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DOE OSTI2016

ZrB 2 -HfB 2 solid solutions as electrode materials for hydrogen reaction in acidic and basic solutions

Spark plasma sintered transition metal diborides such as HfB 2 , ZrB 2 and their solid solutions were investigated as electrode materials for electrochemical hydrogen evolutions reactions (HER) in 1 M H 2 SO 4 and 1 M NaOH electrolytes. HfB 2 and ZrB 2 formed complete solid solutions when mixed in 1:1, 1:4, and 4:1 ratios and they were stable in both electrolytes. The HER kinetics of the diborides were slower in the basic solution than in the acidic solutions. The Tafel slopes in 1 M H 2 SO 4 were in the range of 0.15 - 0.18 V/decade except for pure HfB 2 which showed a Tafel slope of 0.38 V/decade. In 1 M NaOH the Tafel slopes were in the range of 0.12 - 0.27 V/decade. The composition of Hf x Zr 1-x B 2 solid solutions with x = 0.2 - 0.8, influenced the exchange current densities, overpotentials and Tafel slopes of the HER. As a result, the EIS data were fitted with a porous film equivalent circuit model in order to better understand the HER behavior. In addition, modeling calculations, using density functional theory approach, were carried out to estimate the density of states and band structure of the boride solid solutions.

25 ENERGY STORAGE↗

DOE OSTI2022

Influence of living grass Roots and endophytic fungal hyphae on soil hydraulic properties

Soil hydraulic properties are often estimated based on laboratory data or pedotransfer functions dependent on soil physical properties, which often do not consider potential impacts of soil roots or fungal hyphae. Here, we first review current knowledge of how these soil biotic components affect hydraulic properties, then we conducted laboratory experiments to specifically test if the presence of roots and mycorrhizal fungi had a significant effect on the hydraulic properties of two soils with contrasting textures: Flint sand and Hamblen silt loam. Soil cores were seeded with (Panicum virgatum) and grown in a greenhouse over three separate growth periods. The endophytic fungus Serendipita indica was injected as liquid inoculant into designated mycorrhizal cores. Saturated hydraulic conductivity (K sat ) measurements were made with a constant head permeameter, and soil water retention curves were obtained by the evaporation method, supplemented at the dry end for Hamblen silt loam with water activity meter data. Retention curve parameters were obtained by fitting the van Genuchten equation to the resulting measurements. Mean root volume ratios were higher in the mycorrhizal inoculated treatment than in the uninoculated treatment for both soils. For Flint sand, analysis of variance revealed that K sat was reduced by the presence of roots as compared to bare soil. This was likely due to roots clogging soil pores. Results also indicated the presence of roots changed the shape of the water retention curve for Flint sand by increasing water content at saturation and by reducing the slope of the curve. These changes suggested roots created additional porosity and broadened the pore-size distribution. The presence of mycorrhizal fungi accentuated the root effects. The influence of roots and mycorrhizal fungi on hydraulic properties was less obvious for the Hamblen silt loam, as none of the treatments differed from each other at p < 0.05. The results highlight the necessity to consider the impact of root and fungal structures on models of soil hydraulic properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

An indirect latent informational conformity social influence choice model: Formulation and case study

The current state-of-the-art in social influence models of travel behavior is conformity models with direct benefit social influence effects. Indirect effects have seen limited development, but this paper presents a latent class discrete choice model of an indirect informational conformity hypothesis. Moreover, class membership depends on the proportion of group members who adopt a behavior. Membership into the more informed class causes changes in the preferences of those individuals thus making adoption more attractive. Equilibrium properties are derived for this model showing the possibility of multiple equilibria but under different conditions than the direct-benefit formulations. Social influence elasticity is derived for both models types. The informational conformity model can represent non-linear elasticity behavior unlike the direct-benefit formulation. Additionally, a two-stage control function is developed to obtain consistent parameter estimates in the presence of an endogenous class membership model covariate that is correlated with choice model unobservables. A case study to study social influence in bicycle ownership in the United States is presented. Our results showed that more informed households had a greater chance of owning a bike due to preference changes with less sensitivity to smaller home footprints and limited incomes. The behavioral hypothesis of positive preference change due to information transfer was confirmed. Observed ownership share closely matched predicted local-level equilibrium in some metropolitan areas but was unable to achieve expected prediction rate within confidence intervals. Finally, the elasticity of social influence was found to range locally from about 0.5% to 1.0%.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

Life cycle assessment and life cycle costs for pre-disaster waste management systems

Highlights: • Disaster waste management should include disaster waste response. • Environmental and economic disaster waste management system must be constructed. • Temporary incinerators have environmental and economic disadvantages. • Regional air pollution reduction is vital in disaster waste management planning. - Abstract: This study develops a method of environmental and economic evaluation of an integrated disaster waste management system that considers the spatial scale of removal, transport, and treatment of disaster waste. A case study was conducted on combustibles, which is a type of disaster waste derived from dwellings, in Mie Prefecture, Japan. First, we calculated the quantity and the spatial distribution of disaster waste derived from dwellings and tsunami debris produced as a result of a large-scale earthquake. The quantity of disaster waste was estimated as 7,178,000 t with functioning flood-preventing facilities and 11,956,000 t without functioning flood prevention facilities. Ensuring resilience in the face of earthquakes and tsunamis by renovating flood-preventing facilities is extremely important in decreasing the production of wastes, especially in coastal regions. Next, the transportation network for transporting combustibles in disaster waste to temporary storage sites, incineration plants, and landfill was constructed using an optimization model. The results showed that if flood-preventing facilities do not function properly, the installation of temporary incineration facilities becomes essential. Life-cycle emissions of CO{sub 2}, SO{sub x}, NO{sub x}, and PM and the costs of removal, storage, and treatment of combustibles were calculated as 258,000 t, 618 t, 1705 t, 7.9 t, and 246 million USD, respectively, in the case of functioning flood-preventing facilities. If flood-preventing facilities do not function, the quantity of environmentally unfriendly emissions and the costs increase. This result suggested the significance of renovation in order to maintain the conditions of flood-preventing facilities to decrease the environmental burden and costs as well as keep the production of disaster waste at a minimum.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Estimation of Sea Spray Aerosol Surface Area Over the Southern Ocean Using Scattering Measurements

This study focuses on methods to estimate dry marine aerosol surface area (SA) from bulk optical measurements. Aerosol SA is used in many models' ice nucleating particle (INP) parameterizations, as well as influencing particle light scattering, hygroscopic growth, and reactivity, but direct observations are scarce in the Southern Ocean (SO). Two campaigns jointly conducted in austral summer 2018 provided co-located measurements of aerosol SA from particle size distributions and lidar to evaluate SA estimation methods in this region. Mie theory calculations based on measured size distributions were used to test a proposed approximation for dry aerosol SA, which relies on estimating effective scattering efficiency (Q) as a function of Ångström exponent (å). For distributions with dry å < 1, Q = 2 was found to be a good approximation within ±50%, but for distributions with dry å > 1, an assumption of Q = 3 as in some prior studies underestimates dry aerosol SA by a factor of 2 or more. We propose a new relationship between dry å and Q, which can be used for –0.2 < å < 2, and suggest å = 0.8 as the cutoff between primary and secondary marine aerosol-dominated distributions. Application of a published methodology to retrieve dry marine aerosol SA from lidar extinction profiles overestimated aerosol SA by a factor of 3–5 during these campaigns. Using Microtops aerosol optical thickness measurements, we derive alternative lidar conversion parameters from our observations, applicable to marine aerosol over the SO.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Long-range current-induced spin accumulation in chiral crystals

Abstract Chiral materials, similarly to human hands, have distinguishable right-handed and left-handed enantiomers which may behave differently in response to external stimuli. Here, we use for the first time an approach based on the density functional theory (DFT)+PAOFLOW calculations to quantitatively estimate the so-called collinear Rashba–Edelstein effect (REE) that generates spin accumulation parallel to charge current and can manifest as chirality-dependent charge-to-spin conversion in chiral crystals. Importantly, we reveal that the spin accumulation induced in the bulk by an electric current is intrinsically protected by the quasi-persistent spin helix arising from the crystal symmetries present in chiral systems with the Weyl spin–orbit coupling. In contrast to conventional REE, spin transport can be preserved over large distances, in agreement with the recent observations for some chiral materials. This allows, for example, the generation of spin currents from spin accumulation, opening novel routes for the design of solid-state spintronics devices.

Roy, Arunesh↗

DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Approximate explicit analytic solution of the Elenbaas-Heller equation

The Elenbaas-Heller equation describing the temperature field of a cylindrically symmetrical non-radiative electric arc has been solved, and approximate explicit analytic solutions are obtained. The radial distributions of the heat-flux potential and the electrical conductivity have been figured out briefly by using some special simplification techniques. The relations between both the core heat-flux potential and the electric field with the total arc current have also been given in several easy explicit formulas. Besides, the special voltage-ampere characteristic of electric arcs is explained intuitionally by a simple expression involving the Lambert W-function. The analyses also provide a preliminary estimation of the Joule heating per unit length, which has been verified in previous investigations. Helium arc is used to examine the theories, and the results agree well with the numerical computations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

A generalized Ewald decomposition for screened Coulomb interactions

Medium-range interactions occur in a wide range of systems, including charged-particle systems with varying screening lengths. We generalize the Ewald method to charged systems described by interactions involving an arbitrary dielectric response function ϵ(𝐤). We provide an error estimate and optimize the generalization to find the break-even parameters that separate a neighbor list-only algorithm from the particle-particle particle-mesh algorithm. We examine the implications of different choices of the screening length for the computational cost of computing the dynamic structure factor. We then use our new method in molecular dynamics simulations to compute the dynamic structure factor for a model plasma system and examine the wave-dispersion properties of this system.

Dharuman, Gautham↗

DOE OSTI2020

View factor estimation of hot spot velocities in inertial confinement fusion implosions at the National Ignition Facility

nertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) suffer from asymmetries in thex-ray drive that degrade capsule performance compared to expectations for a symmetric one-dimensional implosion.Mode 1, or pole-to-pole, drive asymmetry can reduce confinement and implosion efficiency, driving a bulk motion ofthe hot spot that is detectable with neutron diagnostics. Understanding and removing sources of mode 1 asymmetry inICF implosions is important for improving performance, and the three-dimensional nature of the problem makes high-resolution radiation-hydrodynamic modeling extremely computationally expensive. This work describes a reducedorder view factor model that calculates the drive asymmetry induced by beam-to-beam variations in laser delivery andhohlraum diagnostic windows along the equator. Capsule response is estimated by coupling to a Green’s function thatrelates final hot spot velocity to the applied time-varying mode 1 asymmetry. The model makes several predictionsabout the impact of mode 1 drivers such as laser delivery and target misalignment, and achieves good agreementin both magnitude and vector direction for several shots in three families of high-performance platforms. However,notable discrepancies suggest other potential sources of mode 1 asymmetry not captured by the model are also at play

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

The weighted priors approach for combining expert opinions in logistic regression experiments

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration. While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A possible mass distribution of primordial black holes implied by LIGO-Virgo

The LIGO-Virgo Collaboration has so far detected around 90 black holes, some of which have masses larger than what were expected from the collapse of stars. The mass distribution of LIGO-Virgo black holes appears to have a peak at ~ 30 M ⊙ and two tails on the ends. By assuming that they all have a primordial origin, we analyze the GWTC-1 (O1&O2) and GWTC-2 (O3a) datasets by performing maximum likelihood estimation on a broken power law mass function f ( m ), with the result f ∝ m 1.2 for m < 35 M ⊙ and f ∝ m -4 for m > 35 M ⊙ . This appears to behave better than the popular log-normal mass function. Surprisingly, such a simple and unique distribution can be realized in our previously proposed mechanism of PBH formation, where the black holes are formed by vacuum bubbles that nucleate during inflation via quantum tunneling. Moreover, this mass distribution can also provide an explanation to supermassive black holes formed at high redshifts.

Astronomy & Astrophysics↗

DOE OSTI2022

The Sensitivity of GPz Estimates of Photo-z Posterior PDFs to Realistically Complex Training Set Imperfections

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: (i) where the spectroscopic training set has a very different distribution in color–magnitude space to the test set, and (ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular, we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ~1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Blinding multiprobe cosmological experiments

ABSTRACT The goal of blinding is to hide an experiment’s critical results – here the inferred cosmological parameters – until all decisions affecting its analysis have been finalized. This is especially important in the current era of precision cosmology, when the results of any new experiment are closely scrutinized for consistency or tension with previous results. In analyses that combine multiple observational probes, like the combination of galaxy clustering and weak lensing in the Dark Energy Survey (DES), it is challenging to blind the results while retaining the ability to check for (in)consistency between different parts of the data. We propose a simple new blinding transformation, which works by modifying the summary statistics that are input to parameter estimation, such as two-point correlation functions. The transformation shifts the measured statistics to new values that are consistent with (blindly) shifted cosmological parameters while preserving internal (in)consistency. We apply the blinding transformation to simulated data for the projected DES Year 3 galaxy clustering and weak lensing analysis, demonstrating that practical blinding is achieved without significant perturbation of internal-consistency checks, as measured here by degradation of the χ2 between the data and best-fitting model. Our blinding method’s performance is expected to improve as experiments evolve to higher precision and accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Core formation in high-z massive haloes: heating by post-compaction satellites and response to AGN outflows

ABSTRACT Observed rotation curves in star-forming galaxies indicate a puzzling dearth of dark matter in extended flat cores within haloes of mass ≥1012M⊙ at z ∼ 2. This is not reproduced by current cosmological simulations, and supernova-driven outflows are not effective in such massive haloes. We address a hybrid scenario where post-compaction merging satellites heat up the dark-matter cusps by dynamical friction, allowing active galactic nucleus (AGN)-driven outflows to generate cores. Using analytic and semi-analytic models (SatGen), we estimate the dynamical friction heating as a function of satellite compactness for a cosmological sequence of mergers. Cosmological simulations (VELA) demonstrate that satellites of initial virial masses >1011.3M⊙, which undergo wet compactions, become sufficiently compact for significant heating. Constituting a major fraction of the accretion on to haloes ≥1012M⊙, these satellites heat up the cusps in half a virial time at z ∼ 2. Using a model for outflow-driven core formation (CuspCore), we demonstrate that the heated dark-matter cusps develop extended cores in response to removal of half the gas mass, while the more compact stellar systems remain intact. The mergers keep the dark matter hot, while the gas supply, fresh and recycled, is sufficient for the AGN outflows. AGNs indeed become effective in haloes ≥1012M⊙, where the black hole growth is no longer suppressed by supernovae and its compaction-driven rapid growth is maintained by a hot circumgalactic medium. For simulations to reproduce the dynamical friction effects, they should resolve the compaction of the massive satellites and avoid artificial tidal disruption. AGN feedback could be boosted by clumpy black hole accretion and clumpy response to AGN.

Dekel, Avishai↗

DOE OSTI2022

Accretion disc sizes from continuum reverberation mapping of AGN selected from the ZTF survey

ABSTRACT We present the accretion disc-size estimates for a sample of 19 active galactic nuclei (AGNs) using the optical g-, r-, and i-band light curves obtained from the Zwicky Transient Facility survey. All the AGNs have reliable supermassive black hole (SMBH) mass estimates based on previous reverberation mapping measurements. The multiband light curves are cross-correlated, and the reverberation lag is estimated using the Interpolated Cross-Correlation Function method and the Bayesian method using the javelin code. As expected from the disc-reprocessing arguments, the g − r band lags are shorter than the g − i band lags for this sample. The interband lags for all, but five sources, are larger than the sizes predicted from the standard Shakura Sunyaev (SS) analytical model. We fit the light curves directly using a thin disc model implemented through the javelin code to get the accretion disc sizes. The disc sizes obtained using this model are on an average 3.9 times larger than the prediction based on the SS disc model. We find a weak correlation between the disc sizes and the known physical parameters, namely the luminosity and the SMBH mass. In the near future, a large sample of AGNs covering broader ranges of luminosity and SMBH mass from large photometric surveys would be helpful in a better understanding of the structure and physics of the accretion disc.

Jha, Vivek Kumar (ORCID:0000000232776335)↗

DOE OSTI2022

Nothing to see here: failed supernovae are faint or rare

ABSTRACT The absence of Type IIP core-collapse supernovae arising from progenitors above 17 solar masses suggests the existence of another evolutionary path by which massive stars end their lives. The direct collapse of a stellar core to a black hole without the production of a bright, explosive transient is expected to produce a long-lived, dim, red transient known as a failed supernova. Despite the detection of a number of candidates for disappearing massive stars in recent years, conclusive observational evidence for failed supernovae remains elusive. A custom-built pipeline designed for the detection of faint transients is used to re-analyse 10 yr of observations of 231 nearby galaxies from the PTF/ZTF surveys. This analysis recovers known supernovae, and yields a number of interesting transients. However, none of these are consistent with a failed supernova. Through Monte Carlo tests the recovery efficiency of our pipeline is quantified. By assuming failed supernovae occur as a Poissonian process with zero detections in the data set, 95 per cent upper limits to the rate of failed supernovae are calculated as a function of failed supernova absolute magnitude. We estimate failed supernovae to be less than 0.61, 0.33, 0.26, or 0.23 of the core-collapse SN rate for absolute magnitudes of −11, −12, −13, and −14, respectively. Finally, we show that if they exist, the Vera C. Rubin Observatory will find 1.7–3.7 failed SNe per year for an absolute bolometric luminosity of ∼6 × 1039 erg s−1 out to distances of 33–43 Mpc, depending on their assumed spectral energy distribution.

Byrne, R. A. (ORCID:0000000177661737)↗

DOE OSTI2022

Dark energy survey year 3 results: cosmological constraints from the analysis of cosmic shear in harmonic space

ABSTRACT We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudo-Cℓ method and complement the analysis of the two-point correlation functions in real space, as the two estimators are known to compress and select Gaussian information in different ways, due to scale cuts. They may also be differently affected by systematic effects and theoretical uncertainties, making this analysis an important cross-check. Using the same fiducial Lambda cold dark matter model as in the DES Y3 real-space analysis, we find ${S_8 \equiv \sigma _8 \sqrt{\Omega _{\rm m}/0.3} = 0.793^{+0.038}_{-0.025}}$, which further improves to S8 = 0.784 ± 0.026 when including shear ratios. This result is within expected statistical fluctuations from the real-space constraint, and in agreement with DES Y3 analyses of non-Gaussian statistics, but favours a slightly higher value of S8, which reduces the tension with the Planck 2018 constraints from 2.3σ in the real space analysis to 1.5σ here. We explore less conservative intrinsic alignments models than the one adopted in our fiducial analysis, finding no clear preference for a more complex model. We also include small scales, using an increased Fourier mode cut-off up to $k_{\rm max}={5}\, {h}\, {\rm Mpc}^{-1}$, which allows to constrain baryonic feedback while leaving cosmological constraints essentially unchanged. Finally, we present an approximate reconstruction of the linear matter power spectrum at present time, found to be about 20 per cent lower than predicted by Planck 2018, as reflected by the lower S8 value.

79 ASTRONOMY AND ASTROPHYSICS↗