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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An experimental and kinetic modeling study of cyclopentane and dimethyl ether blends

Cyclopentane is a suitable naphthene, or cycloalkane, in a palette for multi-component gasoline surrogate fuels due to its presence in market fuels and its relevance to alkyl substituted cyclopentanes also present. However, the previous oxidation studies of cyclopentane have primarily focused on neat mixtures. Blending cyclopentane with dimethyl ether in this work therefore serves to inform our understanding of, and improve predictive models for, multi-component mixtures. Here, the auto-ignition of cyclopentane/dimethyl ether blends was studied in a high-pressure shock tube and in a rapid compression machine. A wide range of temperatures (650 – 1350 K) and elevated pressures of 20 and 40 bar were studied at equivalence ratios of 0.5, 1.0 and 2.0 in air for two blending ratios (30/70 and 70/30 mole% cyclopentane/di-methyl ether mixtures). A detailed kinetic model for cyclopentane was revised to capture the measured ignition delay times and apparent heat release rates in this study. Literature ignition delay time, jet-stirred reactor, and laminar burning velocity measurements of neat cyclopentane were used as additional validation. Improvements to the kinetic model were based on recent literature studies related to sub-models including cyclopentene and cyclopentadiene which allowed the removal of previous local rate-constant optimizations. Low temperature reactivity of cyclopentane was found to be controlled by the branching ratio between concerted elimination of HO͘ 2 and the strained formation of Q&#775OOH radicals in agreement with previous studies. In this study, the low branching ratio of Q&#775OOH formation increases the influence of a competing consumption pathway for cyclopentyl-peroxy (CPTO͘ 2 J) radicals. The sensitivity of the simulated ignition delay times to the formation of cyclopentyl hydroperoxide (CPTO 2 H), from CPTO͘ 2 J and HO͘ 2 , is discussed. The current model is used to analyze the influence of dimethyl ether on the reactivity of cyclopentane in the context of previous literature studies of dimethyl ether binary blends with ethanol and toluene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Implications of the search for optical counterparts during the second part of the Advanced LIGO’s and Advanced Virgo’s third observing run: lessons learned for future follow-up observations

ABSTRACT Joint multimessenger observations with gravitational waves and electromagnetic (EM) data offer new insights into the astrophysical studies of compact objects. The third Advanced LIGO and Advanced Virgo observing run began on 2019 April 1; during the 11 months of observation, there have been 14 compact binary systems candidates for which at least one component is potentially a neutron star. Although intensive follow-up campaigns involving tens of ground and space-based observatories searched for counterparts, no EM counterpart has been detected. Following on a previous study of the first six months of the campaign, we present in this paper the next five months of the campaign from 2019 October to 2020 March. We highlight two neutron star–black hole candidates (S191205ah and S200105ae), two binary neutron star candidates (S191213g and S200213t), and a binary merger with a possible neutron star and a ‘MassGap’ component, S200115j. Assuming that the gravitational-wave (GW) candidates are of astrophysical origin and their location was covered by optical telescopes, we derive possible constraints on the matter ejected during the events based on the non-detection of counterparts. We find that the follow-up observations during the second half of the third observing run did not meet the necessary sensitivity to constrain the source properties of the potential GW candidate. Consequently, we suggest that different strategies have to be used to allow a better usage of the available telescope time. We examine different choices for follow-up surveys to optimize sky localization coverage versus observational depth to understand the likelihood of counterpart detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

FiXR : a framework to reconstruct fiber cross-sections from X-ray fiber diffraction experiments

Ab initio reconstruction methods have revolutionized the capabilities of small-angle X-ray scattering (SAXS), allowing the data-driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre-range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross-section of a fiber. This cross-section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non-negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross-sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo-EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Binary Blend All‐Polymer Solar Cells with a Record Efficiency of 17.41% Enabled by Programmed Fluorination Both on Donor and Acceptor Blocks

Abstract Despite remarkable breakthrough made by virtue of “polymerized small‐molecule acceptor (PSMA)” strategy recently, the limited selection pool of high‐performance polymer acceptors and long‐standing challenge in morphology control impede their further developments. Herein, three PSMAs of PYDT‐2F, PYDT‐3F, and PYDT‐4F are developed by introducing different fluorine atoms on the end groups and/or bithiophene spacers to fine‐tune their optoelectronic properties for high‐performance PSMAs. The PSMAs exhibit narrow bandgap and energy levels that match well with PM6 donor. The fluorination promotes the crystallization of the polymer chain for enhanced electron mobility, which is further improved by following n ‐doping with benzyl viologen additive. Moreover, the miscibility is also improved by introducing more fluorine atoms, which promotes the intermixing with PM6 donor. Among them, PYDT‐3F exhibits well‐balanced high crystallinity and miscibility with PM6 donor; thus, the layer‐by‐layer processed PM6/PYDT‐3F film obtains an optimal nanofibril morphology with submicron length and ≈23 nm width of fibrils, facilitating the charge separation and transport. The resulting PM6/PYDT‐3F devices realizes a record high power conversion efficiency (PCE) of 17.41% and fill factor of 77.01%, higher than the PM6/PYDT‐2F (PCE = 16.25%) and PM6/PYDT‐4F (PCE = 16.77%) devices.

Zhou, Dehong↗
DOE OSTI2023

Development of HPC based phase field simulations tool for modification of alloy morphology to enhance material properties during additive manufacturing (AM) process

Currently, additive manufacturing (AM) technology is extensively used to manufacture aerospace components because of the unique advantages of the technique in producing custom designs, complex geometries in a near-net fashion that significantly reduces the manufacturing cost, and improved energy efficiency. However, the thermodynamic properties of existing aerospace alloys and the thermal conditions that prevail in most of the powder-bed based additive manufacturing processes lead to undesirable columnar / columnar-dendritic microstructures that promote solidification cracking during the process, and the development of anisotropy in the mechanical properties of the as-built components. Time consuming, energy-intensive post AM treatments are required to recover the mechanical properties of the wrought components for which the existing alloy compositions were designed for. However, novel alloy compositions, that exploit the AM thermal conditions to produce fine, equiaxed grain structures in the as-built condition, with mechanical properties equal to or exceeding those of the wrought work-horse alloy, Ti-6Al-4V has recently been demonstrated in Ti-Cu alloys. Significant energy savings up to 66% can be obtained for a typical aerospace component through digitally designing the AM process, process parameters, and alloy composition. The current project focused on developing a fundamental understanding of the evolution of the columnar to equiaxed transition (CET) occurring during solidification under AM thermal conditions in Ti-Cu and Ti-Cu-X alloys using high-fidelity phase field (PF) simulations using the leadership class computing facilities that exist in the national laboratories. The simulations were able to capture the effect of alloy and process conditions on CET, and clearly showed the beneficial effect of a ternary solute addition to Ti-Cu binary alloys on CET. The simulations indicated that bulk nucleation in the liquid ahead of the solidifying epitaxial front was promoted by a large, transient, thermal undercooling promoted by the mismatch between the growth rate of the dendrite tips in the epitaxial front and the imposed solidification rate. AM experiments performed at Raytheon Technologies Research Center using the same thermal conditions used in the PF simulations indicated the formation of equiaxed grains, although the grain size was bigger than the ones reported in the literature. On the other hand, the equiaxed grain size predicted by PF simulations were smaller than the grain size of Ti-Cu alloys reported in the literature. The industry will follow up the existing work in a future program that would involve further optimization of the process for the Ti-Cu-X alloys to demonstrate the application of the process and the alloy to a specific aerospace component.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Influence of Cr-Additives on the Polarization Resistance of Praseodymium-Doped Ceria Cathodes for Solid Oxide Fuel Cells

While Cr poisoning of the oxygen reduction reaction (ORR) at SOFC cathodes is widely agreed to involve deactivation of oxygen exchange sites, the degradation mechanism remains ambiguous. Here, we selected an alternative cathode material Pr 0.1 Ce 0.9 O 2− δ , free of Sr segregation, to systematically investigate the effect of Cr-induced degradation in ORR. We expand on our previous studies in which the acidity/basicity of binary additives was found to be a strong indicator of the rate of oxygen surface exchange, by electrochemically investigating the ORR activity of the PCO cathode by impedance spectroscopy. Serial infiltration with acidic Cr-based oxides was found to degrade ORR activity as reflected in a 20-fold increase in area specific resistance (ASR) without corresponding changes in activation energy, with the opposite trend obtained with Ca-based oxides. Detected changes in total capacitance, attributed to changes in surface capacitance, also suggest depressed/enhanced PCO surface redox behavior with Cr/Ca-based infiltrants. Taken together, these results point to a more universal source of ORR poisoning/activation, based on acidity/basicity, rather than physical blocking of active sites. With this improved understanding, one can expect progress to be made in the coming years in optimizing means for protecting catalytic surfaces from degradation and/or improving their performance.

25 ENERGY STORAGE↗
DOE OSTI2020

Complex Disorder in Type-I Clathrates: Synthesis and Structural Characterization of A8GaxSn46−x (A = Rb, Cs; 6.9 < x < 7.5)

Exploratory studies in the systems Rb–Ga–Sn and Cs–Ga–Sn yielded the cubic type-I clathrates with refined compositions Rb8GaxSn46−x and Cs8GaxSn46−x (6.9 < x < 7.5). Nearly single-phase materials with good crystallinity were obtained from stoichiometric reactions of the elements. The structures were characterized by means of single-crystal X-ray diffraction methods. Both Rb8GaxSn46−x and Cs8GaxSn46−x represents cases, where a Group 13 element randomly substitutes a Group 14 element in the structure. The extent of Ga/Sn mixing is apparently governed by the drive of the system to achieve an optimal valence electron count, and hence, Rb8GaxSn46−x and Cs8GaxSn46−x (x ≈ 8) can be regarded as Zintl phases. This notion is supported by structure refinements on a multitude of single-crystal X-ray diffraction data, which also confirm that both types of cages in the cubic type-I structure are fully occupied by Rb and Cs atoms. The open-framework, comprised of 46 nodes per formula unit, adapts to the incorporation of nearly eight Ga atoms within the matrix of Sn, whereby small, short-range distortions result. The exact nature of these effects is still unclear, as so far, the structural variations could only be modeled as both positional and occupational disorder at one of three framework sites. Since vacancies in the structures of the binary type-I clathrates A8Sn46−x☐x (A = Rb, Cs; ☐ = missing Sn atom) are also known to cause local distortions, the latter were also synthesized with the same protocols used for the synthesis of A8GaxSn46−x and structurally re-analyzed. The results from the latter studies confirm that homogeneity issues abound, and that the final structures/compositions are an intricate function of the experimental conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improved Particle Heat Transfer by way of Bimodal Particle Distributions for High Temperature Solar Thermal Energy

High temperature solar thermal facilities are looking to increase operating temperatures through novel heat transfer media, one such being solid particles. These particles operating at high temperatures will require transferring their thermal energy into another working fluid like supercritical carbon dioxide which can be used in advanced power cycles. Achieving high heat transfer between the particles and supercritical carbon dioxide is essential to high efficiency and low-cost operation. Therefore, optimizing the thermal conductivity of these particles is one potential way to ensure high performance. Traditionally, unimodal particle distributions have been employed in high temperature particle solar power plants. However, ambient temperature testing of bimodal particle distributions has revealed a superior thermal conductivity when compared to its unimodal counterpart at the same temperature. This data was obtained by certified, off-the-shelf instruments that can effectively simulate the conditions a particle would be exposed to in a high temperature solar thermal system. Data obtained in this way suggests that the increased thermal conductively imputed by a bimodal particle distribution is significant at working temperatures in solar facilities. Furthermore, the thermal conductivity of these bimodal particle distributions peaks when the best combination of large and small particles is applied. At high temperatures, binary particle distributions are compared to monodispersed distributions of larger particles where heat transfer is more prolific due to the increased surface radiation. Various thermal conductivity, porosity and heat exchanger models are explored in conjunction with data acquired up to 700 C.

Stout, Dallin (ORCID:0009000294586091)↗
DOE OSTI2022

Modernization efforts for the R -Matrix code SAMMY [Abstract]

The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Plasma catalytic non-oxidative methane conversion to hydrogen and value-added hydrocarbons on zeolite 13X

Non-thermal plasma has unfolded highly efficient, safe to operate novel routes for methane conversion to hydrogen. In this work, methane conversion is performed under atmospheric dielectric barrier discharge (DBD) plasma with and without 13X zeolite-based catalysts i.e., 13X, Ga/13X, Pd/13X, and Pd-Ga/13X. Experimental results indicate that the plasma catalytic process delivered almost twofold higher product yield than the plasma only route. The binary Pd-Ga catalyst possesses highest catalytic performance with about 40 % CH 4 conversion at an input flowrate of 5 cm 3 min -1 and 2W due to the formation of the Pd-Ga alloy, which acts as catalytic active centre for activating C–H bonds. Product yield can be tailored by the catalyst design where the bimetallic Pd-Ga/13X preferably favours the hydrocarbon formation while H 2 is the dominant product obtained over the Pd/13X. The cleavage of C–H bonds of methane molecule over the plasma only route is mainly governed by energetic electrons in the gaseous phase the catalyst activity, and plasma-catalyst synergism play a significant role in the plasma catalysis process. Further, the findings from this work provide significant insights into the methane activation for subsequent optimization of the methane conversion processes operated on floating production, storage, and offloading vessels (FPSOVs). Exploiting untapped offshore natural gas reserves, where conventional pipeline systems are less economical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Enhancing carbon dioxide capture under humid conditions by optimizing the pore surface structure

Metal–organic frameworks (MOFs) exhibit significant potential for mitigating carbon emissions due to their high porosity and tunability. Despite numerous reports on CO 2 capture by MOF sorbents, a common challenge is their poor selectivity for CO 2 over water. Moreover, in-depth studies are much needed to elucidate the relationships among the pore surface structure, hydrophobicity, and CO 2 uptake capacity/selectivity. In this work, we investigate the factors influencing CO 2 adsorption capacity and selectivity under humidity in a series of isoreticular pillar-layer structures, Ni 2 (L) 2 (dabco) (L = bdc, ndc, adc). Our study shows that increasing ligand conjugation not only results in increased hydrophobicity, decreased pore size and BET surface area, but also leads to the change of primary binding sites of water molecules and higher binding energy of CO 2 , all of which contribute to largely increased CO 2 uptake capacity under humid conditions. Additionally, increasing ligand conjugation and consequently hydrophobicity slow down and reduce competitive water adsorption drastically. Notably, the MOF made of ligand with the highest conjugation, Ni 2 (adc) 2 (dabco), exhibits significantly enhanced CO 2 adsorption in N 2 /CO 2 binary mixtures under relatively high humidity (50% RH), with an increase of ~31% and ~36% for the composition of 15/85 and 50/50, respectively, compared to dry conditions. An experimental FTIR study and DFT theoretical calculations confirm that H 2 O occupies different primary binding site in Ni 2 (bdc) 2 (dabco) and Ni 2 (adc) 2 (dabco), and under humid conditions a higher binding energy of CO 2 is achieved with preferential H 2 O/CO 2 co-adsorption in Ni 2 (adc) 2 (dabco), potentially creating additional adsorption sites for CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Hypothesis tests on Rayleigh wave radiation pattern shapes: a theoretical assessment of idealized source screening

SUMMARY Shallow seismic sources excite Rayleigh wave ground motion with azimuthally dependent radiation patterns. We place binary hypothesis tests on theoretical models of such radiation patterns to screen cylindrically symmetric sources (like explosions) from non-symmetric sources (like non-vertical dip-slip or non-VDS faults). These models for data include sources with several unknown parameters, contaminated by Gaussian noise and embedded in a layered half-space. The generalized maximum likelihood ratio tests that we derive from these data models produce screening statistics and decision rules that depend on measured, noisy ground motion at discrete sensor locations. We explicitly quantify how the screening power of these statistics increase with the size of any dip-slip and strike-slip components of the source, relative to noise (faulting signal strength) and how they vary with network geometry. As applications of our theory, we apply these tests to (1) find optimal sensor locations that maximize the probability of screening non-circular radiation patterns and (2) invert for the largest non-VDS faulting signal that could be mistakenly attributed to an explosion with damage, at a particular attribution probability. Finally, we quantify how certain errors that are sourced by opening cracks increase screening rate errors. While such theoretical solutions are ideal and require future validation, they remain important in underground explosion monitoring scenarios because they provide fundamental physical limits on the discrimination power of tests that screen explosive from non-VDS faulting sources.

58 GEOSCIENCES↗
DOE OSTI2023

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Challenging combinatorial optimization problems are ubiquitous in science and engineering. Several quantum methods for optimization have recently been developed, in different settings including both exact and approximate solvers. Addressing this field of research, this manuscript has three distinct purposes. First, we present an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent. This compact representation often allows for more efficient problem compilation, automated analyses of different encoding choices, easier interpretability, more complex runtime procedures, and richer programmability, as compared to previous approaches, which we demonstrate with a number of examples. Second, we perform numerical studies comparing several qubit encodings; the results exhibit a number of preliminary trends that help guide the choice of encoding for a particular set of hardware and a particular problem and algorithm. Our study includes problems related to graph coloring, the traveling salesperson problem, factory/machine scheduling, financial portfolio rebalancing, and integer linear programming. Third, we design low-depth graph-derived partial mixers (GDPMs) up to 16-level quantum variables, demonstrating that compact (binary) encodings are more amenable to QAOA than previously understood. We expect this toolkit of programming abstractions and low-level building blocks to aid in designing quantum algorithms for discrete combinatorial problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes ($\ell$, |m|) = {(2,2), (2,1), (3,3), (3,2), (4,4)}, and mode mixing effects in the $\ell$ = 3, |m| = 2 harmonics. These AI models combine hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational waves; and graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a three detector network encompassing the Advanced LIGO and Virgo detectors. We first trained these spatiotemporal-graph AI models using synthetic noise, using 1.2 million modeled waveforms to densely sample this signal manifold, within 1.7 h using 256 NVIDIA A100 GPUs in the Polaris supercomputer at the Argonne Leadership Computing Facility. This distributed training approach exhibited optimal classification performance, and strong scaling up to 512 NVIDIA A100 GPUs. With these AI ensembles we processed data from a three detector network, and found that an ensemble of 4 AI models achieves state-of-the-art performance for signal detection, and reports two misclassifications for every decade of searched data. We distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, and completed the processing of a decade of gravitational wave data from a three detector network within 3.5 h. Finally, we fine-tuned these AI ensembles to process the entire month of February 2020, which is part of the O3b LIGO/Virgo observation run, and found 6 gravitational waves, concurrently identified in Advanced LIGO and Advanced Virgo data, and zero false positives. This analysis was completed in one hour using one NVIDIA A100 GPU.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

EF-Hand Battle Royale: Hetero-ion Complexation in Lanmodulin

The lanmodulin (LanM) protein has emerged as an effective means for rare earth element (REE) extraction and separation from complex feedstocks without the use of organic solvents. Whereas the binding of LanM to individual REEs has been well characterized, little is known about the thermodynamics of mixed metal binding complexes (i.e., heterogeneous ion complexes), which limits the ability to accurately predict separation performance for a given metal ion mixture. In this paper, we employ the law of mass action to establish a theory of perfect cooperativity for LanM-REE complexation at the two highest-affinity binding sites. The theory is then used to derive an equation that explains the nonintuitive REE binding behavior of LanM, where separation factors for binary pairs of ions vary widely based on the ratio of ions in the aqueous phase, a phenomenon that is distinct from single-ion-binding chemical chelators. We then experimentally validate this theory and perform the first quantitative characterization of LanM complexation with heterogeneous ion pairs using resin-immobilized LanM. Importantly, the resulting homogeneous and heterogeneous constants enable accurate prediction of the equilibrium state of LanM in the presence of mixtures of up to 10 REEs, confirming that the perfect cooperativity model is an accurate mechanistic description of REE complexation by LanM. We further employ the model to simulate separation performance over a range of homogeneous and heterogeneous binding constants, revealing important insights into how mixed binding differentially impacts REE separations based on the relative positioning of the ion pairs within the lanthanide series. In addition to informing REE separation process optimization, these results provide mathematical and experimental insight into competition dynamics in other ubiquitous and medically relevant, cooperative binding proteins, such as calmodulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗
DOE OSTI2023

Opacities of singly and doubly ionized neodymium and uranium for kilonova emission modeling

ABSTRACT Even though the electromagnetic counterpart AT2017gfo to the binary neutron star merger GW170817 is powered by the radioactive decay of r-process nuclei, only few tentative identifications of light r-process elements have been made so far. One of the major limitations for the identification of heavy nuclei is incomplete or missing atomic data. While substantial progress has been made on lanthanide atomic data over the last few years, for actinides there has been less emphasis, with the first complete set of opacity data only recently published. We perform atomic structure calculations of neodymium (Z = 60) as well as the corresponding actinide uranium (Z = 92). Using two different codes [flexible atomic code (fac) and hartree–fock-relativistic (hfr)] for the calculation of the atomic data, we investigate the accuracy of the calculated data (energy levels and electric dipole transitions) and their effect on kilonova opacities. For the fac calculations, we optimize the local central potential and the number of included configurations and use a dedicated calibration technique to improve the agreement between theoretical and available experimental atomic energy levels (AELs). For ions with vast amounts of experimental data available, the presented opacities agree quite well with previous estimations. On the other hand, the optimization and calibration method cannot be used for ions with only few available AELs. For these cases, where no experimental nor benchmarked calculations are available, a large spread in the opacities estimated from the atomic data obtained with the various atomic structure codes is observed. We find that the opacity of uranium is almost double the neodymium opacity.

Flörs, A. (ORCID:0000000320242819)↗
DOE OSTI2020

Stochastic Gradients for Large-Scale Tensor Decomposition

Tensor decomposition is a well-known tool for multiway data analysis. This work proposes using stochastic gradients for efficient generalized canonical polyadic (GCP) tensor decomposition of large-scale tensors. GCP tensor decomposition is a recently proposed version of tensor decomposition that allows for a variety of loss functions such as Bernoulli loss for binary data or Huber loss for robust estimation. Here, the stochastic gradient is formed from randomly sampled elements of the tensor and is efficient because it can be computed using the sparse matricized-tensor times Khatri--Rao product tensor kernel. For dense tensors, we simply use uniform sampling. For sparse tensors, we propose two types of stratified sampling that give precedence to sampling nonzeros. Numerical results demonstrate the advantages of the proposed approach and its scalability to large-scale problems.

97 MATHEMATICS AND COMPUTING↗