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At least 901 records · Page 50

Deployment and Evaluation of SciStream on OLCF's Advanced Computing Ecosystem (ACE)

The growing demand for real-time analysis, experimental steering, and decision-making in scientific workflows has created a need for tightly coupled integrations between experimental facilities and high-performance computing (HPC) systems. The Department of Energy’s Integrated Research Infrastructure (IRI) initiative highlights data streaming as a key capability for enabling memory-to-memory data transfers, bypassing the limitations of traditional store-and-forward models. SciStream is a toolkit developed by researchers at Argonne National Laboratory (ANL) to support such streaming by addressing cross-domain security, delegated authentication, and application transparency. We deployed and evaluated SciStream on the Oak Ridge Leadership Computing Facility’s (OLCF) Advanced Computing Ecosystem (ACE) infrastructure, leveraging the Olivine OpenShift cluster and its high-bandwidth Data Streaming Nodes (DSNs) as gateway nodes. Our evaluation included synthetic streaming workloads derived from IRI science workflows, a streaming simulator, and integration with RabbitMQ to handle low-level messaging. This report documents the deployment process, performance evaluation, and challenges encountered, along with opportunities for future improvements.

97 MATHEMATICS AND COMPUTING↗

Galaxy morphological classification in deep-wide surveys via unsupervised machine learning

ABSTRACT Galaxy morphology is a fundamental quantity, which is essential not only for the full spectrum of galaxy-evolution studies, but also for a plethora of science in observational cosmology (e.g. as a prior for photometric-redshift measurements and as contextual data for transient light-curve classifications). While a rich literature exists on morphological-classification techniques, the unprecedented data volumes, coupled, in some cases, with the short cadences of forthcoming ‘Big-Data’ surveys (e.g. from the LSST), present novel challenges for this field. Large data volumes make such data sets intractable for visual inspection (even via massively distributed platforms like Galaxy Zoo), while short cadences make it difficult to employ techniques like supervised machine learning, since it may be impractical to repeatedly produce training sets on short time-scales. Unsupervised machine learning, which does not require training sets, is ideally suited to the morphological analysis of new and forthcoming surveys. Here, we employ an algorithm that performs clustering of graph representations, in order to group image patches with similar visual properties and objects constructed from those patches, like galaxies. We implement the algorithm on the Hyper-Suprime-Cam Subaru-Strategic-Program Ultra-Deep survey, to autonomously reduce the galaxy population to a small number (160) of ‘morphological clusters’, populated by galaxies with similar morphologies, which are then benchmarked using visual inspection. The morphological classifications (which we release publicly) exhibit a high level of purity, and reproduce known trends in key galaxy properties as a function of morphological type at z < 1 (e.g. stellar-mass functions, rest-frame colours, and the position of galaxies on the star-formation main sequence). Our study demonstrates the power of unsupervised machine learning in performing accurate morphological analysis, which will become indispensable in this new era of deep-wide surveys.

Martin, G.↗

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiplex Detection of Multiple-Quantum/Single-Quantum NMR Correlation Spectra

High-ordered multiple-quantum coherences have been used to gauge the size of coupled networks of nuclear spins but are seldom used in modern high-resolution solid-state NMR spectroscopy due to the low resolution of earlier techniques. Herein, we extend this work to the third dimension by designing an MQ spin counting experiment with full chemical resolution of the nuclei involved in the coherences. The technique uses multiplex processing to simultaneously acquire MQ/1Q correlation 2D spectra, with all even-ordered values of M, in the same amount of time it would take to acquire the 2Q/1Q spectrum alone. Further, we apply this multiplexed MQ/1Q correlation method to probe site clustering on functionalized silica surfaces and find the first evidence of clusters involving three or more functionalities. When applied to a supported zirconium metallocene, the observation of a 6Q coherence between six cyclopentadienyl proton nuclei confirms the colocation of two cyclopentadienyl ligands on a single metal center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Mechanistic Fission Gas Release and Swelling Models for UN Fuels in BISON

This report describes the work in NEAMS (Nuclear Energy Advanced Modeling and Simulation) to develop a mechanistic fission gas model for uranium nitride fuels in BISON. The existing Sifgrs (Simple integrated fission gas release and swelling) model tracks the average properties of two bubble populations in the bulk and at the grain boundaries. It was recognized that dislocations play a crucial role in the fission gas swelling of UN, and an irradiation-induced dislocation density model was needed, as well as a model describing how fission gas interacts with dislocations creating a third population of bubbles along dislocations. A mechanistic model that tracks dislocation bubbles was implemented in Sifgrs. This model was used to simulate fission gas swelling and release in UN. Lower-length-scale calculations and experimental observations from carbide fuel were leveraged to help populate the model with essential parameters. As a placeholder, an empirical function was formulated for the evolution of the dislocation network. Because of the difference in evolution of this network at different temperatures, the dislocation bubbles are able to capture behavior that the bulk intragranular bubbles cannot. It was found that the bulk bubbles dominate microscopic swelling at low temperatures, and the dislocation bubbles dominate at higher temperatures. Based on this model, the transition between the two bubble types is the main factor behind the breakaway swelling phenomenon in UN. In order to test the model, a couple of assessments were run. For the lower temperature JOYO pins, the model produces reasonable fission gas release and swelling values. For the higher temperature SP1 pin, the model dramatically underestimates the fission gas release. This issue is attributed to the gas being trapped inside dislocation bubbles, unable to escape to grain boundaries to cause fission gas release, and could be remedied by a mechanistic dislocation model that allows the dislocation density to decrease at very high temperatures. A preliminary mechanistic dislocation model was developed supported by first-principle calculations. These calculations provided valuable insight into how interstitial defects cluster in UN in the {110} orientation, and may eventually form dislocation loops, leading to the conclusion that dislocation loops may nucleate from these clusters. An estimate of the dislocation line energy in UN was obtained and will be improved in future work. The free-energy cluster dynamics code Centipede was used to track interstitial and vacancy absorption at dislocation loops and calculate their growth. In addition, improvements to Centipede were made including new convergence criteria for transient simulations and sink driving force updates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NiAl–MoO 2 S 2 Nanoparticles: Structural Evolution and Mechanistic Insights into High-Performance Selenium Oxyanion Removal across Diverse pH Conditions

Advancing sorbent materials for the selective removal of toxic oxyanions from water requires synthetic control, tunable chemistry, and an atomic-level understanding of structure–function relationships. Here, we report the synthesis and detailed characterization of NiAl–MoO 2 S 2 , a novel layered double hydroxide (LDH) nanomaterial designed for the efficient sequestration of selenium oxoanions (SeO 3 2– and SeO 4 2– ) from complex aqueous environments. The material is synthesized through a room-temperature ion-exchange process, wherein interlayer NO 3 – anions in NiAl–LDH are replaced with MoO 2 S 2 2– clusters, forming high-surface-area, flower-like nanoparticles. Comprehensive structural analysis using the synchrotron X-ray pair distribution function, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy reveals a distinct chemical transformation of intercalated [MoO 2 S 2 ] 2– into [Mo 2 O 2 S 6 ] 2– -like clusters, generating redox-active interlayers that drive selenium capture. This tailored interfacial chemistry underpins the material’s exceptional sorption performance, achieving distribution coefficients (K d ) ≥ 10 6 mL/g and maximum capacities of 343 mg/g for SeO 4 2– and 514 mg/g for SeO 3 2– , outperforming state-of-the-art inorganic sorbents. Importantly, NiAl–MoO 2 S 2 maintains high selectivity and capacity across acidic, neutral, and alkaline pH, efficiently removing selenium from ppm to sub-10 ppb trace levels, even in the presence of competing ions typical of natural and industrial waters. The selenium uptake proceeds via reductive precipitation coupled with the oxidation of molybdenum and sulfide within the LDH framework. This study highlights the power of strategic synthetic modification and interlayer functionalization in LDHs to unlock new structural motifs and redox chemistries, offering a scalable route to advanced materials for environmental remediation.

Adsorption↗

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗

Coupling between bulk thermal defects and surface segregation dynamics

Surface segregation is a phenomenon that depends on the delicate interplay between thermodynamic driving forces and kinetic obstacles, for which elevated temperature is often needed to enhance the atom mobility and reach equilibrium. Using the classic system of Cu 3 Au ( 100 ) under nonisothermal conditions, in this study, we show an adatom process underlying transient surface segregation dynamics through the temperature-change-driven creation and annihilation of thermal vacancies in the bulk and the resulting bulk-surface mass exchanges. This is demonstrated by monitoring the surface composition evolution of Cu 3 Au ( 100 ) with temperature changes between 250 and 500 ° C , showing that the increase in temperature decreases monotonically the surface Au concentration as a result of the transfer of more Cu than Au from the bulk to the surface to form Cu-rich clusters of adatoms. Such a bulk thermal defect effect is expected to be universal in inducing the disparity in the bulk-surface mass exchanges of dissimilar atoms in multicomponent materials because of the inherent differences in the vacancy formation energies of the constituent atoms.

36 MATERIALS SCIENCE↗

Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions

Abstract We computationally explore the relationship between surface–subsurface exchange and hydrological response in a headwater-dominated high elevation, mountainous catchment in East River Watershed, Colorado, USA. In order to isolate the effect of surface–subsurface exchange on the hydrological response, we compare three model variations that differ only in soil permeability. Traditional methods of hydrograph analysis that have been developed for headwater catchments may fail to properly characterize catchments, where catchment response is tightly coupled to headwater inflow. Analyzing the spatially distributed hydrological response of such catchments gives additional information on the catchment functioning. Thus, we compute hydrographs, hydrological indices, and spatio-temporal distributions of hydrological variables. The indices and distributions are then linked to the hydrograph at the outlet of the catchment. Our results show that changes in the surface–subsurface exchange fluxes trigger different flow regimes, connectivity dynamics, and runoff generation mechanisms inside the catchment, and hence, affect the distributed hydrological response. Further, changes in surface–subsurface exchange rates lead to a nonlinear change in the degree of connectivity—quantified through the number of disconnected clusters of ponding water—in the catchment. Although the runoff formation in the catchment changes significantly, these changes do not significantly alter the aggregated streamflow hydrograph. This hints at a crucial gap in our ability to infer catchment function from aggregated signatures. We show that while these changes in distributed hydrological response may not always be observable through aggregated hydrological signatures, they can be quantified through the use of indices of connectivity.

54 ENVIRONMENTAL SCIENCES↗

Influence of Ag metal dispersion on the thermal conversion of ethanol to butadiene over Ag-ZrO 2 /SiO 2 catalysts

Atomistic scale models were developed and coupled with experimental investigation to deliver a functional understanding of catalytic activity and selectivity in the conversion of ethanol to 1,3-butadiene over Ag/ZrO 2 /SiO 2 . A detailed evaluation of the structural and electronic properties of the resultant catalyst models led to the identification of critical active sites of the catalyst. More importantly, the extent of Ag dispersion on the SiO 2 support and relative proximity to ZrO 2 were found to vary with the oxidation state of Ag and local coordination environment (Ag-O SiO2 ) allowing for critical control of ethanol conversion towards butadiene or ethylene. Simulations revealed that less dispersed or clustered Ag contain predominantly Ag 0 charge state and promote conversion of ethanol to ethylene. The well-dispersed Ag/ZrO 2 /SiO 2 catalyst instead contain a larger fraction of cationic Ag δ+ , and predominantly promote ethanol dehydrogenation and subsequent production of butadiene. The theoretical insights drawn were validated and confirmed experimentally using TEM, XRD and reactivity measurements demonstrating the effect of Ag dispersion on the selectivity of ethanol conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin and charge density waves in quasi-one-dimensional KMn 6 Bi 5

The recent observation that pressure could suppress antiferromagnetic (AFM) order in quasi-one-dimensional AMn 6 Bi 5 Mn-cluster chain materials (A=Na, K, Rb, and Cs) and lead to a superconducting dome offers an alternative Mn-based class of materials with which to study unconventional superconductivity. Using neutron diffraction, we elucidate the exact nature of the previously unknown AFM ground state of KMn 6 Bi 5 and report finding transverse incommensurate spin density waves (SDWs) for the Mn atoms with a propagating direction along the chains. The SDWs have distinct refined amplitudes of ~2.46μ B for the Mn atoms in the pentagons and ~0.29μ B with a large standard deviation for Mn atoms at the center between the pentagons. AFM coupling dominates both the nearest-neighbor Mn-Mn interactions within the pentagon and next-nearest-neighbor Mn-Mn interactions out of the pentagon (along the propagating wave). The SDWs exhibit both local and itinerant characteristics potentially due to cooperative interactions between local magnetic exchange and conduction electrons. Single crystal x-ray diffraction below the AFM transition revealed satellite peaks originating from charge density waves along the chain direction with a q vector twice as large as that of the SDW, pointing to a strong real space coupling between them. Additionally, we report a significant magnetoelastic effect during the AFM transition, especially along the chain direction, observed in temperature-dependent x-ray powder diffraction. Our work not only reveals fascinating intertwined spin, charge, and lattice orders in one-dimensional KMn 6 Bi 5 , but also provides an essential piece of information on its magnetic structure to understand the mechanism of superconductivity in this Mn-based family.

1-dimensional systems↗

An electron-bifurcating “plug” to a protein nanowire in tungsten-dependent aldehyde detoxification

Members of the tungsten-containing oxidoreductase (WOR) family, which contain a tungstopyranopterin (Tuco) cofactor, are typically either monomeric (WorL) or heterodimeric (WorLS). These enzymes oxidize aldehydes to the corresponding acids while reducing the redox protein ferredoxin. They have been structurally characterized mainly using WORs from hyperthermophilic archaea. The WORs of some bacteria contain three additional subunits of the BfuABC family and these chimeric WorABCSL enzymes catalyze an electron-bifurcating reaction in which aldehyde oxidation is coupled to the simultaneous reduction of ferredoxin and nicotinamide adenine dinucleotide. In human gut microbes, electron bifurcation by WorABSL is proposed to enable the detoxification of aldehydes generated from cooked foods and in the tungstocentric production of beneficial short chain fatty acids from lactate, potentially impacting health. Herein we present the high-resolution cryogenic electron microscopy (cryo-EM) structure of the WorABCSL purified from the bacteriumAcetomicrobium mobile.The structure reveals a surprising 1:3 stoichiometry between WorABC and WorSL, with the WorSL units forming a nanowire-like architecture leading from three Tuco-containing catalytic sites in WorL via strings of multiple iron-sulfur clusters in WorS to a single bifurcating WorABC core. Our structure uncovers a distinct domain arrangement that links three Tuco-dependent aldehyde oxidation sites with the bifurcation process and potentially facilitates environmental aldehyde oxidation.

Science & Technology - Other Topics↗

Development of a three-dimensional APOLLO3 neutrons deterministic scheme for the CABRI reactor

CABRI is an experimental reactor to study the fuel behavior during reactivity injection transients. These transients being highly multiphysics, the development of suitable modeling and simulation tools to simulate them is important for the optimization of the tests and the control of the experimental conditions. This paper focuses on the development of an APOLLO3 deterministic core calculation tool dedicated to the CABRI transient analysis. It represents the first stage of the incremental process for the implementation of a multiphysics time-dependent modeling of the CABRI transient. The neutron calculation scheme is based on a classical two-step approach. The first step consists of a 281-energy group calculation flux with the TDT-MOC (Method Of Characteristics) solver for cross-section space and energy (23 groups) collapsing for the CABRI different assembly clusters. The bias on a 2D core neutron calculation due to the self-shielding calculation and collapsing on a restricted pattern are investigated thanks to a comparison with a direct full 2D calculation on a quarter of core. The second step relies on a pin-resolved transport 3D transport core calculation with the SN solver MINARET. A progressive numerical validation process is followed to quantify the calculation biases on reactivity and reaction rates at each step using reference calculations with the stochastic code TRIPOLI4. The next development stage toward a multiphysics scheme will be the implementation of the 3D-kinetics equation resolution and the coupling with a core thermal-hydraulics model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Search for a heavy resonance decaying into a top quark and a W boson in the lepton+jets final state at $\sqrt{s}$ = 13 TeV

A search for a heavy resonance decaying into a top quark and a W boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV is presented. The data analyzed were recorded with the CMS detector at the LHC and correspond to an integrated luminosity of 138 fb -1 . The top quark is reconstructed as a single jet and the W boson, from its decay into an electron or muon and the corresponding neutrino. A top quark tagging technique based on jet clustering with a variable distance parameter and simultaneous jet grooming is used to identify jets from the collimated top quark decay. The results are interpreted in the context of two benchmark models, where the heavy resonance is either an excited bottom quark b* or a vector-like quark B. A statistical combination with an earlier search by the CMS Collaboration in the all-hadronic final state is performed to place upper cross section limits on these two models. The new analysis extends the lower range of resonance mass probed from 1.4 down to 0.7 TeV. For left-handed, right-handed, and vector-like couplings, b* masses up to 3.0, 3.0, and 3.2 TeV are excluded at 95% confidence level, respectively. The observed upper limits represent the most stringent constraints on the b* model to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Family of Robust and Strongly Luminescent CuI-Based Hybrid Networks Made of Ionic and Dative Bonds

The CuI-derived inorganic–organic hybrid compounds are considered as promising phosphors for the lighting industry. Herein, exploiting N-monoalkylated hexaminium salts, [R-HMTA]X (R = Me, Et, Pr, and propargyl; X = Cl and I), as multibridging ligands, we have designed and synthesized a unique class of one-dimensional and two-dimensional hybrid CuI-materials. The reactions of these salts with CuI give rise to All-in-One (AIO) type compounds combining ionic and dative bonds between inorganic and organic components. The latter is formed by structurally unique inorganic [Cu x I y ] (y–x)– clusters, chains, or sheets interconnected through [R-HMTA] + cations via multiple Cu–N bonds. The so-designed compounds at ambient temperature exhibit tunable luminescence spanning from deep blue to red color (λ em = 430–625 nm) with microsecond lifetimes and the quantum efficiency of up to 78%. Remarkably, the AIO materials feature nontrivial excitation- (ED) and temperature-dependent (TD) luminescence, allowing their emission color to be finely adjusted from deep blue to red through changing the excitation wavelength and/or temperature. Based on the TD emission spectroscopy and theoretical calculations, a possible mechanism of the luminescence has been proposed. In conclusion, the very interesting luminescence characteristics coupled with good thermal and photostability render these AIO hybrid materials possible candidates for applications in energy-efficient lighting devices.

36 MATERIALS SCIENCE↗

Confinement effects and acid strength in zeolites

Chemical reactivity and sorption in zeolites are coupled to confinement and—to a lesser extent—to the acid strength of Brønsted acid sites (BAS). In presence of water the zeolite Brønsted acid sites eventually convert into hydronium ions. The gradual transition from zeolite Brønsted acid sites to hydronium ions in zeolites of varying pore size is examined by ab initio molecular dynamics combined with enhanced sampling based on Well-Tempered Metadynamics and a recently developed set of collective variables. While at low water content (1–2 water/BAS) the acidic protons prefer to be shared between zeolites and water, higher water contents (n > 2) invariably lead to solvation of the protons within a localized water cluster adjacent to the BAS. At low water loadings the standard free energy of the formed complexes is dominated by enthalpy and is associated with the acid strength of the BAS and the space around the site. Conversely, the entropy increases linearly with the concentration of waters in the pores, favors proton solvation and is independent of the pore size/shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic PRA-Based Estimation of PWR Coping Time Using a Surrogate Model for Accident Tolerant Fuel

In this study, we propose an interpolation-based response surface surrogate methodology to manage a large number of scenarios in dynamic probabilistic risk assessment. It adopts the shape Dynamic Time Warping algorithm to cluster the interpolation neighborhood from time series sample data. The interpolation method was adapted from Taylor Kriging to allow a reduced-order model of the Taylor series. In order to demonstrate its applicability to complex issues in risk assessment for nuclear engineering, an example risk response surface to estimate emergency core cooling system (ECCS) criteria for triplex silicon carbide (SiC) accident-tolerant fuel was constructed. The response surface was exploited to estimate the cumulative failure probability of the fuel cladding structure due to the uncertainties in operator actions and safety systems. The functional failures were assessed based on a combination of individual layer failures computed by coupling Risk Analysis Virtual Environment software with a pressurized water reactor 1000-MW(electric) RELAP5 model and the in-house fuel performance assessment module. Results showed that SiC cladding failure probability spiked less than 1 min after a large-break loss-of- coolant accident whenever the current ECCS criteria for Zircaloy-4 (Zr-4) cladding was used. However, it still provides an increased safety margin of three orders of magnitude compared to Zr-4. This positive margin could be utilized to relax active ECCS requirements by allowing deviations of up to 450 s in its actuation time. The proposed surrogate methodology generated a response surface of SiC cladding failure probability reasonably well, with a significant savings of computation time. This methodology is expected to be useful in the analysis of system response with complex uncertainty sources.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗