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DOE OSTI2025

Material Fracturing and Failure Simulation Datasets

Fracturing is a fundamental physics phenomena with broad relevance across multiple domains, ranging from infrastructure integrity, aerospace durability, reservoir production, and seismic events. We present a diverse dataset of simulated fracture evolution and material failure generated from two numerical solvers: the phase-field method and the combined finite-discrete element method (FDEM). These solvers differ in formulation, physical fidelity, and computational efficiency. The dataset includes five materials: PBX, anisotropic shale, tungsten, aluminum, and steel. For each, phase-field simulations span 400,000 cases: 200,000 under uniaxial tension and 200,000 under biaxial tension. The computationally expensive FDEM simulations include 90,000 split evenly among PBX, shale, and tungsten under uniaxial loading. All simulations begin with randomized initial fracture patterns. Each entry includes temporal data capturing fracture propagation dynamics. This comprehensive dataset is designed to support the development of foundational or surrogate machine learning approaches for predicting material failure. While no such models are introduced here, the dataset lays a robust foundation for advancing future research and innovation in these areas.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamics of heavy quarks in strongly coupled $\mathcal{N}$ = 4 SYM plasma

We calculate the probability distribution P(k) for a heavy quark with velocity v propagating through strongly coupled N = 4 SYM plasma in the ’t Hooft limit (N c → ∞, λ = g 2 N c → ∞) at a temperature T to acquire a momentum k due to interactions with the plasma. This distribution encodes the well-known drag coefficient η D and the transverse and longitudinal momentum diffusion coefficients κ T and κ L . The jet quenching parameter $\hat{q}$ can be extracted from P(k) for v = 1. Going beyond these known Gaussian characteristics of P(k), our calculation determines all of the higher order and mixed moments to leading order in 1/$\sqrt{λ}$ for the first time. These non-Gaussian features of P(k) include qualitatively novel correlations between longitudinal energy loss and transverse momentum broadening at nonzero v. We show that all higher moments scale characteristically with an effective temperature of the boosted plasma in the heavy quark rest frame, and we demonstrate that these non-Gaussian characteristics can be sizable in magnitude and even dominant in physically relevant situations. We use these results to derive a Kolmogorov equation for the evolution of the probability distribution for the total momentum of a heavy quark that propagates through strongly coupled plasma. This evolution equation accounts for all higher order correlations between transverse momentum broadening and longitudinal energy loss, which we have calculated from first principles. It reduces to a Fokker-Planck equation when truncated to only include the effects of η D , κ T and κ L . Remarkably, while heavy quarks do not reach kinetic equilibrium with the plasma if evolved with this Fokker-Planck equation, by showing that the Boltzmann distribution is a static solution of the all-order Kolmogorov equation that we have derived we demonstrate that heavy quarks do reach kinetic equilibrium if evolved with this equation. Our results thus provide a dynamically complete framework for understanding the thermalization of a heavy quark that may be initially far from equilibrium in the strongly coupled N = 4 SYM plasma — as well as new insight into heavy quark transport and equilibration in quark-gluon plasma.

Holography and Hydrodynamics↗
DOE OSTI2025

Comparing Intrinsic Catalytic Activity and Practical Performance of Ni- and Pt-Based Alkaline Anion Exchange Membrane Water Electrolyzer Cathodes

The stringent cost and performance requirements of renewable hydrogen production systems dictate that electrolyzers benefit from the use of nonprecious catalysts only if they deliver the same level of activity and durability as their precious metal counterparts. Here we report on recent work to understand interrelationships between the intrinsic activity of Ni- and Pt-based electrolyzer cathode catalysts and their performance in zero-gap alkaline water electrolyzer assemblies. Our results suggest that nanoparticulate Ni–Mo exhibits HER activity that is roughly 10-fold lower than Pt–Ru on the basis of turnover frequency under low (≤100 mV) polarization conditions. We further found that the HER activity of Ni–Mo/C cathodes is inhibited by aryl piperidinium anionexchange ionomers bearing bicarbonate counter-anions. After addressing this poisoning effect, we produced electrolyzer assemblies based on Ni–Mo/C cathodes that delivered indistinguishable current density vs cell potential relationships compared to otherwise identical assemblies with Pt–Ru cathodes. This result indicates that the contribution of the cathode to the total cell polarization is small, even for the less active Ni–Mo/C catalyst, and further implies that Pt-based cathodes can indeed be replaced by nonprecious alternatives with no loss in performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Primordial black holes and their mass spectra: The effects of mergers and accretion within stasis cosmologies

A variety of processes in the very early Universe can give rise to a population of primordial black holes (PBHs) with an extended mass spectrum. For certain mass spectra of this sort, it has been shown that the evaporation of these PBHs into radiation can drive the universe toward an epoch of cosmological stasis which can persist for a significant number of 𝑒-folds of cosmological expansion. However, in general, the initial mass spectrum which characterizes a population of PBHs at the time of production can subsequently be distorted by processes such as mergers and accretion. Here, in this paper, we examine the effects that these processes have on the spectra that lead to a PBH-induced stasis. Within such stasis models, we find that mergers have only a negligible effect on these spectra within the regime of interest for stasis. We likewise find that the effect of accretion is negligible in many cases of interest. However, we find that the effect of accretion on the PBH mass spectrum is non-negligible in situations in which this spectrum is particularly broad. In such situations, the stasis epoch is abridged or, in extreme cases, does not occur at all. Thus accretion plays a nontrivial role in constraining the emergence of stasis within scenarios which lead to extended PBH mass spectra.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantum Tensor-Product Decomposition from Choi-State Tomography

The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt or tensor-product decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the operator level are harder to extract in the quantum computational framework because of the exponential nature of sample complexity. Here, we present an algorithm for unbalanced partitions into a small subsystem and a large one (the environment) to compute the tensor-product decomposition of a unitary the effect of which on the small subsystem is captured in classical memory, while the effect on the environment is accessible as a quantum resource. This quantum algorithm may be used to make predictions about operator nonlocality and effective open quantum dynamics on a subsystem, as well as for finding low-rank approximations and low-depth compilations of quantum circuit unitaries. We demonstrate the method and its applications on a time-evolution unitary of an isotropic Heisenberg model in two dimensions. Published by the American Physical Society 2024

Mansuroglu, Refik (ORCID:000000017352513X)↗
DOE OSTI2025

Do We Know How to Model Reionization?

I compare the power spectra of the radiation fields from two recent sets of fully-coupled simulations that model cosmic reionization: “Cosmic Reionization On Computers” (CROC) and “Thesan”. While both simulations have similar power spectra of the radiation sources, the power spectra of the photoionization rate are significantly different at the same values of cosmic time or the same values of the mean neutral hydrogen fraction. However, the power spectra of the photoionization rate can be matched at large scales for the two simulations when the matching snapshots are allowed to vary independently. I.e., on large scales, the clustering of the radiation field in two simulations evolves similarly, but the exact timing of this evolution is different in different simulations and is not parameterized by an easily interpretable physical quantity like the mean neutral fraction or the mean free path. On small scales, large differences are present and remain partially unexplained. Both CROC and Thesan use the Variable Eddington Tensor approximation for modeling radiative transfer, but adopt different closure relations (optically thin OTVET versus M1). The role of this key difference is tested by using smaller simulations with a new cosmological simulation code that implements both closure relations in a controlled environment (the same hydro, cooling, and gravity solvers and the star formation recipe). In these controlled tests, both the M1 closure and the OTVET ansatz follow the expected behavior from a simple analytical approximation, demonstrating that the differences in the 2-point function of the radiation field induced by the choice of the Eddington tensor are not dominant.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗
DOE OSTI2024

A performant energy-conserving particle reweighting method for Particle-in-Cell simulations

A new particle-based reweighting method is developed and demonstrated in the Aleph Particle-in-Cell with Direct Simulation Monte Carlo (PIC-DSMC) program. Novel splitting and merging algorithms ensure that modified particles maintain physically consistent positions and velocities. This method allows a single reweighting simulation to efficiently model plasma evolution over orders of magnitude variation in density, while accurately preserving energy distribution functions (EDFs). Demonstrations on electrostatic sheath and collisional rate dynamics show that reweighting simulations achieve accuracy comparable to fixed weight simulations with substantial computational time savings. This highly performant reweighting method is recommended for modeling plasma applications that require accurate resolution of EDFs or exhibit significant density variations in time or space.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

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

Hydrogenation of Covalent Organic Framework Induces Conjugated π Bonds and Electronic Topological Transition to Enhance Hydrogen Evolution Catalysis

Recently, many topological materials have been discovered as promising electrocatalysts in chemical conversion processes and energy storage. However, it remains unclear how the topological electronic states specifically modulate the catalytic reaction. Here, the two-dimensional metal phthalocyanine-based covalent organic framework (MP c -COF) is studied by ab initio thermodynamic calculations to clearly reveal the promotional effect on the electrochemical hydrogen evolution reaction (HER) induced by topological gapless bands (TGBs). We find that the prehydrogenated (and fluorinated) H 4 CdPc-COF(F) shows the best HER performance, with 0.016 V (near zero) overpotential. By tracking changes to the electronic structure and free energy as the prehydrogenation and HER processes occur, we are able to separately attribute the high HER efficiency in part due to the increase of the electron bath by donating electrons to the conjugated π bonds and also to the existence of TGBs. Specifically, the significant catalytic promotion by TGBs is proven to decrease the free energy by 0.218 eV to near zero. When the TGBs are destroyed, e.g., by replacing N with P and opening a band gap, the HER efficiency is reduced. As a result, this study opens avenues for deterministically harnessing topological band features to improve electrocatalysis.

25 ENERGY STORAGE↗
DOE OSTI2026

Modeling The Nucleosynthetic Imprint of Stellar Merger Phenomena - Final Technical Report

This DOE CAREER project developed a comprehensive, multi-physics framework for modeling stellar mergers and their observable consequences. The work successfully integrated analytical models, three-dimensional hydrodynamic simulations, stellar evolution calculations, nucleosynthesis, and radiation transport into a unified pipeline. Key scientific advances include demonstrating stellar mergers as a unifying explanation for systems such as Betelgeuse and R Coronae Borealis stars, quantifying merger-driven chemical signatures, and establishing the connection between merger physics and circumstellar environments. A major outcome of the project is the development of SuperLite, an open-source Monte Carlo radiation transport code that enables the generation of synthetic spectra for astrophysical transients. This work bridges dynamical, thermal, and radiative timescales and provides a powerful, DOE-relevant computational framework for interpreting observations of supernovae and related transient phenomena, while also contributing to workforce development through the training of postdoctoral researchers and graduate students.

Chatzopoulos, Emmanouil [Louisiana State Universit↗
DOE OSTI2025

Oxygen Evolution on Mechanically Strained TiO2/NiTi: Implications of Compositional Heterogeneity at (Photo)Electrocatalytic Interfaces

The adsorption and activation energetics underpinning small molecule conversion on heterogeneous (photo)electrocatalysts are intrinsically tied to catalyst surface properties. Absent compositional characterization techniques with sufficient interface sensitivity, however, (photo)electrochemical performance can be misinterpreted in the context of bulk or near-surface material properties. Here we provide a fundamental investigation of the convoluting role of near-surface compositional heterogeneity in the interpretation of (photo)electrochemical alkaline oxygen evolution reaction (OER) activity, highlighting challenges in correlating composition measured by surface- and near-surface-sensitive probes. TiO2 thin films grown by air-annealing the superelastic alloy Nitinol (TiO2/NiTi) crack under tensile mechanical strain, increasing the number of electrochemically active Ni sites (Ni site density) that are probed via voltammetric features corresponding to Ni3+/Ni2+ redox events. (Photo)electrochemical OER kinetics trend with Ni site density, with overpotentials and Tafel slopes decreasing for Ni site densities < 1013 Ni/cm2geo and asymptotically approaching the performance of the base NiTi substrate for Ni site densities > 1013 Ni/cm2geo. Photoelectrochemical fill factors follow similar Ni site density dependent trends. When probing unstrained TiO2/NiTi, Ni site densities are two orders of magnitude higher when comparing near-surface-sensitive techniques (e.g., X-ray photoelectron spectroscopy (XPS), time of flight secondary ion mass spectrometry (TOF-SIMS), and scanning transmission electron microscopy-energy dispersive X-ray spectroscopy (STEM-EDS)) to surface-sensitive electrochemical measurements. This result highlights the challenge of correlating kinetic performance with intrinsic surface properties of electrochemical interfaces in the presence of near-surface compositional heterogeneity. Further, it reinforces the importance of fundamental investigations of surfaces with well-controlled composition and structure and the need for physically grounded and self-consistent interpretation of multiple near-surface characterization techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Particle‐In‐Cell Simulations of Starfish Prime

The Starfish Prime high altitude nuclear test created a transient diamagnetic cavity in the Earth's magnetic field above Johnston Island and launched an electromagnetic pulse (EMP) that was detected around the globe. For this work, we use the ion‐kinetic particle‐in‐cell code Topanga to simulate diamagnetic cavity evolution and the E3 EMP signal for Starfish Prime out to over a minute of physical time. The simulation domain has a longitudinal and latitudinal extent of 60° X 60° and a vertical extent of 2,000 km from the surface of the Earth. We compare our simulated results to magnetometer measurements taken in space and on the ground, finding good agreement in both cases. The diamagnetic cavity in the simulation forms in about a second, while the associated debris flux tube takes approximately 30 s to decay. The debris flux tube undergoes significant motion during this timeframe, rising upward. The measured E3 EMP signal on the ground consists of several components, all of which are present in our simulations. We discuss the physical origin of these components in relation to E3a (blast) and E3b (heave).

Belyaev, Mikhail A. [Lawrence Livermore National L↗
DOE OSTI2025

Validation of Fast Reactor Depletion Tools Using EBR-II Measured Data

The validation of simulation tools for calculating fuel depletion and evolution in fast reactors is vital for design, licensing, deployment, operations, and material accountancy. The Physics Analysis Database (PADB) and Analytical Laboratory (AL) database contain measured data collected from Experimental Breeder Reactor II (EBR-II) and were used to validate the most recent versions of the Argonne Reactor Computation (ARC) tool suite and ORIGEN-S for calculating isotopic compositions in irradiated fast reactor fuel. The PADB contains important modeling and operational information about the EBR-II core design, fuel cycle, and analytical results from the legacy versions of the ARC tool suite. The AL database contains the measured isotopic compositions of irradiated samples taken from core subassemblies. A new procedure was developed for the ARC tool suite to perform the EBR-II depletion simulation, as well as to perform more detailed isotopic calculations using ORIGEN-S calculations by coupling it with the ARC suite. Both the ARC and ARC-ORIGEN results were compared with the AL measured data for all relevant samples and showed good agreement for the major actinides. Good agreement with measured data was also achieved using the ARC-ORIGEN approach for several fission products.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Neutrino many-body flavor evolution: The full Hamiltonian

We study neutrino flavor evolution in the quantum many-body approach using the full neutrino-neutrino Hamiltonian, including the usually neglected terms that mediate nonforward scattering processes. Working in the occupation number representation with plane waves as single-particle states, we explore the time evolution of simple initial states with up to N = 10 neutrinos. We discuss the time evolution of the Loschmidt echo, one body flavor and kinetic observables, and the one-body entanglement entropy. For the small systems considered, we observe “thermalization” of both flavor and momentum degrees of freedom on comparable time scales, with results converging towards expectation values computed within a microcanonical ensemble. We also observe that the inclusion of nonforward processes generates a faster flavor evolution compared to the one induced by the truncated (forward) Hamiltonian. Published by the American Physical Society 2024

Cirigliano, Vincenzo (ORCID:000000029056754X)↗
DOE OSTI2025

Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization using Dynamic Evolutionary Systems or NODES. We apply this approach to real-time combustion engine control and develop an engine-specific hardware platform for NODES called FireBox. We demonstrate how the real-time evolution approach works in simulation and the performance of networks trained in simulation on the physical engine.

Maldonado Puente, Bryan [ORNL] (ORCID:000000033880↗
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗