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At least 559 records · Page 31

A Comprehensive Chemistry Evaluation and Diagnostics Package for E3SM – ChemDyg Version 1.1.0

The Chemistry Evaluation and Diagnostics Package (ChemDyg) is an open-source tool designed for the Energy Exascale Earth System Model (E3SM) developed by the U.S. Department of Energy. ChemDyg facilitates routine evaluation, tailored development, and in-depth analysis of atmospheric chemistry through its modular architecture, allowing users to compare model outputs with observational data. Version 1.1.0 introduces a robust set of diagnostic capabilities, including climatology, time evolution of key tracers, diurnal and annual cycle analyses, and extensive budget diagnostics. These features help identify model discrepancies and enhance the representation of atmospheric chemistry in E3SM. Each self-contained diagnostic set includes dedicated scripts and documentation for ease of use. The interactive HTML output improves data accessibility, accelerating chemistry model development. Additionally, ChemDyg's flexible framework allows for customization, enabling users to create unique diagnostic sets for specific scientific contributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of spatially and temporally resolved electron density measurements for the assessment of radiation hydrodynamics simulations of laboratory X-ray photoionized plasmas

The photoionized plasma gas cell experiment is an established platform we use to make at-parameter (ξ > > 1 ergs cm s –1 ) measurements of plasma properties with application to high-energy astrophysical systems. We model the experiments with 1D radiation hydrodynamics simulations using the HELIOS-CR code to inform our understanding and assist in the interpretation of results. The simulations predict that the bulk of the plasma is in a quasi-uniform and hydrodynamically unperturbed state throughout the duration of the experiment. To evaluate this prediction, we introduced a photonic Doppler velocimetry (PDV) diagnostic to measure spatially and temporally resolved plasma electron density. The initial measurements were successful but had limitations that made model-data comparisons challenging. To address this, we re-designed the gas cell PDV diagnostic and doubled the number of measurement locations to sample across two thirds of the depth of the cell. We also present a comparison of the results from the upgraded PDV diagnostic to the HELIOS-CR simulations for the first time. As a result, the experimental data confirms the prediction of an unperturbed region in the bulk of the plasma but reveals discrepancies in the time evolution and spatial distribution of the simulated electron density.

79 ASTRONOMY AND ASTROPHYSICS↗

High and Ultra-High Temperature Reaction Kinetics by Single Nanoparticle Mass Spectrometry

Methodology is presented for non-destructive, optically-detected single nanoparticle (NP) mass spectrometry, with the goal of extracting surface reaction kinetics for single NPs at high temperatures. Methods for determining the NP charge, mass, and temperature as a function of time are discussed, and the data are used to extract both the absolute kinetics for mass change, as well as the efficiencies of the surface processes that cause them. Factors that contribute to the uncertainties in absolute and relative mass determination, and in the resulting kinetic parameters, are discussed. The method allows the NP-to-NP variations in initial reactivity to be measured directly, along with the time evolution of reactivity resulting from NP structural/compositional changes that occur under reaction conditions. The strengths and limitations of single nanoparticle mass spectrometry as a high temperature surface kinetics tool are discussed in the context of sublimation and O2 oxidation kinetics experiments for single hafnium (Hf) NPs at temperatures ranging above 2400 K. The Hf oxidation kinetics are compared to analogous oxidation experiments for silicon, graphite, and carbon black NPs. In all four cases, the oxidation chemistry was dominated by processes that result in net mass loss, and the distinct mechanisms responsible are discussed. All four NPs also eventually passivated, i.e., the efficiencies for oxidative etching decreased by at least two orders of magnitude, relative to the initial efficiencies. Furthermore, the passivation mechanisms, which are quite different for carbon, compared to silicon or hafnium, are discussed. Carbon NP passivation is attributed to structural isomerization leading to fully coordinated, fullerene-like NP surfaces, while for silicon and hafnium, passivation results from delayed formation of an oxide layer, triggered by accumulation of oxygen in the NP sub-surface region.

36 MATERIALS SCIENCE↗

Maximum bound principle preserving integrating factor Runge–Kutta methods for semilinear parabolic equations

A large class of semilinear parabolic equations satisfy the maximum bound principle (MBP) in the sense that the time-dependent solution preserves for any time a uniform pointwise bound imposed by its initial and boundary conditions. Here, the MBP plays a crucial role in understanding the physical meaning and the well-posedness of the mathematical model. Investigation on numerical algorithms with preservation of the MBP has attracted increasingly attentions in recent years, especially for the temporal discretizations, since the violation of MBP may lead to nonphysical solutions or even blow-ups of the algorithms. In this paper, we study high-order MBP-preserving time integration schemes by means of the integrating factor Runge-Kutta (IFRK) method. Beginning with the space-discrete system of semilinear parabolic equations, we present the IFRK method in general form and derive the sufficient conditions for the method to preserve the MBP. In particular, we show that the classic four-stage, fourth-order IFRK scheme is MBP preserving for some typical semilinear systems although not strong stability preserving, which can be instantly applied to the Allen-Cahn type of equations. To our best knowledge, this is the first time to present a fourth-order linear numerical method preserving the MBP. In addition, convergence of these numerical schemes is proved theoretically and verified numerically, as well as their efficiency by simulations of 2D and 3D long-time evolutional behaviors. Numerical experiments are also carried out for a model which is not a typical gradient flow as the Allen-Cahn type of equations.

97 MATHEMATICS AND COMPUTING↗

Cluster dynamics modeling of irradiation growth in single crystal Zr

Irradiation growth of single-crystal Zr is modeled with a reduced set of cluster dynamics equations. Nucleation and growth of basal and prismatic dislocation loops are both accounted for in the model. Equations are developed for the time evolution of single point defects, a limited number of point defect clusters, interstitial and vacancy loop nucleation rates, as well as for the growth of vacancy loops on basal planes and interstitial loops on prismatic planes. Reduction of the usual infinite hierarchy of cluster dynamics equations to the simple set studied here is justified on the physical basis of the stability of small loops once nucleated. This simplified cluster dynamics model with a small number of adjustable parameters avoids the complexity of explicit representation of higher order point defect clusters. The model shows consistency with experimental observations of the following aspects: (1) the growth rates of Zr crystals along the a- and c-axes; (2) the onset dose for breakaway irradiation growth; (3) the saturation dislocation loop densities of vacancy and interstitial loops; (4) the effects of cold work and temperature on irradiation growth.

36 MATERIALS SCIENCE↗

Do atoms age?

Time evolution generically entangles a quantum state with environmental degrees of freedom. The resulting increase in entropy changes the properties of that quantum system leading to “aging”. It is interesting to ask if this familiar property also applies to simple, single particle quantum systems such as the decay of a radioactive particle. We propose a test of such aging in an ion clock setup where we probe for temporal changes to the energies of the electronic state of an ion containing a radioactive nucleus. Such effects are absent in standard quantum mechanics and this test is thus a potent null test for violations of quantum mechanics. As a proof of principle, we show that these effects exist in causal non-linear modifications of quantum mechanics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Stopping to reflect: Asymptotic static moving mirrors as quantum analogs of classical radiation

Radiation from an accelerating charge is a basic process that can serve as an intersection between classical and quantum physics. We present two exactly soluble electron trajectories that permit analysis of the radiation emitted, exploring its time evolution and spectrum by analogy with the moving mirror model of the dynamic Casimir effect. These classical solutions are finite energy, rectilinear (nonperiodic), asymptotically zero velocity worldlines with corresponding quantum analog beta Bogolyubov coefficients. One of them has an interesting connection to uniform acceleration and Leonardo da Vinci's water pitcher experiment.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantum state preparation with resolution refinement

We introduce a method called resolution refinement that allows one to bootstrap eigenstate preparation on a quantum computer. We first prepare an eigenstate of a low-resolution Hamiltonian using any method of choice. The eigenstate is then lifted to higher resolution and adiabatically evolved to produce the corresponding eigenstate of a higher-fidelity Hamiltonian. We give examples of resolution refinement applied to both single-particle basis states as well as a spatial lattice grid. For basis refinement, we compute few-body ground states of the Busch model for interacting particles in a harmonic trap in one dimension. For lattice refinement, we compute Hartree-Fock nuclear states for a central Woods-Saxon potential in three dimensions, and we compute bound states and continuum states in a multi-species Hubbard model of fermions in one dimension. In all cases, the method is efficient and requires an adiabatic evolution time that scales with the inverse of the energy gap times the square root of the system size. We show that this very favorable scaling arises from the fact that resolution refinement does not make large changes to the structure or energies of the low-energy eigenstates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quasi-periodic travelling gravity–capillary waves

We present a numerical study of spatially quasi-periodic travelling waves on the surface of an ideal fluid of infinite depth. This is a generalization of the classic Wilton ripple problem to the case when the ratio of wavenumbers satisfying the dispersion relation is irrational. We propose a conformal mapping formulation of the water wave equations that employs a quasi-periodic variant of the Hilbert transform to compute the normal velocity of the fluid from its velocity potential on the free surface. We develop a Fourier pseudo-spectral discretization of the travelling water wave equations in which one-dimensional quasi-periodic functions are represented by two-dimensional periodic functions on the torus. This leads to an overdetermined nonlinear least-squares problem that we solve using a variant of the Levenberg–Marquardt method. We investigate various properties of quasi-periodic travelling waves, including Fourier resonances, time evolution in conformal space on the torus, asymmetric wave crests, capillary wave patterns that change from one gravity wave trough to the next without repeating and the dependence of wave speed and surface tension on the amplitude parameters that describe a two-parameter family of waves.

97 MATHEMATICS AND COMPUTING↗

Impulse-driven release of gas-encapsulated drops

Gas-encapsulated drops, much like antibubbles, are drops enclosed in a bubble within a liquid. They show potential as payload carriers in fluid transport and mixing techniques where sound waves can be leveraged to induce the collapse of the gas core and the subsequent release of the drop. Here, the interaction of millimetre-sized gas-encapsulated drops with impulsive laser-induced shock waves is investigated to gain fundamental insights into the release process. Experimental synchrotron X-ray phase contrast imaging, which allows the drop dynamics to be visualised inside the encapsulating bubble, is complemented by numerical simulations to study the intricate physics at play. Three drop dynamical release regimes are discovered, namely the drop impact , partial deposition and jet impact regimes. The regime type is mainly dependent on the shape of the bubble interface impacting the drop and the associated Weber and Reynolds numbers. The drop dynamics of the drop impact and partial deposition regimes show similarities with the canonical configuration of drops impacting flat liquid surfaces, whereas the jet impact regime resembles binary drop collisions, which allows existing scaling laws to be applied to describe the underlying processes. The release of the drop is investigated numerically. The time evolution of the drop dissemination within the surrounding liquid discloses enhanced mixing for dynamics involving high Weber and Reynolds numbers such as the drop impact and jet impact regimes.

42 ENGINEERING↗

Learning Latent Representations to Bridge Coarse-Grained and Atomistic Resolutions in Polymer Simulations

We present a machine-learning-based framework for learning reduced-order representations of polymer chain conformations across coarse-grained (CG) and united-atom (UA) fidelities. By employing linear singular value decomposition and nonlinear autoencoders, we compress high-dimensional polymer configurations into latent spaces with minimal loss of structural accuracy. Crucially, we demonstrate a near-perfect linear mapping between CG and UA latent spaces, enabling an efficient super-resolution back-mapping procedure that reconstructs high-fidelity UA configurations from CG simulations. While minor structural inaccuracies occur, they are effectively corrected through a brief molecular dynamics relaxation, forming a practical hybrid machine learning−physics scheme. This approach establishes the key structural prerequisites for accelerated polymer dynamics simulations: a compact and accurate latent encoding of polymer chain conformations and a validated multi-fidelity mapping that permits reconstruction of UA structures from CG configurations. The extension of this framework to explicit time evolution within the latent space, enabling dynamics to be propagated at CG fidelity and decoded to UA resolution only when required, represents a natural and well-motivated direction for future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Multireference Quantum Krylov Algorithm for Strongly Correlated Electrons

We introduce a multireference selected quantum Krylov (MRSQK) algorithm suitable for quantum simulation of many-body problems. MRSQK is a low-cost alternative to the quantum phase estimation algorithm that generates a target state as a linear combination of non-orthogonal Krylov basis states. This basis is constructed from a set of reference states via real-time evolution; thus, avoiding the numerical optimization of parameters. An efficient algorithm for the evaluation of the off-diagonal matrix elements of the overlap and Hamiltonian matrices is discussed and a selection procedure is introduced to identify a basis of orthogonal references that ameliorates the linear dependency problem. Preliminary benchmarks on linear H 6 , H 8 , and BeH 2 indicate that MRSQK can predict the energy of these systems accurately using very compact Krylov bases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strongly Anisotropic Thermomechanical Response to Shock Wave Loading in Oriented Samples of the Triclinic Molecular Crystal 1,3,5-Triamino-2,4,6-trinitrobenzene

All-atom molecular dynamics (MD) simulations were used to study shock wave loading in oriented single crystals of the highly anisotropic triclinic molecular crystal 1,3,5-triamino-2,4,6-trinitrobenzene (TATB). The crystal structure consists of planar hydrogen-bonded sheets of individually planar TATB molecules that stack into graphitic-like layers. Shocks were studied for seven systematically prepared crystal orientations with limiting cases that correspond to shock propagation exactly perpendicular and exactly parallel to the graphitic-like layers. The simulations were performed for initially defect-free crystals using a reverse-ballistic configuration that generates explicit, supported shocks. Final longitudinal stress components are between ≈8.5 and ≈10.5 GPa for the 1.0 km s –1 impact speed studied. Orientation-dependent properties are reported including shock speeds, stresses, temperatures, compression ratios, and local material strain rates. Spatiotemporal maps of the temperature, stress tensor, material flow, and molecular orientations reveal complicated processes that arise for specific shock directions. Furthermore, the results indicate that TATB shock response is highly sensitive to crystal orientation, with significant qualitative differences for the time evolution of the stress tensor and temperature, elastic/inelastic compression response, defect formation and growth, critical von Mises stress, and strain rates during shock rise that span nearly an order of magnitude. A variety of inelastic deformation mechanisms are identified, ranging from crumpling of graphitic-like layers to dislocation-mediated plasticity to intense shear strain localization. To our knowledge, these are the first systematic MD simulations and analysis of explicit shock wave propagation along nontrivial crystal directions in a triclinic molecular crystal.

36 MATERIALS SCIENCE↗

Nanobubble Formation and Coverage during High Current Density Alkaline Water Electrolysis

Gas bubbles are a necessary byproduct of water electrolysis whereby hydrogen and oxygen are produced from water. These attached gases reduce the electrode’s active area, which necessitates a deep understanding of the bubble life cycle starting from nanobubbles. Synchronized with the electrochemistry, the time evolution of the surface nanobubble size and coverage is resolved using grazing incidence small-angle X-ray scattering (GISAXS) and correlated with optical microscopy and theoretical calculations to show that a significant portion of the surface is covered in nanobubbles after larger micron-sized bubbles are observed. Further, these nanobubbles increase in number and decrease in size, toward 2 nm diameter, with the charge passed. The trend in size and number is consistent with an increase in supersaturation, which reduces the nascent bubble size. Altogether, this study suggests a significant portion of the surface contains nanobubbles and that strategies to reduce the dissolved hydrogen would be effective at reducing the nanobubble surface coverage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermal Hydroquinone Oxidation on Co/N-doped Carbon Proceeds by a Band-Mediated Electrochemical Mechanism

Molecules catalyze aerobic oxidation reactions via redox cycling at the metal center to effect sequential activation of O 2 and the substrate. Metal surfaces can catalyze the same transformations by coupling independent half-reactions for oxygen reduction and substrate oxidation mediated via the exchange of band-electrons. Metal/nitrogen-doped carbons (MNCs) are promising catalysts for aerobic oxidation that consist of molecule-like active sites embedded in a conductive carbon host. Owing to their combining molecular and metallic features, it remains unclear whether they proceed via the sequential redox cycling pathways of molecules or the band-mediated pathways of metals. Herein, we simultaneously track the potential of the catalyst and the rate of the turnover of aerobic hydroquinone oxidation on a cobalt-based MNC catalyst contacted to a catalytically inactive carbon electrode. By comparing operando measurements of rate and potential with the current-voltage behavior of each constituent half-reaction under identical conditions, we show that these molecular materials can display the band-mediated reaction mechanisms of extended metallic solids. Further, we show that the action of these band-mediated mechanisms explains fractional reaction orders in both oxygen and hydroquinone, the time evolution of catalyst potential and rate, and the dependence of rate on overall reaction free energy. Selective poisoning experiments suggest that oxygen reduction proceeds at cobalt sites, whereas quinone oxidation proceeds at native oxidic defects on the carbon. These findings highlight that molecule-like active sites can take advantage of band-mediated mechanisms when coupled to conductive hosts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Solvent-Assisted Li+ Transport in the Solid Electrolyte Interphase operando

The performance of energy-dense lithium metal batteries is critically influenced by the properties of the solid electrolyte interphase (SEI). Yet, progress in understanding this layer has been limited by the lack of accurate operando characterization because the SEI evolves dynamically during cycling. Here, we apply dynamic electrochemical impedance spectroscopy (dEIS) to resolve the real-time evolution of the SEI on lithium metal in ether-based electrolytes with varying degrees of fluorination. We find that faster stabilization of the compact SEI resistance correlates with improved passivation and higher Coulombic efficiency. Unexpectedly, compact SEI resistance correlates directly with Li+ solvation energy, revealing that weaker Li+ solvation increases not only bulk but also interphase resistance. These findings challenge the conventional view of the SEI as a purely solid-phase conductor and instead support a solvent-assisted Li+ transport mechanism within the compact SEI. This framework emphasizes the need to balance SEI ionic conductivity with the Li+ solvation environment to maximize lithium metal battery performance.

Sacci, Robert [ORNL] (ORCID:0000000200735221)↗

Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks

Abstract Assessing forced climate change requires the extraction of the forced signal from the background of climate noise. Traditionally, tools for extracting forced climate change signals have focused on one atmospheric variable at a time, however, using multiple variables can reduce noise and allow for easier detection of the forced response. Following previous work, we train artificial neural networks to predict the year of single‐ and multi‐variable maps from forced climate model simulations. To perform this task, the neural networks learn patterns that allow them to discriminate between maps from different years—that is, the neural networks learn the patterns of the forced signal amidst the shroud of internal variability and climate model disagreement. When presented with combined input fields (multiple seasons, variables, or both), the neural networks are able to detect the signal of forced change earlier than when given single fields alone by utilizing complex, nonlinear relationships between multiple variables and seasons. We use layer‐wise relevance propagation, a neural network explainability tool, to identify the multivariate patterns learned by the neural networks that serve as reliable indicators of the forced response. These “indicator patterns” vary in time and between climate models, providing a template for investigating inter‐model differences in the time evolution of the forced response. This work demonstrates how neural networks and their explainability tools can be harnessed to identify patterns of the forced signal within combined fields.

54 ENVIRONMENTAL SCIENCES↗

Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets

The intensification of extreme precipitation under anthropogenic forcing is robustly projected by global climate models, but highly challenging to detect in the observational record. Large internal variability distorts this anthropogenic signal. Models produce diverse magnitudes of precipitation response to anthropogenic forcing, largely due to differing schemes for parameterizing subgrid-scale processes. Meanwhile, multiple global observational datasets of daily precipitation exist, developed using varying techniques and inhomogeneously sampled data in space and time. Previous attempts to detect human influence on extreme precipitation have not incorporated model uncertainty, and have been limited to specific regions and observational datasets. Using machine learning methods that can account for these uncertainties and capable of identifying the time evolution of the spatial patterns, we find a physically interpretable anthropogenic signal that is detectable in all global observational datasets. Machine learning efficiently generates multiple lines of evidence supporting detection of an anthropogenic signal in global extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗