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At least 1,027 records · Page 57

PyFLOSIC: Python-based Fermi–Löwdin orbital self-interaction correction

We present pyflosic, an open-source, general-purpose python implementation of the Fermi–Löwdin orbital self-interaction correction (FLO-SIC), which is based on the python simulation of chemistry framework (pyscf) electronic structure and quantum chemistry code. Thanks to pyscf, pyflosic can be used with any kind of Gaussian-type basis set, various kinds of radial and angular quadrature grids, and all exchange-correlation functionals within the local density approximation, generalized-gradient approximation (GGA), and meta-GGA provided in the libxc and xcfun libraries. A central aspect of FLO-SIC is the Fermi-orbital descriptors, which are used to estimate the self-interaction correction. Importantly, they can be initialized automatically within pyflosic; they can also be optimized within pyflosic with an interface to the atomic simulation environment, a python library that provides a variety of powerful gradient-based algorithms for geometry optimization. Although pyflosic has already facilitated applications of FLO-SIC to chemical studies, it offers an excellent starting point for further developments in FLO-SIC approaches, thanks to its use of a high-level programming language and pronounced modularity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-learning accelerated geometry optimization in molecular simulation

Geometry optimization is an important part of both computational materials and surface science because it is the path to finding ground state atomic structures and reaction pathways. These properties are used in the estimation of thermodynamic and kinetic properties of molecular and crystal structures. This process is slow at the quantum level of theory because it involves an iterative calculation of forces using quantum chemical codes such as density functional theory (DFT), which are computationally expensive and which limit the speed of the optimization algorithms. It would be highly advantageous to accelerate this process because then one could do either the same amount of work in less time or more work in the same time. Here, we provide a neural network (NN) ensemble based active learning method to accelerate the local geometry optimization for multiple configurations simultaneously. We illustrate the acceleration on several case studies including bare metal surfaces, surfaces with adsorbates, and nudged elastic band for two reactions. In all cases, the accelerated method requires fewer DFT calculations than the standard method. In addition, we provide an Atomic Simulation Environment (ASE)-optimizer Python package to make the usage of the NN ensemble active learning for geometry optimization easier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dark Energy Survey Year 1 Results: Cosmological constraints from cluster abundances and weak lensing

In this work we perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =\sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $\Omega_{\rm m}=0.179^{+0.031}_{-0.038}$, with $\sigma_8-\Omega_{\rm m}$ posteriors in $2.4\sigma$ tension with the DES Y1 3x2pt results, and in $5.6\sigma$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($\lambda \ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Climate, food and humans predict communities of mammals in the United States

Abstract Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty‐five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard‐mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine‐scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Kays, Roland↗

Cherenkov Gamma Ray Detectors on High-Energy-Density Systems

Cherenkov gamma ray detectors are a valuable diagnostic technique for HED systems. Inertial confinement fusion is working towards high gain ignition. Gamma rays from ICF systems can help inform the degradation mechanisms preventing ignition: Carbon ablator is not being degraded, unlike the DT fuel; carbon γ timing can estimate shell energy during bangtime and may suggest hot spot cooling rate; and Cherenkov detectors are also used for high spatial and temporal resolution ICF mix studies on OMEGA. Cherenkov systems also inform energy spectrum of radiographic sources: ARC laser and Mercury pulsed power machine.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sludge Batch 11 Assembly: Tank 15

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 15 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 15 prior to transfer from Tank 15 to Tank 13 (prior to sending to Tank 51) in order to demonstrate that the transfer is "Low Rem" and ensure the sludge concurs with the estimated transfer mass for the SB11 recipe. A total of 3 sets of Tank 15 samples were delivered to SRNL from December 2022 to August 2023. The individual sets of composite samples were analyzed for density, weight percent solids, chemical composition, radionuclides, and/or supernate corrosion control tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Stochastic Framework for Optimal Control of Planetary Reentry Trajectories Under Multilevel Uncertainties

We present a novel stochastic optimal control framework that accounts for various types of uncertainties, with application to reentry trajectory planning. The formulation of the optimal trajectory control problem is presented in the context of an indirect method where a functional objective associated with the terminal vehicle speed is to be minimized. Uncertain input parameters in the optimal trajectory control model, including aerodynamic parameters and initial and terminal conditions, are modeled as aleatory random variables, while the statistical parameters of these aleatory distributions are themselves random variables. The parametric and model uncertainties are simultaneously propagated through an extended polynomial chaos expansion (EPCE) formalism. Several metrics are described to evaluate response statistics and presented as insightful tools for robust decision making. Specifically, the response probability density function (PDF) reflecting influence of both epistemic and aleatory uncertainties is obtained. By sampling over the random variables representing model error, an ensemble of response PDFs is generated and the associated failure probability is estimated as a random variable with its own polynomial chaos expansion. Besides, the sensitivity index functions of response PDF with respect to the statistical parameters are evaluated. Coupling parametric and model uncertainties within the EPCE framework leads to a robust and efficient paradigm for multilevel uncertainty propagation and PDF characterization in general optimal control problems.

Engineering↗

Allometric and Mobile Terrestrial LiDAR Modeling of Aboveground Woody Biomass of Populus in Coppice Production

Poplars ( Populus spp.) and their hybrids are increasingly being grown in coppice production to generate bioenergy feedstocks at frequent intervals. Allometric equations are re-quired to predict aboveground biomass (AGB) of coppiced individuals with minimal field measurements. Likewise, remote sensing tools like LiDAR (light detection and ranging) can be used if models are available to predict AGB from point cloud data. Therefore, this study sought to develop equations to predict dry woody AGB from field measurements and LiDAR data from coppiced poplar field trials containing eastern cottonwood ( P. del-toides ) and hybrid poplar taxa. We found that taxa-specific allometric models containing the summed basal area of the three largest stems in the coppice provided the best predictive model, with stem height and stem count failing to provide additional explanatory power. The best predictive LiDAR-based model was independent of taxa but had slightly lower adjusted R 2 and higher RMSE than the allometric model. It contained four parameters including crown volume, leaf area index, variance of height returns, and the top point density (i.e., density metric 9 or the proportion of points in the highest point interval when the point cloud is evenly divided into ten vertical intervals). In total, these models can be used to quickly and efficiently estimate dry woody AGB of Populus coppice systems for bioenergy feedstock production.

AGB↗

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multi-Polymer Matrix

Advanced manufacturing techniques, such as additive manufacturing (AM), that can directly integrate phase change materials (PCMs) have garnered interest in recent years due to their potential for development of highly efficient thermal energy storage architectures. Complex, high surface area geometries embedded with PCMs that are only feasible with AM can improve thermal management with reduced material waste. Our work focuses on developing composite filaments with microencapsulated phase change materials (MEPCM) bound within a single or dual polymer matrix that can be processed through standard filament extruders and additively manufactured using off-the-shelf 3D printers. Polymer powders, rather than polymer pellets, were key to homogenously mixed filaments achieving high MEPCM loadings with no deterioration in thermal energy storage (TES) capability during extrusion. Composite filaments contain upwards of 60 wt% MEPCM and were printed without loss in feature resolution, print speed, or layer adhesion. Storage enthalpies of printed composites range from 100 - 130 kJ/kg, which were within 5% of the theoretical enthalpy based on weight fraction of MEPCM and maintained enthalpies within 1% over 500 thermal cycles. We can reliably manufacture low density, high surface area structures like 15% gyroid infill, along with dense, compact pucks at a 100% concentric infill. Prints were also scalable to a 900 cm3 honeycomb infill heat exchanger model that has an estimated energy storage capacity of 9 Wh.

3D printing↗

Don't cross the streams: caustics from fuzzy dark matter

Here we study how tidal streams from globular clusters may be used to constrain the mass of ultra-light dark matter particles, called `fuzzy' dark matter (FDM). A general feature of FDM models is the presence of ubiquitous density fluctuations in bound, virialized dark matter structures, on the scale of the de Broglie wavelength, arising from wave interference in the evolving dark matter distribution. These time-varying fluctuations can disturb the motions of stars, leading to potentially observable signatures in cold thin tidal streams in our own Galaxy. The study of this effect has been hindered by the difficulty in simulating the FDM wavefunction in Milky Way-sized systems. We present a simple method to evolve realistic wavefunctions in nearly static potentials, that should provide an accurate estimate of this granulation effect. We quantify the impact of FDM perturbations on tidal streams, and show that initially, while stream perturbations are small in amplitude, their power spectra exhibit a sharp cutoff corresponding to the de Broglie wavelength of the FDM potential fluctuations. Eventually, when stream perturbations become nonlinear, fold caustics generically arise that lead to density fluctuations with universal behavior. This erases the signature of the de Broglie wavelength in the stream density power spectrum, but we show that it will still be possible to determine the FDM mass in this regime, by considering the fluctuations in quantities like angular momenta or actions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Planck 2018 results - VIII. Gravitational lensing

We present measurements of the cosmic microwave background (CMB) lensing potential using the final Planck 2018 temperature and polarization data. Using polarization maps filtered to account for the noise anisotropy, we increase the significance of the detection of lensing in the polarization maps from 5σ to 9σ. Combined with temperature, lensing is detected at 40σ. We present an extensive set of tests of the robustness of the lensing-potential power spectrum, and construct a minimum-variance estimator likelihood over lensing multipoles 8 ≤ L ≤ 400 (extending the range to lower L compared to 2015), which we use to constrain cosmological parameters. We find good consistency between lensing constraints and the results from the Planck CMB power spectra within the ΛCDM model. Combined with baryon density and other weak priors, the lensing analysis alone constrains σ 8 Ωm 0.25 = 0.589 ± 0.020 (1σ errors). Also combining with baryon acoustic oscillation data, we find tight individual parameter constraints, σ8 = 0.811 ± 0.019, H0 = 67.9-1.3+1.2 km s -1 Mpc -1 , and Ω m = 0.303 -0.018 +0.016 . Combining with Planck CMB power spectrum data, we measure σ 8 to better than 1% precision, finding σ 8 = 0.811 ± 0.006. CMB lensing reconstruction data are complementary to galaxy lensing data at lower redshift, having a different degeneracy direction in σ 8 - Ω m space; we find consistency with the lensing results from the Dark Energy Survey, and give combined lensing-only parameter constraints that are tighter than joint results using galaxy clustering. Using the Planck cosmic infrared background (CIB) maps as an additional tracer of high-redshift matter, we make a combined Planck-only estimate of the lensing potential over 60% of the sky with considerably more small-scale signal. We additionally demonstrate delensing of the Planck power spectra using the joint and individual lensing potential estimates, detecting a maximum removal of 40% of the lensing-induced power in all spectra. The improvement in the sharpening of the acoustic peaks by including both CIB and the quadratic lensing reconstruction is detected at high significance.

79 ASTRONOMY AND ASTROPHYSICS↗

Estimating Beam-Target Heating

At Los Alamos National Laboratory, two high-current linear induction accelerators (LIAs) are used to produce bremsstrahlung source spots for flash radiography of high-explosive driven hydrodynamic experiments at the Dual Axis Radiographic Hydrodynamic Test (DARHT) facility. Measurements of the electron-beam current density profile are valuable for understanding the beam dynamics in order to improve the quality of the radiography source spot. A technique commonly used at DARHT is to image the profile in Cerenkov or Optical Transition Radiation (OTR) light created by the beam striking a thin target inserted into the beam line. Target materials include aluminized dielectrics and titanium foils for OTR, and fused silica wafers for Cerenkov radiation. A practical complication with this technique is heating of the target by the electron beam. If the beam density is too great, the target can be destroyed. Moreover, even if the beam density is kept low enough to be nondestructive, the beam can heat the target to a high enough temperature to desorb gas from the surface. In that case, direct impact ionization of the gas by beam electrons can partially neutralize the beam, causing it to over-focus, thereby spoiling the data, if not destroying the target. The purpose of this note is to review some of the fundamental physics of electron beam heating in order to provide some elementary guidance for design of these imaging experiments to avoid overheating the target. Some specific examples for materials that we often use for imaging targets and beam-target experiments are provided.

43 PARTICLE ACCELERATORS↗

Radiation-induced alteration of sandstone concrete aggregate

This study investigates the alteration of felsic sandstone-type rock, which is used as a coarse aggregate in concrete, subject to the effects of gamma-ray and neutron irradiation. The effects of three gamma-ray doses (27, 55, and 108 MGy) and four neutron fluence levels (1.22, 2.19, 6.99, and 14.30 × 10 19 n/cm 2 , $E$ ≥ 0.01 MeV) were investigated. Quartz and albite were found to be the major rock-forming minerals, with microcline intermediates, chlorite, and muscovite as the minors. Gamma rays caused no significant changes to the physical properties of the sandstone aggregates, even at high doses (108 MGy). In contrast, neutron irradiation caused alterations that became more pronounced at higher neutron fluences. The solid was confirmed to expand through metamictization of the rock-forming minerals. Quartz and muscovite were the most affected phases, whereas albite and microcline intermediates were only slightly affected, and chlorite was almost unaffected. The decrease in density was measured by He and water pycnometry, and this value was almost reproduced by calculations using the rock-forming mineral composition of the pristine sample measured using X-ray powder diffraction/Rietveld analysis and the cell volume change of the major forming minerals. In addition, light optical microscopy and scanning electron microscopy images confirmed the presence of intergranular and intragranular cracks. Intergranular cracks appeared to have initiated from the quartz grains, which expanded significantly. The intragranular cracks were frequently observed in the albite and microcline intermediates. These cracks can be described as radial cracks starting from the expanding quartz, caused by enforced displacement for deformation consistency with quartz expansion. The crack area ratio quantified by SEM image analysis corresponds to the discrepancy of the volume expansion difference calculated by He or water pycnometry and dimensional change measurements. In conclusion, an evaluation of solid expansion and crack openings in aggregates is important to estimate concrete degradation.

36 MATERIALS SCIENCE↗

Design of 1500V/200kW 99.6% Efficiency Dual Active Bridge Converters Based on 1700V SiC Power MOSFET Module

High efficiency, high density and galvanically isolated power converters are attractive for medium voltage high power applications. This paper presents a 1.5kV/200kW bidirectional Dual Active Bridge (DAB) converter using a newly developed 1.7kV SiC MOSFET module. The intended application is megawatt scale solid state transformer (SST) and 1500V PV inverter application using modular architecture. One novel model to estimate the turn-off loss using snubber capacitors is proposed and experimentally verified. An optimized PCB-based busbar design is introduced to reduce the voltage overshoot across the SiC device, making the design suitable for 1.5kVdc applications. The mechanism of how the optimized PCB-based busbar can reduce the voltage overshoot is quantitatively interpreted and experimentally verified. The DAB converter achieved an efficiency of 98.85% at 200kW and a maximum of 99.53% at 60kW. The maximum efficiency for series-resonant mode is 99.6% at 85kW and 99.3% at 200kW. The power density is 26W/inch3 (1.6MW/m3) which is much higher than traditional industry products.

Xu, Wei↗

Optical Properties of Neutral F Centers in Bulk MgO with Density Matrix Embedding

The optical spectra of neutral oxygen vacancies (F 0 centers) in the bulk MgO lattice are investigated using density matrix embedding theory. The impurity Hamiltonian is solved with the complete active space self-consistent field and second-order n-electron valence state perturbation theory (NEVPT2-DMET) multireference methods. Here, to estimate defect-localized vertical excitation energies at the nonembedding and thermodynamic limits, a double extrapolation scheme is employed. The extrapolated NEVPT2-DMET vertical excitation energy value of 5.24 eV agrees well with the experimental absorption maxima at 5.03 eV, whereas the excitation energy value of 2.89 eV at the relaxed triplet defect-localized state geometry overestimates the experimental emission at 2.4 eV by only nearly 0.5 eV, indicating the involvement of the triplet–singlet decay pathway.

embedding↗

Positron stopping in multilayer materials

Positron annihilation spectroscopy provides a sensitive toolset for defect characterization. In beam based studies of single-layer targets, the form of implantation profiles is well established, depending on the kinetic energy and angle of incident positrons relative to the target surface and the density and average atomic number of the target. For multilayer systems, the difference in density and across the layers makes derivation of an analytical form difficult. To date, the determination of positron stopping profiles in multilayer targets has primarily involved Monte Carlo simulations. We present here an alternative approach that estimates the energy distribution dN/dE of those positrons transmitted past each layer boundary, by fitting the remaining tail of the stopping profile after each layer with a basis set comprised of calculated stopping profiles in the same material they are transmitted through. The stopping profile in the next layer is then found by summing a series of stopping profiles in the new medium in proportion to the determined distribution dN/dE. The results of our model are compared with simulation results in a system of alternating layers of Al and Au and find reasonable agreement in the predicted profile and excellent agreement in the predicted mean implantation depth. Finally, we derived a simple formula-based approach for the calculation of the mean implantation depth in two-layer systems that provides results in excellent agreement with the full model.

Jones, A. C. L. [Arizona State University, Tempe, ↗

Nonlinear self-focusing in strongly magnetized pair plasma

An intense radiation field can modify plasma properties and the corresponding refractive index and lead to nonlinear propagation effects such as self-focusing. In this work, we estimate the corresponding effects in pair plasmas for circularly polarized waves, in both unmagnetized and strongly magnetically dominated cases. First, in the unmagnetized pair plasma the ponderomotive force does not lead to charge separation but to density depletion. Second, for astrophysically relevant plasmas of pulsar magnetospheres [and possible loci of fast radio bursts (FRBs)], where the cyclotron frequency $ω_B$ dominates over the plasma frequency $ω_p$ and the frequency of the electromagnetic wave $ω_B \gg ω_p, ω$, we show that (i) there is virtually no nonlinearity due to changing effective mass in the field of the wave; (ii) the ponderomotive force is $F^{(B)}_p = –m_ec^2/4B^2_0∇E^2$, which is reduced by a factor $(ω/ω_B)^2$ if compared to the unmagnetized case ($B_0$ is the external magnetic field and $\textit{E}$ is the electric field of the wave); and (iii) for a radiation beam propagating along a constant magnetic field in the pair plasma with density $n_±$, the ponderomotive force leads to the appearance of circular currents that lead to a decrease of the field within the beam by a factor $ΔB/B_0 = 2πn_±m_ec^2E^2 /B^4_0$. Applications to the physics of FRBs are discussed; we conclude that for the parameters of FRBs, the dominant magnetic field completely suppresses nonlinear self-focusing or filamentation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structural motifs and bonding in two families of boron structures predicted at megabar pressures

The complex crystal chemistry of elemental boron has led to numerous proposed structures with distinctive motifs as well as contradictory findings. Herein, evolutionary structure searches performed at 100 GPa have uncovered a series of metastable phases of boron, and bonding analyses were carried out to elucidate their electronic structure. These polymorphs, dynamically stable at 100 GPa, were grouped into two families. Here, the first was derived from the thermodynamic minimum at these conditions, α-Ga, whereas channels comprised the second. Two additional intergrowth structures were uncovered, and it was shown they could be constructed by stacking layers of α-Ga-like and channel-like allotropes on top of each other. A detailed bonding analysis revealed networks of four-center σ-bonding functions linked by two-center B-B bonds in the α-Ga based structures, and networks that were largely composed of three-center σ-bonding functions in the channel-based structures. Seven of these high-pressure phases were found to be metastable at atmospheric conditions, and their Vickers hardnesses were estimated to ≈ 36 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗