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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Measurement of Two-Point Energy Correlators within Jets in 𝑝 + 𝑝 Collisions at $\sqrt{𝑠}$ = 200 GeV

Hard-scattered partons ejected from high-energy proton-proton collisions undergo parton shower and hadronization, resulting in collimated collections of particles that are clustered into jets. A substructure observable that highlights the transition between the perturbative and nonperturbative regimes of jet evolution in terms of the angle between two particles is the two-point energy correlator (EEC). In this Letter, the first measurement of the EEC at RHIC is presented, using data taken from 200 GeV 𝑝 + 𝑝 collisions by the STAR experiment. The EEC is measured both for all the pairs of particles in jets and separately for pairs with like and opposite electric charges. These measurements demonstrate that the transition between perturbative and nonperturbative effects occurs within an angular region that is consistent with expectations of a universal hadronization regime that scales with jet momentum for a given initiator flavor. Additionally, a deviation from Monte Carlo predictions at small angles in the charge-selected sample could result from mechanics of hadronization not fully captured by current models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2010

With phases: how two wrongs can sometimes make a right

Combining experimental phases and those from refinement of very incomplete models significantly improves electron-density maps. In isolation, both weak isomorphous/anomalous difference signals from heavy-atom derivatization and phases from partial molecular-replacement solutions for a subset of the asymmetric unit often fall short of producing interpretable electron-density maps. Phases generated from very partial molecular-replacement models (if generated carefully) can be used to reliably locate heavy-atom sites, even if the signal is not sufficiently strong to allow robust finding of the sites using Patterson interpretation or direct methods. Additional advantages are that using molecular-replacement phases to define the heavy-atom substructure avoids the need for subsequent hand determination and/or origin-choice reconciliation and that the partial model can be used to aid the mask determination during solvent flattening. Two case studies are presented in which it was only by combining experimental and molecular-replacement phasing approaches that the crystal structures could be determined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

The magic triangle goes MAD: experimental phasing with a bromine derivative

5-Amino-2, 4, 6-tribromoisophthalic acid is used as a phasing tool for protein structure determination by MAD phasing. It is the second representative of a novel class of compounds for heavy-atom derivatization that combine heavy atoms with amino and carboxyl groups for binding to proteins. Experimental phasing is an essential technique for the solution of macromolecular structures. Since many heavy-atom ion soaks suffer from nonspecific binding, a novel class of compounds has been developed that combines heavy atoms with functional groups for binding to proteins. The phasing tool 5-amino-2, 4, 6-tribromoisophthalic acid (B3C) contains three functional groups (two carboxylate groups and one amino group) that interact with proteins via hydrogen bonds. Three Br atoms suitable for anomalous dispersion phasing are arranged in an equilateral triangle and are thus readily identified in the heavy-atom substructure. B3C was incorporated into proteinase K and a multiwavelength anomalous dispersion (MAD) experiment at the Br K edge was successfully carried out. Radiation damage to the bromine–carbon bond was investigated. A comparison with the phasing tool I3C that contains three I atoms for single-wavelength anomalous dispersion (SAD) phasing was also carried out.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

Introduction to phasing

This introductory paper to the CCP4 weekend on experimental phasing introduces the concept of the ‘phase problem’ for non-experts. Modern methods of phasing are explored, including some recent examples that can be downloaded as tutorials. When collecting X-ray diffraction data from a crystal, we measure the intensities of the diffracted waves scattered from a series of planes that we can imagine slicing through the crystal in all directions. From these intensities we derive the amplitudes of the scattered waves, but in the experiment we lose the phase information; that is, how we offset these waves when we add them together to reconstruct an image of our molecule. This is generally known as the ‘phase problem’. We can only derive the phases from some knowledge of the molecular structure. In small-molecule crystallography, some basic assumptions about atomicity give rise to relationships between the amplitudes from which phase information can be extracted. In protein crystallography, these ab initio methods can only be used in the rare cases in which there are data to at least 1.2 Å resolution. For the majority of cases in protein crystallography phases are derived either by using the atomic coordinates of a structurally similar protein (molecular replacement) or by finding the positions of heavy atoms that are intrinsic to the protein or that have been added (methods such as MIR, MIRAS, SIR, SIRAS, MAD, SAD or combinations of these). The pioneering work of Perutz, Kendrew, Blow, Crick and others developed the methods of isomorphous replacement: adding electron-dense atoms to the protein without disturbing the protein structure. Nowadays, methods from small-molecule crystallography can be used to find the heavy-atom substructure and the phases for the whole protein can be bootstrapped from this prior knowledge. More recently, improved X-ray sources, detectors and software have led to the routine use of anomalous scattering to obtain phase information from either incorporated selenium or intrinsic sulfurs. In the best cases, only a single set of X-ray data (SAD) is required to provide the positions of the anomalous scatters, which together with density-modification procedures can reveal the structure of the complete protein.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Multi-crystal Anomalous Diffraction for Low-resolution Macromolecular Phasing

Multiwavelength anomalous diffraction (MAD) and single-wavelength anomalous diffraction (SAD) are the two most commonly used methods for de novo determination of macromolecular structures. Both methods rely on the accurate extraction of anomalous signals; however, because of factors such as poor intrinsic order, radiation damage, inadequate anomalous scatterers, poor diffraction quality and other noise-causing factors, the anomalous signal from a single crystal is not always good enough for structure solution. In this study, procedures for extracting more accurate anomalous signals by merging data from multiple crystals are devised and tested. SAD phasing tests were made with a relatively large (1456 ordered residues) poorly diffracting (d{sub min} = 3.5 {angstrom}) selenomethionyl protein (20 Se). It is quantified that the anomalous signal, success in substructure determination and accuracy of phases and electron-density maps all improve with an increase in the number of crystals used in merging. Structure solutions are possible when no single crystal can support structural analysis. It is proposed that such multi-crystal strategies may be broadly useful when only weak anomalous signals are available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Robust structural analysis of native biological macromolecules from multi-crystal anomalous diffraction data

Anomalous diffraction signals from typical native macromolecules are very weak, frustrating their use in structure determination. Here, native SAD procedures are described for enhancing the signal to noise in anomalous diffraction by using multiple crystals are described. Five applications demonstrate that truly routine structure determination is possible without the need for heavy atoms. Structure determinations for biological macromolecules that have no known structural antecedents typically involve the incorporation of heavier atoms than those found natively in biological molecules. Currently, selenomethionyl proteins analyzed using single- or multi-wavelength anomalous diffraction (SAD or MAD) data predominate for such de novo analyses. Naturally occurring metal ions such as zinc or iron often suffice in MAD or SAD experiments, and sulfur SAD has been an option since it was first demonstrated using crambin 30 years ago; however, SAD analyses of structures containing only light atoms (Z{sub max} ≤ 20) have not been common. Here, robust procedures for enhancing the signal to noise in measurements of anomalous diffraction by combining data collected from several crystals at a lower than usual X-ray energy are described. This multi-crystal native SAD method was applied in five structure determinations, using between five and 13 crystals to determine substructures of between four and 52 anomalous scatterers (Z ≤ 20) and then the full structures ranging from 127 to 1200 ordered residues per asymmetric unit at resolutions from 2.3 to 2.8 Å. Tests were devised to assure that all of the crystals used were statistically equivalent. Elemental identities for Ca, Cl, S, P and Mg were proven by f′′ scattering-factor refinements. The procedures are robust, indicating that truly routine structure determination of typical native macromolecules is realised. Synchrotron beamlines that are optimized for low-energy X-ray diffraction measurements will facilitate such direct structural analysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Automated identification of elemental ions in macromolecular crystal structures

The solvent-picking procedure in phenix.refine has been extended and combined with Phaser anomalous substructure completion and analysis of coordination geometry to identify and place elemental ions. Many macromolecular model-building and refinement programs can automatically place solvent atoms in electron density at moderate-to-high resolution. This process frequently builds water molecules in place of elemental ions, the identification of which must be performed manually. The solvent-picking algorithms in phenix.refine have been extended to build common ions based on an analysis of the chemical environment as well as physical properties such as occupancy, B factor and anomalous scattering. The method is most effective for heavier elements such as calcium and zinc, for which a majority of sites can be placed with few false positives in a diverse test set of structures. At atomic resolution, it is observed that it can also be possible to identify tightly bound sodium and magnesium ions. A number of challenges that contribute to the difficulty of completely automating the process of structure completion are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Pushing the limits of sulfur SAD phasing: de novo structure solution of the N-terminal domain of the ectodomain of HCV E1

The sulfur SAD phasing method was successfully used to determine the structure of the N-terminal domain of HCV E1 from low-resolution diffracting crystals by combining data from 32 crystals. Single-wavelength anomalous dispersion of S atoms (S-SAD) is an elegant phasing method to determine crystal structures that does not require heavy-atom incorporation or selenomethionine derivatization. Nevertheless, this technique has been limited by the paucity of the signal at the usual X-ray wavelengths, requiring very accurate measurement of the anomalous differences. Here, the data collection and structure solution of the N-terminal domain of the ectodomain of HCV E1 from crystals that diffracted very weakly is reported. By combining the data from 32 crystals, it was possible to solve the sulfur substructure and calculate initial maps at 7 Å resolution, and after density modication and phase extension using a higher resolution native data set to 3.5 Å resolution model building was achievable.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Undistorted linear Bi chains with hypervalent bonding in La 3 TiBi 5 from single-crystal X-ray diffraction

The crystal structure of the lanthanum titanium bis­muthide La 3 TiBi 5 (Pearson code hP18, Wyckoff sequence b d g2) has been established from single-crystal X-ray diffraction data and analyzed in detail using first-principles calculations. There are no anomalies pertaining to the atomic displacement parameter of the Ti site, previously reported based on a powder X-ray diffraction analysis of this compound. The anionic substructure contains columns of face-sharing TiBi 6 octa­hedra and linear Bi chains. Due to a significant La(5d) and Bi(6p) orbital mixing, a perfectly one-dimensional character of the Bi chains is not realised, while a three-dimensional electronic structure is established instead. The latter fact explains the stability of the polyanionic pnictide units against Peierls distortions. The hypervalent bonding in the Bi chains is reflected in a rather long Bi—Bi distance of 3.2264 (4) Å and a typical pattern of bonding and anti­bonding inter­actions, as revealed by electronic structure calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The hidden treasure in your data: phasing with unexpected weak anomalous scatterers from routine data sets

Single-wavelength anomalous dispersion (SAD) utilizing anomalous signal from native S atoms, or other atoms with Z ≤ 20, generally requires highly redundant data collected using relatively long-wavelength X-rays. Here, the results from two proteins are presented where the anomalous signal from serendipitously acquired surface-bound Ca atoms with an anomalous data multiplicity of around 10 was utilized to drive de novo structure determination. In both cases, the Ca atoms were acquired from the crystallization solution, and the data-collection strategy was not optimized to exploit the anomalous signal from these scatterers. The X-ray data were collected at 0.98 Å wavelength in one case and at 1.74 Å in the other (the wavelength was optimized for sulfur, but the anomalous signal from calcium was exploited for structure solution). Similarly, using a test case, it is shown that data collected at ~1.0 Å wavelength, where the f '' value for sulfur is 0.28 e, are sufficient for structure determination using intrinsic S atoms from a strongly diffracting crystal. Interestingly, it was also observed that SHELXD was capable of generating a substructure solution from high-exposure data with a completeness of 70% for low-resolution reflections extending to 3.5 Å resolution with relatively low anomalous multiplicity. Considering the fact that many crystallization conditions contain anomalous scatterers such as Cl, Ca, Mn etc. , checking for the presence of fortuitous anomalous signal in data from well diffracting crystals could prove useful in either determining the structure de novo or in accurately assigning surface-bound atoms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Imaging pion showers with the CALICE analogue hadron calorimeter

The CALICE collaboration investigates different technology options for highly granular calorimeters for detectors at a future electron-positron collider. One of the devices constructed and tested by the collaboration is a 1 m{sup 3} prototype for an imaging scintillator-steel sampling calorimeter for hadrons with analogue readout (AHCAL). The light from 7608 small scintillator cells is detected with silicon photomultipliers. The AHCAL has been successfully operated during electron and hadron test-beam measurements at DESY, CERN, and Fermilab since 2005. The collected data allow for evaluating the novel technologies employed. In addition, these data provide a valuable basis for validating pion cascade simulations. This paper presents the current status of comparisons between the AHCAL data and predictions from different Monte Carlo models implemented in GEANT4. The comparisons cover the total visible energy, longitudinal and radial shower profiles, and the shower substructure. Furthermore, this paper discusses a software compensation algorithm for improving the energy resolution of the AHCAL for single pions. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

EGBTER: Capturing Degree Distribution, Clustering Coefficients, and Community Structure in a Single Random Graph Model

Random graph models are important constructs for data analytic applications as well as pure mathematical developments, as they provide capabilities for network synthesis and principled analysis. Several models have been developed with the aim of faithfully preserving important graph metrics and substructures. With the goal of capturing degree distribution, clustering coefficient, and communities in a single random graph model, we propose a new model to address shortcomings in a progression of network modeling capabilities. The Block Two-Level Erdos-Rényi (BTER) model of Seshadhri et aI., designed to allow prescription of expected degree and clustering coefficient distributions, neglects community modeling, while the Generalized BTER (GBTER) model of Bridges et aI., designed to add community modeling capabilities to BTER, struggles to faithfully represent all three characteristics simultaneously. In this work, we fit BTER and two GBTER configurations to several real-world networks and compare the results with that of our new model, the Extended GBTER (EGBTER) model. Our results support that EBGTER adds a community-modeling flexibility to BTER, while retaining a satisfactory level of accuracy in terms of degree and clustering coefficient. Our insights and empirical testing of previous models as well as the new model are novel contributions to the literature.

El-Daghar, Omar↗
DOE OSTI2022

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗
DOE OSTI2017

BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI

Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad application is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity, and complexity generated by MSI experiments. The development and application of cutting-edge analytical methods is a core driver in MSI research for new scientific discoveries, medical diagnostics, and commercial-innovation. However, the lack of means to share, apply, and reproduce analyses hinders the broad application, validation, and use of novel MSI analysis methods. To address this central challenge, we introduce the Berkeley Analysis and Storage Toolkit (BASTet), a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. Based on BASTet, we describe the extension of the OpenMSI mass spectrometry imaging science gateway to enable web-based sharing, reuse, analysis, and visualization of data analyses and derived data products. Here, we demonstrate the application of BASTet and OpenMSI in practice to identify and compare characteristic substructures in the mouse brain based on their chemical composition measured via MSI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Anisotropies in the diffuse gamma-ray background from dark matter with Fermi LAT: A closer look

We perform a detailed study of the sensitivity to the anisotropies related to dark matter (DM) annihilation in the isotropic gamma-ray background (IGRB) as measured by the Fermi Large Area Telescope ( Fermi LAT). For the first time, we take into account the effects of the Galactic foregrounds and use a realistic representation of the Fermi LAT. We implement an analysis pipeline which simulates Fermi LAT data sets starting from model maps of the Galactic foregrounds, the Fermi -resolved point sources, the extragalactic diffuse emission and the signal from DM annihilation. The effects of the detector are taken into account by convolving the model maps with the Fermi LAT instrumental response. We then use the angular power spectrum to characterize the anisotropy properties of the simulated data and to study the sensitivity to DM. We consider DM anisotropies of extragalactic origin and of Galactic origin (which can be generated through annihilation in the Milky Way substructures) as opposed to a background of anisotropies generated by sources of astrophysical origin, blazars for example. We find that with statistics from 5 yr of observation, Fermi is sensitive to a DM contribution at the level of 1–10 per cent of the measured IGRB depending on the DM mass m χ and annihilation mode. In terms of the thermally averaged cross-section <σAv>, this corresponds to ~10 –25 cm 3 s –1 , i.e. slightly above the typical expectations for a thermal relic, for low values of the DM mass m χ ≲ 100 GeV. As a result, the anisotropy method for DM searches has a sensitivity comparable to the usual methods based only on the energy spectrum and thus constitutes an independent and complementary piece of information in the DM puzzle.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Optimizing weak lensing mass estimates for cluster profile uncertainty

Weak lensing measurements of cluster masses are necessary for calibrating mass-observable relations (MORs) to investigate the growth of structure and the properties of dark energy. However, the measured cluster shear signal varies at fixed mass M 200m due to inherent ellipticity of background galaxies, intervening structures along the line of sight, and variations in the cluster structure due to scatter in concentrations, asphericity and substructure. We use N-body simulated halos to derive and evaluate a weak lensing circular aperture mass measurement M ap that minimizes the mass estimate variance <(M ap - M 200m ) 2 > in the presence of all these forms of variability. Depending on halo mass and observational conditions, the resulting mass estimator improves on M ap filters optimized for circular NFW-profile clusters in the presence of uncorrelated large scale structure (LSS) about as much as the latter improve on an estimator that only minimizes the influence of shape noise. Optimizing for uncorrelated LSS while ignoring the variation of internal cluster structure puts too much weight on the profile near the cores of halos, and under some circumstances can even be worse than not accounting for LSS at all. As a result, we discuss the impact of variability in cluster structure and correlated structures on the design and performance of weak lensing surveys intended to calibrate cluster MORs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Rerouting of the lignin biosynthetic pathway by inhibition of cytosolic shikimate recycling in transgenic hybrid aspen

Lignin is a phenolic polymer deposited in the plant cell wall and is mainly polymerized from three canonical monomers (monolignols), i.e., p-coumaryl, coniferyl, and sinapyl alcohols. After polymerization, these alcohols form different lignin substructures. In dicotyledons, monolignols are biosynthesized from phenylalanine, an aromatic amino acid. Shikimate acts at two positions in the route to the lignin building blocks. It is part of the shikimate pathway which provides the precursor for the biosynthesis of phenylalanine, and is involved in the transesterification of pcoumaroyl- CoA to p-coumaroyl shikimate, one of key steps in the biosynthesis of coniferyl and sinapyl alcohols. The shikimate residue in p-coumaroyl shikimate is released in later steps, and the resulting shikimate becomes available again for the biosynthesis of new p-coumaroyl shikimate molecules. In this study, we inhibited cytosolic shikimate recycling in transgenic hybrid aspen by accelerated phosphorylation of shikimate in the cytosol through expression of a bacterial shikimate kinase. Here, this expression elicited an increase in p-hydroxyphenyl units of lignin and, by contrast, a decrease in guaiacyl and syringyl units. Transgenic plants with high shikimate kinase activity produced a lignin content comparable to that in wild-type plants and had an increased processability via enzymatic saccharification. Although expression of many genes was altered in the transgenic plants, elevated shikimate kinase activity did not exert a significant effect on the expression of the majority of genes responsible for lignin biosynthesis. The present results indicate that cytosolic shikimate recycling is crucial to the monomeric composition of lignin rather than for lignin content.

shikimate pathway↗
DOE OSTI2024

Efficient Modeling of Floating Wind Arrays Including Current Loads and Seabed Bathymetry

Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasi-static solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.

bathymetry↗