neutron irradiation effects on domain wall mobility and reversibility in lead zirconate titanate thin films

The effects of neutron-induced damage on the ferroelectric properties of thin film lead zirconate titanate (PZT) were investigated. Two sets of PbZr{sub 0.52}Ti{sub 0.48}O{sub 3} films of varying initial quality were irradiated in a research nuclear reactor up to a maximum 1 MeV equivalent neutron fluence of (5.16 {+-} 0.03) Multiplication-Sign 10{sup 15} cm{sup -2}. Changes in domain wall mobility and reversibility were characterized by polarization-electric field measurements, Rayleigh analysis, and analysis of first order reversal curves (FORC). With increasing fluence, extrinsic contributions to the small-signal permittivity diminished. Additionally, redistribution of irreversible hysterons towards higher coercive fields was observed accompanied by the formation of a secondary hysteron peak following exposure to high fluence levels. The changes are attributed to the radiation-induced formation of defect dipoles and other charged defects, which serve as effective domain wall pinning sites. Differences in damage accumulation rates with initial film quality were observed between the film sets suggesting a dominance of pre-irradiation microstructure on changes in macroscopic switching behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nondestructive Photo-Cross-Linking of Microphase-Separated Diblock Polymers through Coumarin Dimerization

The effect of long-wavelength ultraviolet photocrosslinking on microphase-separated coumarin-containing block polymers was studied by photo-rheometry and small-angle X-ray scattering. This model system consisted of three photocrosslinkable diblock polymers of poly(methoxyethyl acrylate)-b-poly(hexyl methacrylate-co-coumarin methacrylate) with different volume fractions of the crosslinkable coumarin-containing block, which microphase separated into lamellar and cylindrical morphologies. All polymers stiffened upon exposure to 365 nm light, with much greater relative increases in moduli recorded for lamellae-forming polymers (ca. 3200% increase) compared to the cylinder-forming polymer (ca. 550% increase). Disordering transitions that were evident in uncrosslinked samples were no longer observed after crosslinking in the ordered state, and domain sizes were found to remain stable to heating. The photocrosslinking reaction only proceeded under active irradiation, indicating a high degree of spatiotemporal control over curing in this system. Finally, at constant concentration of couamarin within the crosslinkable block, the cure rate was largely independent of polymer composition, suggesting a constant local concentration of coumarin moieties within the segregated crosslinkable domains. Lastly, these findings establish a set of specific structure-property relationships governing the phase-selective photocrosslinking of diblock polymers that can guide the design of robust nanostructured materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A critical appraisal of the zero-multipole method: Structural, thermodynamic, dielectric, and dynamical properties of a water system

We performed extensive and strict tests for the reliability of the zero-multipole (summation) method (ZMM), which is a method for estimating the electrostatic interactions among charged particles in a classical physical system, by investigating a set of various physical quantities. This set covers a broad range of water properties, including the thermodynamic properties (pressure, excess chemical potential, constant volume/pressure heat capacity, isothermal compressibility, and thermal expansion coefficient), dielectric properties (dielectric constant and Kirkwood-G factor), dynamical properties (diffusion constant and viscosity), and the structural property (radial distribution function). We selected a bulk water system, the most important solvent, and applied the widely used TIP3P model to this test. In result, the ZMM works well for almost all cases, compared with the smooth particle mesh Ewald (SPME) method that was carefully optimized. In particular, at cut-off radius of 1.2 nm, the recommended choices of ZMM parameters for the TIP3P system are α ≤ 1 nm{sup −1} for the splitting parameter and l = 2 or l = 3 for the order of the multipole moment. We discussed the origin of the deviations of the ZMM and found that they are intimately related to the deviations of the equilibrated densities between the ZMM and SPME, while the magnitude of the density deviations is very small.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Reconstruction of the primordial power spectrum of curvature perturbations using multiple data sets

Detailed knowledge of the primordial power spectrum of curvature perturbations is essential both in order to elucidate the physical mechanism ('inflation') which generated it, and for estimating the cosmological parameters from observations of the cosmic microwave background and large-scale structure. Hence it ought to be extracted from such data in a model-independent manner, however this is difficult because relevant cosmological observables are given by a convolution of the primordial perturbations with some smoothing kernel which depends on both the assumed world model and the matter content of the universe. Moreover the deconvolution problem is ill-conditioned so a regularisation scheme must be employed to control error propagation. We demonstrate that 'Tikhonov regularisation' can robustly reconstruct the primordial spectrum from multiple cosmological data sets, a significant advantage being that both its uncertainty and resolution are then quantified. Using Monte Carlo simulations we investigate several regularisation parameter selection methods and find that generalised cross-validation and Mallow's C{sub p} method give optimal results. We apply our inversion procedure to data from the Wilkinson Microwave Anisotropy Probe, other ground-based small angular scale CMB experiments, and the Sloan Digital Sky Survey. The reconstructed spectrum (assuming the standard ΛCDM cosmology) is not scale-free but has an infrared cutoff at k∼<5 × 10{sup −4} Mpc{sup −1} (due to the anomalously low CMB quadrupole) and several features with ∼ 2σ significance at k/Mpc{sup −1} ∼ 0.0013–0.0025, 0.0362–0.0402 and 0.051–0.056, reflecting the 'WMAP glitches'. To test whether these are indeed real will require more accurate data, such as from the Planck satellite and new ground-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

TURBULENCE SETS THE INITIAL CONDITIONS FOR STAR FORMATION IN HIGH-PRESSURE ENVIRONMENTS

Despite the simplicity of theoretical models of supersonically turbulent, isothermal media, their predictions successfully match the observed gas structure and star formation activity within low-pressure (P/k < 10{sup 5} K cm{sup –3}) molecular clouds in the solar neighborhood. However, it is unknown whether or not these theories extend to clouds in high-pressure (P/k > 10{sup 7} K cm{sup –3}) environments, like those in the Galaxy's inner 200 pc central molecular zone (CMZ) and in the early universe. Here, we present Atacama Large Millimeter/submillimeter Array 3 mm dust continuum emission within a cloud, G0.253+0.016, which is immersed in the high-pressure environment of the CMZ. While the log-normal shape and dispersion of its column density probability distribution function (PDF) are strikingly similar to those of solar neighborhood clouds, there is one important quantitative difference: its mean column density is one to two orders of magnitude higher. Both the similarity and difference in the PDF compared to those derived from solar neighborhood clouds match predictions of turbulent cloud models given the high-pressure environment of the CMZ. The PDF shows a small deviation from log-normal at high column densities confirming the youth of G0.253+0.016. Its lack of star formation is consistent with the theoretically predicted, environmentally dependent volume density threshold for star formation which is orders of magnitude higher than that derived for solar neighborhood clouds. Our results provide the first empirical evidence that the current theoretical understanding of molecular cloud structure derived from the solar neighborhood also holds in high-pressure environments. We therefore suggest that these theories may be applicable to understand star formation in the early universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Stochastic embedding DFT: Theory and application to p -nitroaniline in water

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham density functional theory (DFT) method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here in this paper, we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected subsystem(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest, the properties are often determined by only a small subsystem. In stochastic embedding DFT, two sets of orbitals are used: a deterministic one associated with the embedded subspace and the rest, which is described by a stochastic set. The method agrees exactly with deterministic calculations in the limit of a large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with nonembedding stochastic DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A numerical method for deriving shape functions of nanoparticles for pair distribution function refinements

We report that in the structural refinement of nanoparticles, discrete atomistic modeling can be used for small nanocrystals (< 15 nm), but becomes computationally unfeasible at larger sizes, where instead unit-cell-based small-box modeling is usually employed. However, the effect of the nanocrystal's shape is often ignored or accounted for with a spherical model regardless of the actual shape due to the complexities of solving and implementing accurate shape effects. Recent advancements have provided a way to determine the shape function directly from a pair distribution function calculated from a discrete atomistic model of any given shape, including both regular polyhedra (e.g. cubes, spheres, octahedra) and anisotropic shapes (e.g. rods, discs, ellipsoids) [Olds et al. (2015). J. Appl. Cryst. 48, 1651–1659], although this approach is still limited to small size regimes due to computational demands. In order to accurately account for the effects of nanoparticle size and shape in small-box refinements, a numerical or analytical description is needed. This article presents a methodology to derive numerical approximations of nanoparticle shape functions by fitting to a training set of known shape functions; the numerical approximations can then be employed on larger sizes yielding a more accurate and physically meaningful refined nanoparticle size. Lastly, the method is demonstrated on a series of simulated and real data sets, and a table of pre-calculated shape function expressions for a selection of common shapes is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electronic structure and lattice dynamics of 1⁢𝑇−VSe 2 : Origin of the three-dimensional charge density wave

To characterize in detail the charge density wave (CDW) transition of 1⁢𝑇−VSe 2 , its electronic structure and lattice dynamics are comprehensively studied by means of x-ray diffraction, muon spectroscopy, angle resolved photoemission (ARPES), diffuse and inelastic x-ray scattering, and state-of-the-art first-principles density functional theory calculations. Resonant elastic x-ray scattering does not show any resonant enhancement at either V or Se, indicating that the CDW peak at the 𝐾 edges describes a purely structural modulation of the electronic ordering. ARPES experiments identify (i) a pseudogap at 𝑇 > 𝑇⁢ CDW , which leads to a depletion of the density of states in the ML-M'L' plane at 𝑇 < 𝑇⁢ CDW , and (ii) anomalies in the electronic dispersion reflecting a sizable impact of phonons on it. A diffuse scattering precursor, characteristic of soft phonons, is observed at room temperature (RT) and leads to the full collapse of the low-energy phonon (𝜔 1 ) with propagation vector (0.25 0 −0.3) r.l.u. Here, we show that the frequency and linewidth of this mode are anisotropic in momentum space, reflecting the momentum dependence of the electron-phonon interaction (EPI), hence demonstrating that the origin of the CDW is, to a much larger extent, due to the momentum dependent EPI with a small contribution from nesting. The pressure dependence of the 𝜔 1 soft mode remains nearly constant up to 13 GPa at RT, with only a modest softening before the transition to the high-pressure monoclinic C2/m phase. The wide set of experimental data is well captured by our state-of-the art first-principles anharmonic calculations with the inclusion of van der Waals corrections in the exchange-correlation functional. The comprehensive description of the electronic and dynamical properties of VSe 2 reported here adds important pieces of information to the understanding of the electronic modulations in the family of transition-metal dichalcogenides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Localizing Clinical Patterns of Blast Traumatic Brain Injury Through Computational Modeling and Simulation

Blast traumatic brain injury is ubiquitous in modern military conflict with significant morbidity and mortality. Yet the mechanism by which blast overpressure waves cause specific intracranial injury in humans remains unclear. Reviewing of both the clinical experience of neurointensivists and neurosurgeons who treated service members exposed to blast have revealed a pattern of injury to cerebral blood vessels, manifested as subarachnoid hemorrhage, pseudoaneurysm, and early diffuse cerebral edema. Additionally, a seminal neuropathologic case series of victims of blast traumatic brain injury (TBI) showed unique astroglial scarring patterns at the following tissue interfaces: subpial glial plate, perivascular, periventricular, and cerebral gray-white interface. The uniting feature of both the clinical and neuropathologic findings in blast TBI is the co-location of injury to material interfaces, be it solid-fluid or solid-solid interface. This motivates the hypothesis that blast TBI is an injury at the intracranial mechanical interfaces. In order to investigate the intracranial interface dynamics, we performed a novel set of computational simulations using a model human head simplified but containing models of gyri, sulci, cerebrospinal fluid (CSF), ventricles, and vasculature with high spatial resolution of the mechanical interfaces. Simulations were performed within a hybrid Eulerian—Lagrangian simulation suite (CTH coupled via Zapotec to Sierra Mechanics). Because of the large computational meshes, simulations required high performance computing resources. Twenty simulations were performed across multiple exposure scenarios—overpressures of 150, 250, and 500 kPa with 1 ms overpressure durations—for multiple blast exposures (front blast, side blast, and wall blast) across large variations in material model parameters (brain shear properties, skull elastic moduli). All simulations predict fluid cavitation within CSF (where intracerebral vasculature reside) with cavitation occurring deep and diffusely into cerebral sulci. These cavitation events are adjacent to high interface strain rates at the subpial glial plate. Larger overpressure simulations (250 and 500kPa) demonstrated intraventricular cavitation—also associated with adjacent high periventricular strain rates. Additionally, models of embedded intraparenchymal vascular structures—with diameters as small as 0.6 mm—predicted intravascular cavitation with adjacent high perivascular strain rates. The co-location of local maxima of strain rates near several of the regions that appear to be preferentially damaged in blast TBI (vascular structures, subpial glial plate, perivascular regions, and periventricular regions) suggest that intracranial interface dynamics may be important in understanding how blast overpressures leads to intracranial injury.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

SASI ACTIVITY IN THREE-DIMENSIONAL NEUTRINO-HYDRODYNAMICS SIMULATIONS OF SUPERNOVA CORES

The relevance of the standing accretion shock instability (SASI) compared to neutrino-driven convection in three-dimensional (3D) supernova-core environments is still highly controversial. Studying a 27 M{sub Sun} progenitor, we demonstrate, for the first time, that violent SASI activity can develop in 3D simulations with detailed neutrino transport despite the presence of convection. This result was obtained with the PROMETHEUS-VERTEX code with the same sophisticated neutrino treatment so far used only in one-dimensional and two-dimensional (2D) models. While buoyant plumes initially determine the nonradial mass motions in the postshock layer, bipolar shock sloshing with growing amplitude sets in during a phase of shock retraction and turns into a violent spiral mode whose growth is only quenched when the infall of the Si/SiO interface leads to strong shock expansion in response to a dramatic decrease of the mass accretion rate. In the phase of large-amplitude SASI sloshing and spiral motions, the postshock layer exhibits nonradial deformation dominated by the lowest-order spherical harmonics (l = 1, m = 0, {+-}1) in distinct contrast to the higher multipole structures associated with neutrino-driven convection. We find that the SASI amplitudes, shock asymmetry, and nonradial kinetic energy in three dimensions can exceed those of the corresponding 2D case during extended periods of the evolution. We also perform parameterized 3D simulations of a 25 M{sub Sun} progenitor, using a simplified, gray neutrino transport scheme, an axis-free Yin-Yang grid, and different amplitudes of random seed perturbations. They confirm the importance of the SASI for another progenitor, its independence of the choice of spherical grid, and its preferred growth for fast accretion flows connected to small shock radii and compact proto-neutron stars as previously found in 2D setups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Magnetic topological quantum chemistry

For over 100 years, the group-theoretic characterization of crystalline solids has provided the foundational language for diverse problems in physics and chemistry. However, the group theory of crystals with commensurate magnetic order has remained incomplete for the past 70 years, due to the complicated symmetries of magnetic crystals. In this work, we complete the 100-year-old problem of crystalline group theory by deriving the small corepresentations, momentum stars, compatibility relations, and magnetic elementary band corepresentations of the 1,421 magnetic space groups (MSGs), which we have made freely accessible through tools on the Bilbao Crystallographic Server. We extend Topological Quantum Chemistry to the MSGs to form a complete, real-space theory of band topology in magnetic and nonmagnetic crystalline solids – Magnetic Topological Quantum Chemistry (MTQC). Using MTQC, we derive the complete set of symmetry-based indicators of electronic band topology, for which we identify symmetry-respecting bulk and anomalous surface and hinge states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Revisiting Five Years of CASMI Contests with EPA Identification Tools

Software applications for high resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) continue to enhance chemical identification capabilities. Given the variety of available applications, determining the most fit-for-purpose tools and workflows can be difficult. The Critical Assessment of Small Molecule Identification (CASMI) contests were initiated in 2012 to provide a means to evaluate compound identification tools on a standardized set of blinded tandem mass spectrometry (MS/MS) data. Five CASMI contests have resulted in recommendations, publications, and invaluable datasets for practitioners of HRMS-based screening studies. The US Environmental Protection Agency’s (EPA) CompTox Chemicals Dashboard is now recognized as a valuable resource for compound identification in NTA studies. However, this application was too new and immature in functionality to participate in the five previous CASMI contests. In this work, we performed compound identification on all five CASMI contest datasets using Dashboard tools and data in order to critically evaluate Dashboard performance relative to that of other applications. CASMI data was accessed via the CASMI webpage and processed for use in our spectral matching and identification workflow. Relative to applications used by former contest participants, our tools, data, and workflow performed well, placing more challenge compounds in the top five of ranked candidates than did the winners of three contest years and tying in a fourth. In addition, we conducted an in-depth review of the CASMI structure sets and made these reviewed sets available via the Dashboard. Our results suggest that Dashboard data and tools would enhance chemical identification capabilities for practitioners of HRMS-based NTA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Minimally Mutated HIV-1 Broadly Neutralizing Antibodies to Guide Reductionist Vaccine Design

An optimal HIV vaccine should induce broadly neutralizing antibodies (bnAbs) that neutralize diverse viral strains and subtypes. However, potent bnAbs develop in only a small fraction of HIV-infected individuals, all contain rare features such as extensive mutation, insertions, deletions, and/or long complementarity-determining regions, and some are polyreactive, casting doubt on whether bnAbs to HIV can be reliably induced by vaccination. We engineered two potent VRC01-class bnAbs that minimized rare features. According to a quantitative features frequency analysis, the set of features for one of these minimally mutated bnAbs compared favorably with all 68 HIV bnAbs analyzed and was similar to antibodies elicited by common vaccines. This same minimally mutated bnAb lacked polyreactivity in four different assays. We then divided the minimal mutations into spatial clusters and dissected the epitope components interacting with those clusters, by mutational and crystallographic analyses coupled with neutralization assays. Finally, by synthesizing available data, we developed a working-concept boosting strategy to select the mutation clusters in a logical order following a germline-targeting prime. We have thus developed potent HIV bnAbs that may be more tractable vaccine goals compared to existing bnAbs, and we have proposed a strategy to elicit them. This reductionist approach to vaccine design, guided by antibody and antigen structure, could be applied to design candidate vaccines for other HIV bnAbs or protective Abs against other pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Fast Magnetic Reconnection: “Ideal” Tearing and the Hall Effect

One of the main questions in magnetic reconnection is the origin of triggering behavior with on/off properties that, once it is activated, accounts for the fast magnetic energy conversion to kinetic and thermal energies at the heart of explosive events in astrophysical and laboratory plasmas. Over the past decade, progress has been made on the initiation of fast reconnection via the plasmoid instability and what has been called “ideal” tearing, which sets in once current sheets thin to a critical inverse aspect ratio (a/L){sub c}. As shown by Pucci and Velli, at (a/L){sub c}∼S{sup −1/3}, the timescale for the instability to develop becomes of the order of the Alfvén time and independent of the Lundquist number (here defined in terms of current sheet length L). However, given the large values of S in natural plasmas, this transition might occur for thicknesses of the inner resistive singular layer that are comparable to the ion inertial length d {sub i}. When this occurs, Hall currents produce a three-dimensional quadrupole structure of the magnetic field, and the dispersive waves introduced by the Hall effect accelerate the instability. Here we present a linear study showing how the “ideal” tearing mode critical aspect ratio is modified when Hall effects are taken into account, including more general scaling laws of the growth rates in terms of sheet inverse aspect ratio: the critical inverse aspect ratio is amended to a/L≃(di/L){sup 0.29}(1/S){sup 0.19}, at which point the instability growth rate becomes Alfvénic and does not depend on either of the (small) parameters d{sub i}/L,1/S. We discuss the implications of this generalized triggering aspect ratio for recently developed phase diagrams of magnetic reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Conceptual Framework to Enable Early Warning of Relevant Phenomena (Emerging Phenomena and Big Data)

Graphs are commonly used to represent natural and man-made dynamic systems such as food webs, economic and social networks, gene regulation, and the internet. We describe a conceptual framework to enable early warning of relevant phenomena that is based on an artificial time-based, evolving network graph that can give rise to one or more recognizable structures. We propose to quantify the dynamics using the method of delays through Takens Theorem to produce another graph we call the Phase Graph. The Phase Graph enables us to quantify changes of the system that form a topology in phase space. Our proposed method is unique because it is based on dynamic system analysis that incorporates Takens Theorem, Graph Theory, and Franzosi-Pettini (F-P) theorem about topology and phase transitions. The F-P Theorem states that the necessary condition for phase transition is a change in the topology. By detecting a change in the topology that we represent as a set of M-order Phase Graphs, we conclude a corresponding change in the phase of the system. The onset of this phase change enables early warning of emerging relevant phenomena.

complexity↗