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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward the Observation of Dimagnesocene

We have examined the electronic structure of C 5 H 5 MgMgC 5 H 5 , or dimagnesocene, using high-level coupled-cluster techniques. This research is suitable in light of the remarkable synthesis of the valence-isoelectronic diberyllocene by Boronski, Crumpton, Wales, and Aldridge. The Mg–Mg bond distance is predicted to be 2.758 Å, and the Mg–Mg bond dissociation energy is predicted to be 51.8 kcal/mol. Unique aspects to the present research is our characterization of the ionization energy and the electron affinity of this molecule, the energy of dissociation into two neutral cyclopentadienyl magnesium radicals, the determination of the neutral structure at the CCSD(T)/cc-pVTZ level, and the computation of the Raman intensities at the MP2/cc-pVDZ level. Apart from mass spectroscopy, the simplest means of experimental detection is gas-phase or matrix-isolated infrared spectroscopy, in which the A 2 ″ peak at 801 cm –1 should be the most prominent, with an intensity of 581 km/mol.

bond cleavage↗
DOE OSTI2024

Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters

Introduction (120 words): Transport of metal ions across the aqueous-organic phase boundary is an essential step in a hydrometallurgical nuclear fuel reprocessing strategy. The study of transport agents for nuclear fuel elements is imperative to guide the design of ligands that boost the separation efficiency of the recovery process from fission products. However, limited studies have been made on the chemistry of these transport agents when complexing with transuranic elements in gas-phase where all surrounding factors are essentially excluded. This work investigates the reagent ligand complexations to transuranic and other metals and their dissociations in the gas phase. Comparisons are made between 4f and 5f elements and between ligands. Methods (120 words): (N,N-diisobutylcarbamoylmethyl)phenyloctylphosphine oxide (CMPO) and N,N,N',N'-tetraoctyldiglycolamide (TODGA) have been selected to complex with metal nitrates. The actinide americium and lanthanides neodymium, samarium, and europium were investigated as part of this work. The lanthanides were selected to act as size and electron configuration analogues of the minor actinides. Metal complexes with two ligands and two nitrates ([M(NO3)2(CMPO)2]+, for example) are studied in Bruker micrOTOF-Q II mass spectrometer equipped with collision-induced dissociation capability. The comparisons of the mass spectra are made in groups of homogenous ligands and mixed TODGA-CMPO ligands clusters. Comparisons are also made based on the complexed metals (Am and lanthanides). Preliminary data (300 words): Collision-induced dissociation mass spectrometry data are collected on two ligands complexed with metal nitrates where the two ligands are homogenous, with (CMPO)2 or (TODGA)2, or heterogeneous, with (TODGA)(CMPO). Several fragmentation patterns are observed among complexes with the CMPO ligand whereas the TODGA ligand commonly dissociates intact from the complex. Most of the metal complexes exhibit similar fragmentation patterns, but there are a few notable deviations in fragmentation patterns between the Am and Ln-bearing complexes. For the [M(CMPO)2(NO3)2]+ complexes, the initial loss of nitrate in the form of nitric acid is observed in all four complexes. However, [Am(CMPO)2(NO3)2]+ exhibits an additional fragmentation not found in the lanthanide complexes. Also, a significantly different ratio of the second nitric acid loss is found in the Am complex. These deviations may indicate the different interaction behaviors between actinides and lanthanides. The [M(TODGA)2(NO3)2]+ complexes exhibit the fragmentation as the loss of one TODGA ligand as an intact form and the loss of nitrate as nitric acid. The Am complex exhibits an additional fragmentation after losing the TOGDA ligand, which is not observed among the Ln complexes. The heterogeneous [M(TODGA)(CMPO)(NO3)2]+ complexes exhibit both similarities and differences between the Am and Ln complexes. For example, the heterogenous Am complex does not exhibit the loss of an intact TODGA ligand while all three Ln complexes do. This indicates that TODGA may bind more strongly to Am than Ln. Additionally, the intensity of the loss of CMPO ligand (as partially or whole) is found to be significantly larger than that of the loss of TODGA (as partially of whole) indicating that TODGA is bound to the metal significantly stronger than CMPO. Planned computational analysis will help understand the deviation in fragmentation behaviors between americium and lanthanide metal centers, or between TODGA and CMPO ligands. Novel aspect (20 words): Gas-phase actinide and lanthanide complex formation and fragmentation provide insight into the coordination environment differences of f-element metals.

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

Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters

Title (20 word): Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters Introduction (120 words): Transport of metal ions across the aqueous-organic phase boundary is an essential step in a hydrometallurgical nuclear fuel reprocessing strategy. The study of transport agents for nuclear fuel elements is imperative to guide the design of ligands that boost the separation efficiency of the recovery process from fission products. However, limited studies have been made on the chemistry of these transport agents when complexing with transuranic elements in gas-phase where all surrounding factors are essentially excluded. This work investigates the reagent ligand complexations to transuranic and other metals and their dissociations in the gas phase. Comparisons are made between 4f and 5f elements and between ligands. Methods (120 words): (N,N-diisobutylcarbamoylmethyl)phenyloctylphosphine oxide (CMPO) and N,N,N',N'-tetraoctyldiglycolamide (TODGA) have been selected to complex with metal nitrates. The actinide americium and lanthanides neodymium, samarium, and europium were investigated as part of this work. The lanthanides were selected to act as size and electron configuration analogues of the minor actinides. Metal complexes with two ligands and two nitrates ([M(NO3)2(CMPO)2]+, for example) are studied in Bruker micrOTOF-Q II mass spectrometer equipped with collision-induced dissociation capability. The comparisons of the mass spectra are made in groups of homogenous ligands and mixed TODGA-CMPO ligands clusters. Comparisons are also made based on the complexed metals (Am and lanthanides). Preliminary data (300 words): Collision-induced dissociation mass spectrometry data are collected on two ligands complexed with metal nitrates where the two ligands are homogenous, with (CMPO)2 or (TODGA)2, or heterogeneous, with (TODGA)(CMPO). Several fragmentation patterns are observed among complexes with the CMPO ligand whereas the TODGA ligand commonly dissociates intact from the complex. Most of the metal complexes exhibit similar fragmentation patterns, but there are a few notable deviations in fragmentation patterns between the Am and Ln-bearing complexes. For the [M(CMPO)2(NO3)2]+ complexes, the initial loss of nitrate in the form of nitric acid is observed in all four complexes. However, [Am(CMPO)2(NO3)2]+ exhibits an additional fragmentation not found in the lanthanide complexes. Also, a significantly different ratio of the second nitric acid loss is found in the Am complex. These deviations may indicate the different interaction behaviors between actinides and lanthanides. The [M(TODGA)2(NO3)2]+ complexes exhibit the fragmentation as the loss of one TODGA ligand as an intact form and the loss of nitrate as nitric acid. The Am complex exhibits an additional fragmentation after losing the TOGDA ligand, which is not observed among the Ln complexes. The heterogeneous [M(TODGA)(CMPO)(NO3)2]+ complexes exhibit both similarities and differences between the Am and Ln complexes. For example, the heterogenous Am complex does not exhibit the loss of an intact TODGA ligand while all three Ln complexes do. This indicates that TODGA may bind more strongly to Am than Ln. Additionally, the intensity of the loss of CMPO ligand (as partially or whole) is found to be significantly larger than that of the loss of TODGA (as partially of whole) indicating that TODGA is bound to the metal significantly stronger than CMPO. Planned computational analysis will help understand the deviation in fragmentation behaviors between americium and lanthanide metal centers, or between TODGA and CMPO ligands. Novel aspect (20 words): Gas-phase actinide and lanthanide complex formation and fragmentation provide insight into the coordination environment differences of f-element metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2025

The hierarchical growth of bright central galaxies and intracluster light as traced by the magnitude gap

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range 0.20 < z < 0.60, we characterize the hierarchical assembly of bright central galaxies (BCGs) and the surrounding intracluster light (ICL). To quantify hierarchical formation we use the stellar mass–halo mass (SMHM) relation, comparing the halo mass, estimated via the mass–richness relation, to the stellar mass within the BCG + ICL system. Moreover, we incorporate the magnitude gap (M14), the difference in brightness between the BCG (measured within 30 kpc) and fourth brightest cluster member galaxy within 0.5 $R_{200,c}$, as a third parameter in this linear relation. The inclusion of M14, which traces BCG hierarchical growth, increases the slope and decreases the intrinsic scatter, highlighting that it is a latent variable within the BCG + ICL SMHM relation. Moreover, the correlation with M14 decreases at large radii. However, the stellar light within the BCG + ICL transition region (30 –80 kpc) most strongly correlates with halo mass and has a statistically significant correlation with M14. Since the transition region and M14 are independent measurements, the transition region may grow due to the BCG’s hierarchical formation. Additionally, as M14 and ICL result from hierarchical growth, we use a stacked sample and find that clusters with large M14 values are characterized by larger ICL and BCG + ICL fractions, which illustrates that the merger processes that build the BCG stellar mass also grow the ICL. Furthermore, this may suggest that M14 combined with the ICL fraction can identify dynamically relaxed clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Symbolic diagnostics to interpret and analyze neural network models

Embedded machine-learned models (EMLMs) have the promise to improve the predictive accuracy of engineering simulators in environments of national interest. EMLMs often comprise complex input-output maps (e.g., neural networks), which make them unamenable to rigorous analysis and generally difficult to interpret. In the face of decades of theory, this lack of interpretability is a significant barrier to building confidence in these models. This work outlines an approach to interpret EMLMs using sparse polynomial regression for comparison with theoretical understanding. To do so, we build on the concept of Locally Interpretable Model-agnostic Explanations (LIME) using physics-informed clustering, prototype selection, and library construction. While general, we demonstrate our method on tensor-basis neural networks used in Reynolds-Averaged Navier-Stokes simulations of hypersonic fluid flows. Results are presented for a simulated toy model and for direct numerical simulations (DNS) of turbulent flows over a flat plate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Prong Segmentation using Point Set Transformers in Multiple View Neutrino Detectors

NOvA is a long-baseline neutrino experiment studying neutrino oscillations by detecting neutrinos from the NuMI beam at Fermilab. Its physics analysis relies on accurate prong segmentation, which involves matching each hit to its source particle and identifying the particle type. This task has commonly been addressed using a combination of traditional clustering algorithms and convolutional neural networks (CNNs). However, NOvA’s detector design presents data as two sparse and decoupled 2D images (XZ and YZ views) rather than a native 3D representation, posing a significant challenge for traditional CNN-based models. In this talk, we propose a novel neural network based on the Point Set Transformer. By treating detector hits as sparse point clouds and implementing a cross-view attention mechanism, our model enables efficient information mixing between both views. Evaluated on NOvA simulated data, our model achieves superior accuracy while requiring significantly fewer computational resources compared to other models. Furthermore, the model demonstrates great performance when applied to Liquid Argon Time Projection Chamber (LArTPC) data, which shows its potential as a universal prong segmentation algorithm for multiple view neutrino detectors.

Liu, Jiaxi [UC, Irvine]↗
DOE OSTI2024

High-Entropy Metal-Organic Frameworks (HEMOFs): A New Frontier in Materials Design for CO 2 Utilization

High-entropy materials (HEMs) emerged as promising candidates for a diverse array of chemical transformations, including CO 2 utilization. However, traditional HEMs catalysts are nonporous, limiting their activity to surface sites. Designing HEMs with intrinsic porosity can open the door toward enhanced reactivity while maintaining the many benefits of high configurational entropy. Here, in this study, a synergistic experimental, analytical, and theoretical approach to design the first high-entropy metal-organic frameworks (HEMOFs) derived from polynuclear metal clusters is implemented, a novel class of porous HEMs that is highly active for CO 2 fixation under mild conditions and short reaction times, outperforming existing heterogeneous catalysts. HEMOFs with up to 15 distinct metals are synthesized (the highest number of metals ever incorporated into a single MOF) and, for the first time, homogenous metal mixing within individual clusters is directly observed via high-resolution scanning transmission electron microscopy. Importantly, density functional theory studies provide unprecedented insight into the electronic structures of HEMOFs, demonstrating that the density of states in heterometallic clusters is highly sensitive to metal composition. This work dramatically advances HEMOF materials design, paving the way for further exploration of HEMs and offers new avenues for the development of multifunctional materials with tailored properties for a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Extending GPU-accelerated Gaussian integrals in the TeraChem software package to f type orbitals: Implementation and applications

Here, the increasing availability of graphics processing units (GPUs) for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. However, the complexity of integral kernels for high angular momentum basis functions often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report the implementation of f function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH 3 ) with complete active space self-consistent field are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules.

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

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2025

Exploring Geothermal Potential of Great Basin Sub-Regions

The INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project aims to discover new, economically viable hidden geothermal systems in the Great Basin region by building on previous work in play fairway analysis and machine learning. A key objective of this project is to develop an exploration workflow to reduce geothermal exploration risks for hidden geothermal systems. A single preliminary play fairway workflow was developed from the assessment of the regional INGENIOUS geological, geophysical, and geochemical datasets. This workflow provided new preliminary predictive geothermal fairway maps for the INGENIOUS study area, which encompasses most of Nevada, western Utah, southern Idaho, southeastern Oregon, and easternmost California. However, a recent study (incorporating machine learning techniques) of a portion of Nevada identified four geologic domains and determined that the relative importance of individual datasets or features as indicators of geothermal potential may differ across these domains. The INGENIOUS study area includes a much larger and more geologically diverse region; therefore, additional geologic domains or sub-regions are expected. To assess the sub-regions in the INGENIOUS study area, principal component analysis and k-means clustering were applied. Preliminary results indicate that the INGENIOUS regional data cluster into groups that relate to different geologic domains in the Great Basin region. These include domains such as the Walker Lane, extensional western Great Basin region, broad lower strain region in the eastern Great Basin of western Utah and eastern Nevada, Quaternary volcanic fields, and the area adjacent to the Snake River Plain. These clusters are assessed to determine the key geologic drivers of the identified clusters. Understanding this variability can provide key insights for the exploration and characterization of hidden geothermal systems in the Great Basin region and could indicate the need to develop multiple geothermal conceptual models and play fairway workflows for the INGENIOUS study area.

exploration↗
DOE OSTI2026

CoLoRe-2LPT: Lyman-$α$ mock catalogues for the validation of DESI cosmological analyses

The Lyman-$α$ (Ly$α$) forest has become a crucial probe for studying the large-scale structure of the universe at high redshift ($z > 2$), providing powerful constraints on Baryon Acoustic Oscillations (BAO) and the full-shape (FS) clustering of matter. As a key ingredient for upcoming BAO and FS analyses, we present a new generation of fast cosmological Ly$α$ mocks based on second-order Lagrangian perturbation theory (2LPT). These new mocks significantly improve upon previous log-normal approaches, both at accurately capturing small scale clustering and at recovering the non-linear broadening of the BAO peak. They are able to reproduce Ly$α$ statistics within $10\%$ of the latest DESI measurement; including the Ly$α$ bias and the redshift-space distortion $β$ parameter, mean transmitted flux, and 1D power spectrum. The corresponding quasar (QSO) clustering is also improved with respect to previous approaches, calibrated against high-resolution Abacus simulations, recovering the observational QSO linear bias to less than $5\%$ and improving redshift-space distortions via 2LPT velocities and the addition of Fingers-of-God effects. Furthermore, these mocks incorporate high column density systems and metal lines, allowing us to explore the effects and systematics induced by these astrophysical contaminants. This new set of mocks has been key for enhancing the modeling and validation of the DESI DR2 Ly$α$ full shape cosmological analysis. This work provides a physically motivated and computationally efficient tool for simulating current and next-generation Ly$α$ surveys and validating FS and BAO analysis.

Bernal, M.F. Ruiz-Herrera [Madrid, CIEMAT] (ORCID:↗
DOE OSTI2026

DTLMod: A simulation framework for in situ workflow optimization

In situ processing workflows have become essential for coping with the explosion in data volume and velocity in large-scale scientific computing, providing domain scientists with early insights at runtime. Multiple frameworks implement this paradigm through a data transport layer (DTL), offering different data access modes and deployment schemes, but researchers currently lack the appropriate tools to assess design and deployment options before committing to costly real experiments. We introduce DTLMod, an open-source simulated DTL that enables performance evaluation of in situ workflow configurations at scale. Built on SimGrid, it links into any SimGrid-based simulator and is available in C++ and Python. We evaluate DTLMod along four axes: scalability (tens of thousands of simulated processes across interconnected clusters in seconds, with linear memory scaling), versatility (three implementation variants trading fidelity for speed), accuracy (simulated times faithfully reflecting real behavior), and practical utility (two use cases demonstrating evidence-based workflow design decisions).

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2026

Transfer Learning Meets Embedded Correlated Wavefunction Theory for Chemically Accurate Molecular Simulations: Application to Calcium Carbonate Ion Pairing

Achieving chemical accuracy for molecular simulations remains a central challenge in computational chemistry. Here, we present an embedded correlated wavefunction transfer learning (ECW-TL) framework for accurately simulating molecular dynamics in the condensed phase. ECW-TL incorporates high-level electron exchange and correlation effects in ECW theory while preserving the training and computational efficiency of machine-learned interatomic potentials. We demonstrate the framework on Ca 2+ –CO 3 2– ion pairing in aqueous solution, a key process underlying CO 2 mineralization in seawater. As proof of principle, we first show that fine-tuning a DFT-revPBE-D3(BJ) baseline model with embedded-DFT-SCAN data reproduces the DFT-SCAN free-energy surface within 1 kcal/mol across all solvation states. Extending the framework to embedded MP2 and localized natural-orbital CCSD(T) further refines the free-energy profile, revealing the crucial role of exact electron exchange and correlation in determining ion-pair stability and structure. The computed ion-pair association free energy is in quantitative agreement with experimental measurements, further validating the accuracy of the ECW-TL framework. ECW-TL thus provides a general, data-efficient route for transferring CW accuracy to efficient simulations of complex aqueous and interfacial chemical processes.

cluster chemistry↗
DOE OSTI2025

The dynamical state of eROSITA clusters and its impact on the brightest cluster galaxy luminosity

The first Spectrum-Roentgen-Gamma (SRG) eROSITA public release contains 12 247 clusters and groups from its first 6 months of operation. We used the offset between the brightest cluster galaxy (BCG) and the X-ray peak ( D BCG − X ) to classify the cluster dynamical state of 3946 galaxy clusters and groups. We aim to investigate the evolution of the merger and relaxed cluster distributions with redshift and mass, and the distributions’ impact on the BCG. We used the X-ray peak from the eROSITA survey and the BCG position from the LS DR10 optical data, which includes the DECam eROSITA Survey optical data, to measure the D BCG − X offset. We modelled the distribution of D BCG − X , in units of R 500 , as the sum of two Rayleigh distributions representing the cluster’s relaxed and disturbed populations, and explored their evolution with redshift and mass. To explore the impact of the cluster’s dynamical state on the BCG luminosity, we separated the main sample according to the dynamical state. We defined clusters as relaxed if D BCG − X < 0.25R500, disturbed if D BCG − X > 0.5R500, and ‘diverse’ if 0.25R500 < D BCG − X < 0.5R500. We find no evolution of the merging fraction with redshift or mass. The width of the relaxed distribution increases with redshift, while the width of the two Rayleigh distributions decreases with mass. The analysis reveals that BCGs in relaxed clusters are brighter than BCGs in both the disturbed and diverse cluster populations. The most significant differences are found for high-mass clusters at higher redshifts. The results suggest that BCGs in low-mass clusters are less centrally bound than those in high-mass systems, irrespective of the dynamical state. Over time, BCGs in relaxed clusters progressively align with the potential centre. This alignment correlates with their luminosity growth relative to BCGs in dynamically disturbed clusters, underscoring the critical role of the cluster’s dynamical state in regulating BCG evolution.

galaxy clusters↗
DOE OSTI2024

Shape effects on the local dynamics of suspensions of spheroidal particles

The effect of shape on the dynamics of suspensions of non-spherical heavy particles is examined by fully resolved numerical simulations of oblate and prolate spheroids, as well as spheres, for a density ratio of ten, volume fractions ranging from 0.5% to 5%, and Reynolds numbers between 20 and 30. The dynamics is determined both by the interactions of the particles with the fluid as well as by collisions, with the number and importance of collisions increasing with volume fractions. A single isolated oblate or prolate spheroid falling under gravity generally falls broadside on, for the governing parameters examined here, and at low-volume fractions, the majority of particles in a suspension fall that way. At higher-volume fractions, the orientation is more random. The slip velocity decreases as the volume fraction increases for all shapes, as expected, but the effect of the shape is much less than seen for a single particle. Furthermore, this seems to be due to two effects. For all volume fractions, the most deformed particles cluster more than spheres and less deformed particles, which increases their slip velocity. As the concentration increases, the increased particle interactions also causes more particles to fall short side-on, which reduces the frontal area and the resulting drag, increasing the slip velocity. This second effect is, of course, absent for spherical particles.

42 ENGINEERING↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2025

Defect Generation and Evolution in Irradiated Epitaxial Films and Heterostructures of Fe 3 O 4 and Cr 2 O 3

Abstract The functionality of nuclear structural materials, sensors, and microelectronics in harsh environments such as radiation relies on understanding defect generation and evolution processes in oxide layers. The initial radiation response of epitaxial thin films of Fe 3 O 4 (111), Cr 2 O 3 (0001), and Fe 3 O 4 (111)/Cr 2 O 3 (0001) heterostructures deposited on Al 2 O 3 (0001) by oxygen‐assisted molecular beam epitaxy and irradiated with 200 keV He + is characterized. X‐ray diffraction and X‐ray absorption near edge spectroscopy showed that the Cr 2 O 3 layers underwent significant lattice expansion and disordering under irradiation, whereas the Fe 3 O 4 layers do not exhibit noticeable changes. In contrast, positron annihilation spectroscopy revealed an evolution of cation vacancy point defects in the Fe 3 O 4 layers into larger vacancy clusters with increasing irradiation, while the cation vacancies in Cr 2 O 3 remained primarily as single vacancies and small clusters. The results suggest that the Fe 3 O 4 lattice can utilize the free volume of the larger vacancy clusters to relax but the small vacancies in the Cr 2 O 3 lattice do not facilitate relaxation. Comparing defect concentrations in the single layer films versus the heterostructure suggests that point defects may cross the interface from Fe 3 O 4 into Cr 2 O 3 . Together, these results enhance the understanding of the initial defect evolution mechanisms in oxide layers in harsh irradiation environments.

36 MATERIALS SCIENCE↗