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DOE OSTI2022

Breaking adsorption-energy scaling limitations of electrocatalytic nitrate reduction on intermetallic CuPd nanocubes by machine-learned insights

The electrochemical nitrate reduction reaction (NO 3 RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d-states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO 3 is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO 3 RR to ammonia with a Faradaic efficiency of 92.5% at –0.5 V RHE and a yield rate of 6.25 mol h –1 g –1 at –0.6 V RHE . This study provides machine-learned design rules besides the d-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

Dual-Frequency VLBI Study of Centaurus A on Sub-Parsec Scales: The Highest-Resolution View of an Extragalactic Jet

Centaurus A is the closest active galactic nucleus. High resolution imaging using Very Long Baseline Interferometry (VLBI) enables us to study the spectral and kinematic behavior of the radio jet-<:ounterjet system on sub-parsec scales, providing essential information for jet emission and formation models. Aims. Our aim is to study the structure and spectral shape of the emission from the central-parsec region of Cen A. Methods. As a target of the Southern Hemisphere VLBI monitoring program TANAMI (Tracking Active Galactic Nuclei with Millliarcsecond Interferometry), VLBI observations of Cen A are made regularly at 8.4 and 22.3 GHz with the Australian Long Baseline Array (LBA) and associated telescopes in Antarctica, Chile, and South Africa. Results. The first dual-frequency images of this source are presented along with the resulting spectral index map. An angular resolution of 0.4 mas x 0.7 mas is achieved at 8.4 GHz, corresponding to a linear scale of less than 0.013 pc. Hence, we obtain the highest resolution VLBI image of Cen A, comparable to previous space-VLBI observations. By combining with the 22.3 GHz image, we present the corresponding dual-frequency spectral index distribution along the sub-parsec scale jet revealing the putative emission regions for recently detected y-rays from the core region by Fermi/LAT. Conclusions. We resolve the innermost structure of the milliarcsecond scale jet and counter jet system of Cen A into discrete components. The simultaneous observations at two frequencies provide the highest resolved spectral index map of an AGN jet allowing us to identify up to four possible sites as the origin of the high energy emission. Key words. galaxies: active galaxies: individual (Centaurus A, NGC 5128) - galaxies: jets - techniques: high angular resolution

Mueller, C.↗

DOE OSTI2025

Cosmological Constraints from Full-Scale Clustering and Galaxy-Galaxy Lensing with DESI DR1

We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy-galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. We analyze four samples drawn from the Bright Galaxy Survey (BGS) and the Luminous Red Galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing measurements from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to $0.4 \, h^{-1} \, \mathrm{Mpc}$ for clustering and $2.5 \, h^{-1} \, \mathrm{Mpc}$ for lensing, leading to stringent constraints on $S_8 = σ_8 \sqrt{Ω_\mathrm{m} / 0.3}$ and $Ω_\mathrm{m}$ when fixing other cosmological parameters to those preferred by the CMB. We find $S_8 = 0.794 \pm 0.023$ and $Ω_\mathrm{m} = 0.295 \pm 0.012$ when using lensing measurements from DES and KiDS. Similarly, for HSC, we find $S_8 = 0.793 \pm 0.017$ and $Ω_\mathrm{m} = 0.303 \pm 0.010$ when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of non-linear scales.

Lange, Johannes U. [American U.] (ORCID:0000000224↗

DOE OSTI2023

Ion cyclotron heating at high plasma density in Proto-MPEX

The physics of ion cyclotron heating (ICH) relevant to the steady-state linear machine MPEX (Material Plasma Exposure eXperiment) has been explored in its predecessor, short-pulse device: Proto-MPEX. MPEX will utilize fundamental ICH to increase heat flux at the target and produce ion temperatures and velocity distributions with improved fidelity to those found in a tokamak divertor region, in comparison to those produced by substrate biasing. In the experiments on Proto-MPEX described here, bulk ion temperatures up to ~15 eV have been achieved with 20 kW net ICH power at 6.5 MHz, using ICH heating of a deuterium plasma produced by a helicon plasma source. The heat flux at the target has been observed to increase throughout the plasma cross section, including in the core region. Core $T_i$ and target heat flux are observed to scale linearly with injected ICH power. Further, measurements of plasma loading and target heat flux as a function of the magnetic field strength at the antenna, together with modeling of the wave propagation from the antenna to the ion cyclotron resonance using the ANTENA and COMSOL codes with a warm plasma dielectric tensor, indicate that power is coupled to the core plasma via fast wave excitation of a kinetic Alfvén wave.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

XRISM Forecast for the Coma Cluster: Stormy, with a Steep Power Spectrum

The XRISM Resolve microcalorimeter array measured the velocities of hot intracluster gas at two positions in the Coma galaxy cluster: ${3}^{{\prime} }\times {3}^{{\prime} }$ squares at the center and at 6$^{\prime} $ (170 kpc) to the south. We find the line-of-sight velocity dispersions in those regions to be σ z = 208 ± 12 km s −1 and 202 ± 24 km s −1 , respectively. The central value corresponds to a 3D Mach number of M = 0.24 ± 0.015 and a ratio of the kinetic pressure of small-scale motions to thermal pressure in the intracluster plasma of only 3.1% ± 0.4%, at the lower end of predictions from cosmological simulations for merging clusters like Coma, and similar to that observed in the cool core of the relaxed cluster A2029. Meanwhile, the gas in both regions exhibits high line-of-sight velocity differences from the mean velocity of the cluster galaxies, Δv z = 450 ± 15 km s −1 and 730 ± 30 km s −1 , respectively. A small contribution from an additional gas velocity component, consistent with the cluster optical mean, is detected along a sight line near the cluster center. The combination of the observed velocity dispersions and bulk velocities is not described by a Kolmogorov velocity power spectrum of steady-state turbulence; instead, the data imply a much steeper effective slope (i.e., relatively more power at larger linear scales). This may indicate either a very large dissipation scale, resulting in the suppression of small-scale motions, or a transient dynamic state of the cluster, where large-scale gas flows generated by an ongoing merger have not yet cascaded down to small scales.

coma cluster↗

DOE OSTI2024

Wakefield generation in hydrogen and lithium plasmas at FACET-II: Diagnostics and first beam-plasma interaction results

Plasma wakefield acceleration provides ultrahigh acceleration gradients of tens of GeV/m, providing a novel path toward efficient, compact, TeV-scale linear colliders, and high brightness free electron lasers. Critical to the success of these applications is demonstrating simultaneously high gradient acceleration, high energy transfer efficiency, and preservation of emittance, charge, and energy spread. Experiments at the FACET-II National User Facility at SLAC National Accelerator Laboratory aim to achieve all of these milestones in a single-stage plasma wakefield accelerator, providing a 10 GeV energy gain in a < 1 m plasma with high energy transfer efficiency. Such a demonstration depends critically on diagnostics able to measure emittance with mm mrad accuracy, energy spectra to determine both percent level energy spread, and broadband energy gain and loss, incoming longitudinal phase space, and matching dynamics. This paper discusses the experimental setup at FACET-II, including the incoming beam parameters from the FACET-II linac, plasma sources, and diagnostics developed to meet this challenge. Initial progress on the generation of beam ionized wakes in meter-scale hydrogen gas is discussed as well as commissioning of the plasma sources and diagnostics. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗

NASA NTRS2016

Multiparameter Flowfield Measurements in High-Pressure, Cryogenic Environments Using Femtosecond Lasers

Femtosecond laser electronic excitation tagging (FLEET) and Rayleigh scattering (RS) from a femtosecond laser are demonstrated in the NASA Langley 0.3-m Transonic Cryogenic Tunnel (TCT). The measured signals from these techniques are examined for their thermodynamic dependencies in pure nitrogen. The FLEET signal intensity and signal lifetimes are found to scale primarily with the gas density, as does the RS signal. Several models are developed, which capture these physical behaviors. Notably, the FLEET and Rayleigh scattering intensities scale linearly with the flow density, while the FLEET signal decay rates are a more complex function of the thermodynamic state of the gas. The measurement of various flow properties are demonstrated using these techniques. While density was directly measured from the signal intensities and FLEET signal lifetime, temperature and pressure were measured using the simultaneous FLEET velocity measurements while assuming the flow had a constant total enthalpy. Measurements of density, temperature, and pressure from the FLEET signal are made with accuracies as high as 5.3 percent, 0.62 percent, and 6.2 percent, respectively, while precisions were approximately 10 percent, 0.26 percent, and 11 percent for these same quantities. Similar measurements of density from Rayleigh scattering showed an overall accuracy of 3.5 percent and a precision of 10.2 percent over a limited temperature range (T greater than 195 K). These measurements suggest a high degree of utility at using the femtosecond-laser based diagnostics for making multiparameter measurements in high-pressure, cryogenic environments such as large-scale TCT facilities.

Burns, Ross A.↗

DOE OSTI2021

encore : an O ( N g2) estimator for galaxy N -point correlation functions

ABSTRACT We present a new algorithm for efficiently computing the N-point correlation functions (NPCFs) of a 3D density field for arbitrary N. This can be applied both to a discrete spectroscopic galaxy survey and a continuous field. By expanding the statistics in a separable basis of isotropic functions built from spherical harmonics, the NPCFs can be estimated by counting pairs of particles in space, leading to an algorithm with complexity $\mathcal {O}(N_\mathrm{g}^2)$ for Ng particles, or $\mathcal {O}(N_\mathrm{FFT}\log N_\mathrm{FFT})$ when using a Fast Fourier Transform with NFFT grid-points. In practice, the rate-limiting step for N > 3 will often be the summation of the histogrammed spherical harmonic coefficients, particularly if the number of radial and angular bins is large. In this case, the algorithm scales linearly with Ng. The approach is implemented in the encore code, which can compute the 3PCF, 4PCF, 5PCF, and 6PCF of a BOSS-like galaxy survey in ${\sim}100$ CPU-hours, including the corrections necessary for non-uniform survey geometries. We discuss the implementation in depth, along with its GPU acceleration, and provide practical demonstration on realistic galaxy catalogues. Our approach can be straightforwardly applied to current and future data sets to unlock the potential of constraining cosmology from the higher point functions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

We present a novel machine learning (ML)-based method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural networks (NNC2PS and NNC2PL), trained in PyTorch (2.0+) and optimized for GPU inference using NVIDIA TensorRT (8.4.1), achieving significant speedups with minimal accuracy loss. The NNC2PS model achieves 𝐿 1 and 𝐿 ∞ errors of 4.54 × 10 −7 and 3.44 × 10−6, respectively, while the NNC2PL model exhibits even lower error values. TensorRT optimization with mixed-precision deployment substantially accelerates performance compared to traditional root-finding methods. Specifically, the mixed-precision TensorRT engine for NNC2PS achieves inference speeds approximately 400 times faster than a traditional single-threaded CPU implementation for a dataset size of 1,000,000 points. Ideal parallelization across an entire compute node in the Delta supercomputer (dual AMD 64-core 2.45 GHz Milan processors and 8 NVIDIA A100 GPUs with 40 GB HBM2 RAM and NVLink) predicts a 25-fold speedup for TensorRT over an optimally parallelized numerical method when processing 8 million data points. Moreover, the ML method exhibits sub-linear scaling with increasing dataset sizes. We release the scientific software developed, enabling further validation and extension of our findings. By exploiting the underlying symmetries within the equation of state, these findings highlight the potential of ML, combined with GPU optimization and model quantization, to accelerate conservative-to-primitive inversion in relativistic hydrodynamics simulations.

conservative-to-primitive conversion↗

DOE OSTI2023

Full forward model of galaxy clustering statistics with AbacusSummit light cones

ABSTRACT Novel summary statistics beyond the standard 2-point correlation function (2PCF) are necessary to capture the full astrophysical and cosmological information from the small-scale (r < 30h−1Mpc) galaxy clustering. However, the analysis of beyond-2PCF statistics on small scales is challenging because we lack the appropriate treatment of observational systematics for arbitrary summary statistics of the galaxy field. In this paper, we develop a full forward modelling pipeline for a wide range of summary statistics using the large high-fidelity AbacusSummit light cones that account for many systematic effects as well as remain flexible and computationally efficient to enable posterior sampling. We apply our forward model approach to a fully realistic mock galaxy catalog and demonstrate that we can recover unbiased constraints on the underlying galaxy–halo connection model using two separate summary statistics: the standard 2PCF and the novel k-th nearest neighbour (kNN) statistics, which are sensitive to correlation functions of all orders. We will demonstrate its strong constraining power on extended galaxy–halo connection models and cosmology in follow up papers. We expect this to become a powerful approach when applying to upcoming surveys such as DESI where we can leverage a multitude of summary statistics across a wide redshift range to maximally extract information from the non-linear scales.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2006

Development of a Liner Design Methodology and Relevant Results of Acoustic Suppression in the Farfield for Mixer-Ejector Nozzles

We have developed a process to predict noise field interior to the ejector and in the farfield for any liner design for a mixer-ejector of arbitrary scale factor. However, a number of assumptions, not verified for the current application, utilized in this process, introduce uncertainties in the final result, especially, on a quantitative basis. The normal impedance model for bulk with perforated facesheet is based on homogeneous foam materials of low resistivity. The impact of flow conditions for HSCT application as well as the impact of perforated facesheet on predicted impedance is not properly accounted. Based on the measured normal impedance for deeper bulk samples (i.e., 2.0 in.) the predicted reactance is much higher compared to the data at frequencies above 2 kHz for T-foam and 200 ppi SiC. The resistance is under predicted at lower frequencies (below 4 kHz) for these samples. Thus, the use of such predicted data in acoustic suppression is likely to introduce inaccuracies. It should be noted that the impedance prediction methods developed recently under liner technology program are not utilized in the studies described in this report due to the program closeout. Acoustic suppression prediction is based on the uniform flow and temperature conditions in a two-sided treated constant area rectangular duct. In addition, assumptions of equal energy per mode noise field and interaction of all frequencies with the treated surface for the entire ejector length may not be accurate. While, the use of acoustic transfer factor minimizes the inaccuracies associated with the prediction for a known test case, the assumption of the same factor for other liner designs and with different linear scale factor ejectors seems to be very optimistic. As illustrated in appendix D that the predicted noise suppression for LSM-1 is lower compared to the measured data is an indication of the above argument. However, the process seems to be more reliable when used for the same scale models for different liner designs as demonstrated for Gen. 1 mixer-ejectors.

Salikuddin, M.↗

DOE OSTI2025

Peeling-ballooning modes in spherical tokamaks: Multi-branch instabilities and effects beyond ideal MHD

A number of important physics effects on the stability of relatively high-n (n is the toroidal mode number) peeling-ballooning modes (PBMs) are investigated based on an equilibrium reconstructed from a NSTX discharge, utilizing extended magnetohydrodynamic (MHD) eigenvalue solvers. For a given toroidal mode number n, multiple branches of instabilities are computed, with the total number of unstable branches roughly linearly scaling with n. Most of the unstable branches are located in the plasma core region, but edge-localized branches, i.e., PBMs, are also identified at higher n-numbers. For the single-fluid-wise most unstable PBM with n = 19⁠, stabilizing/destabilizing effects due to various physics beyond ideal MHD are systematically investigated. Plasma toroidal flow is found to be weakly stabilizing. Local flow shear is generally stabilizing as well, with the degree of stabilization depending on the initial growth rate (without flow shear) of the mode. The plasma resistivity can strongly destabilize the PBM within the single-fluid framework. Anisotropic thermal transport, strong parallel sound wave damping, as well as two-fluid effects are all stabilizing to the mode. In particular, diamagnetic stabilization (within the two-fluid model) is found to be very strong for this mode.

Linear stability analysis↗

DOE OSTI2025

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗

DOE OSTI2023

Giant Spontaneous Magnetostriction in MnTe Driven by a Novel Magnetostructural Coupling Mechanism

A comprehensive x-ray scattering study of spontaneous magnetostriction in hexagonal MnTe, an antiferromagnetic semiconductor with a Néel temperature of T N = 307 K, is presented. The largest spontaneous magnetovolume effect known for an antiferromagnet is observed, reaching a volume contraction of |ΔV/V| > 7 × 10 -3 . This can be justified semiquantitatively by considering bulk material properties, the spatial dependence of the superexchange interaction, and the geometrical arrangement of magnetic moments in MnTe. The highly unusual linear scaling of the magnetovolume effect with the short-range magnetic correlations, beginning in the paramagnetic state well above T N , points to a novel physical mechanism, which is explained in terms of a trilinear coupling of the elastic strain with superposed distinct domains of the antiferromagnetic order parameter. Furthermore, this novel mechanism for coupling lattice strain to robust short-range magnetic order casts new light on magnetostrictive phenomena and also provides a template by which the exceptional magnetostrictive properties of MnTe might be realized in a wide range of other functional materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Abstract The improvement of Pt‐based catalysts for propane dehydrogenation (PDH) has progressed by recent investigations that have identified Zn as a promising promoter for Pt subnanometer catalysts. It is desirable to gain insights into the structure, stability, and activity of such active sites and the factors that influence them, such as Zn : Pt ratio, Pt coordination and nuclearity. Here, we employ density functional theory and microkinetic simulations to investigate the stability of Pt x Zn y ( x =1–3, y=0–3) active sites grafted on silanols of Silicalite‐1 and the PDH activity of Pt. We find that the coordination of a Pt atom to a nest of grafted Zn(II) atoms increases the stability of the Pt 1 Zn y sites, whose activity is similar for y=0–2 and drops dramatically for y>2. We further demonstrate, via linear scaling relations and microkinetic simulations, that the turnover frequency obeys a volcano law as a function of propylene binding strength. The Pt 2 Zn 1 and Pt 3 Zn 1 sites are stable and exhibit activity similar to Pt 1 Zn 2 , but only Pt 1 Zn 2 manifests reaction kinetics consistent with experimental data, strongly suggesting the active site composition in the synthesized catalyst samples. The methodology presented here suggests a general strategy for deducing active site information such as composition through simple kinetic experiments.

Liu, Yilang↗

DOE OSTI2024

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Liu, Yilang↗

DOE OSTI2022

Fluxionality of Subnano Clusters Reshapes the Activity Volcano of Electrocatalysis

The Sabatier activity volcano provides intuitive guide for catalyst design, but also imposes fundamental limitations on the composition and maximal activity of catalysts. Here we show that the ORR activity volcano is shifted and reshaped by the potential-dependent fluxionality of subnano cluster catalysts. Fluxionality causes the typically under-binding Ag/Au to gain optimal activity in the cluster form, and surpass Pt/Pd. Furthermore, isomerization of clusters as a function of the potential breaks linear scaling relationships, enabling surpassing the volcano “apex” relative to the bulk. The effect is likely general for fluxional cluster catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗