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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models

Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's n). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2024

Quantum computation of frequency-domain molecular response properties using a three-qubit iToffoli gate

The quantum computation of molecular response properties on near-term quantum hardware is a topic of substantial interest. Computing these properties directly in the frequency domain is desirable, but the circuits require large depth if the typical hardware gate set consisting of single- and two-qubit gates is used. While high-fidelity multipartite gates have been reported recently, their integration into quantum simulation and the demonstration of improved accuracy of the observable properties remains to be shown. Here, we report the application of a high-fidelity multipartite gate, the iToffoli gate, to the computation of frequency-domain response properties of diatomic molecules. The iToffoli gate enables a ~50% reduction in circuit depth and ~40% reduction in circuit execution time compared to the traditional gate set. We show that the molecular properties obtained with the iToffoli gate exhibit comparable or better agreement with theory than those obtained with the native CZ gates. Our work is among the first demonstrations of the practical usage of a native multi-qubit gate in quantum simulation, with diverse potential applications to near-term quantum computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Investigating property-porosity relationships for micro-architected lattice structures

Micro-architected structures are increasingly valued for their light weight and tunable mechanical properties; this class of material includes sheet structures like the Schöen gyroid and beam lattices like the octet. For design purposes, it is critical to understand how to tune the relative density (RD) to obtain desired mechanical properties. This study investigates the mechanical response of Ti-6Al-4V gyroid structures, spanning a broad range of RDs (0.03–0.90), unit cell sizes (1–4 cm), and sheet thicknesses (0.2–7.8 mm). Results demonstrate that the classical Gibson-Ashby power law scaling between RD and modulus and yield stress does not adequately capture the response over a wide range of RDs, nor does it extrapolate correctly to the fully dense solid. Analytical models, in concert with experimental results and high-fidelity finite element calculations, show that the deviation from Gibson-Ashby reflects a transition from structure-dominated to material-dominated behavior. Distinctions are drawn between scaling relationships and property-porosity models, and an analytical model is proposed to better capture the evolution of mechanical properties with RD. These observations are mirrored in other architected topologies, like the octet, and highlight the importance of understanding the relationship between mechanical properties and geometry for design purposes.

Materials science↗
DOE OSTI2020

Active Learning-driven Quantitative Synthesis-Structure-Property Relations for Improving Performance and Revealing Active Sites of Nitrogen-Doped Carbon for the Hydrogen Evolution Reaction

While quantitative structure-properties relations (QSPRs) have been developed successfully in multiple fields, catalyst synthesis affects structure and in turn performance, making simple QSPRs inadequate. Furthermore, catalysts often have multiple active sites preventing one from obtaining insights into structure-property relations. Here, we develop a data-driven quantitative synthesis-structure-property relation (QS2PRs) methodology to elucidate correlations between catalyst synthesis conditions, structural properties as well as observed performance and to provide fundamental insights into active sites and a systematic way to optimize practical catalysts. Here, we demonstrate the approach to the synthesis of nitrogen-doped catalysts (NDC) made via pyrolysis for the performance of the electrochemical hydrogen evolution reaction (HER), quantified by the onset potential and the current density. We determine crystallinity, nitrogen species type and fraction, surface area, and pore structure of the NDC’s using XRD, XPS, and BET characterization. We demonstrated that an active learning-based optimization combined with various elementary machine learning tools (regression, principal component analysis, partial least squares) can efficiently identify optimum pyrolysis conditions to tune structural characteristics and performance with concomitant savings in materials and experimental time. Unlike previous reports on the importance of pyridinic or graphitic nitrogen, we discover that the electrochemical performance is not driven by a single catalyst property; rather, it arises from a multivariate influence of nitrogen dopants, pore structure and disorder in the NDC materials. Identification of active sites can help mechanistic understanding and further catalyst improvement.

42 ENGINEERING↗
DOE OSTI2020

Influence of Hydrogen and Oxygen on the Structure and Properties of Sputtered Magnesium Zirconium Oxynitride Thin Films

Nitride materials with mixed ionic and covalent bonding character and resulting good charge transport properties are attractive for optoelectronic devices. Recently, Mg-based ternary nitride materials were found to have large dielectric constants and high absorption coefficients with bandgaps appropriate for photovoltaic applications. However, their degenerate carrier concentrations still hinder their possible applications in solar cells and related optoelectronic devices. Therefore, further understanding and engineering of the parameters controlling the material properties of these ternary nitrides is highly desirable. In this paper we report that the structural, optical and electrical properties of magnesium zirconium oxynitride (MZNO) thin films synthesized by combinatorial sputtering with a wide range of cation compositions can be affected by incorporation of oxygen and hydrogen. Excess oxygen improved the crystallinity of MZNO thin films whereas hydrogen attracted oxygen and formed Mg-rich oxide layers at the grain boundaries which in turn reduced the conductivity. On the other hand, optical properties are more sensitive to the composition – both cation and anion ratios – rather than the presence of hydrogen. Compared to cation-stoichiometric MZNO (10 19 –10 20 cm -3 ), substantial reduction of carrier concentration down to ~10 14 cm -3 was achieved under Mg-rich conditions by supplying hydrogen during growth. Photoluminescence measurements showed that the films prepared with hydrogen were optoelectronically active. Overall, this study demonstrates that the material properties of MZN thin films can be significantly influenced by incorporation of oxygen and hydrogen.

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

Are you using the right probe molecules for assessing the textural properties of metal–organic frameworks?

Textural properties—such as the surface area, pore size distribution, and pore volume—are at the forefront of characterization for porous materials. Therefore, it is essential to accurately and reproducibly report a material's textural properties as they could ultimately dictate its applicability. This work aims to provide insightful and comprehensive studies of textural properties for a set of metal–organic frameworks (MOFs), a class of porous materials, using various gases to equip researchers in the field with a helpful guide and reference. Here, we selected a series of nine MOFs with different surface areas, pore sizes, shapes, and chemical environments to represent a wide range of materials. We probed the textural properties of these MOFs using traditional and distinctive gases: N 2 , Kr and O 2 at 77 K, Ar at 87 K, and CO 2 at 195 and 273 K. With regard to surface area, we discuss the validity and challenges associated with the current BET method, the importance of utilizing the Rouquerol et al. consistency criteria to ensure accuracy and reproducibility, and the recommended gas probes for certain materials. For pore size distribution, we discuss the efficacy of each probe for determining the pore sizes within a porous material relative to the calculated distribution from its crystal structure, the limitations of current computational kernels used to calculate pore size distributions, and the need for advanced kernels to envelope the diversity of porous materials. Finally, for pore volume, we discuss the use of the Gurvich rule to obtain the total pore volume in comparison with calculated values from crystal structures and its consistency as a metric for porous materials. Ultimately, we hope that this article will aid researchers in characterizing the textural properties of porous materials and encourage the development of new kernels capable of encompassing the complexity of MOFs and other porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

XANES analysis of phosphate glasses melted with Tb 4 O 7 and SnO: evaluating the impact of valence states on structural, thermal, and luminescent properties

Barium phosphate glasses were prepared with 0.5 mol% Tb 4 O 7 added alongside SnO up to 5 mol% with the purpose of evaluating the resulting terbium and tin oxidation states and their impact on glass structural, thermal, and luminescent properties. In this work, following material synthesis by melt-quenching, the composition-structure–property investigation was pursued encompassing measurements by X-ray diffraction (XRD), X-ray absorption near-edge spectroscopy (XANES), Raman spectroscopy, differential scanning calorimetry (DSC), dilatometry, and photoluminescence (PL) spectroscopy. While XRD confirmed the amorphous nature of the glasses, results from XANES indicated that terbium occurs as terbium(III) with a predisposition for tin to exist as tin(IV) which decreased at high SnO content. The structural as well as the thermal properties appeared to be mostly impacted by the presence of tin(IV). Specifically, glass depolymerization was indicated to be induced by Sn 4+ ions, and their concentration was observed to correlate with glass transition and softening temperatures. On the other hand, the tin(II) remnants were observed to exert an impact on the luminescent properties shifting light emission from the green towards the blue-green (cyan). It is indicated that Tb 4 O 7 reacting to produce Tb 2 O 3 supports the oxidation of tin(II) to tin(IV) which in turn dominates the physical properties. However, this was somewhat circumvented at the highest SnO content wherein tin(IV) appeared to be lower.

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

Side chain engineering in indacenodithiophene- co -benzothiadiazole and its impact on mixed ionic–electronic transport properties

Organic semiconductors are increasingly being decorated with hydrophilic solubilising chains to create materials that can function as mixed ionic–electronic conductors, which are promising candidates for interfacing biological systems with organic electronics. While numerous organic semiconductors, including p- and n-type materials, small molecules and polymers, have been successfully tailored to encompass mixed conduction properties, common to all these systems is that they have been semicrystalline materials. Here, we explore how side chain engineering in the nano-crystalline indacenodithiophene-co-benzothiadiazole (IDTBT) polymer can be used to instil ionic transport properties and how this in turn influences the electronic transport properties. This allows us to ultimately assess the mixed ionic–electronic transport properties of these new IDTBT polymers using the organic electrochemical transistor as the testing platform. Using a complementary experimental and computational approach, we find that polar IDTBT derivatives can be infiltrated by water and solvated ions, they can be electrochemically doped efficiently in aqueous electrolyte with fast doping kinetics, and upon aqueous swelling there is no deterioration of the close interchain contacts that are vital for efficient charge transport in the IDTBT system. Despite these promising attributes, mixed ionic–electronic charge transport properties are surprisingly poor in all the polar IDTBT derivatives. Albeit a “negative” result, this finding clearly contradicts established side chain engineering rules for mixed ionic–electronic conductors, which motivated our continued investigation of this system. We eventually find this anomalous behaviour to be caused by increasing energetic disorder in the polymers with increasing polar side chain content. We have investigated computationally how the polar side chain motifs contribute to this detrimental energetic inhomogeneity and ultimately use the learnings to propose new molecular design criteria for side chains that can facilitate ion transport without impeding electronic transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Revisiting stellar properties of star-forming galaxies with stellar and nebular spectral modelling

Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions (SEDs) into the main luminosity contributors (e.g. stellar populations of distinct age and metallicity or ionised gas). However, the impact nebular emission has on the inferred properties of star-forming (SF) galaxies has been largely overlooked over the years, with unknown ramifications to the current understanding of galaxy evolution. The objective of this work is to estimate the relations between stellar properties (e.g. total mass, mean age, and mean metallicity) of SF galaxies by simultaneously fitting the stellar and nebular continua and comparing them to the results derived through the more common purely stellar spectral synthesis approach. The main galaxy sample from SDSS DR7 was analysed with two distinct population synthesis codes: FADO, which estimates self-consistently both the stellar and nebular contributions to the SED, and the original version of STARLIGHT, as representative of purely stellar population synthesis codes. Differences between codes regarding average mass, mean age and mean metallicity values can go as high as ~0.06 dex for the overall population of galaxies and ~0.12 dex for SF galaxies (galaxies with EW(Hα) > 3 Å), with the most prominent difference between both codes in the two populations being in the light-weighted mean stellar age. FADO presents a broader range of mean stellar ages and metallicities for SF galaxies than STARLIGHT, with the latter code preferring metallicity solutions around the solar value (Z ⊙ = 0.02). A closer look into the average light- and mass-weighted star formation histories of intensively SF galaxies (EW(Hα) > 75 Å) reveals that the light contributions of simple stellar populations (SSPs) younger than ≤10 7 (10 9 ) years in STARLIGHT are higher by ~5.41% (9.11%) compared to FADO. Moreover, FADO presents higher light contributions from SSPs with metallicity ≤ Z ⊙ /200 (Z ⊙ /50) of around 8.05% (13.51%) when compared with STARLIGHT. This suggests that STARLIGHT is underestimating the average light-weighted age of intensively SF galaxies by up to ~0.17 dex and overestimating the light-weighted metallicity by up to ~0.13 dex compared to FADO (or vice versa). The comparison between the average stellar properties of passive, SF and intensively SF galaxy samples also reveals that differences between codes increase with increasing EW(Hα) and decreasing total stellar mass. Moreover, comparing SF results from FADO in a purely stellar mode with the previous results qualitatively suggests that differences between codes are primarily due to mathematical and statistical differences and secondarily due to the impact of the nebular continuum modelling approach (or lack thereof). However, it is challenging to adequately quantify the relative role of each factor since they are likely interconnected. This work finds indirect evidence that a purely stellar population synthesis approach negatively impacts the inferred stellar properties (e.g. mean age and mean metallicity) of galaxies with relatively high star formation rates (e.g. dwarf spirals, ‘green peas’, and starburst galaxies). In turn, this can bias interpretations of fundamental relations such as the mass-age or mass-metallicity, which are factors worth bearing in mind in light of future high-resolution spectroscopic surveys at higher redshifts (e.g. MOONS and 4MOST-4HS).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The strain-induced transitions of the piezoelectric, pyroelectric, and electrocaloric properties of the CuInP 2 S 6 films

Low-dimensional ferroelectrics, ferrielectrics, and antiferroelectrics are of urgent scientific interest due to their unusual polar, piezoelectric, electrocaloric, and pyroelectric properties. The strain engineering and strain control of the ferroelectric properties of layered two-dimensional van der Waals materials, such as CuInP 2 (S,Se) 6 monolayers, thin films, and nanoflakes, are of fundamental interest and especially promising for their advanced applications in nanoscale nonvolatile memories, energy conversion and storage, nano-coolers, and sensors. Here, we study the polar, piezoelectric, electrocaloric, and pyroelectric properties of thin strained films of a ferrielectric CuInP 2 S 6 covered by semiconducting electrodes and reveal an unusually strong effect of a mismatch strain on these properties. In particular, the sign of the mismatch strain and its magnitude determine the complicated behavior of piezoelectric, electrocaloric, and pyroelectric responses. The strain effect on these properties is opposite, i.e., “anomalous,” in comparison with many other ferroelectric films, for which the out-of-plane remanent polarization, piezoelectric, electrocaloric, and pyroelectric responses increase strongly for tensile strains and decrease or vanish for compressive strains.

antiferroelectricity↗
DOE OSTI2024

Properties of photocurrent and metal contacts of highly resistive ultrawide bandgap semiconductors

Ultrawide bandgap (UWBG) semiconductors inherently exhibit very high electrical resistivities. This property presents not only challenges in probing their electrical transport properties but also difficulties to fabricate, understand, and characterize the electrical properties of metal contacts on these materials. Here, we report the measurements and analysis of the applied electric field dependence of photocurrent to reveal the effect of metal contacts on the transport properties of highly resistive h-BN. Our results indicate that even for h-BN with a room temperature resistivity as high as 1014 Ω cm, the as-deposited metal contact is not a completely blocking type as commonly assumed in previous analyses for other large bandgap insulating materials. By modifying the boundary condition between the metal/semiconductor interface, a quantitative description has been obtained, which can be used to determine if the metal contact is Ohmic or blocking type. This quantitative description should be applicable to all UWBG semiconductors with extremely high electrical resistivities. The work also provides a better understanding of how the metal contact type affects the transport properties of UWBG semiconductors in general.

Physics↗
DOE OSTI2025

Control of core–shell nanoparticles properties through plasma synthesis: a computational study

The improved properties of core–shell nanoparticles (CSNPs) over homogeneous nanoparticles (NPs) have expanded and diversified the applications of these nanomaterials. However, controlling the properties of CSNPs can be a challenging task. Low temperature plasmas have proven to be an effective method of producing NPs with uniform size and morphology, and high yield. That said, NP transport and growth dynamics are sensitive to LTP properties. We report on a computational investigation of the evolution of Ge–Si CSNP properties as a function of operating conditions through the modeling of a flowing, two-zone inductively coupled plasma (ICP) reactor. Ar/GeH 4 and Ar/SiH 4 gas mixtures were supplied to separate plasma zones at a pressure of 1 Torr to promote growth of Ge cores and Si shells. The negatively charged CSNPs are trapped electrostatically in the vicinity of the antennas where the plasma is generated and where the majority of particle growth occurs. Particles that grow to a critical size are then de-trapped by fluid drag due to neutral gas flow. A two-dimensional hybrid plasma model coupled with a three-dimensional kinetic NP transport model were utilized to resolve plasma chemistry and NP growth processes that take place on distinct timescales. The trends in CSNP properties and trapping mechanisms associated with flow rate, applied ICP power and inlet precursor fraction are discussed. While the spatial distribution of plasma produced radical species can have significant impact on the NP growth process, the NP transport dynamics are what ultimately dictates the growth environment that is unique to each particle and so determines their final dimension and composition. The key to optimizing reactor conditions involves controlling the spatial density of growth species and plasma profile as a means to tailor particle trapping dynamics suitable to produce CSNPs for a specific application.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fast and stable deep-learning predictions of material properties for solid solution alloys

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical properties mutually serve as constraints during the training of the multitasking NN, resulting in more reliable DL models because multiple physics properties are correctly learned by a single model. Two binary alloys, copper–gold (CuAu) and iron–platinum (FePt), were studied. Our results show that once the multitasking NN's are trained, they can estimate the material properties for a specific configuration hundreds of times faster than first-principles density functional theory calculations while retaining comparable accuracy. We used a simple measure based on the root-mean-squared errors to quantify the quality of the NN models, and found that the inclusion of charge density and magnetic moment as physical constraints leads to more stable models that exhibit improved accuracy and reduced uncertainty for the energy predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Deep learning the properties of inorganic perovskites

We report the ability to accurately and quickly predict the stability of materials and their structural and electronic properties remains a grand challenge in materials science. Density functional theory is widely used as a means of predicting these material properties, but is known to be computationally expensive and scales as the cube of the number of electrons in the material’s unit cell. In this article, for a previously published dataset of inorganic perovskites, we show that a single neural network model using only the elemental properties of the compounds’ constituents can predict lattice constants to within 0.1 Å, heat of formation to within 0.2 eV, and band gaps to within 0.7 eV RMSE. We also compare the performance of the trained network to two widely used regression techniques, namely random forest and Kernel ridge regression, and find that the neural network’s predictions are more accurate for each of the properties. The simultaneous accurate prediction of multiple key properties of technologically relevant materials is promising for rational design and optimization in known and novel chemical spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impact of CH 4 addition on the electron properties and electric field dynamics in a Ar nanosecond-pulsed dielectric barrier discharge

Non-equilibrium plasmas derive their low temperature reactivity from producing and driving energetic electrons and active species under large electric fields. Therefore, the impact of reactants on the plasma properties including electron number density, electric field, and electron temperature is critical for applications such as plasma CH 4 reforming. Due to experimental complexity, electron properties and the electric field are rarely measured together in the same discharge. Here, we combine time-resolved Thomson scattering and electric field induced second harmonic generation (EFISH) to probe electron temperature, electron density, and electric field strength in a 60 Torr CH 4 /Ar nanosecond-pulsed dielectric barrier discharge (ns-DBD) while varying the CH 4 mole fraction from 0 to 8%. These measurements are compared to a 1-D numerical model to benchmark its predictions and identify areas of uncertainty. Nonlinear coupling between CH 4 addition, electron temperature, electron density, and the electric field was directly observed. Contrary to previous measurements in He, the electron temperature increased with CH 4 mole fraction. This rise in electron temperature is identified as electron heating by residual electric fields that increased with larger CH 4 mole fraction. Moreover, the electron number density has been found to decrease rapidly with the increase of methane mole fraction. Comparison of these measurements with the model yielded better agreement at higher CH 4 mole fractions and with the usage of ab initio calculated Ar electron-impact cross-sections from the B-spline R-matrix (BSR) database. Furthermore, the calculated plasma properties are shown to be sensitive to the residual surface charge implanted on the quartz dielectric surfaces. Without considering surface charge in the simulations, the calculated electric field profiles agreed well with the measurements, but the electron properties were underpredicted by more than a factor of three. Therefore, measurements of either the electric field or electron properties measurements alone are insufficient to fully validate modelling predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Observational measures of halo properties beyond mass

Different properties of dark matter haloes, including growth rate, concentration, interaction history, and spin, correlate with environment in unique, scale-dependent ways. While these halo properties are not directly observable, galaxies will inherit their host haloes’ correlations with environment. In this paper, we show how these characteristic environmental signatures allow using measurements of galaxy environment to constrain which dark matter halo properties are most tightly connected to observable galaxy properties. Here, we show that different halo properties beyond mass imprint distinct scale-dependent signatures in both the galaxy two-point correlation function and the distribution of distances to galaxies’ kth nearest neighbours, with features strong enough to be accessible even with low-resolution (e.g. grism) spectroscopy at higher redshifts. As an application, we compute observed two-point correlation functions for galaxies binned by half-mass radius at $z$ = 0 from the Sloan Digital Sky Survey, showing that classic galaxy size models (i.e. galaxy size being proportional to halo spin) as well as other recent proposals show significant tensions with observational data. We show that the agreement with observed clustering can be improved with a simple empirical model in which galaxy size correlates with halo growth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

No redshift evolution in the rest-frame ultraviolet emission line properties of quasars from z = 1.5 to z = 4.0

We analyse the rest-frame ultraviolet (UV) spectra of 2531 high-redshift (3.5 < z < 4.0) quasars from the Sloan Digital Sky Survey DR16Q catalogue. In combination with previous work, we study the redshift evolution of the rest-frame UV line properties across the entire redshift range, 1.5 < z < 4.0. We improve the systemic redshift estimates at z > 3.5 using a cross-correlation algorithm that employs high signal-to-noise template spectra spanning the full range in UV emission line properties. We then quantify the evolution of C iv and He ii emission line properties with redshift. The increase in C iv blueshifts with cosmological redshift can be fully explained by the higher luminosities of quasars observed at high redshifts. We recover broadly similar trends between the He ii equivalent width and C iv blueshift at both 1.5 < z < 2.65 and 3.5 < z < 4.0 suggesting that the blueshift depends systematically on the spectral energy density (SED) of the quasar and there is no evolution in the SED over the redshift range 1.5 < z < 4.0. C iv blueshifts are highest when L/L Edd ≥ 0.2 and M BH ≥ 10 9 M ⊙ for the entire 1.5 < z < 4.0 sample. We find that luminosity matching samples as a means to explore the evolution of their rest-frame UV emission line properties is only viable if the samples are also matched in the M BH –L/L Edd plane. Quasars at z ≥ 6 are on average less massive and have higher Eddington-scaled accretion rates than their luminosity-matched counterparts at 1.5 < z < 4.0, which could explain the observed evolution in their UV line properties.

79 ASTRONOMY AND ASTROPHYSICS↗