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DOE OSTI2023

Wetting Behavior of A -block- (B- random -C) Copolymers with Equal Block Surface Energies on Surfaces Functionalized with B- random -C Copolymers

To form nanopatterns with self-assembled block copolymers (BCPs), it is desirable to have through-film domains that are oriented perpendicular to the substrate. The domain orientation is determined by the interfacial interactions of the BCP domains with the substrate and with the free surface. Here, we use thin films of two different sets of BCPs with A-block-(B-random-C) architecture matched with a corresponding B-random-C copolymer nanocoating on the substrate to demonstrate two distinct wetting behaviors. The two sets of A-b-(B-r-C) BCPs are made by using thiol–epoxy click chemistry to functionalize polystyrene-block-poly(glycidyl methacrylate) with trifluoroethanethiol (TFET) and either 2-mercaptopyridine (2MP) or methyl thioglycolate (MTG). For each set of BCPs, the composition ratio of the two thiols in the BCP (φ 1 ) is found that results in the two blocks of the modified BCP having equal surface energies (Δγ air = 0). The corresponding B-r-C random copolymers were synthesized and used to modify the substrate, and the composition ratio (φ 2 ) values that resulted in the two blocks of the BCP having equal interfacial energy with the substrate (Δγ sub = 0) were determined with scanning electron microscopy. The correlation between each block’s γ sub value and the interaction parameter, χ, is employed to explain the different wetting behaviors of the two sets of BCPs. For the thiol pair 2MP and TFET, the values of φ 1 and φ 2 that lead to Δγ air = 0 and Δγ sub = 0, respectively, are significantly different. A similar difference was observed between the φ 1 and φ 2 values that lead to Δγ air = 0 and Δγ sub = 0 for the BCPs made with the thiol pair MTG and TFET. In the latter case, for Δγ sub = 0 two windows of φ 2 are identified, which can be explained by the thermodynamic interactions of the specific thiol pair and the A-b-(B-r-C) architecture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Observations of phase changes in monoolein during high viscous injection

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Magnetic field screening in hydrogen-rich high-temperature superconductors

In the last few years, the superconducting transition temperature, T c , of hydrogen-rich compounds has increased dramatically, and is now approaching room temperature. However, the pressures at which these materials are stable exceed one million atmospheres and limit the number of available experimental studies. Superconductivity in hydrides has been primarily explored by electrical transport measurements, whereas magnetic properties, one of the most important characteristic of a superconductor, have not been satisfactory defined. Here, we develop SQUID magnetometry under extreme high-pressure conditions and report characteristic superconducting parameters for Im-3m-H 3 S and Fm-3m-LaH 10 —the representative members of two families of high-temperature superconducting hydrides. We determine a lower critical field H c1 of ~0.82 T and ~0.55 T, and a London penetration depth λ L of ~20 nm and ~30 nm in H 3 S and LaH 10 , respectively. The small values of λ L indicate a high superfluid density in both hydrides. These compounds have the values of the Ginzburg-Landau parameter κ ~12–20 and belong to the group of “moderate” type II superconductors, rather than being hard superconductors as would be intuitively expected from their high T c s.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Computationally Accelerated Discovery and Experimental Demonstration of Gd0.5La0.5Co0.5Fe0.5O3 for Solar Thermochemical Hydrogen Production

Solar thermochemical hydrogen (STCH) production is a promising method to generate carbon neutral fuels by splitting water utilizing metal oxide materials and concentrated solar energy. The discovery of materials with enhanced water-splitting performance is critical for STCH to play a major role in the emerging renewable energy portfolio. While perovskite materials have been the focus of many recent efforts, materials screening can be time consuming due to the myriad chemical compositions possible. This can be greatly accelerated through computationally screening materials parameters including oxygen vacancy formation energy, phase stability, and electron effective mass. In this work, the perovskite Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF), was computationally determined to be a potential water splitter, and its activity was experimentally demonstrated. During water splitting tests with a thermal reduction temperature of 1,350°C, hydrogen yields of 101 μmol/g and 141 μmol/g were obtained at re-oxidation temperatures of 850 and 1,000°C, respectively, with increasing production observed during subsequent cycles. This is a significant improvement from similar compounds studied before (La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 and LaFe 0.75 Co 0.25 O 3 ) that suffer from performance degradation with subsequent cycles. Confirmed with high temperature x-ray diffraction (HT-XRD) patterns under inert and oxidizing atmosphere, the GLCF mainly maintained its phase while some decomposition to Gd 2-x La x O 3 was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Materials Science of the Interstitial Doping Process

Particle accelerators are an increasingly important tool for frontier science. Growing initial and operating costs are a significant barrier for upgrades and for new machines. While everything matters, the major cost contributor is the SRF cavities and their ancillary facilities (e.g., cryoplant). Accordingly, the accelerator science community devotes much R&D effort to improving their energy efficiency (increased Q o ) and gradient (E acc ). While improved gradient is at the forefront for certain machines (ILC), improved quality factor has broader impact, benefitting all SRF applications. An important opportunity for accelerator science and technology to move forward arose in the course of building the LCLS-II, the second generation Linac Coherent Light Source at SLAC. At more or less the same time, researchers at Fermilab discovered that introducing a small amount of nitrogen to the niobium surface could improve the mid-range quality factor as much as three-fold. A firm resolution of how nitrogen confers its benefit attracts much current research interest. The key elements of the “nitrogen doping” process were vacuum bake at 800 °C, brief exposure to mTorr of nitrogen at several hundred degrees followed by electropolish (EP) to remove several microns from the surface to eliminate unwanted nitrides: While the process as a whole was novel, the comprising unit operations are familiar to the accelerator community. It was judged reasonable to adopt it as a cost-reduction technology for LCLS-II. Researchers carried out a program of varying process parameters and measuring performance in single-cell cavities, leading to a consensus stable protocol for the project. The transition to vendor fabrication and multiple niobium sources has presented unforeseen challenges of performance variation evidently not connected to anything that could be incorporated in a purchase specification. Moving beyond the high temperature N-doping process above, researchers reported a simplified process consisting entirely of tens of hours anneal in a N atmosphere at low temperatures (~120°C – 160°C) after 800 °C UHV bake. These processes typically yield a few-nm doped layer while the high temperature process yields at least a few to many micron doped layer. Even more recently, oxygen has been used to dope instead of nitrogen which leaves a few-µm O-alloyed layer upon vacuum annealing for 300 °C for ~3 hours. The investigation of these materials is just beginning, but the process simplification they may offer is surely attractive. The very low quantity of material that appears to be significant in the “infusion” process indicates the need for very careful control of gas species available for diffusion into the surface during low temperature treatment, both for process control and research to characterize the underlying dynamics. Oxygen alloying offers the further opportunity to utilize the decomposition of the surface native oxide as the dopant source. It is necessary to understand and (thus) manage this process. We have been supported by the Department of Energy Offices of High Energy Physics and Nuclear Physics to pursue this goal.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Early- and late-time dynamics of laser-produced plasmas by combining emission and absorption spectroscopy

Optical emission spectroscopy and laser absorption spectroscopy are two highly complementary techniques for diagnosing plasmas, specifically in the determination of important parameters such as temperature and density. In this work, we characterized a laser-produced plasma by combining emission and tunable absorption spectroscopy. Plasmas are produced by focusing pulses from a frequency quadrupled Nd:YAG laser onto a glass target containing a minor concentration of aluminum in an ambient atmosphere of ~100 Torr N 2 . Here, emission spectroscopy is used to investigate the line behavior of Al and Ca, electron density, and excitation temperature at times = 5 μs, while absorption spectroscopy is used to investigate the line behavior of Al and Ca, species density, and kinetic temperature at times = 5-100 μs. A comparison is made between the excitation temperature measured from emission using the Boltzmann plot method and the kinetic temperature measured from absorption; the implications of this comparison on local thermodynamic equilibrium and line-of-sight averaging are discussed. By combining the two methods of optical emission and laser absorption spectroscopy, a comprehensive characterization of the plasma over the entire lifetime of its evolution is possible, leading to a greater understanding of the plasma behavior including particle condensation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Perspectives on Systematic Cloud Microphysics Scheme Development With Machine Learning

Cloud microphysics—the collection of processes that govern the small‐scale formation, evolution, and interactions of liquid droplets and ice crystals in clouds and precipitation—remains a major source of uncertainty in weather and climate models. Although too small in scale to be explicitly resolved in any large‐eddy simulation, weather, or climate model, the representation of cloud microphysical processes has significant impact at the climate scale. Current microphysical schemes are limited by both parametric uncertainty, linked to uncertainty in physical parameter values, and structural uncertainty, arising from incomplete physical understanding of the processes at play or approximations made for computational efficiency. Recent advances in the application of machine learning (ML) to the physical sciences show significant potential for minimizing these limitations by leveraging high‐fidelity simulations and observations. Here we outline the challenges that must be addressed to apply ML toward cloud microphysics scheme development. This perspectives paper synthesizes recent progress in using data‐driven methods, including ML, to improve cloud microphysics parameterizations and highlights opportunities to address key uncertainties. We discuss the roles of aleatoric (irreducible, or statistical) and epistemic (reducible, or systematic) errors in contributing to microphysics parameterization uncertainty. ML can leverage observations to improve microphysical schemes via bottom‐up and top‐down constraints. Methods such as differentiable programming and ML‐enhanced sampling strategies and the creation of large scale benchmark data sets promise to bridge the gap between observations and models and to improve the consistency of cloud microphysical representation across temporal and spatial scales.

Lamb, Kara D. [Columbia Univ., New York, NY (Unite↗

DOE OSTI2020

Characterizing Complex Gas–Solid Interfaces with in Situ Spectroscopy: Oxygen Adsorption Behavior on Fe–N–C Catalysts

Electrocatalysts for the oxygen reduction reaction within polymer electrolyte membrane fuel cells based on iron, nitrogen, and carbon elements (Fe–N–C) are receiving significant research attention as they offer an inexpensive alternative to catalysts based on platinum-group metals. Although both the performance and the fundamental understanding of Fe–N–C catalysts have improved over the past decade, there remains a need to differentiate the relative activity of different active sites. Toward this goal, our study is focused on characterizing the interactions between O 2 and a set of five structurally different Fe–N–C materials. Detailed characterization of the Fe speciation was performed with 57 Fe Mössbauer spectroscopy and soft X-ray absorption spectroscopy of the Fe L 3,2 -edge, whereas nitrogen chemical states were investigated with X-ray photoelectron spectroscopy (XPS). In addition to initial sXAS and XPS measurements performed in ultra-high vacuum (UHV), measurements were also performed (at the identical location) in an atmosphere of 100 mTorr of O 2 at 80 °C (O 2 -rich). XPS and sXAS results reveal the presence of several types of FeNxCy adsorption sites. FeNxCy sites that are proposed as the most active ones do not show significant change (based on the techniques used in this study) when their environment is changed from UHV to O 2 -rich. Correlation with Mössbauer and sXAS results suggests that this is most likely due to the persistence of strongly adsorbed O 2 molecules from their previous exposure to air. However, other species do show spectroscopic changes from UHV conditions to O 2 -rich. This implies that these sites have a weaker interaction with O 2 that results in their desorption in vacuum conditions and re-adsorption when exposed to the O 2 -rich environment. The nature of these weakly and strongly O 2 -adsorbing FeN x C y sites is discussed in the context of different synthetic and processing parameters employed to fabricate each of these five Fe–N–C materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Search for photons above 10 18 eV by simultaneously measuring the atmospheric depth and the muon content of air showers at the Pierre Auger Observatory

The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above 1 0 17 eV . It measures extensive air showers generated by ultrahigh energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ( X max ) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV ( 1 EeV = 1 0 18 eV ) has been developed by combining the fluorescence detector-based measurement of X max with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and 0.0021 km − 2 sr − 1 yr − 1 above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultrahigh energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Combustion of petroleum-based transportation fuels and their blends with biofuels: a new approach for developing surrogates and understanding the effects of blending

Accurate and versatile reaction mechanisms are necessary to simulate combustion of transportation fuels blended with biofuels for improving fuel efficiency, reducing fuel consumption and mitigating the formation and emissions of combustion products harmful to the atmosphere. This project involved a combined effort of simulation and experimentation of liquid fuel burning using a combustion configuration amenable to numerical modeling with a level of detail not previously achieved for blends of biofuels with gasoline certification and surrogate fuels. The configuration of an isolated droplet burning under conditions where gas transport arises solely from fuel evaporation was selected as the platform for experiments and numerical modeling. The spherical symmetry and one-dimensional gas transport that results enabled simulating the droplet burning process with an precedented level of detail. Processes associated with unsteady gas and liquid transport, formation of particulate and gaseous products, radiation, multicomponent phase equilibrium at the droplet surface and moving boundary effects from droplet evaporation, were incorporated in a single numerical framework. The numerical model was based on the open source code OPENSmoke++ (OS) adapted to incorporate the effects noted above. In addition to simulation, an experimental design was developed for the isolated droplet configuration to acquire the data needed for validating the numerical model. Several broad accomplishments of the project were the following: demonstrating generally excellent agreement between measured and simulated combustion parameters for the fuel blends examined that included mixtures of heptane and isobutanol as a model system, and surrogates comprised of up to seven miscible components mixed with ethanol or isobutanol as representative biofuel additives; using a new approach to validate reaction mechanisms of biofuel blends which incorporated fuel evaporation into the process along with developing an experimental design for acquiring data to compare with simulations; and showing that a wealth of information could be obtained on the combustion physics of biofuels from experiments requiring volumes on the order of only nanoliters at a time thus opening the way to evaluating biofuels synthesized by new processes early in development.

02 PETROLEUM↗

DOE OSTI2022

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Characterization of high-frequency waves in the Martian magnetosphere

Context.Various high-frequency waves in the vicinity of upper-hybrid and Langmuir frequencies are commonly observed in different space plasma environments. Such waves and fluctuations have been reported in the magnetosphere of the Earth, a planet with an intrinsic strong magnetic field. Mars has no intrinsic magnetic field and, instead, it possesses a weak induced magnetosphere, which is highly dynamic due to direct exposure to the solar wind. In the present paper, we investigate the presence of high-frequency plasma waves in the Martian plasma environment by making use of the high-resolution electric field data from the Mars Atmosphere and Volatile Evolution missioN (MAVEN) spacecraft. Aims.This study aims to provide conclusive observational evidence of the occurrence of high-frequency plasma waves around the electron plasma frequency in the Martian magnetosphere. We observe two distinct wave modes with frequency below and above the electron plasma frequency. The characteristics of these high-frequency waves are quantified and presented here. We discuss the generation of possible wave modes by taking into account the ambient plasma parameters in the region of observation. Methods.We have made use of the medium frequency (100 Hz–32 kHz) burst mode-calibrated electric field data from the Langmuir Probe and Waves instrument on board NASA’s MAVEN mission. Due to the weak magnetic field strength, the electron gyro-frequency is much lower than the electron plasma frequency, which implies that the upper-hybrid and Langmuir waves have comparable frequencies. A total of 19 wave events with wave activities around electron plasma frequency were identified by examining high-resolution spectrograms of the electric field. Results.These waves were observed around 5 LT when MAVEN crossed the magnetopause boundary and entered the magnetosheath region. These waves are either a broadband- or narrowband-type with distinguishable features in the frequency domain. The narrowband-type waves have spectral peak above the electron plasma frequency. However, in the case of broadband-type waves, the spectral peak always occurred below the electron plasma frequency. The broadband waves consistently show a periodic modulation of 8–14 ms. Conclusions.The high-frequency narrowband-type waves observed above the electron plasma frequency are believed to be associated with upper-hybrid or Langmuir waves. However, the physical mechanism responsible for the generation of broadband-type waves and the associated 8–14 ms modulation remain unexplained and further investigation is required.

Astronomy & Astrophysics↗

DOE OSTI2021

Evaluating the effects of structural disorder on the magnetic properties of Nd 2 Zr 2 O 7

Motivated by the variation in reported lattice parameters of floating-zone-grown Nd 2 Zr 2 O 7 crystals, we have performed a detailed study of the relationship between synthesis environment, structural disorder, and magnetic properties. Using a combination of polycrystalline standards, electron-probe microanalysis, and scattering techniques, we show that crystals grown under atmospheric conditions have a reduced lattice parameter relative to pristine polycrystalline powders due to occupation of the Nd site by excess Zr (i.e., negative stuffing). In contrast, crystals grown under high-pressure Ar are nearly stoichiometric with an average lattice parameter approaching the polycrystalline value. While minimal disorder of the oxygen sublattices is observed on the scale of the average structure, neutron pair-distribution function analysis indicates a highly local disorder of the oxygen coordination, which is only weakly dependent on growth environment. Most importantly, our magnetization, heat capacity, and single-crystal neutron scattering data show that the magnetic properties of crystals grown under high-pressure Ar match closely with those of stoichiometric powders. Neutron scattering measurements reveal that the signature of magnetic moment fragmentation—the coexistence of all-in-all-out (AIAO) magnetic Bragg peaks and diffuse pinch-point scattering due to spin-ice correlations–persists in these nearly stoichiometric crystals. However, in addition to an increased AIAO transition temperature, the diffuse signal is seemingly stabilized and remains nearly unchanged upon warming to 800 mK. This behavior indicates that both the AIAO magnetic order and spin-ice correlations are sensitive to deviations of the Nd stoichiometry.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Latest Three Flavor Neutrino Oscillation Results from the NOvA Experiment.

NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters such as the atmospheric mass squared splitting, $\Delta m^2_{32}$, the mixing angle, $\theta_{23}$, neutrino mass hierachy, and the CP-violating phase, $\delta_{CP}$, using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. NOvA receives a high purity instense beam of neutrinos and anti-neutrinos from Fermilab's Neutrinos at Main Injector (NuMI) beamline. The NOvA near detector (ND) observes un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ events, while the far detector (FD), which is situated 810 km away from the near detector, records un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and oscillated $\nu_e \ (\bar{\nu}_e)$ events. The best fit values of the oscillation parameters are extracted by performing a joint fit of the far detector predicted events to data from $\nu_\mu \to \nu_\mu$, $\bar{\nu}_\mu \to \bar{\nu}_\mu$, $\nu_\mu \to \nu_e$, and $\bar{\nu}_\mu \to \bar{\nu}_e$ oscillation channels. We present latest joint fit results from NOvA based on a neutrino-beam exposure of $27.24 \times 10^{20}$ POT and an anti-neutrino beam exposure of $12.55\times 10^{20}$ POT and improved simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Latest Three Flavor Neutrino Oscillation Results from the NOvA Experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

A Scalable Solution Route to Porous Networks of Nanostructured Black Tungsten

This paper studied the feasibility of a new solution-processed method to manufacture black tungsten nanostructures by laser conversion of tungsten hexacarbonyl precursor on the Inconel 625 substrate under argon atmosphere at ambient pressure. The results show that sublimation of the precursor can be prevented if the decomposition temperature (>170 °C) is achieved using the laser heating method. Three different laser powers from 60–400 W were used to investigate the role of laser parameters on the conversion. It was found that lower laser power of 60 W resulted in a mixture of unconverted precursor and converted tungsten. Higher laser powers >200 W resulted in α-W (BCC) in one step without further heat treatment. Different oxygen concentrations from 0.5 ppm to 21 vol% were used in the laser canister to investigate the effect of oxygen concentration on the conversion. It was found that the hard vacuum (>10−4 torr) or hydrogen is not necessary to obtain α-W (BCC). The solar absorptance varied from 63–97%, depending on the amount of precursor deposited on the substrate and oxygen content in the laser canister. This solution-based laser conversion of tungsten precursor is a scalable method to manufacture tungsten coatings for high-temperature applications.

14 SOLAR ENERGY↗