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At least 1,621 records · Page 90

Second-Nearest-Neighbor Correlations from Connection of Atomic Packing Motifs in Metallic Glasses and Liquids

Using molecular dynamics simulations, we have studied the atomic correlations characterizing the second peak in the radial distribution function (RDF) of metallic glasses and liquids. The analysis was conducted from the perspective of different connection schemes of atomic packing motifs, based on the number of shared atoms between two linked coordination polyhedra. The results demonstrate that the cluster connections by face-sharing, specifically with three common atoms, are most favored when transitioning from the liquid to glassy state, and exhibit the stiffest elastic response during shear deformation. These properties of the connections and the resultant atomic correlations are generally the same for different types of packing motifs in different alloys. Splitting of the second RDF peak was observed for the inherent structure of the equilibrium liquid, originating solely from cluster connections; this trait can then be inherited in the metallic glass formed via subsequent quenching of the parent liquid through the glass transition, in the absence of any additional type of local structural order. In conclusion, increasing ordering and cluster connection during cooling, however, may tune the position and intensity of the split peaks.

36 MATERIALS SCIENCE↗

On the use of air temperature and precipitation as surrogate predictors in soil respiration modelling

Soil respiration (R S ), the soil-to-atmosphere CO 2 flux that is a major component of the global carbon cycle, is strongly influenced by local soil temperature (T soil ) and water content (SWC). Regional to global-scale R S modelling thus requires this information at local scales, but few high-quality, wall-to-wall (global) T soil and SWC data exist. As a result, such modelling efforts commonly use air temperature (T air ) and monthly precipitation (P m ) as surrogate predictors, but their site-scale accuracy and potential bias are unknown. In this report we used monthly data from 880 sites across a wide variety of different environmental conditions (i.e., climate, ecosystem type, elevation, vegetation leaf habit and drainage conditions) to determine the suitability of T air as a surrogate for T soil , and data from 507 sites to examine the suitability of P m as a surrogate for SWC. Site-specific linear and second-order exponential non-linear models were compared using model evaluation metrics (i.e., slope, p-value of slope, root mean square error [RMSE], index of agreement and model efficiency). We found that T soil and T air are highly correlated and explain similar R S variability. In contrast, P m is not a good surrogate for SWC, even though P m explains a similar amount of R S variability to SWC. The wide variability in the site-specific relationships between R S and SWC means that no single relationship can be used for large-scale modelling. The results from this study support the use of T air in continental-to-global scale R S models, and highlight the urgent need for continental-to-global scale SWC datasets for the modelling and evaluation of future soil carbon dynamics under global climate change.

54 ENVIRONMENTAL SCIENCES↗

Effect of temperature and magnetic field on disorder in semiconductor structures

We present the results of consistent theoretical analysis of various factors that may lead to influence of temperature and external magnetic field on disorder in semiconductor structures. Main attention is paid to quantum well (QW) structures in which only QWs or both QW and barriers are doped (the doping level is assumed to be close to the value corresponding to the metal–insulator transition). The above factors include (i) ionization of localized states to the region of delocalized states above the mobility edge, which is presumed to exist in the impurity band; (ii) the coexistence in the upper and lower Hubbard bands (upon doping of QWs as well as barriers); in this case, in particular, the external magnetic field determines the relative contribution of the upper Hubbard band due to spin correlations at doubly filled sites; and (iii) the contribution of the exchange interaction at pairs of sites, in which the external magnetic field can affect the relation between ferromagnetic and antiferromagnetic configurations. All these factors, which affect the structure and degree of disorder, lead to specific features in the temperature dependence of resistivity and determine specific features of the magnetoresistance. Our conclusions are compared with available experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stabilization of three-dimensional charge order through interplanar orbital hybridization in Pr x Y 1–x Ba 2 Cu 3 O 6+δ

The shape of 3d-orbitals often governs the electronic and magnetic properties of correlated transition metal oxides. In the superconducting cuprates, the planar confinement of the d x 2 –y 2 orbital dictates the two-dimensional nature of the unconventional superconductivity and a competing charge order. Achieving orbital-specific control of the electronic structure to allow coupling pathways across adjacent planes would enable direct assessment of the role of dimensionality in the intertwined orders. Using Cu L 3 and Pr M 5 resonant x-ray scattering and first-principles calculations, we report a highly correlated three-dimensional charge order in Pr-substituted YBa 2 Cu 3 O 7 , where the Pr f-electrons create a direct orbital bridge between CuO 2 planes. With this we demonstrate that interplanar orbital engineering can be used to surgically control electronic phases in correlated oxides and other layered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

NASA Discipline Neuroscience↗

Detection and Monitoring of Stratigraphic Markers and Temperature Trends at the Greenland Ice Sheet Project 2 Using Passive-Microwave Remote-Sensing Data

Satellite passive-microwave sensors provide a sensitive means of studying ice-sheet surface processes that assists ice-core interpretation and can extend local observations across regional scales. Analysis of special sensor microwave/imager (SSM/I) brightness temperature (TB) data supports ice-core research in two specific ways. First, the summer hoar complex layers used to date the Holocene portion of the Greenland Ice Sheet Project 2 ice core can be defined temporally and spatially by SSM/I 37-GHz vertically (V) and horizontally (H) polarized B ratio (V/H) trends. Second, comparison of automatic weather station temperatures to SSM/I 37-GHz V TB data shows that they are an effective proxy temperature record in this region. Also, the TB data can be correlated with proxy temperature trends from stable-isotope-ratio (delta O-18 and delta-D) profiles from snow pits and this allows the assignment of dates to specific snow depths.

Shuman, C. A.↗

ExaTN

A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.

McCaskey, AlexanderJ↗

SU-D-204-01: A Methodology Based On Machine Learning and Quantum Clustering to Predict Lung SBRT Dosimetric Endpoints From Patient Specific Anatomic Features

Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space to identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong correlation between this feature and both endpoints. Conclusion: This pilot study shows that it is feasible to predict dose-volume endpoints based on patient-specific anatomic features. The developed methodology can potentially help to identify patients at risk for higher OAR doses, thus improving the efficiency of treatment planning. R01-184173.

60 APPLIED LIFE SCIENCES↗

Non-Abelian bosonization and modular transformation approach to superuniversality

Quantum Hall inter-plateau transitions are physical exemplars of quantum phase transitions. Near each of these transitions, the measured electrical conductivity scales with the same correlation length and dynamical critical exponents, i.e., the critical points are superuniversal. In apparent contradiction to these experiments, prior theoretical studies of quantum Hall phase transitions within the framework of Abelian Chern-Simons theory coupled to matter found correlation length exponents that depend on the value of the quantum critical Hall conductivity. Here, we use non-Abelian bosonization and modular transformations to theoretically study the phenomenon of superuniversality. Specifically, we introduce a new effective theory that has an emergent U(N) gauge symmetry with any N > 1 for a quantum phase transition between an integer quantum Hall state and an insulator. We then use modular transformations to generate from this theory effective descriptions for transitions between a large class of fractional quantum Hall states whose quasiparticle excitations have Abelian statistics. We find the correlation length and dynamical critical exponents are independent of the particular transition within a controlled 't Hooft large N expansion, i.e., superuniversal! Furthermore, we argue that this superuniversality could survive away from this controlled large N limit using recent duality conjectures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Degradation Pathways of Cobalt–Free LiNiO 2 Cathode in Lithium Batteries

Electrode-electrolyte reactivity (EER) and particle cracking (PC) are considered two main causes of capacity fade in high-nickel layered oxide cathodes in lithium-based batteries. However, whether EER or PC is more critical remains debatable. Herein, the fundamental correlation between EER and PC is systematically investigated with LiNiO 2 (LNO), the ultimate cobalt-free lithium layered oxide cathode. Specifically, EER is found more critical than secondary particle cracking (SPC) in determining the cycling stability of LNO; EER leads to primary particle cracking, but mitigates SPC due to the inhibition of H2-H3 phase transformation. Two surface degradation pathways are identified for cycled LNO under low and high EERs. A common blocking surface reconstruction layer (SRL) containing electrochemically-inactive Ni 3 O 4 spinel and NiO rock-salt phases is formed on LNO in an electrolyte with a high EER; in contrast, an electrochemically-active SRL featuring regions of electron- and lithium-ion-conductive LiNi 2 O 4 spinel phase is formed on LNO in an electrolyte with a low EER. These findings unveil the intrinsic degradation pathways of LNO cathode and are foreseen to provide new insights into the development of lithium-based batteries with a minimized EER and a maximized service life.

25 ENERGY STORAGE↗

From charge storage mechanism to performance: A roadmap toward high specific energy sodium-ion batteries through carbon-anode optimization

Serious critical issues hamper the arrival on the market of sodium-ion batteries (SIBs) as a lower cost substitute to Li-ion batteries (LIBs). Among these, the negligible sodium uptake into graphite, which is the keystone of the present LIB technology, appears to be one of the toughest to tackle. Although hard carbon is known for years as one of the best substitutes, its performance remains below that of graphite in Li-ion batteries, while its mechanism of sodium storage is still under debate. Many other carbons are studied since a few years, some of which presenting capacities far beyond that of graphite. However, they tend to present larger voltage and high first cycle loss, leading to limited benefit in terms of specific energy at full cell level. Overcoming this preoccupying tradeoff requires a deep understanding of the charge storage mechanisms and the correlation between structure, microstructure and performance. The present Review aims at bringing light to this question by drawing a roadmap of the emerging routes for the optimization of carbon materials as SIB anode, on the basis of a critical survey of their reported electrochemical performance and charge storage mechanisms.

Saurel, Damien↗

Microstructure of room temperature ionic liquids at stepped graphite electrodes

Molecular dynamics simulations of room temperature ionic liquid (RTIL) [emim][TFSI] at stepped graphite electrodes were performed to investigate the influence of the thickness of the electrode surface step on the microstructure of interfacial RTILs. A strong correlation was observed between the interfacial RTIL structure and the step thickness in electrode surface as well as the ion size. Specifically, when the step thickness is commensurate with ion size, the interfacial layering of cation/anion is more evident; whereas, the layering tends to be less defined when the step thickness is close to the half of ion size. Furthermore, two-dimensional microstructure of ion layers exhibits different patterns and alignments of counter-ion/co-ion lattice at neutral and charged electrodes. As the cation/anion layering could impose considerable effects on ion diffusion, the detailed information of interfacial RTILs at stepped graphite presented here would help to understand the molecular mechanism of RTIL-electrode interfaces in supercapacitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biodeactivation of Lipopolysaccharide Correlates with Surface‐Bound NO 3 After Cold Atmospheric Plasma Treatment

Cold atmospheric plasma (CAP) treatment of biological surfaces results in important changes of biological functions, but little knowledge on specific surface‐chemical changes is available. We measured surface‐bound NO 3 on polymer and biomolecular films after CAP treatment. An O 2 /N 2 ‐based surface microdischarge was used to deactivate lipopolysaccharide (LPS), an immune‐stimulating biomolecule found in Gram negative bacteria. The observed LPS biodeactivation was highest for low N 2 concentrations in O 2 , increased roughly linearly with surface NO 3 , and then saturated. NO 3 was also observed after treatment by a very different source: an atmospheric pressure plasma jet operating with an Ar carrier gas. Thus, NO 3 formation is a generic surface chemical modification of these materials by CAP sources.

Bartis, Elliot A. J.↗

Adrenergic receptor-mediated activation of FGF-21-adiponectin axis exerts atheroprotective effects in brown adipose tissue-transplanted apoE −/− mice

Highlights: • Transplantation of BAT, but not WAT, reduces the plaque size in apoE{sup −/−} mice. • Serum levels of noradrenalin, FGF-21, and adiponectin are increased in BAT-transplanted mice. • β3-AR blocker abrogates the atheroprotective effect of BAT transplantation. • β3-AR blocker abrogates the elevations of serum FGF-21 and adiponectin. • Adiponectin levels show a significant inverse correlation with plaque size in BAT-transplanted mice. Brown adipose tissue (BAT) has been found as an endocrine organ that maintains metabolic homeostasis; however, the effects on atherosclerosis remain undefined. Here, we investigated the effect of experimental BAT transplantation on atherosclerosis. Interscapular BAT was dissected from wild-type mice and transplanted into the visceral cavity of 12-week-old apoE{sup −/−} mice. Oil-red O staining of whole aortas after 3 months of a high-cholesterol diet showed a significant decrease in atherosclerotic lesion area in BAT-transplanted mice by 32% compared with the sham control mice. Lipid profiles, except for serum triglyceride level, showed no difference between the 2 groups. BAT-transplanted mice showed higher concentrations of serum noradrenalin, fibroblast growth factor 21 (FGF-21), and adiponectin. Treatment with the β3-adrenergic receptor (AR) blocker completely abrogated the atheroprotective effects of BAT transplantation, with serum concentrations of FGF-21 and adiponectin being equivalent between the 2 groups. Homologous transplantation of BAT from apoE{sup −/−} mice also showed a significant decrease in atherosclerotic lesion area by 28% without affecting lipid profiles, while epidydimal white adipose tissue transplantation did not affect atherosclerosis. Serum and endogenous BAT concentrations of FGF-21 were significantly higher in BAT-transplanted mice than sham control mice. Concomitantly, serum adiponectin levels were elevated in BAT-transplanted mice and showed a significant inverse correlation with atherosclerotic lesion area. Our findings show for the first time that atheroprotective effect of BAT transplantation is BAT-specific and independent of lipid-lowering effect, accompanied by AR-mediated activation of the FGF-21-adiponectin axis.

60 APPLIED LIFE SCIENCES↗

Interpreting biomarker data from the COPHES/DEMOCOPHES twin projects: Using external exposure data to understand biomarker differences among countries

In 2011 and 2012, the COPHES/DEMOCOPHES twin projects performed the first ever harmonized human biomonitoring survey in 17 European countries. In more than 1800 mother–child pairs, individual lifestyle data were collected and cadmium, cotinine and certain phthalate metabolites were measured in urine. Total mercury was determined in hair samples. While the main goal of the COPHES/DEMOCOPHES twin projects was to develop and test harmonized protocols and procedures, the goal of the current paper is to investigate whether the observed differences in biomarker values among the countries implementing DEMOCOPHES can be interpreted using information from external databases on environmental quality and lifestyle. In general, 13 countries having implemented DEMOCOPHES provided high-quality data from external sources that were relevant for interpretation purposes. However, some data were not available for reporting or were not in line with predefined specifications. Therefore, only part of the external information could be included in the statistical analyses. Nonetheless, there was a highly significant correlation between national levels of fish consumption and mercury in hair, the strength of antismoking legislation was significantly related to urinary cotinine levels, and we were able to show indications that also urinary cadmium levels were associated with environmental quality and food quality. These results again show the potential of biomonitoring data to provide added value for (the evaluation of) evidence-informed policy making. - Highlights: • External data was collected to interpret HBM data from DEMOCOPHES. • Hg in hair could be related to fish consumption across different countries. • Urinary cotinine was related to strictness of anti-smoking legislation. • Urinary Cd was borderline significantly related to air and food quality. • Lack of comparable data among countries hampered the analysis.

54 ENVIRONMENTAL SCIENCES↗

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principal components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

High-throughput enzyme screening platform for the IPP-bypass mevalonate pathway for isopentenol production

Isopentenol (or isoprenol, 3-methyl-3-buten-1-ol) is a drop-in biofuel and a precursor for commodity chemicals such as isoprene. Biological production of isopentenol via the mevalonate pathway has been optimized extensively in Escherichia coli , yielding 70% of its theoretical maximum. However, high ATP requirements and isopentenyl diphosphate (IPP) toxicity pose immediate challenges for engineering bacterial strains to overproduce commodities utilizing IPP as an intermediate. To overcome these limitations, we developed an “IPP-bypass” isopentenol pathway using the promiscuous activity of a mevalonate diphosphate decarboxylase (PMD) and demonstrated improved performance under aeration-limited conditions. However, relatively low activity of PMD toward the non-native substrate (mevalonate monophosphate, MVAP) was shown to limit flux through this new pathway. By inhibiting all IPP production from the endogenous non-mevalonate pathway, we developed a high-throughput screening platform that correlated promiscuous PMD activity toward MVAP with cellular growth. Successful identification of mutants that altered PMD activity demonstrated the sensitivity and specificity of the screening platform. Strains with evolved PMD mutants and the novel IPP-bypass pathway increased titers up to 2.4-fold. Further enzymatic characterization of the evolved PMD variants suggested that higher isopentenol titers could be achieved either by altering residues directly interacting with substrate and cofactor or by altering residues on nearby α-helices. These altered residues could facilitate the production of isopentenol by tuning either k cat or K i of PMD for the non-native substrate. The synergistic modification made on PMD for the IPP-bypass mevalonate pathway is expected to significantly facilitate the industrial scale production of isopentenol.

09 BIOMASS FUELS↗

High Accuracy Transition Metal Effective Cores for the Many-Body Diffusion Monte Carlo Method

Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semilocal potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown that the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the 3d transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semilocal representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases-on par with the most accurate semilocal pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semilocal pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗