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At least 451 records · Page 25

Electrostatic Barriers to Nanoparticle Accessibility of a Porous Matrix

Translocation from one cavity to another through a narrow constriction (i.e., a “hole”) represents the fundamental elementary process underlying hindered mass transport of nanoparticles and macromolecules within many natural and synthetic porous materials, including intracellular environments. This process is complex and may be influenced by long-range (e.g., electrostatic) particle–wall interactions, transient adsorption/desorption, surface diffusion, and hydrodynamic effects. In this study, we used a three-dimensional (3D) tracking method to explicitly visualize the process of nanoparticle diffusion within periodic porous nanostructures, where electrostatic interactions were mediated via ionic strength. The effects of electrostatic interactions on nanoparticle transport were surprisingly large. For example, an increase in the Debye length of only a few nanometers (in a material with a hole diameter of ~100 nm) increased the mean cavity escape time 3-fold. A combination of computational and experimental analyses indicated that this hindered cavity escape was due to an electrostatic energy barrier in the region of the hole, which was quantitatively explained using DLVO theory. These findings explicitly demonstrate that the cavity escape process was barrier-limited and dominated by electrostatic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Initial Evaluation of the Elevated-Temperature Cyclic Properties of Optimized 316H Stainless Steel Fabricated by Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is a mature advanced manufacturing technology, which can consolidate metallic powder under high temperature and pressure to generate near-net shape components. This process can lower production costs and reduce component lead times for nuclear reactor construction and can be readily deployed in the near term for microreactor components because of their smaller size. The purpose of this work is to continue the evaluation of elevated-temperature cyclic material properties for PM-HIP 316H stainless steel. Prior scoping results have shown that the commercially procured PM-HIP stainless-steel materials have reduced creep-fatigue performance compared to wrought 316 stainless steels. To better understand how PM-HIP processed material properties compare to traditional manufacturing methods, additional billets of PM-HIP 316H stainless steel were procured and tested. This testing is necessary to understand how elevated-temperature properties are influenced by the PM-HIP process and what data are needed for incorporating PM HIP 316H into the American Society of Mechanical Engineers Boiler Pressure Vessel Code, Section III, Division 5 for high temperature reactor construction. Specifically, an additional PM-HIP 316H stainless steel billet with lower oxygen and nitrogen concentrations was fabricated by the Nuclear Advanced Manufacturing Research Centre of the United Kingdom and tested to understand if elevated-temperature cyclic properties can be improved. The creep-fatigue resistance of the material from this new billet did not show appreciable improvement compared to prior testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Gene drive by Fusarium SKC1 is dependent on its competing allele

The Fusarium verticillioides SKC1 gene driver is transmitted to offspring in a biased manner through spore killing. The mechanism that allows SKC1 to kill non-SKC1 offspring while sparing others is poorly understood. Here we report that gene drive by SKC1 is dependent on SKC1's competing allele. We propose that SKC1's competing allele influences the ability of a genome defense process to detect SKC1, and we provide evidence that this genome defense process is meiotic silencing by unpaired DNA (MSUD). Furthermore, our findings suggest that the successful deployment of gene drivers to control pathogenic fungi will require researchers to consider how competing alleles influence the ability of gene drivers to be detected by genome defense processes.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Metal Ion Complexation on the Radiolytic Longevity of Butyramide Extractants under Direct Dissolution Process Conditions

The direct dissolution of voloxidized used nuclear fuel (UNF) into an organic solution–comprised of diluent and specialized extractants–poses a promising alternative to the traditional liquid–liquid solvent extraction approach to reprocessing UNF. However, moving to direct dissolution removes the presence of a concentrated nitric acid aqueous phase, which has been shown to significantly influence the radiolytic longevity of extractants in conventional extraction flowsheets. Given the limited knowledge of radiation effects under direct dissolution conditions, here we present a time-resolved and dose-accumulation study on the impact of direct dissolution conditions on the radiolytic longevity of two candidate butyramide extractants, N,N-di(2-ethylhexyl) butyramide (DEHBA) and N,N-di(2-ethylhexyl)isobutyramide (DEHiBA), in pre-equilibrated n-dodecane solvent in the presence and absence of process-relevant metal ions, specifically, uranium and rhenium. Loss G(DEHBA) and G(DEHiBA) values were found to be comparable to each other, with an average of 0.37 ± 0.02 μmol J –1 , and to previous data from the γ irradiation of DEHBA and DEHiBA under conventional solvent extraction conditions. Rhenium, and by extension technetium, extraction had a modest decrease (~10%) in the overall radiolytic stability of DEHiBA only, despite >2× observed increases in chemical kinetic reactivity of the corresponding complexes with the n-dodecane radical cation. Uranium loading, on the other hand, significantly improved the lifetime of both ligands (>30%) under γ irradiation, with a greater stabilization observed for DEHBA over DEHiBA. The observed radioprotective effect afforded by uranium loading is fortuitous for the longevity of direct dissolution solvent.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Phase Formation in Nuclear Fallout

An understanding of the physical and chemical process occurring in a nuclear explosion enables predictions of the effects of nuclear weapons, including characteristics of radioactive fallout resulting from the explosion. Near-surface nuclear explosions are of particular interest due to the potential for significant amounts of environmental material to interact with and alter the physical and chemical behavior of the fireball. Such interactions have the potential to affect the distribution of radioactive species in the fireball and subsequently become incorporated into fallout through a process known as radiochemical fractionation. Studying variations in fallout formed in different historical testing environments allows us to understand the influence of local environments on fallout formation processes. In particular, constraining variations in thermal evolution and redox conditions during the evolution of the fireball can be useful to understanding how sensitive fallout radiochemical fractionation may be to the local explosion environment. However, untangling these conditions in complex, multicomponent fallout is a challenge. Here we present one method of constraining and interpreting fallout formation conditions by relating computationally derived phase stability predictions to observations in historic fallout. Development of such approaches will help improve physics-based models of fallout formation and radiochemical fractionation in complex, near surface nuclear detonations.

36 MATERIALS SCIENCE↗

Influence of twist pitch on hysteretic losses and transport J c in overpressure processed high J c Bi-2212 round wires

Abstract Bi-2212 is the only high field, high-temperature superconductor (HTS) available in the macroscopically isotropic, multifilament high J c round wire (RW) form capable of generating high uniformity fields with minimum-screening current errors. However, the heat treatment that enables impressively high J c (4.2 K, 30 T) values that can attain ∼5000 A mm −2 also produces significant filament bonding (bridging). Filament bridging appears to significantly enhance hysteretic losses of the filaments themselves by coupling neighboring, nominally independent filaments, enabling shielding currents to flow across multiple filaments as though they were one filament of much larger diameter. Wire twisting can be employed to reduce filament-to-filament eddy current coupling losses due to induced currents flowing across the matrix, but twisting is less effective in reducing increased losses from bridging. Here, we compare the twist-pitch dependence of the losses of overpressure processed (OP) high J c Bi-2212 RWs with partially bridged filaments to those found in OP Bi-2212 RWs with discrete, not-bridged filaments. We show that filament sub-bundles in standard, partially-bridged wires that have some superconducting connections between filaments can exhibit significant coupling (much larger effective filament diameter), but twisting still reduces their hysteretic losses to values close to or below the ITER Nb 3 Sn wire loss specification, even though Bi-2212 wires have significantly larger J c values. Although it has been reported that twisting can reduce wire J c by damaging filaments, we found no reduction in transport J c , even for nominal twist pitches of 12 mm in 0.8 mm diameter wires. Evaluation of more-recent, higher J c Engi-Mat powder wires showed that their reduced filament bridging and improved longitudinal connectivity significantly improved transport J c and reduced the J c normalized losses, signaling that J c can be further improved without commensurate increase in losses. This important result strengthens the argument for production of high field, low loss HTS magnets made with Bi-2212 RWs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Texture Evolution of Plated Lithium in Anode-Free Solid-State Batteries

Here, this study investigates lithium plating texture in anode-free solid-state batteries using synchrotron-based X-ray diffraction. Conventional methods are limited by lithium’s low electron density and softness, which hinders direct interrogation in anode-free solid-state batteries. Results reveal that lithium plating texture is influenced by temperature and current density. Under mild conditions, lithium exhibited a ⟨110⟩ fiber texture. However, higher current densities and elevated temperatures led to a more randomized orientation, suggesting a dependence on plating conditions. The results highlight how the operating and processing conditions for lithium metal can influence the texture of lithium metal and reversible operation.

36 MATERIALS SCIENCE↗

TunIO: An AI-powered Framework for Optimizing HPC I/O

I/O operations are a known performance bottleneck of HPC applications. To achieve good performance, users often employ an iterative multistage tuning process to find an optimal I/O stack configuration. However, an I/O stack contains multiple layers, such as high-level I/O libraries, I/O middleware, and parallel file systems, and each layer has many parameters. These parameters and layers are entangled and influenced by each other. The tuning process is time-consuming and complex. In this work, we present TunIO, an AI-powered I/O tuning framework that implements several techniques to balance the tuning cost and performance gain, including tuning the high-impact parameters first. Furthermore, TunIO analyzes the application source code to extract its I/O kernel while retaining all statements necessary to perform I/O. It utilizes a smart selection of high-impact configuration parameters of the given tuning objective. Finally, it uses a novel Reinforcement Learning (RL)-driven early stopping mechanism to balance the cost and performance gain. Experimental results show that TunIO leads to a reduction of up to ≈73% in tuning time while achieving the same performance gain when compared to H5Tuner. It achieves a significant performance gain/cost of 208.4 MBps/min (I/O bandwidth for each minute spent in tuning) over existing approaches under our testing.

Rajesh, Neeraj↗

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗

When x-rays alter the course of your experiments

The continuing increase in the brilliance of synchrotron radiation beamlines allows for many new and exciting experiments that were impossible before the present generation of synchrotron radiation sources came on line. However, the exposure to such intense beams also tests the limits of what samples can endure. Whilst the effects of radiation induced damage in a static experiment often can easily be recognized by changes in the diffraction or spectroscopy curves, the influence of radiation on chemical or physical processes, where one expects curves to change, is less often recognized and can be misinterpreted as a 'real' result instead of as a 'radiation influenced result'. This is especially a concern in time-resolved materials science experiments using techniques as powder diffraction, small angle scattering and x-ray absorption spectroscopy. In this work, the effects of radiation (5–50 keV) on some time-resolved processes in different types of materials and in different physical states are discussed. We show that such effects are not limited to soft matter and biology but rather can be found across the whole spectrum of materials research, over a large range of radiation doses and is not limited to very high brilliance beamlines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Production Agency Quality Assurance Management Execution Strategy [Thesis]

There are multiple federal directives that Los Alamos National Laboratory (LANL) must follow for the proper implementation of quality assurance, strategic planning, and execution of manufacturing and surveillance operations. Recent assessments identified that manufacturing in all processing areas is dynamic due to influencing scope changes, design modifications, funding adjustments, and staff attrition. In response, this project was started to develop a comprehensive PAQ execution strategy to support the success of LANL’s manufacturing mission. This project’s method for developing an updated architecture was to create an integrated, flexible, reliable, and agile strategic process. The execution plan has five deliverables: 1) an integrated schedule view of PAQ work scope, 2) a resource management plan that aligns with the required scope, 3) a metrics monitoring dashboard, 4) a project management plan for sustaining NAP 401.1A implementation, and 5) a risk management plan. The research design is a mixed-method approach focused on data collection for each deliverable. The methodology entails qualitative and quantitative research, metrics monitoring, data analysis, and the creation of a dashboard. The qualitative methods used include literature reviews and interviews. The quantitative methods include resource, financial, schedule and survey data analysis. Preliminary and final results were peer reviewed by subject matter experts both within the ALDWP organization and deployed support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗

GraMeR: Gra ph Me ta R einforcement learning for multi-objective influence maximization

Influence maximization (IM) is a combinatorial problem of identifying a subset of seed nodes in a network (graph), which when activated, provide a maximal spread of influence in the network for a given diffusion model and a budget for seed set size. IM has numerous applications such as viral marketing, epidemic control, sensor placement and other network-related tasks. However, its practical uses are limited due to the computational complexity of current algorithms. Recently, deep reinforcement learning has been leveraged to solve IM in order to ease the computational burden. However, there are serious limitations in current approaches, including narrow IM formulation that only consider influence via spread and ignore self-activation, low scalability to large graphs, and lack of generalizability across graph families leading to a large running time for every test network. In this work, we address these limitations through a unique approach that involves: (1) Formulating a generic IM problem as a Markov decision process that handles both intrinsic and influence activations; (2)incorporating generalizability via meta-learning across graph families. There are previous works that combine deep reinforcement learning with graph neural network, but this work solves a more realistic IM problem and incorporates generalizability across graphs via meta reinforcement learning. Extensive experiments are carried out in various standard networks to validate performance of the proposed Graph Meta Reinforcement learning (GraMeR) framework. Finally, the results indicate that GraMeR is multiple orders faster and generic than conventional approaches when applied on small to medium scale graphs.

97 MATHEMATICS AND COMPUTING↗

Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup

Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Water Structure and Dynamics Near the Surfaces of Silicalite-1

Zeolites are crystalline microporous aluminosilicates that are commonly used as industrial sorbents and membranes. Solvent structuring and dynamics near zeolite crystal surfaces are thought to influence interfacial transport and molecular recognition processes, as well as fundamental aspects of their crystallization from solution. Here, in this work, we use molecular dynamics (MD) simulations to investigate the behavior of interfacial water near the exposed (010), (100), and (101) crystal faces of silicalite-1, one of the most widely studied zeolites. The MD simulations reveal that water’s translational and orientational order is strongly influenced by the distinct corrugations, pore apertures, and functional group distributions presented on each surface. Specifically, we observe two distinct hydration layers near each surface. Water molecules in the contact layer are hydrogen bonded to two or three exposed surface silanol groups. The relative populations of water molecules that are doubly and triply hydrogen bonded to the surface strongly depend on the distribution of the exposed silanols. The interactions with exposed surface silanols also influence water’s local orientational order and distribution across each surface. We also show that the structuring of the solvent near the different faces of silicalite-1 strongly impacts the interfacial dynamics. The translational and orientational relaxation dynamics of water are slowest in the contact layers and correlate with structural ordering near each face.

42 ENGINEERING↗

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE↗

Investigation of interlayer adhesion of 3D printable cementitious material from the aspect of printing process

The safety of structure printed by extrusion-based 3D concrete printing (3DCP) is significantly influenced by interlayer bonding, which is governed by fresh material properties and processes, including mixing, printing, and post-processing phases. Much literature focused on improving interlayer bond strength via material tailoring/bonding agent addition but gave insufficient attention to other phases' impacts. This study investigates the effects of parameters on interlayer bond strength from different phases in 3DCP, including superplasticizer dosage, printing speed, and curing condition. In the mixing phase, the superplasticizer dosage was increased to reduce I{sub thix} and increase surface moisture content (SMC), consequently improving interface microstructure and interlayer bond strength. In the printing phase, similar results were observed by increasing pumping speed to increase material shear rate. In the post-processing phase, proper curing also improved interlayer bond strength. While SMC has a critical impact on interlayer bond strength, material thixotropic index (I{sub thix}) probably has a stronger influence.

36 MATERIALS SCIENCE↗