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At least 181 records · Page 10

Importance of σ Bonding Electrons for the Accurate Description of Electron Correlation in Graphene

Electron correlation in graphene is unique because of the interplay between the Dirac cone dispersion of π electrons and long-range Coulomb interaction. Because of the zero density of states at Fermi level, the random phase approximation predicts no metallic screening at long distance and low energy, so one might expect that graphene should be a poorly screened system. However, empirically graphene is a weakly interacting semimetal, which leads to the question of how electron correlations take place in graphene at different length scales. Here, we address this question by computing the equal time and dynamic structure factor S(q) and S(q,ω) of freestanding graphene using ab initio fixed-node diffusion Monte Carlo simulations and the random phase approximation. We find that the σ electrons contribute strongly to S(q,ω) for relevant experimental values of ω even at distances up to around 80 Å. These findings illustrate how the emergent physics from underlying Coulomb interactions results in the observed weakly correlated semimetal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Experimental validation and model development for thermal transmittances of porous window screens and horizontal louvred blind systems

Virtually every home in the US has some form of shades, blinds, drapes, or other window attachment, but few have been designed for energy savings. In order to provide a common basis of comparison for thermal performance it is important to have validated simulation tools. This study outlines a review and validation of the ISO 15099 centre-of-glass thermal transmittance correlations for naturally ventilated cavities through measurement and detailed simulations. The focus is on the impacts of room-side ventilated cavities, such as those found with solar screens and horizontal louvred blinds. The thermal transmittance of these systems is measured experimentally, simulated using computational fluid dynamics analysis, and simulated utilizing simplified correlations from ISO 15099. Finally, correlation coefficients are proposed for the ISO 15099 algorithm that reduces the mean error between measured and simulated heat flux for typical solar screens from 16% to 3.5% and from 13% to 1% for horizontal blinds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Second-order spectral line shift comparisons

The second-order spectral line width formulae from the projection operator and kinetic theory methods were recently compared. It was shown that a systematic expansion of the projection operator width expression including initial correlations formally agrees with the second-order kinetic theory result. It is now shown that the second-order dynamic shifts are also formally the same. The static shifts, however, differ due to an ad hoc treatment of electron-electron correlations in the projection operator method. The approximation is necessary in order to screen the radiator-electron interactions. The differences, however, are expected to be small. Finally, the results suggest using the rigorous and more compact second-order width and shift expressions from the kinetic theory method as the starting point for spectral line shape calculations. At line center, however, the projection operator second-order expression for the width and shift simplifies and reduces to the kinetic theory result.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Liquid–Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl 3 ) Enabled by Machine Learning Interatomic Potentials

Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl 3 molten salt across varied thermodynamic conditions (T = 473–613 K and P = 2.7–23.4 bar), which allowed us to predict temperature-surface tension correlations and liquid–vapor phase diagram from direct simulations of two-phase coexistence in this molten salt. Two MLIP architectures, a Kernel-based potential and neural network interatomic potential (NNIP), were considered to benchmark their performance for AlCl 3 molten salt using experimental structure and density values. The NNIP potential employed in two-phase equilibrium simulations yields the critical temperature and critical density of AlCl 3 that are within 10 K (∼3%) and 0.03 g/cm 3 (∼7%) of the reported experimental values. An accurate correlation between temperature and viscosities is obtained as well. In doing so, we report that the inclusion of low-density configurations in their training is critical to more accurately represent the AlCl 3 system across a wide phase-space. The MLIP trained using PBE-D3 functional in the ab initio molecular dynamics (AIMD) simulations (120 atoms) also showed close agreement with experimentally determined molten salt structure comprising Al 2 Cl 6 dimers, as validated using Raman spectra and neutron structure factor. Furthermore, the PBE-D3 as well as its trained MLIP showed better liquid density and temperature correlation for AlCl 3 system when compared to several other density functionals explored in this work. Overall, the demonstrated approach to predict temperature correlations for liquid and vapor densities in this study can be employed to screen nuclear reactors-relevant compositions, helping to mitigate safety concerns.

Ab initio molecular dynamics↗

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↗

Characterization of rattling in relation to thermal conductivity: Ordered half-Heusler semiconductors

We report that the factors that affect the thermal conductivity of semiconductors is a topic of great scientific interest, especially in relation to thermoelectrics. Key developments have been the concept of the phonon-glass-electron-crystal (PGEC) and the related idea of rattling to achieve this. We use first-principles phonon and thermal conductivity calculations to explore the concept of rattling for stoichiometric-ordered half-Heusler compounds. These compounds can be regarded as filled zinc blende materials, and the filling atom could be viewed as a rattler if it is weakly bound. We use two simple metrics, one related to the frequency and the other to bond frustration and anharmonicity. We find that both measures correlate with thermal conductivity. Lastly, this suggests that both may be useful in screening materials for low thermal conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Theoretical studies on the relationship between the thermionic work functions of refractory-metal intermetallic compounds and their electronic and crystal structures Final summary report

The Group VIA-Re binary systems are characterized by the presence of several intermediate phases. The u phase is present in all of the systems, but the a-Mn phases occur in only the Mo-Re and W-Re systems. The occurrence of these intermediate phases appears to be governed largely by electronic factors and is predictable on the basis of electron/atom ratio. The thermionic work functions of the intermediate phase materials were experimentally determined. function and the screening of the outermost electrons in the Group VIA metals was found. A correlation between the work As might be expected for purely metallic substances, the work functions were relatively high, in the range 4. 5 to 5. 0 eV, and in each case were bracketed by the work functions of the pure constituents. A discontinuous change in the average work function with composition is proposed, based on a thermodynamical treatment of the electron vapor.

REFRACTORY METAL↗

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

Smith, Paul L.↗

Spin-selective evolution of the Zhang-Rice state in binary transition metal oxide MnO(001) film

Here, the Zhang-Rice (ZR) state is a strongly hybridized bound state formed by transition-metal and oxygen atoms. The spin fluctuations within the ZR state are known to play an important role in high-T c superconductivity in cuprates. Here, we employ a combination of angle-resolved photoemission spectroscopy (ARPES), x-ray photoemission spectroscopy (XPS), and ab initio embedded dynamical mean-field theory (eDMFT) to investigate the influence of magnetic ordering on the spectral characteristics of the valence band and Mn 2⁢p core-level in MnO (001) ultrathin films. Our results demonstrate that a complex spin-selective evolution of Mn 3⁢d-O2⁢p hybridization develops due to the long-range antiferromagnetic (AFM) ordering. This hybridization significantly alters the spectral shape and weight of the ZR state. Specifically, in the AFM phase, we observed the sharpening of the ZR state and band folding with the periodicity of the AFM unit cell of MnO(001). We also demonstrated a strong connection between the spectral evolution of the ZR state and the non-local screening channels of the photoexcited core holes. Further, our detailed temperature-dependent study reveals the presence of short-range antiferromagnetic correlations that exist at much higher temperatures than Neel temperature (T N ) and shows the evolution of the ZR state across the magnetic transitions and its implication to the core-hole screening in 3⁢d binary transition metal oxides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrated chronostratigraphy of Proterozoic-Cambrian boundary beds in the western Anabar region, northern Siberia

Carbonate-rich sedimentary rocks of the western Anabar region, northern Siberia, preserve an exceptional record of evolutionary and biogeochemical events near the Proterozoic/Cambrian boundary. Sedimentologically, the boundary succession can be divided into three sequences representing successive episodes of late transgressive to early highstand deposition; four parasequences are recognized in the sequence corresponding lithostratigraphically to the Manykal Formation. Small shelly fossils are abundant and include many taxa that also occur in standard sections of southeastern Siberia. Despite this coincidence of faunal elements, biostratigraphic correlations between the two regions have been controversial because numerous species that first appear at or immediately above the basal Tommotian boundary in southeastern sections have first appearances scattered through more than thirty metres of section in the western Anabar. Carbon- and Sr-isotopic data on petrographically and geochemically screened samples collected at one- to two-metre intervals in a section along the Kotuikan River, favour correlation of the Staraya Reckha Formation and most of the overlying Manykai Formation with sub-Tommotian carbonates in southeastern Siberia. In contrast, isotopic data suggest that the uppermost Manykai Formation and the basal 26 m of the unconformably overlying Medvezhya Formation may have no equivalent in the southeast; they appear to provide a sedimentary and palaeontological record of an evolutionarily significant time interval represented in southeastern Siberia only by the sub-Tommotian unconformity. Correlations with radiometrically dated horizons in the Olenek and Kharaulakh regions of northern Siberia suggest that this interval lasted approximately three to six million years, during which essentially all 'basal Tommotian' small shelly fossils evolved.

Non-NASA Center↗

Use of high throughput screening methods to study dual-functional crosslinkable latexes

Herein, structure-formulation-property relationships for crosslinkable core-shell latexes were studied initially using high throughput screening methods and then using conventional experimental methods to determine optimum coating formulations. Two approaches that are used within coatings technology to improve sustainability are reduction in volatile organic compounds (VOC) and reduction in energy needed to cure coatings. Hybrid crosslinkable core-shell latexes have shown potential in meeting these challenges where film properties provided by particle coalescence are not sufficient and chemical crosslinking is needed. However, with numerous parameters involved such as latex particle architecture, nature and amount of crosslinker, and curing conditions, the screening of formulations via conventional coating testing methods becomes laborious and time-consuming. The results from high-throughput dye extraction and puncture testing were compared to data from conventional testing methods such as chemical resistance (MEK double rubs), pendulum hardness, and tensile testing to identify correlations. The dye extraction results have shown a strong correlation to solvent resistance and pendulum hardness data whereas toughness from puncture testing data correlated to tensile testing. Both high throughput dye extraction and puncture testing methods can be used for the accelerated screening of crosslinkable coating formulations to optimize curing parameters to achieve the best coating performance.

36 MATERIALS SCIENCE↗

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

NASA Discipline Cardiopulmonary↗

On the Interpretation and Correlation of High-Temperature Ignition Delays in Reactors with Varying Thermodynamic Conditions

Ignition delay time (IDT) is a useful global metric for fuel performance screening and a major target for kinetic modeling. Measurements of IDT are conceptually straightforward, however interpretation could be complicated, especially for systems with changing temperature and pressure. Some experimental conditions in the high repetition rate miniature shock tube (HRRST) exhibit complex temperature and pressure state histories. To better interpret and correlate IDTs, especially those obtained in reactors with varying thermodynamic conditions, an inverse Livengood-Wu (L-W) integral technique is applied to de-convolve the constant condition IDTs from measured IDTs in the HRRST using information on the varying state history. In this paper, the approximate problem is demonstrated using only the measured pressure history leading up to ignition, where the temperature history is estimated based on an isentropic assumption. The IDTs of several fuels were first measured in the HRRST including isooctane and acetone to represent those fuels without strong low temperature chemistry effects. Based on the measured pressure and approximated temperature history, measurements of IDTs in the HRRST compare very favorably with those measured using more conventional techniques, including conventionally sized shock tubes, via the inverse L-W correlation with relaxed Newton iteration and Genetic Algorithm (GA). Furthermore, this study demonstrates the feasibility of using a high throughput ignition testing facility, like the HRRST to extract the constant state IDT measured in regular shock tubes, assisted by the inverse L-W correlation. It is expected with an independent temperature measurement available in the future, IDTs in a broader range of thermodynamic conditions and effects of heat loss could be better resolved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Creep Behavior and Phase Equilibria in Model Precipitate Strengthened Alumina-Forming Austenitic Alloys

Abstract Creep-rupture behavior and microstructural response in alumina-forming austenitic (AFA) alloys with two different precipitation strengthening mechanisms, “Laves-phase + M 23 C 6 carbide” and “coherent L1 2 γ′-Ni 3 (Al,Ti),” were explored as “model” cases of multi-phase, multi-scale heat-resistant AFA alloys for 650–750°C use. These alloys will be used to guide and verify computational alloy design and life-prediction modeling under an on-going eXtremeMAT project through the Office of Fossil Energy and Carbon Management, US Department of Energy. Computational thermodynamics were used to design and predict the amounts of strengthening and deteriorating secondary phases at 750°C. Creep-rupture lives of the alloys tested at 750°C and 100 MPa were in a range of 4000–9000 h, and the microstructure at the gage/grip after creep-rupture testing was compared with isothermally aged alloys for 1500 h, as well as the calculated phases. Detailed microstructure characterization includes phase identification, volume fraction measurement, and compositional analysis, which were correlated with the creep-rupture properties. High-temperature oxidation resistance was also screened and compared with commercial, chromia-forming heat-resistant steels. These model alloys also provide the basis for further design and optimization of next generation AFA alloys with improved creep resistance.

36 MATERIALS SCIENCE↗

Using yttrium as an indicator to estimate total rare earth element concentration: a case study of anthracite-associated clays from northeastern Pennsylvania

Abstract This study demonstrated using yttrium (Y) as an indicator to estimate the total rare earth element and Y contents (REY) in coal-associated samples and to facilitate selection of samples with high REY assays in a fast and inexpensive manner. More than 10 anthracite-associated samples were collected from each of three Pennsylvanian sites (sites B, J and C) based on Thorium gamma ray logging suggesting high REY content. Several samples from each site were analyzed by ICP-MS to determine the rare earth distribution patterns and to establish the site-specific linear equations of Y and REY. The Y contents of the remaining samples were measured by a portable X-ray fluorescence analyzer, and the REY values were estimated based on the site-specific linear equation developed earlier. R-squared values above 0.70 were obtained for all the estimation equations from all three sites on both a whole sample basis and an ash basis. Previously, ash content has been widely used as an indicator of high REY content. This may not be applicable for a specific site. Site B in this study is an example where ash contents could not be statistically correlated with REY, so using Y for estimation is more applicable. The demonstrated sample screening process is suitable for samples from sites that share more similar distribution patterns (either MREY or LREY or HREY) as well as for samples from sites that share multiple distribution patterns (LREY/MREY/HREY) depending on the desirable accuracy. The demonstrated process lowers the analytical cost from $70 to 80 dollars per sample to $10–15 per sample while significantly reducing the processing time and acid consumption for ICP digestion. This is particularly true when a relatively large sample size is involved, for example, 100 samples from one site analyzed by ICP-MS/OES.

Yang, Xiaojing↗