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At least 955 records · Page 53

Revealing multiscale competing processes in the solid-state synthesis of single-crystalline layered oxide positive electrodes

Solid-state synthesis involves a web of coupled chemical reactions and physical changes that unfold across multiple scales. Efforts to fine-tune its parameters have historically followed heuristic, trial-driven workflows that demand significant time and resources. In this study, we aimed to open this black box by employing multiscale in situ synchrotron imaging and diffraction. Using LiNi 0.5 Mn 0.3 Co 0.2 O 2 battery positive electrode material as a model system and Ba-based sintering aids, we reveal dopant segregation, intergranular mass transport, and porosity evolution as key drivers of single-crystalline particle formation. Notably, we uncovered a dynamic competition between particle-level grain coalescence and atomic-scale cation disordering, both of which are thermally activated yet have opposing impacts on battery performance. These findings highlight the coupled, multiscale nature of structure development and offer a mechanistic basis for optimizing the solid-state synthesis process. This framework provides a path toward more controlled, efficient, and scalable production of high-performance battery positive electrode materials.

36 MATERIALS SCIENCE↗

Characterization of transverse electron pulse trains using RF powered traveling wave metallic comb striplines

Advancements in ultrafast electron microscopy have allowed elucidation of spatially selective structural dynamics. However, as the spatial resolution and imaging capabilities have made progress, quantitative characterization of the electron pulse trains has not been reported at the same rate. In fact, inexperienced users have difficulty replicating the technique because only a few dedicated microscopes have been characterized thoroughly. Systems replacing laser driven photoexcitation with electrically driven deflectors especially suffer from a lack of quantified characterization because of the limited quantity. The primary advantages to electrically driven systems are broader frequency ranges, ease of use and simple synchronization to electrical pumping. Here, we characterize the technical parameters for electrically driven UEM including the shape, size and duration of the electron pulses using low and high frequency chopping methods. At high frequencies, pulses are generated by sweeping the electron beam across a chopping aperture. For low frequencies, the beam is continuously forced off the optic axis by a DC potential, then momentarily aligned by a countering pulse. Using both methods, we present examples that measure probe durations of 2 ns and 10 ps for the low and high frequency techniques, respectively. Here, we also discuss how the implementation of a pulsed probe affects STEM imaging conditions by adjusting the first condenser lens.

36 MATERIALS SCIENCE↗

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗

High-performance computing with quantum processing units

The prospects of quantum computing have driven efforts to realize fully functional quantum processing units (QPUs). Recent success in developing proof-of-principle QPUs has prompted the question of how to integrate these emerging processors into modern high-performance computing (HPC) systems. We examine how QPUs can be integrated into current and future HPC system architectures by accounting for func- tional and physical design requirements. We identify two integration pathways that are differentiated by infrastructure constraints on the QPU and the use cases expected for the HPC system. This includes a tight integration that assumes infrastructure bottlenecks can be overcome as well as a loose integration that as- sumes they cannot. We find that the performance of both approaches is likely to depend on the quantum interconnect that serves to entangle multiple QPUs. As a result, we also identify several challenges in assessing QPU performance for HPC, and we consider new metrics that capture the interplay between system architecture and the quantum parallelism underlying computational performance.

97 MATHEMATICS AND COMPUTING↗

Revealing EDL-driven reduction mechanisms in binary, ternary, and quaternary fluorinated electrolytes via an integrated MD–DFT–ML framework

Accurately predicting solid electrolyte interphase (SEI) formation requires explicitly resolving the electric double layer (EDL) structure, which deviates significantly from that of the bulk electrolyte. Although an established molecular dynamics (MD) and Density Functional Theory (DFT) framework can model SEI formation by evaluating reduction reactions of local clusters in the EDL, it suffers from a combinatorial computational bottleneck. To overcome this limitation, we introduce a machine-learning-accelerated simulation workflow (MD–DFT–ML), integrating a gradient-boosted regression model trained on EDL composition data to efficiently predict reduction potentials. We apply this framework to seven fluorinated electrolytes comprising fluorinated anions, a fluorinated ester solvent, two types of diluent (ion-solvating ester vs. non-solvating ether), and an FEC additive. The analysis shows that the EDL selectively accumulates cation-binding species; consequently, the non–cation-binding ether diluent rarely enters the EDL and makes minimal contributions to SEI formation. DFT calculations on statistically representative EDL clusters provide reduction potentials and fluorine-release pathways, while the ML model, which substantially reduces the DFT workload, predicts cluster reduction energies with a mean absolute error of 0.1 eV. The combined MD–DFT–ML approach also quantifies contributions from different sources to LiF formation in the SEI. This methodology establishes a generalizable route for multiscale modeling electrolyte and interphase design for next-generation electrochemical energy-storage systems.

DFT-MD-ML workflow↗

RDPP: Accelerating Diversity in DOE Climate Science and Resilience Research (Final Report)

The scope of the project was set out to accelerate the inclusion of diversity into the Department of Energy (DOE) Earth and Environmental Systems Sciences Division (EESSD) relevant climate science and resilience research to inclusively advance solutions. The Project Objectives were to usher in equitable use-inspired climate-related research with underrepresented Minorities of which this project helped fund 7 HU graduate students work with the DOE (three of which will graduate in Spring 2025). The two key aims underpinning that core goal were AIM1: developing partnerships (18 organized engaged, see partners list) and AIM2: Developing capabilities (3 visits to DOE facilities, 5 DOE partners visits to HU, increased visiting faculty participation in BNL-DOE lab, secured 5 grants together totaling 1.2 million in funds for HU). The project objectives were highly successful as they were designed to ambitiously pull together DOE lab researchers with the long-standing and successful transdisciplinary climate science research programs of the PI and local DC groups. The major outcomes of this RDPP program will be in the new fundamentally inclusive partnerships with DOE and HU tasked to understand the urban-rural impacts due to climate change in the US, Eastern South Atlantic (ESA) Region, related to energy issues driven by heat stress and the water cycle. Overall, this project contributes to the DOE and science community vision for catalyze connections for project-ready underrepresented minorities (URMs) at a prominent HBCU to DOE projects supported by the Biological and Environmental research (BER) Program; particularly, the Earth and Environmental Systems Sciences Division (EESSD).

54 ENVIRONMENTAL SCIENCES↗

Ion beam driven ion-acoustic waves in a plasma cylinder with negatively charged dust grains

An ion beam propagating through a magnetized potassium plasma cylinder having negatively charged dust grains drives electrostatic ion-acoustic waves to instability via Cerenkov interaction. The phase velocity of sound wave increases with the relative density of negatively charged dust grains. The unstable wave frequencies and the growth rate increase, with the relative density of negatively charged dust grains. The growth rate of the unstable mode scales as one-third power of the beam density. The real part of frequency of the unstable mode increases with the beam energy and scales as almost the one-half power of the beam energy.

43 PARTICLE ACCELERATORS↗

First study of neutrino angle reconstruction using quasielasticlike interactions in MicroBooNE

We investigate the expected precision of the reconstructed neutrino direction using a 𝜈 𝜇 -argon quasielasticlike event topology with one muon and one proton in the final state and the reconstruction capabilities of the MicroBooNE liquid argon time projection chamber. This direction is of importance in the context of DUNE sub-GeV atmospheric oscillation studies. MicroBooNE allows for a data-driven quantification of this resolution by investigating the deviation of the reconstructed muon-proton system orientation with respect to the well-known direction of neutrinos originating from the Booster Neutrino Beam with an exposure of 1.3 ×10 21 protons on target. Using simulation studies, we derive the expected sub-GeV DUNE atmospheric-neutrino reconstructed simulated spectrum by developing a reweighting scheme as a function of the true neutrino energy. We further report flux-integrated single- and double-differential cross section measurements of charged-current 𝜈 𝜇 quasielasticlike scattering on argon as a function of the muon-proton system angle using the full MicroBooNE data sets. We also demonstrate the sensitivity of these results to nuclear effects and final state hadronic reinteraction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Future Battery Material Demand Analysis Based on U.S. Department of Energy R&D Targets

The U.S. Department of Energy’s Vehicle Technologies Office (VTO) supports research, development, and deployment of efficient, sustainable transportation technologies that will improve energy efficiency and fuel economy, and enable America to use less petroleum. To accelerate the development and adoption of new technologies, VTO has developed specific targets for a wide range of powertrain components, including the energy storage system. In this study, we use Autonomie, Argonne National Laboratory’s (Argonne’s) vehicle system simulation tool to evaluate future energy storage requirements (power, energy, etc.) for different vehicle classes, powertrains, component technologies and timeframes. BatPac, Argonne’s tool dedicated to energy storage pack design and costs, is then used to quantify the materials required for each pack. Market penetrations are then used to estimate the overall material demand worldwide and in the United States, with or without recycling. The results demonstrate that the positive impact of VTO research and development will lead to significant reduction in material compared to business-as-usual due to new anode and cathode designs, along with acceleration in battery cell chemistry penetrations. In terms of material demands, it is observed that lithium demand reaches about 80,000 tons (by a factor of 42–45), nickel demand reaches about 500,000 tons (by a factor of 47–56), manganese demand reaches about 30,000–50,000 tons (by a factor of 20–34), and cobalt demand reaches about 30,000 tons (by a factor of 13–28) in the future by 2050. The individual material demand per unit energy, however, decreases significantly in the future due to advances in VTO research and development activities. The increase in battery material demands is mostly driven by increased electrified vehicle fleet penetration in the markets.

25 ENERGY STORAGE↗

Extraction of low-energy negative oxygen ions for thin film formation

Coextraction of low-energy positive and negative ions were performed using a plasma sputter-type ion source system driven by a 13.56 MHz radio frequency (rf) power. Titanium (Ti) atoms were sputtered out from a target and the sputtered neutrals were postionized in oxygen/argon (O{sub 2}/Ar) plasma prior to extraction. The negative O ions were surface-produced and self-extracted. Mass spectral analyses of the extracted ion beams revealed the dependence of the ion current on the incident rf power, induced target bias and O{sub 2}/Ar partial pressure ratio. Ti{sup +} current was found to be dependent on Ar{sup +} current and reached a saturation value with increasing O{sub 2} partial pressure while the O{sup -} current showed a peak current at around 1:9 O{sub 2}/Ar partial pressure ratio. Ti{sup +} current was several orders of magnitude higher than that of the O{sup -} current.

36 MATERIALS SCIENCE↗

Stabilization of gaze during circular locomotion in darkness. II. Contribution of velocity storage to compensatory eye and head nystagmus in the running monkey

1. Yaw eye in head (Eh) and head on body velocities (Hb) were measured in two monkeys that ran around the perimeter of a circular platform in darkness. The platform was stationary or could be counterrotated to reduce body velocity in space (Bs) while increasing gait velocity on the platform (Bp). The animals were also rotated while seated in a primate chair at eccentric locations to provide linear and angular accelerations similar to those experienced while running. 2. Both animals had head and eye nystagmus while running in darkness during which slow phase gaze velocity on the body (Gb) partially compensated for body velocity in space (Bs). The eyes, driven by the vestibuloocular reflex (VOR), supplied high-frequency characteristics, bringing Gb up to compensatory levels at the beginning and end of the slow phases. The head provided substantial gaze compensation during the slow phases, probably through the vestibulocollic reflex (VCR). Synchronous eye and head quick phases moved gaze in the direction of running. Head movements occurred consistently only when animals were running. This indicates that active body and limb motion may be essential for inducing the head-eye gaze synergy. 3. Gaze compensation was good when running in both directions in one animal and in one direction in the other animal. The animals had long VOR time constants in these directions. The VOR time constant was short to one side in one animal, and it had poor gaze compensation in this direction. Postlocomotory nystagmus was weaker after running in directions with a long VOR time constant than when the animals were passively rotated in darkness. We infer that velocity storage in the vestibular system had been activated to produce continuous Eh and Hb during running and to counteract postrotatory afterresponses. 4. Continuous compensatory gaze nystagmus was not produced by passive eccentric rotation with the head stabilized or free. This indicates that an aspect of active locomotion, most likely somatosensory feedback, was responsible for activating velocity storage. 5. Nystagmus was compared when an animal ran in darkness and in light. the beat frequency of eye and head nystagmus was lower, and the quick phases were larger in darkness. The duration of head and eye quick phases covaried. Eye quick phases were larger when animals ran in darkness than when they were passively rotated. The maximum velocity and duration of eye quick phases were the same in both conditions. 6. The platform was counterrotated under one monkey in darkness while it ran in the direction of its long vestibular time constant.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗

Visible-light-driven ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} photocatalysts with enhanced photocatalytic activity under visible light irradiation

Highlights: • The ZnFe2O4/Ag/Ag3VO4 composites were successfully synthesized by a hydrothermal method. • ZnFe2O4/Ag/Ag3VO4 composites showed better photocatalytic activity for MO and TC degradation under visible light. • The ZnFe2O4/Ag/Ag3VO4 photocatalyst is promising for designing an environmental purification material. - Abstract: A novel visible-light driven ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} photocatalyst was successfully fabricated through a two-step hydrothermal method. The structure, morphology and composition of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and X-ray photo-electron spectroscopy (XPS). The as-prepared ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} composites possessed an excellent performance in the photocatalytic degradation of methyl orange and tetracycline under visible-light irradiation. The results of electrochemical impedance spectroscopy (EIS) indicated that the ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} composite could facilitate the separation of photo-generated carriers, as well as accelerated charge transfer. The 5% ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} composite exhibited the upmost photocatalytic activity, the degradation constant of 5% ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} is as high as 1.49 times to that of Ag/Ag{sub 3}VO{sub 4}. Also, according to the trapping experiments, it’s found that the superoxide radicals (·O{sub 2}{sup −}) and hole (h{sup +}) were the predominant reactive species in this system. The ZnFe{sub 2}O{sub 4}/Ag/Ag{sub 3}VO{sub 4} photocatalyst is promising for designing as an environmental purification material in treatment of antibiotic pollutant.

36 MATERIALS SCIENCE↗

SPREADING LAYERS IN ACCRETING OBJECTS: ROLE OF ACOUSTIC WAVES FOR ANGULAR MOMENTUM TRANSPORT, MIXING, AND THERMODYNAMICS

Disk accretion at a high rate onto a white dwarf (WD) or a neutron star has been suggested to result in the formation of a spreading layer (SL)—a belt-like structure on the object's surface, in which the accreted matter steadily spreads in the poleward (meridional) direction while spinning down. To assess its basic characteristics, we perform two-dimensional hydrodynamic simulations of supersonic SLs in the relevant morphology with a simple prescription for cooling. We demonstrate that supersonic shear naturally present at the base of the SL inevitably drives sonic instability that gives rise to large-scale acoustic modes governing the evolution of the SL. These modes dominate the transport of momentum and energy, which is intrinsically global and cannot be characterized via some form of local effective viscosity (e.g., α-viscosity). The global nature of the wave-driven transport should have important implications for triggering Type I X-ray bursts in low-mass X-ray binaries. The nonlinear evolution of waves into a system of shocks drives effective rearrangement (sensitively depending on thermodynamical properties of the flow) and deceleration of the SL, which ultimately becomes transonic and susceptible to regular Kelvin–Helmholtz instability. We interpret this evolution in terms of the global structure of the SL and suggest that mixing of the SL material with the underlying stellar fluid should become effective only at intermediate latitudes on the accreting object's surface, where the flow has decelerated appreciably. In the near-equatorial regions the transport is dominated by acoustic waves and mixing is less efficient. We speculate that this latitudinal nonuniformity of mixing in accreting WDs may be linked to the observed bipolar morphology of classical nova ejecta.

79 ASTRONOMY AND ASTROPHYSICS↗

SLAC National Accelerator Laboratory FACET & TEST BEAM FACILITIES PROPOSAL: Development of Electron Radiography for Material Science

The material science community is presently limited by diagnostics in both the fabrication of materials and measuring the resulting materials characteristics of these new fabrication techniques. Because of this limitation the community is forced into an empirical mode of material fabrication, where expert judgment is used to guide manufacturing processes and the resulting materials are inspected and tested for the desired characteristics. This development approach can be time consuming and costly. The solution to this problem is to improve our fundamental understanding of materials, which requires the development of new diagnostics capable of measurement at the micron length scale, during both processing and during testing. These new measurements will enable a fundamental understanding of material characteristics allowing the development of predictive models, which will in turn enable material engineering by design rather than today’s empirical approach. Solving this problem has become a grand challenge for the materials science community. Los Alamos plans to address this challenge through the development of new diagnostics capable of measurements at the smallest length scales through the Multi-Probe Diagnostic Hall (MPDH) at the planned MaRIE (Material and Radiation In Extremes) Facility. One of the probes will be a coherent photon beam generated by an FEL driven by a multi-GeV electron beam. The photons will be used for diffraction measurements as well as radiography of relatively thin samples (nearly single grains). The same multi-GeV electron beam can be used to directly radiograph thicker systems (many grains or “bulk” material), providing high resolution measurements of the density distribution of materials during both fabrication and dynamic testing. This technique, electron radiography or eRad, that has been identified by LANL as one of the probes required to meet this grand challenge has never been demonstrated with high energy electrons. We propose to begin development of this technique with the electron beam available at FACET.

47 OTHER INSTRUMENTATION↗

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗

Production and Persistence of Extreme Two-temperature Plasmas in Radiative Relativistic Turbulence

Turbulence is a predominant process for energizing electrons and ions in collisionless astrophysical plasmas, and thus is responsible for shaping their radiative signatures (luminosity, spectra, and variability). To better understand the kinetic properties of a collisionless radiative plasma subject to externally driven turbulence, we investigate particle-in-cell simulations of relativistic plasma turbulence with external inverse Compton cooling acting on the electrons. We find that ions continuously heat up while electrons gradually cool down (due to the net effect of radiation), and hence the ion-to-electron temperature ratio T i /T e grows in time. Furthermore, we show that Ti/Te is limited only by the size and duration of the simulations (reaching ${T}_{i}/{T}_{e}\sim {10}^{3}$), indicating that there are no efficient collisionless mechanisms of electron–ion thermal coupling. This result has implications for models of radiatively inefficient accretion flows, such as observed in the Galactic center and in M87, for which so-called two-temperature plasmas with ${T}_{i}/{T}_{e}\gg 1$ have been invoked to explain their low luminosity. Additionally, we find that electrons acquire a quasi-thermal distribution (dictated by the competition of turbulent particle energization and radiative cooling), while ions undergo efficient nonthermal acceleration (acquiring a harder distribution than in equivalent nonradiative simulations). There is a modest nonthermal population of high-energy electrons that are beamed intermittently in space, time, and direction; these beamed electrons may explain rapid flares in certain high-energy astrophysical systems (e.g., in the Galactic center). These numerical results demonstrate that extreme two-temperature plasmas can be produced and maintained by relativistic radiative turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of Multi-Step CADIS Parameter Sensitivity to Neutron Flux Spectrum in Shutdown Dose Rate Calculations

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final dose rate. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. For example, SDDR assessments are required throughout the biological shield (bio-shield) of the ITER experimental facility to evaluate the required waiting period after the shutdown of ITER and to identify the locations where human accessibility should be prohibited. The bio-shield is a large cylindrical concrete structure (30 m tall and 34 m in diameter) surrounding the very complex tokamak machine. Determining the effects on SDDR of important factors, such as the cross talk (interactions) between the different ports of ITER, is possible only through full-scale simulations that involve all the complex inner details of the ITER tokamak machine. These simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate the distribution of radioisotopes causing the SDDR. Determining a good importance function that can be used in biasing a neutron MC calculation for SDDR is complicated because it is difficult to explicitly express the SDDR response function, which depends on subsequent computational steps. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid MC/deterministic method was developed to speed up the SDDR MC neutron transport calculation using an importance function that represents the neutron importance to the final SDDR. The MS-CADIS method uses the CADIS method, which has been Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). successfully used for more than a decade in radiation shielding applications to generate consistent source biasing and weight window (WW) variance reduction parameters to accelerate continuous-energy MC simulations. However, because MS-CADIS focuses on multi-step shielding calculations such as SDDR calculations, it develops an importance function for the initial radiation transport calculation (e.g., the neutron calculations in SDDR simulations) that represents the importance of particles to the final response of the overall simulation. To develop this importance function, the MS-CADIS method uses an adjoint calculation with a specific neutron adjoint source that represents the neutron's contribution to the final SDDR. Brute force calculation of the MS-CADIS neutron adjoint source requires a deterministic neutron transport calculation coupled with activation calculations in each element of the deterministic mesh. These calculations are needed to determine the MS-CADIS parameter for the neutron interactions that produce radioisotopes contributing to the SDDR. The MS-CADIS parameter is the microscopic cross section of the radioisotope-producing interaction, multiplied by the mass of this radioisotope existing at the end of the irradiation and decay scenario, and divided by the steady-state rate of the interaction. Because the activation calculations are performed for each radionuclide in each mesh element, implementation of the MS-CADIS method can be computationally expensive. However, these neutron transport and activation calculations are not needed if we assume that the radioisotopes are created due to single neutron interactions and their concentrations do not change as a result of burnup by neutron irradiation. The use of this approximation, which renders the MS-CADIS parameter independent of the neutron flux, seems reasonable in calculating the MS-CADIS importance function because this function is needed only to speed up the MC calculation, not to calculate the final SDDR. In this work, we investigate the validity of this approximation by investigating the behavior of the MS-CADIS parameter as a function of the neutron flux spectra in the Fusion Evaluated Nuclear Data Library (FENDL) Neutronics and Shielding Benchmark problem that contains representative isotopes and flux environments of fusion energy systems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Failure Mode Classification for Life Prediction Modeling of Solid-State Lighting

Since the passing of the Energy Independence and Security Act of 2007, the U.S. government has mandated greater energy independence which has acted as a catalyst for accelerating and facilitating research efforts toward the development and deployment of market-driven solutions for energy-saving homes, buildings and manufacturing, as well as sustainable transportation and renewable electricity generation. As part of this effort, an emphasis toward advancing solid-state lighting technology through research, development, demonstration, and commercial applications is assisting in the phase out of the common incandescent light bulb, as well as developing a more economical lighting source that is less toxic than compact fluorescent lighting. This has led lighting manufacturers to pursue SSL technologies for a wide range of consumer lighting applications. An SSL luminaire’s lifetime can be characterized in terms of lumen maintenance life. Lumen maintenance or lumen depreciation is the percentage decrease in the relative luminous flux from that of the original, pristine luminous flux value. Lumen maintenance life is the estimated operating time, in hours, when the desired failure threshold is projected to be reached at normal operating conditions. One accepted failure threshold of SSL luminaires is lumen maintenance of 70% -- a 30% reduction in the light output of the luminaire. Currently, the only approved lighting standard that puts forth a recommendation for long-term luminous flux maintenance projections towards a specified failure threshold of an SSL luminaire is the IES TM-28-14 (TM28) standard. iii TM28 was derived as a means to compare luminaires that have been tested at different facilities, research labs or companies. TM28 recommends the use of the Arrhenius equation to determine SSL device specific reaction rates from thermally driven failure mechanisms used to characterize a single failure mode – the relative change in the luminous flux output or “light power” of the SSL luminaire. The use of the Arrhenius equation necessitates two different temperature conditions, 25°C and 45°C are suggested by TM28, to determine the SSL lamp specific activation energy. One principal issue with TM28 is the lack of additional stresses or parameters needed to characterize non-temperature dependent failure mechanisms. Another principal issue with TM28 is the assumption that lumen maintenance or lumen depreciation gives an adequate comparison between SSL luminaires. Additionally, TM28 has no process for the determination of acceleration factors or lifetime estimations. Currently, a literature gap exists for established accelerated test methods for SSL devices to assess quality, reliability and durability before being introduced into the marketplace. Furthermore, there is a need for Physics-of-Failure based approaches to understand the processes and mechanisms that induce failure for the assessment of SSL reliability in order to develop generalized acceleration factors that better represent SSL product lifetime. This and the deficiencies in TM28 validate the need behind the development of acceleration techniques to quantify SSL reliability under a variety of environmental conditions. The ability to assess damage accrual and investigate reliability of SSL components and systems is essential to understanding the life time of the SSL device itself. The methodologies developed in this work increases the understanding of SSL devices iv through the investigation of component and device reliability under a variety of accelerated test conditions. The approaches for suitable lifetime predictions through the development of novel generalized acceleration factors, as well as a prognostics and health management framework, will greatly reduce the time and effort needed to produce SSL acceleration factors for the development of lifetime predictions.

Sakalaukus, Peter Joseph↗