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At least 1,603 records · Page 89

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic structure of rhombohedral Cr X 3 ( X = Br, Cl, I) van der Waals crystals

We perform a comprehensive analysis of both the chemical and correlated electronic structure reconstruction of rhombohedral Cr X 3 (X = Br, Cl, I) van der Waals bulk crystals. Using the generalized gradient approximation (GGA) plus dynamical mean-field theory we explicitly demonstrate the importance of local dynamical correlations for a consistent understanding of emergent Kondo quasiparticles and Mott localized electronic states, showing the interplay between material-dependent one-electron GGA line-shape and multiorbital electronic interactions. To probe the correlated paramagnetic electronic state we performed x-ray absorption spectroscopy measurements for CrCl 3 and CrBr 3 bulk crystals. Furthermore, our correlated many-body study is relevant to understanding the electronic structure reconstruction of paramagnetic Cr-trihalide crystals and should be widely applicable to other van der Waals magnetic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

System Integration Analysis for Modular Solid-State Substations

Structural modularity is critical to solid-state transformer (SST) and solid-state power substation (SSPS) concepts, but operational aspects related to this modularity are not yet fully understood. Previous studies and demonstrations of modular power conversion systems assume identical module compositions, but dependence on module uniformity undercuts the value of the modular framework. In this project, a hierarchical control approach was developed for modular SSTs which achieves system-level objectives while ensuring equitable power sharing between nonuniform building block modules. This enables module replacements and upgrades which leverage circuit and device technology advancements to improve system-level performance. The functionality of the control approach is demonstrated in detailed time-domain simulations. Results of this project provide context and strategic direction for future LDRD projects focusing on technologies supporting the SST crosscut outcome of the resilient energy systems mission campaign.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The BOSS bispectrum analysis at one loop from the Effective Field Theory of Large-Scale Structure

Abstract We analyze the BOSS power spectrum monopole and quadrupole, and the bispectrum monopole and quadrupole data, using the predictions from the Effective Field Theory of Large-Scale Structure (EFTofLSS). Specifically, we use the one loop prediction for the power spectrum and the bispectrum monopole, and the tree level for the bispectrum quadrupole. After validating our pipeline against numerical simulations as well as checking for several internal consistencies, we apply it to the observational data. We find that analyzing the bispectrum monopole to higher wavenumbers thanks to the one-loop prediction, as well as the addition of the tree-level quadrupole, significantly reduces the error bars with respect to our original analysis of the power spectrum at one loop and bispectrum monopole at tree level. After fixing the spectral tilt to Planck preferred value and using a Big Bang Nucleosynthesis prior, we measureσ 8 = 0.794 ± 0.037,h = 0.692 ± 0.011, and Ω m = 0.311 ± 0.010 to about 4.7%, 1.6%, and 3.2%, at 68% CL, respectively.This represents an error bar reduction with respect to the power spectrum-only analysis of about 30%, 18%, and 13% respectively. Remarkably, the results are compatible with the ones obtained with a power-spectrum-only analysis, showing the power of the EFTofLSS in simultaneously predicting several observables. We find no tension with Planck.

Astronomy & Astrophysics↗

Probing lead acetate in solution using X-ray diffraction

Here, for the purpose of water purification involving toxic metal sensing and removal, high energy X-ray diffraction experiments have been performed on lead acetate Pb(Ac) 2 solutions, liquid and amorphous glutathione disulfide (GSSG), and their mixtures. The data have been interpreted using Empirical Potential Structure Refinement and pair distribution function analysis. At the highest concentration of 1 M Pb(Ac) 2 in water, the lead molecules are found to cluster and the second shell in the water structure becomes slightly more ordered as the water molecules become compressed. Liquid and amorphous GSSG are found to hydrogen bond primarily via OH-O interactions, while NH-O bonds are much more distorted. Aqueous solutions of Pb(Ac) 2 + GSSG show the closest Pb-O (carboxyl) and Pb-N (amine) bonds both at a distance of 2.5 ± 0.1 Å at a concentration of 1 M Pb(Ac) 2 in water. At 0.75 M Pb(Ac) 2 in water, strong Pb-S bonds are found at a distance of 2.8 ± 0.1 Å. The implications for lead removal using capacitive deionization are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering fast solid-acid proton conductors based on dynamics of polyanion groups and proton bonding strength

Achieving high proton conductivity in inorganic solids is key for advancing many electrochemical technologies, including low-energy nano-electronics and energy-efficient fuel cells and electrolyzers. A quantitative understanding of the physical traits of a material that regulate proton diffusion is necessary for accelerating the discovery of fast proton conductors. In this work, we have mapped the structural, chemical and dynamic properties of solid acids to the elementary steps of the Grotthuss mechanism of proton diffusion. Our approach combines ab initio molecular dynamics simulations, analysis of phonon spectra and atomic structure calculations. We have identified the donor–hydrogen bond lengths and the acidity of polyanion groups as key descriptors of local proton transfer and the vibrational frequencies of the cation framework as the key descriptor of lattice flexibility. The latter facilitates rotations of polyanion groups and long-range proton migration in solid acid proton conductors. The calculated lattice flexibility also correlates with the experimentally reported superprotonic transition temperatures. Using these descriptors, we have screened the Materials Project database and identified potential solid acid proton conductors with monovalent, divalent and trivalent cations, including Ag + , Sr 2+ , Ba 2+ and Er 3+ cations, which go beyond the traditionally considered monovalent alkali cations (Cs + , Rb + , K + , and NH 4 + ) in solid acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

Data for Robust Paths to Net Greenhouse Gas Mitigation and Negative Emissions via Advanced Biofuels

This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script “autodaycent.py” (written for Python 2.7) opens an interactive command line routine that facilitates: Calibrating the DayCent pine growth model; Initializing DayCent for a set of case studies sites; Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation; and Results analysis & generation of manuscript Fig. 3. Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model compatible with other operating systems are available upon request.

Feedstock Production↗

Machine learning inversion from small-angle scattering for charged polymers

We develop Monte Carlo simulations for uniformly charged polymers and a machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments. The polymer is modeled as a chain of fixed-length bonds, where the connected bonds are subject to bending energy, and there is also a screened Coulomb potential for charge interaction between all joints. The bending energy is determined by the intrinsic bending stiffness, and the charge interaction depends on the interaction strength and screening length. All three contribute to the stiffness of the polymer chain and lead to longer and larger polymer conformations. The screening length also introduces a second length scale for the polymer besides the bending persistence length. To obtain the inverse mapping from the structure factor to these polymer conformation and energy-related parameters, we generate a large data set of structure factors by running simulations for a wide range of polymer energy parameters. We use principal component analysis to investigate the intra-polymer structure factors and determine the feasibility of the inversion using the nearest neighbor distance. We employ Gaussian process regression to achieve the inverse mapping and extract the characteristic parameters of polymers from the structure factor with low relative error.

36 MATERIALS SCIENCE↗

Coupling between plasmonic and photonic crystal modes in suspended three-dimensional meta-films

A complementary metal oxide semiconductor (CMOS) compatible fabrication method for creating three-dimensional (3D) meta-films is presented. In contrast to metasurfaces, meta-films possess structural variation throughout the thickness of the film and can possess a sub-wavelength scale structure in all three dimensions. Here we use this approach to create 2D arrays of cubic silicon nitride unit cells with plasmonic inclusions of elliptical metallic disks in horizontal and vertical orientations with lateral array-dimensions on the order of millimeters. Fourier transform infrared (FTIR) spectroscopy is used to measure the infrared transmission of meta-films with either horizontally or vertically oriented ellipses with varying eccentricity. Shape effects due to the ellipse eccentricity, as well as localized surface plasmon resonance (LSPR) effects due to the effective plasmonic wavelength are observed in the scattering response. The structures were modeled using rigorous coupled wave analysis (RCWA), finite difference time domain (Lumerical), and frequency domain finite element (COMSOL). The silicon nitride support structure possesses a complex in-plane photonic crystal slab band structure due to the periodicity of the unit cells. We show that adjustments to the physical dimensions of the ellipses can be used to control the coupling to this band structure. The horizontally oriented ellipses show narrow, distinct plasmonic resonances while the vertically oriented ellipses possess broader resonances, with lower overall transmission amplitude for a given ellipse geometry. We attribute this difference in resonance behavior to retardation effects. The ability to couple photonic slab modes with plasmonic inclusions enables a richer space of optical functionality for design of metamaterial-inspired optical components.

42 ENGINEERING↗

MURR LEU structural and thermal hydraulics analyses: Part I – Preliminary irradiation thermo-mechanical behavior

The University of Missouri Research Reactor (MURR) is expected to be converted from highly enriched uranium (HEU, ≥ 20 wt% U-235) U-Al x dispersion fuel to low-enriched uranium (LEU, < 20 wt% U-235) with U-10Mo monolithic fuel. This work introduces high-fidelity irradiation thermo–mechanical (T-M) analysis of the MURR LEU focusing on changes in coolant channel gap thickness. Three-dimensional (3D) finite element (FE) models were developed to simulate the irradiation T-M behavior of the MURR LEU element with all 23 curved fuel plates, the two side plates, and the combs. It was shown that channel gap thickness changes were influenced not only by plate thickness variations due to fuel swelling and creep but also by the radial displacement of consecutive MURR LEU plates. Modeling the fuel element assembly captured side plate displacements, which were shown to reduce radial fuel plate displacements towards the convex side. The maximum local radial displacement in the element was predicted at the end of life (EOL) as 23.7 mil (602.0 µm) on the lateral centerline of plate 23 towards the convex side. The maximum stripe-averaged reduction in channel gap thickness, particularly relevant for thermal hydraulics (TH) safety analysis, was calculated as 15.9 mil (403.9 µm) in single-side heated channel 24 (the outermost channel). These results account for the thermal resistance from the oxide build-up on cladding surfaces which was shown to be up to 0.82 mil (20.8 µm) thick. It was demonstrated that accounting for oxide layer thermal resistance led to a 10 °C higher peak fuel temperature and a 4.4 mil (111.8 µm) greater maximum local radial displacement. The impact of the calculated channel gap thickness changes on the MURR LEU TH safety analysis is evaluated in Part II.

Irradiation thermo-mechanical analysis↗

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Summary Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction‐diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf‐level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

Material Extrusion Printing of Poly(Acrylonitrile‐Styrene‐Acrylate) and Poly(Acrylonitrile‐Butadiene‐Styrene) Structures Reinforced with Poly(Phenylene Oxide) Additives for Improved Thermomechanical Properties and their Surface Analysis by Time‐of‐Flight Secondary Ion Mass Spectrometry

Fused filament fabrication offers the ability to 3D print complex geometries made from plastic filament materials; however, these parts are mechanically outperformed by parts created by traditional fabrication methods. To overcome this challenge, a high-performance polymer poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) is incorporated as an additive into two common engineering thermoplastics, poly(acrylonitrile-styrene-acrylate) (ASA) and poly(acrylonitrile-butadiene-styrene) (ABS). Structures printed from these polymer blends are more mechanically robust compared to those prepared from the parent polymers, with low loading levels (1–5 wt%) of PPO improving the elastic strength by up to ≈30% relative to the parent terpolymers. Even at higher loading levels (10 and 20 wt% PPO), there is no evidence of additive aggregation in the model thin films, which is supported by compositional analysis of the copolymers and chemical analysis via time-of-flight secondary ion mass spectrometry. The enhancements in mechanical properties of ASA and ABS blends appear to be a consequence of homogeneous incorporation of the PPO additive. In conclusion, this work explores expanding materials-property space using miscible blends of engineering thermoplastics to improve mechanical performance as a general approach to overcoming challenges with parts created by melt-based material extrusion printing.

additive manufacturing↗

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

Weighted Mobility

Engineering semiconductor devices requires an understanding of charge carrier mobility. Typically, mobilities are estimated using Hall effect and electrical resistivity meausrements, which are are routinely performed at room temperature and below, in materials with mobilities greater than 1 cm 2 V -1 s -1 . With the availability of combined Seebeck coefficient and electrical resistivity measurement systems, it is now easy to measure the weighted mobility (electron mobility weighted by the density of electronic states). A simple method to calculate the weighted mobility from Seebeck coefficient and electrical resistivity measurements is introduced, which gives good results at room temperature and above, and for mobilities as low as 10 -3 cm 2 V -1 s -1 , <!--FIGURE--> μ w = 331 c m 2 V s ( m Ω c m ρ ) ( T 300 K ) - 3 / 2 [ e x p [ | S | k B / e - 2 ] 1 + exp [ - 5 ( | S | k B / e - 1 ) ] + 3 π 2 | S | k B / e 1 + exp [ 5 ( | S | k B / e - 1 ) ] ] In this paper, μ w is the weighted mobility, ρ is the electrical resistivity measured in mΩ cm, T is the absolute temperature in K, S is the Seebeck coefficient, and k B /e = 86.3 µV K -1 . Weighted mobility analysis can elucidate the electronic structure and scattering mechanisms in materials and is particularly helpful in understanding and optimizing thermoelectric systems.

36 MATERIALS SCIENCE↗

Nanoscale Antiferromagnetic Domain Imaging using Full-Field Resonant X-ray Magnetic Diffraction Microscopy

The physical properties of magnetic materials frequently depend not only on the microscopic spin and electronic structures, but also on the structures of mesoscopic length scales that emerge, for instance, from domain formations, or chemical and/or electronic phase separations. However, experimental access to such mesoscopic structures is currently limited, especially for antiferromagnets with net zero magnetization. Here, full-field microscopy and resonant magnetic X-ray diffraction are combined to visualize antiferromagnetic (AF) domains of the spin–orbit Mott insulator Sr 2 IrO 4 with area over ≈0.1 mm 2 and with spatial resolution as high as ≈150 nm. With the unprecedented wide field of views and high spatial resolution, an intertwining of two AF domains on a length comparable to the measured average AF domain wall width of 545 nm is revealed. This mesoscopic structure comprises a substantial portion of the sample surface, and thus can result in a macroscopic response unexpected from its microscopic magnetic structure. In particular, the symmetry analysis presented in this work shows that the inversion symmetry, which is preserved by the microscopic AF order, becomes ill-defined at the mesoscopic length scale. We report this result underscores the importance of this novel technique for a thorough understanding of the physical properties of antiferromagnets.

36 MATERIALS SCIENCE↗