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At least 37 records · Page 2

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗

MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models

Mixture of Experts (MoE) models have enabled the scaling of Large Language Models (LLMs) and Vision Language Models (VLMs) by achieving massive parameter counts while maintaining computational efficiency. However, MoEs introduce several inference-time challenges, including load imbalance across experts and the additional routing computational overhead. To address these challenges and fully harness the benefits of MoE, a systematic evaluation of hardware acceleration techniques is essential. We present MoE-Inference-Bench, a comprehensive study to evaluate MoE performance across diverse scenarios. We analyze the impact of batch size, sequence length, and critical MoE hyperparameters such as FFN dimensions and number of experts on throughput. We evaluate several optimization techniques on Nvidia H100 GPUs, including pruning, Fused MoE operations, speculative decoding, quantization, and various parallelization strategies. Our evaluation includes MoEs from the Mixtral, DeepSeek, OLMoE and Qwen families. The results reveal performance differences across configurations and provide insights for the efficient deployment of MoEs.

Chitty-Venkata, Krishna Teja↗

Small-scale Assessment of Simplified Ceramic Waste Form Processing

The feasibility of directly processing glass-bonded sodalite ceramic waste form materials by heating a mixture of Zeolite 4A, chloride salt, and sodium borosilicate binder glass was demonstrated by generating laboratory-scale materials. This direct processing method eliminates pre-setting the moisture content of the Zeolite 4A, eliminates the step of occluding salt in the prepared Zeolite 4A prior to processing, and can be conducted using larger particle sizes of crushed Zeolite 4A and crushed borosilicate glass than those called for in the current method. These simplifications are expected to facilitate material transfer and handling in a hot cell or controlled atmosphere environment and be more readily implemented at large scale than the current method. Most materials made to assess these simplifications were directly processed at 925 °C for two hours in an argon atmosphere glovebox, but one material was processed at 925 °C for four hours and one material was processed at 880 °C for two hours. Sodalite was generated and became microencapsulated by the binder glass in all materials. The microstructures were uniform throughout each product, were similar in all products, and were similar to the microstructures of materials made previously using the pressureless consolidation or hot isostatic pressing methods. Various formulations showed the efficiency of sodalite generation was not sensitive to the salt-to-Zeolite 4A ratio or salt-to-glass mass ratio, although a greater relative mass of glass is required to encapsulate sodalite generated from large particles of aggregated Zeolite 4A. The upper limit of salt loadings that can be effectively processed remains to be determined. The effectiveness of direct processing provided new insights into the conversion mechanism. The salt was likely dissolved into the glass that transported NaCl into the Zeolite 4A aggregates and sodalite was generated in situ as NaCl migrated from the outside of the aggregate inward. Other salt cations (e.g., potassium, strontium, cesium, and probably lithium) remain dissolved in the glass encapsulating the zeolite/sodalite domains. When the glass solidifies during cooling, small halite inclusion phases form in glass within sodalite domains and large mixed salt inclusions form in glass surrounding the sodalite due to the low solubility of chloride in the (solid) glass. Other salt cations were oxidized during processing and formed inclusions in the bulk glass (e.g., neodymium). Initial degradation tests show the dissolution behavior of directly processed CWF (SCWF) materials is similar to CWF materials made using different methods.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Mixed Precursor and Future Climate in the Southeast U.S. Field Campaign Report

The generation of atmospheric aerosols is a fundamental process in aerosol-climate interactions, where particles act as nuclei for cloud formation and ultimately influence Earth’s radiative balance. Understanding aerosol precursors, chemical compositions, and formation mechanisms, particularly for secondary organic aerosols (SOAs), is essential for assessing their overall impact on climate. Aerosol-climate interactions are especially important in the Southeastern United States (SE-US), where the atmosphere is strongly influenced by both biogenic and anthropogenic emissions, as well as intense land-atmosphere convective coupling. Current mechanistic representations of SOA formation under ambient conditions are largely extrapolated from laboratory-scale oxidation experiments involving individual volatile organic compounds (VOCs), which are often assumed to behave independently when present in mixtures. However, recent empirical evidence demonstrates that coexisting VOC precursors can undergo previously unexplored molecular-scale interactions that significantly alter SOA physicochemical properties, including mass loading, yield, and water uptake.

54 ENVIRONMENTAL SCIENCES↗

Experimental analysis of gas dynamics in the reactor cavity section of a High-Temperature Gas-Cooled Reactor during an accident scenario

Here, this study investigates the behavior of a High-Temperature Gas-Cooled Reactor (HTGR) during a break of the helium pressure boundary event. Understanding the gas dynamics that occur during a break could help develop safety systems that reduce the probability of air entering the reactor core. To achieve this objective, experimental studies were conducted in a scaled-down HTGR experimental facility to provide information on the air-helium gas mixture within the confinement building and the impact of the ventilation system on the helium/air gas concentration following the depressurization event. The study evaluated different configurations, including active ventilation time scales, break sizes, and locations. The analysis of the active ventilation time revealed that a ventilation time of 22 seconds produced positive results, and smaller break sizes resulted in longer depressurization times, which improved the ventilation process. The orientation and elevation of the breaks had little effect on the oxygen concentration in the cavity but did impact the gas velocities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Organic Evaporation, Oxidation, and Hydrolysis Testing in Support of Hanford Sample-and-Send

The Hanford site has approximately 54 to 56 million gallons of radioactive mixed waste stored in 156 unretrieved underground storage tanks. The Hanford Waste Treatment and Immobilization Plant (WTP) is being built to treat and immobilize the tank waste. The baseline method for immobilization of Low Activity Waste (LAW) through the WTP is vitrification, but additional immobilization capacity is needed to supplement the initial LAW melters. An alternative cementitious waste form is being investigated for that future immobilization method. However, one impediment to a cementitious waste form is the presence of Land Disposal Restricted (LDR) organic chemicals in tank waste, which are regulated on a concentration based standard in the final waste form. Hence, if the quantity of organics in LAW is high enough, they must be destroyed or removed to make a waste form compatible with disposal in a mixed low level waste landfill. This work evaluates potential avenues for treatment of LDR organics to eliminate the impediment and permit possible use of a cementitious waste form. Vacuum evaporation testing to remove LDR organics consisted of preparing a non-radioactive LAW simulant, spiking that simulant with organic chemicals, and evaporating the mixture via differential distillation. The apparatus was a laboratory-scale vacuum evaporator operated at 60 ±5 torr absolute (vacuum evaporation). The LAW simulant represented the liquid expected to be retrieved from the Hanford tank farms at approximately 4.0 M [Na+] total sodium ion concentration. The concentration of the organic chemicals added was significantly higher than typically found in the tank waste samples since the higher levels were necessary to assist in analytical measurement and tracking of the spiked species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Impact of Small-Alkane Solvents on Polyolefin Hydrogenolysis over a Ruthenium Catalyst

Selective catalytic hydrogenolysis of polyolefins is a promising route to convert plastic waste into valuable liquid products, such as lubricants, waxes, and surfactants. However, the high viscosity of polymer melts imposes mass transfer limitations on this reaction. Solvents can mitigate these challenges, but their effects on reaction kinetics and product selectivity remain underexplored. Here, we systematically explore the effects of small n-alkanes and cycloalkanes on the hydrogenolysis of polyethylene and polypropylene over a Ru/TiO 2 catalyst. Using kinetic measurements and isotopic labeling, we show that n-octane at high mass fractions alters the mechanism from direct hydrogenation to solvent-mediated hydrogen transfer, reducing the rate of C–C bond cleavage. Longer alkanes further inhibit reactivity due to stronger surface binding. 1,4-Dimethylcyclohexane suppresses methane formation, favoring heavier products, while decalin likely forms surface-bound aromatics that poison the catalyst. Overall, alkane solvents modulate product selectivity and reduce the yield of methane byproduct, allowing for ∼35–40% selectivity to valuable C 20 -C 30 alkane products. This work highlights the complex impact of polymer–alkane mixtures on hydrogenolysis kinetics relevant to the design of commercial-scale plastic waste valorization processes.

Catalysts↗

A study on the scale dependence of mixing indices for Eulerian multiphase models

Abstract Mixing can vary based on the scale at which the system is observed, and a mixing index that can capture the features at different length scales is desirable. In this article, we analyze the scale dependence of the mixing indices developed for Eulerian multiphase models. Relevant length scales are distinguished by filtering solid fraction fields. The scale‐dependence study is first done on manufactured fields of solid fraction to assess the performance of the mixing indices. The study is extended to a two‐dimensional CFD simulation of the segregation of a bidisperse gas–solid mixture. The local mixing index performs well in capturing the spatial variation of mixing at different scales. The scale dependence of two global mixing indices is considered in the study, where the state of mixing is defined based on statistical measures. We demonstrate that the choice of measures influences the sensitivity of mixing indices to mixing at different scales.

Nagawkar, Barlev R.↗

Method of tuning physical properties of thermosets

Polymerization-induced phase separation enables fine control over thermoset network morphologies, yielding heterogeneous structures with domain sizes tunable over 1-100 nm. However, the controlled chain-growth polymerization techniques exclusively employed to regulate morphology at these length scales are unsuitable for most thermoset materials typically formed through step-growth mechanisms. By employing binary mixtures in place of the classic constituents of phase-separating thermosets—resin, curing agent, and secondary polymer—facile tunability over morphology can be achieved through a single compositional parameter. Indeed, this method yields morphologies spanning nano-scale to macro-scale, controlled by the relative reactivities and thermodynamic compatibility of the network components. Due to the connection between chain dynamics and microstructure in these materials, the tunable morphology enables exquisite control over glass transition and other physical and mechanical properties.

Jones, Brad Howard↗

A regularized-interface method as a unified formulation for simulations of high-pressure multiphase flows

The injection of multi-species fluids into high-pressure and high-temperature environments beyond the species' critical points is commonly found in engineering applications. At these conditions, for immiscible species, both subcritical interfacial dynamics and supercritical mixing can coexist due to variations in temperature around the mixture critical point. The modeling of these complex transcritical phenomena for large-scale configurations is so far not possible. To address this issue, we propose the Regularized-Interface Method (RIM) as a unified formulation that can describe both sub- and supercritical processes as well as the transition between them. The proposed method is derived via filtering of the nanoscale interface-resolving formulation based on van der Waals' linear gradient theory. Thus, this approach allows for the consistent modeling of interfacial dynamics that vanishes at supercritical conditions, while significantly reducing the temporal and spatial resolution constraints of the original nanoscale formulation. The resulting RIM formulation is examined in interface-capturing simulations of sub-, trans-, and supercritical fuel injection processes, involving droplets and jets. Furthermore, these results highlight the importance of resolving spatio-temporal transitions from subcritical interfacial dynamics to supercritical mixing in high-pressure multiphase simulations, in contrast to commonly employed diffused-interface methods, where interfacial dynamics are often neglected.

Interface capturing↗

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient ultrafast quantum well IR photodetectors

This project, titled “Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors”, was funded by the U.S. Department of Energy to explore a new class of materials that could make future light-sensing technologies, such as infrared (IR) cameras and detectors more efficient, affordable, and widely available. The research focused on special layered materials called 2D halide perovskites, which are made up of alternating organic and inorganic layers only a few atoms thick. These materials can be tuned at the atomic level to absorb and emit light in precise ways, making them very attractive for use in optoelectronic devices. The main goal of the project was to understand how these perovskite materials absorb light and move electrical charges at very small scales. However, this is not an easy task. These materials often contain a mixture of different structures in the same film, and traditional tools like regular absorption or photoluminescence spectroscopy are not good at telling those structures apart. To solve this, the research team, led by Professor Luisa Whittaker-Brooks at the University of Utah developed a powerful method called electroabsorption spectroscopy. This technique uses electric fields to highlight the unique “fingerprints” of different excitons, which are tiny packets of energy formed when light hits the material. By using this method, the team could separate overlapping signals and learn exactly how the materials respond to light under different conditions, including changes in temperature, thickness, and chemical makeup.

36 MATERIALS SCIENCE↗

Empirical scaling of the L–H threshold power for metal wall tokamaks using a multi-device database

The empirical scaling for the H-mode power threshold in tokamaks has been revisited using a database with threshold data from machines with a metallic first wall as part of International Tokamak Physics Activity (ITPA) task TC-26. The database contains discharges from ASDEX Upgrade (AUG) (W), JET (Be/W) and Alcator C-Mod (Mo). This was motivated by reports that in like-for-like discharges the power threshold was reduced by approximately 30% after the change from carbon based to metallic first wall materials on AUG (Ryter et al 2013 Nucl. Fusion 53 113003) and JET (Maggi et al 2014 Nucl. Fusion 54 023007). The database contains L–H transition data for all hydrogen isotopes and mixtures, including T and DT from the recent JET campaigns. Compared to the ITPA 2008 scaling (Martin et al 2008 J. Phys.: Conf. Ser. 123 012033), the metal wall scaling has a smaller magnetic field exponent but a larger density exponent. We present an additional parameter to capture the strong dependence of the L–H power threshold (approx. factor 2) on the magnetic configuration in the divertor on JET. The scaling recovers the approximate inverse isotope mass scaling of the threshold power. Alternative scalings involving the plasma current and poloidal magnetic field are explored. Despite the reduction in threshold observed earlier, the scalings based on the metal wall database do not necessarily extrapolate to a lower threshold for ITER compared to the ITPA 2008 scaling, especially at high density. The divertor configuration effect induces the largest uncertainty in the extrapolation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

CFD Model Development of a Small-Scale Fixed-Bed Reactor for Direct Air Capture of CO2

Direct air capture (DAC) is a promising approach to significantly reduce the CO2 concentration in the ambient air. This approach requires the extraction of CO2 from air with ultra dilute CO2 concentration which makes this approach more expensive than point source CO2 capture. Several efforts are being made in academics and industry to develop cost-efficient sorbents and solvents suitable for DAC. One of them is polymer with intrinsic microporosity (PIM) which is often used for CO2 capture because of its higher porosity and rigidity. A novel, cost-efficient aminated PIM sorbent, PF-15-TAEA, was developed at the National Energy Technology Laboratory for DAC applications. The current work is focused on the computational investigation of the CO2 capture by this novel sorbent from a gas mixture with ultra dilute concentration of CO2 in dry and humid conditions in a laboratory-scale fixed-bed reactor.

Aziz, Hossain↗

Unraveling the structure of molten salts: a review of high-energy x-ray diffraction (HEXRD) studies

High energy x-ray diffraction (HEXRD) has emerged as a pivotal technique for examining the structural properties of molten salts, which play vital roles in various high-temperature applications, such as energy storage, nuclear reactors, and metallurgy. This review provides a comprehensive analysis of recent progress in HEXRD studies of various molten salt systems, including molten halide salts, their mixtures, and salts with molecular anions, focusing on the insights into their atomic-scale arrangements. Additionally, we discuss methodological advancements that have improved the resolution and accuracy of HEXRD measurements, as well as recent developments in computational simulations, such as machine learning interatomic potentials, for interpreting results. This review aims to serve as a valuable resource for researchers in this field, offering a detailed overview of the progress of HEXRD studies of molten salts and suggesting pathways for further exploration.

Blockmon, Avery L. [Argonne National Laboratory (A↗

Experimental Combustion and Flame Characterization of a Chemical Looping-Based Oxidative Dehydrogenation Byproduct Fuel Mixture Containing High CO2 Dilution

Abstract This study investigates the combustion performance of a CO2-rich fuel mixture containing ethane and methane as active species using a constant volume combustion chamber. This fuel is obtained as a byproduct of a chemical looping-based oxidative dehydrogenation (Cl-ODH) process ethylene production. The byproduct gas mixture has 40.79% CO2, 39.49% ethane, and 4.88% methane by weight with other minor compounds. Using this fuel for energy extraction would improve the process efficiency of the ethane to ethylene conversion. After initial combustion modeling, the gas fuel mixture was reduced to just the major species: CO2, ethane, and methane. The mixture was then tested for flammability limits and combustion performance under spark-ignition conditions. Effects of ambient conditions like temperatures between 300 and 400 K with initial pressures from 1 to 10 bar were tested. The effects of stoichiometry were tested to understand flame velocities and heat release. The fuel mixture showed an overall reduced flame velocity compared to gasoline. Instability in combustion was believed to be caused by the dissociation of ethane under elevated conditions. At higher pressures, the flame produces lower cumulative heat release. Simulations were also performed using a model tuned to replicate the operations of the combustion chamber used in the experiments. Heat release and unburnt fuel mass data were calculated to identify the discrepancies in the combustion completeness at elevated pressures. The effects of CO2 quenching the flame coupled with the increased dissociation of the fuel species can lead to up to more than 75% of the fuel mixture being unburnt. Data from this study were used to modify a small-scale spark-ignition engine to use this fuel and produce usable energy.

Energy & Fuels↗

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

Raccoon density estimation from camera traps for raccoon rabies management

Abstract Density estimation for unmarked animals is particularly challenging, yet density estimates are often necessary for effective wildlife management. Raccoons ( Procyon lotor ) are the primary terrestrial wildlife reservoir for Lyssavirus rabies within the United States. The raccoon rabies variant (RRVV) is actively managed at landscape scales using oral rabies vaccination (ORV) within the eastern United States. To effectively manage RRVV, it is important to know the density of raccoons to appropriately scale the density of ORV baits distributed on the landscape. We compared methods to estimate raccoon densities from camera‐trap data versus more intensive capture‐mark‐recapture (CMR) estimates across 2 land cover types (upland pine and bottomland hardwood) in the southeastern United States during 2019 and 2020. We evaluated the effect of alternative camera configurations and durations of camera trapping on density estimates and used an N‐mixture model to estimate raccoon densities, including covariates on abundance and detection. We further compared different methods of scaling camera‐based counts, with the maximum number of raccoons seen on any given image within a day best explaining density. Camera‐trap density estimates were moderately correlated with CMR estimates ( r = 0.56). However, densities from camera‐trap data were more reliable when classifying category of density as an index used to inform management (83% correct when compared to CMR estimates), although the densities in our study fell into the 2 lowest density classes only. Using more cameras reduced bias and uncertainty around density estimates; however, if ≤6 camera traps were used at a site, a line transect approach proved less biased than a grid design. Camera trapping should be conducted for at least 3 weeks for more accurate estimates of raccoon population density in our study area (<5% bias). We show that camera‐trap data can be used to assign raccoon densities to management‐relevant density index bins, but more studies are needed to ensure reliability across a greater range of environmental conditions and raccoon densities.

Davis, Amy J.↗

Calculation of monomer yields, verification of PG concentration approximation, catalyst comparison for neat aromatic RCF, SEM micrographs for postreaction pulps, yields of aqueous-phase sugar derivatives after PG-H2O RCF, reactor pressure transients, GPC comparing pre- and postreaction organic solvent composition, PG-H2O miscibility testing, GPC probing dimer/oligomer fractionation in PG-H2O mixtures for

Reductive catalytic fractionation (RCF) is an effective lignin-first biorefining method to extract lignin as a stabilized oil from lignocellulosic biomass. To realize RCF at scale, process modeling has shown that minimizing the use of exogenous organic solvents is critical. To this end, here we investigate the ability of lignin-derived monomers to act as either solvents or cosolvents for RCF. We begin by examining the influence of lignin-derived aromatic compounds (4-propylguaiacol, 4-propylphenol, and propylbenzene) on RCF monomer yields and subsequently extend our analysis to mixtures of 4-propylguaiacol and either methanol or water. We demonstrate that 4-propylguaiacol is an effective solvent for lignin extraction and depolymerization during RCF, especially when used in combination with water as a cosolvent. Cosolvent mixtures of 4-propylguaiacol and water enable up to 81% lignin extraction, monomer yields up to 25 wt %, and postreaction phase separation. However, unlike methanol, water as a cosolvent fails to inhibit aromatic ring hydrogenation when conducted over Ru/C as a catalyst, potentially leading to excess hydrogen consumption in a process utilizing this approach. Nonetheless, these results suggest a promising strategy for eliminating external organic solvents from RCF by utilizing mixtures of lignin-derived compounds and water as alternative extraction solvents.

biorefining↗