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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Raman Fingerprints of Phase Transitions and Ferroic Couplings in van der Waals Multiferroic CuCrP 2 S 6
CuCrP 2 S 6 (CCPS), a type-II multiferroic material, exhibits unique phase transitions involving ferroelectric, antiferroelectric, and antiferromagnetic ordering. Here, in this study, we conduct a comprehensive investigation on the intricate phase transitions and their multiferroic couplings in CCPS across a wide temperature range from 4 to 345 K through Raman spectroscopic measurements down to 5 cm –1 . We first assign the observed Raman modes with the support of theoretical calculations and angle-resolved polarized Raman measurements. We further present clear signatures of phase transitions from the analyses of temperature-dependent Raman spectral parameters. Particularly, two low-frequency soft modes are observed at 36.1 cm –1 and 70.5 cm –1 below 145 K, indicating the antiferroelectric to quasi-antiferroelectric transition. Moreover, phonon mode hardening is observed when the temperature increases from 4 to 65 K, suggesting negative thermal expansion (NTE) and strong magnetoelastic coupling below 65 K. These findings advance the understanding of vdW multiferroic CCPS, paving the way for future design and engineering of multiferroicity in cutting-edge technologies, such as spintronics and quantum devices.
Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling
This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.
Reactions of atomic thorium and uranium cations with CF 4 studied by guided ion beam tandem mass spectrometry
The fundamental chemistry of the actinides continues to be an area of interest because of their use in nuclear fuel cycles. Here, the kinetic energy dependences of the reactions of thorium and uranium cations with CF 4 were studied using guided ion beam tandem mass spectrometry. The products observed include AnF x + (An = Th or U, x = 1-3) and CF y + (y = 1-3). Although most reactions are exothermic according to literature thermochemistry, all cross sections display strong endothermic features indicating a restriction in the reactivity at low energies. For both actinides, only the AnF + + CF 3 product channel is observed at low energies; however, its formation proceeds very inefficiently. Furthermore, these results indicate that the reactions of Th + and U + with CF 4 are not thermodynamically driven and suggest that the low-energy reactivity results from precise alignment of the reactants.
The effect of equilibration time on Al uptake in C-S-H
Calcium silicate hydrate (C-S-H) is the main hydration product of Portland cements. The partial replacement of Portland cements by supplementary cementitious materials can result in C-S-H with lower Ca/Si ratios and more aluminum and alkalis. The effect of equilibration time on Al uptake in C-S-H was investigated using equilibration times from 7 days up to 3 years. Lower Al concentrations were measured in the solution after longer equilibration times. In addition, a higher uptake of Al in C-S-H was observed based on the decrease in the content of secondary phases. Little further decrease in Al concentrations was observed after 2 years and longer at low Ca/Si. At high Ca/Si no significant change in solution concentrations was observed after more than 3 month, while the destabilization of secondary phases continued up to 1 year, indicating that a (meta)stable equilibrium was reached faster at higher Ca/Si ratios.
Understanding Biases in Simulated Cloud Radiative Effects in E3SMv3
This study systematically investigates biases in cloud radiative effects (CREs) within the recently released Energy Exascale Earth System Model version 3 (E3SMv3). Compared to its previous version (E3SMv2), E3SMv3 shows excessively strong shortwave CRE over tropical and subtropical oceans, the Southern Ocean, and the Northern Hemisphere storm tracks, which is primarily caused by an overestimation of optically intermediate low clouds. The model also displays excessive longwave CRE over the Maritime Continent and other tropical deep convection regions, resulting from an overestimation of optically thick high clouds. Implementing the Predicted Particle Properties (P3) scheme for stratiform clouds played the most significant role in these cloud changes. In addition, using a double-moment scheme for convective clouds contributed to the increase in intermediate low clouds and optically thick clouds in tropical deep convection regions. Error metrics for total cloud amount (E TCA ), cloud properties (E ctp-τ ), and cloud properties weighted by their SW and LW radiative impacts (E SW and E LW ) indicate that E3SMv3's ability to reproduce observed cloud radiative effect of low, middle, and high clouds has not been improved compared to E3SMv2. Nevertheless, the performance of E3SMv3 remains well within the spread of CMIP6 models, with E SW and E LW values smaller than those in most CMIP6 models. This study underscores the importance of integrating diverse satellite observations for robust cloud evaluation and using cloud-radiation relationships as consistency check for model errors. It suggests that further model developments focus on improving cloud microphysics and their interactions with radiation.
Solid-state synthesis of UV-plasmonic Cr2N nanoparticles
Materials that exhibit plasmonic response in the UV region can be advantageous for many applications, such as biological photodegradation, photocatalysis, disinfection, and bioimaging. Transition metal nitrides have recently emerged as chemically and thermally stable alternatives to metal-based plasmonic materials. However, most free-standing nitride nanostructures explored so far have plasmonic responses in the visible and near-IR regions. Herein, we report the synthesis of UV-plasmonic Cr2N nanoparticles using a solid-state nitridation reaction. The nanoparticles had an average diameter of 9 ± 5 nm and a positively charged surface that yields stable colloidal suspension. The particles were composed of a crystalline nitride core and an amorphous oxide/oxynitride shell whose thickness varied between 1 and 7 nm. Calculations performed using the finite element method predicted the localized surface plasmon resonance (LSPR) for these nanoparticles to be in the UV-C region (100–280 nm). While a distinctive LSPR peak could not be observed using absorbance measurements, low-loss electron energy loss spectroscopy showed the presence of surface plasmons between 80 and 250 nm (or ∼5 to 15 eV) and bulk plasmons centered around 50–62 nm (or ∼20 to 25 eV). Plasmonic coupling was also observed between the nanoparticles, resulting in resonances between 250 and 400 nm (or ∼2.5 to 5 eV).
Development of a creep model informed by lower-length scale simulations to simulate creep in doped UO 2
Using molecular dynamics, we predict information at the atomistic scale used to develop a mechanistic UO 2 creep model for use in higher length-scale fuel performance codes. The ultimate objective of the model is to better describe the grain size dependence and therefore impact of doping on creep rates in UO 2 . In a previous NEAMS milestone, we found that Nabarro-Herring (bulk diffusional) creep was too low to capture the experimentally observed creep rates in standard UO 2 . Moreover, in that milestone, other mechanisms were explored, such as Coble (grain boundary) creep and dislocation climb, with each mechanism exhibiting different grain size dependencies. Again, these were orders of magnitude too low to describe the experimental creep rates. In this work, we address the previous assumptions made for the Coble creep mechanism by investigating the diffusivity of various defects at grain boundaries in UO 2 and, critically, to determine if enhanced grain boundary diffusivity allows the model to better reproduce experimental results. The diffusivity as a function of temperature for different concentrations of uranium vacancies and interstitials for bulk UO 2 have also been examined using cluster dynamics. Furthermore, using a concentration dependent segregation model, the concentration of defects at the grain boundary were predicted. This atomistic data was then input into the various creep mechanisms and the creep rates compared to the empirical MATPRO correlation (used in BISON) and experiment.
Independent Fuel Property Effects of Fuel Volatility on Low Temperature Heat Release and Fuel Autoignition (Final Report)
This Cooperative Research and Development Agreement (CRADA) project between Argonne National Laboratory (ANL), Oak Ridge National Laboratory (ORNL), and Shell Global Solutions (Shell) was initiated as part of a Directed Funding Opportunity (DFO) call for proposals from the Co-Optimization of Fuels and Engines (Co-Optima) initiative. Shell had observed that volatile fuels suppress low temperature heat release (LTHR) more than expected based on conventional gasoline autoignition metrics: research octane number (RON) and motor octane number (MON). The role of LTHR contributes to autoignition phenomena for both boosted spark ignition (BSI) and advanced compression ignition (ACI) combustion modes. ACI combustion modes are applicable to large engines in the hard-to-electrify applications such as off-road, rail, and marine. Thus, having a reliable understanding of autoignition phenomena, including being able to accurately account for the effects of fuel volatility, is particularly important as new synthetic and bio-fuel compositions are considered.This CRADA project aimed to test the hypothesis that the decreased LTHR is due to preferential evaporation of multicomponent fuels when using direct injection (DI) fueling technology, creating composition and reactivity stratification. A custom set of fuels was designed and blended to test this hypothesis by Shell, with experimental engine studies at ORNL and engine combustion modeling by ANL. However, the initial experimental findings did not show the expected effect of fuel volatility suppressing LTHR. Instead, the LTHR propensity observed was independent of the fuel volatility. Due to the unexpected experimental result, the remainder of the experimental effort was redirected to study the effect of fuel volatility on emissions under spark-ignited cold-start conditions. However, as with the LTHR experiments, the cold start effort did not show a meaningful effect of fuel volatility on cold start emissions. Meanwhile, improved engine CFD models have been developed for both LTHR and cold start operations for the Shell fuels with different volatilities. While the simulation efforts were not pursued further due to the insignificant effects of fuel volatility as shown in experiments, the models developed can be easily retooled for off-road, rail, and marine applications.
Non-catalytic gas phase NO oxidation in the presence of decane
In this study, experiments without a catalyst revealed that NO was oxidized in a diesel exhaust gas phase mixture due to the presence of n -C 10 H 22 (decane). This reaction was observed to occur following the low temperature oxidation catalyst test protocol (LTC-D) defined by U.S. DRIVE. The purpose of LTC-D conditions is to simulate an aftertreatment diesel combustion gas mixture in order to test candidate catalyst materials. 100% NO conversion was observed, without a catalyst, after beginning to react at 330 °C accompanied by consumption of decane. After experiments that isolated hydrocarbons, ethylene was also observed to facilitate NO oxidation to a lesser degree (>470 °C). Density functional theory (DFT) calculations were conducted to investigate thermodynamically-possible initiating elementary steps during n -C 10 H 22 consumption and NO oxidation. Two feasible intermediate radicals to oxidize NO to NO 2 are ·C 10 H 21 O 2 and ·HO
Solution and Active Site Speciation Drive Selectivity for Electrocatalytic Reactive Carbon Capture in Diethanolamine over Ni–N–C Catalysts
Direct conversion of captured forms of carbon, or reactive carbon capture (RCC), presents an opportunity to reduce the energy intensity and cost of direct CO 2 utilization from dilute sources. While amine-based sorbents effectively capture CO 2 , their use for RCC presents numerous challenges with typical pure metal catalysts used for electrochemical CO 2 reduction (CO 2 R). Here, using both theory and experiments, we find that Ni–N–C single atom catalysts are effective for RCC conversion to CO using a diethanolamine sorbent, in contrast to pure metal catalysts. Computational analysis reveals that RCC can proceed directly through direct reduction of the sorbent-CO 2 adduct or indirectly by C–N bond breaking facilitating CO 2 adsorption and subsequent reduction. We find that the latter mechanism is most prevalent at low overpotentials where we experimentally observe RCC selectivity. We also find experimentally that the rate of CO production for RCC with Ni–N–C catalysts can exceed pure bicarbonate solutions at intermediate sorbent concentration (0.1–0.5 M DEA) under dilute (10–25%) streams of CO 2 at low overpotentials. The coordination environment of Ni sites and the solution speciation influence their RCC activity, with changes in protonation to coordinating N/C atoms resulting in changing the RCC mechanism and consequent activity. In situ X-ray absorption spectroscopy and computational analysis reveal restructuring under RCC conditions due to hydrogen coadsorption with DEA that limits the stability of Ni–N–C catalysts. This work highlights the importance of carefully controlling the catalyst and solution environment to achieve active and stable RCC electrocatalysis.
SDSS-IV MaNGA: calibration of astrophysical line-widths in the Hα region using HexPak observations
ABSTRACT We have re-observed $\rm \sim$40 low-inclination, star-forming galaxies from the MaNGA survey (σ ∼ 65 km s−1) at ∼6.5 times higher spectral resolution (σ ∼ 10 km s−1) using the HexPak integral field unit on the WIYN 3.5-m telescope. The aim of these observations is to calibrate MaNGA’s instrumental resolution and to characterize turbulence in the warm interstellar medium and ionized galactic outflows. Here we report the results for the Hα region observations as they pertain to the calibration of MaNGA’s spectral resolution. Remarkably, we find that the previously reported MaNGA line-spread-function (LSF) Gaussian width is systematically underestimated by only 1 per cent. The LSF increase modestly reduces the characteristic dispersion of H ii regions-dominated spectra sampled at 1–2 kpc spatial scales from 23 to 20 km s−1 in our sample, or a 25 per cent decrease in the random-motion kinetic energy. This commensurately lowers the dispersion zeropoint in the relation between line-width and star-formation rate surface-density in galaxies sampled on the same spatial scale. This modest zero-point shift does not appear to alter the power-law slope in the relation between line-width and star-formation rate surface-density. We also show that adopting a scheme whereby corrected line-widths are computed as the square root of the median of the difference in the squared measured line width and the squared LSF Gaussian avoids biases and allows for lower signal-to-noise data to be used reliably.
Crystals of $\mathrm{TELSAM}$–target protein fusions that exhibit minimal crystal contacts and lack direct inter-$\mathrm{TELSAM}$ contacts
While conducting pilot studies into the usefulness of fusion to TELSAM polymers as a potential protein crystallization strategy, we observed novel properties in crystals of two TELSAM–target protein fusions, as follows. (i) A TELSAM–target protein fusion can crystallize more rapidly and with greater propensity than the same target protein alone. (ii) TELSAM–target protein fusions can be crystallized at low protein concentrations. This unprecedented observation suggests a route to crystallize proteins that can only be produced in microgram amounts. (iii) The TELSAM polymers themselves need not directly contact one another in the crystal lattice in order to form well-diffracting crystals. This novel observation is important because it suggests that TELSAM may be able to crystallize target proteins too large to allow direct inter-polymer contacts. (iv) Flexible TELSAM–target protein linkers can allow target proteins to find productive binding modes against the TELSAM polymer. (v) TELSAM polymers can adjust their helical rise to allow fused target proteins to make productive crystal contacts. (vi). Fusion to TELSAM polymers can stabilize weak inter-target protein crystal contacts. We report features of these TELSAM–target protein crystal structures and outline future work needed to validate TELSAM as a crystallization chaperone and determine best practices for its use.
Cosmological Constraints from Gas Mass Fractions of Massive, Relaxed Galaxy Clusters
We present updated cosmological constraints from measurements of the gas mass fractions (f(gas)) of massive, dynamically relaxed galaxy clusters. Our new data set has greater leverage on models of dark energy, thanks to the addition of the Perseus cluster at low redshifts, two new clusters at redshifts z greater than or similar to 1, and significantly longer observations of four clusters at 0.6 < z < 0.9. Our low-redshift (z < 0.16) f(gas) data, combined with the cosmic baryon fraction measured from the cosmic microwave background (CMB), imply a Hubble constant of h = 0.722 +/- 0.067. Combining the full f(gas) data set with priors on the cosmic baryon density and the Hubble constant, we constrain the dark energy density to be Omega(Lambda) = 0.865 +/- 0.119 in non-flat Lambda cold dark matter (cosmological constant) models, and its equation of state to be in flat, constant-w models, respectively 41percent and 29percent tighter than our previous work, and comparable to the best constraints available from other probes. Combining f(gas), CMB, supernova, and baryon acoustic oscillation data, we also constrain models with global curvature and evolving dark energy. For the massive, relaxed clusters employed here, we find the scaling of f(gas) with mass to be consistent with a constant, with an intrinsic scatter that corresponds to just similar to 3percent in distance.
Development of the Senseiver for efficient field reconstruction from sparse observations
Abstract The reconstruction of complex time-evolving fields from sensor observations is a grand challenge. Frequently, sensors have extremely sparse coverage and low-resource computing capacity for measuring highly nonlinear phenomena. While numerical simulations can model some of these phenomena using partial differential equations, the reconstruction problem is ill-posed. Data-driven-strategies provide crucial disambiguation, but these suffer in cases with small amounts of data, and struggle to handle large domains. Here we present the Senseiver, an attention-based framework that excels in reconstructing complex spatial fields from few observations with low overhead. The Senseiver reconstructs n -dimensional fields by encoding arbitrarily sized sparse sets of inputs into a latent space using cross-attention, producing uniform-sized outputs regardless of the number of observations. This allows efficient inference by decoding only a sparse set of output observations, while a dense set of observations is needed to train. This framework enables training of data with complex boundary conditions and extremely large fine-scale simulations. We build on the Perceiver IO by enabling training models with fewer parameters, which facilitates field deployment, and a training framework that allows a flexible number of sensors as input, which is critical for real-world applications. We show that the Senseiver advances the state-of-the-art of field reconstruction in many applications.
An investigation of non-canonical mixing in red giant stars using APOGEE 12 C/ 13 C ratios observed in open cluster stars
Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p–p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12 C/ 13 C ratio is a highly sensitive abundance metric used to probe this mixing. We investigate extra RGB mixing by examining: (1) how 12 C/ 13 C is altered along the RGB, and (2) how 12 C/ 13 C changes for stars of varying age and mass. Our sample consists of 43 red giants, spread over 15 open clusters from the Sloan Digital Sky Survey’s APOGEE DR17, that have reliable 12 C/ 13 C ratios derived from their APOGEE spectra. We vetted these 12 C/ 13 C ratios and compared them as a function of evolution and age/mass to the standard mixing model of stellar evolution, and to a model that includes prescriptions for RGB thermohaline mixing and stellar rotation. We find that the observations deviate from standard mixing models, implying the need for extra mixing. Additionally, some of the abundance patterns depart from the thermohaline model, and it is unclear whether these differences are due to incomplete observations, issues inherent to the model, our assumption of the cause of extra mixing, or any combination of these factors. Nevertheless, the surface abundances across our age/mass range clearly deviate from the standard model, agreeing with the notion of a universal mechanism for RGB extra mixing in low-mass stars.
Orbit-following simulations of fast-ion transport and losses due to the Alfvén eigenmode burst in the Large Helical Device
Orbit-following simulations of fast-ion transport and losses with time-dependent electromagnetic perturbations are performed to clarify the roles of Alfvén eigenmodes (AEs) and the low-frequency magnetohydrodynamic (MHD) mode observed in the kinetic-MHD hybrid simulation of AE bursts in the Large Helical Device. Fast-ion pressure profile flattening in the kinetic-MHD hybrid simulation can be reproduced by an orbit-following simulation with only the primary single AE of the time-dependent amplitude following the kinetic-MHD hybrid simulation result, while orbit-following simulations with constant AE amplitude of average level during AE burst cannot reproduce the fast-ion pressure profile flattening observed. The effects of other modes are negligible on the fast-ion pressure profile flattening. The fast-ion losses in kinetic-MHD hybrid simulation can be reproduced by an orbit-following simulation with time-dependent amplitude when the low-frequency MHD mode is considered in addition to multiple AEs. This indicates the synergetic effect of multiple AEs and the low-frequency MHD mode on fast-ion losses.
Cosmic Reionization On Computers: The Galaxy-Halo Connection between $5 \leq z \leq10$
We explore the connection between the stellar component of galaxies and their host halos during the epoch of reionization (5 ≤ z ≤ 10) using the CROC (Cosmic Reionization on Computers) simulations. We compare simulated galaxies with observations and find that CROC underpredicts the abundance of luminous galaxies when compared to observed UV luminosity functions, and analogously the most massive galaxies when compared to observed stellar mass functions. We can trace the deficit of star formation to high redshifts, where the slope of the star formation rate to stellar mass relation is consistent with observations, but the normalization is systematically low. This results in a star formation rate density and stellar mass density that are systematically offset from observations. However, the less luminous or lower stellar mass objects have luminosities and stellar masses that agree fairly well with observational data. We explore the stellar-to-halo mass ratio (SHMR), a key quantity that is difficult to measure at high redshifts and that models do not consistently predict. In CROC, the SHMR decreases with redshift, a trend opposite to some abundance-matching studies. These discrepancies uncover where future effort should be focused in order to improve the fidelity of modeling cosmic reionization. We also compare the CROC galaxy bias with observational measurements using Lyman-break galaxy samples, finding reasonable consistency.