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At least 55 records · Page 3

Lifetime measurements in 206 Po with a shell-model interpretation

The lifetimes of the first excited 2⁺ and 4⁺ states in 206 Po were measured using the recoil-distance Dopplershift method. The experimental results were compared to large-scale shell-model calculations that describe the deduced transition probabilities well. Those calculations were extended to the neighboring 204,208 Po isotopes giving a good overall description of the yrast states. However, the calculations underpredict the energies of the 6+1 and 8+1 states, which suggests that further improvement of the proton-neutron interaction is required.

190 ≤ A ≤ 219↗

Tensile Property and Lifetime Prediction for Low-Temperature Aged Uranium-Niobium Alloys

Thermal aging models and lifetime predictions for uranium-niobium (U-Nb) alloys were created using an approach similar to those previously employed. Lifetime estimates for generic U-6Nb components were thus updated; the reported value being 800 years. This update represents a small change in lifetime vs. that of the 2012 assessment (540 years). This lifetime estimate emerged from consideration of several model fits specific to the aging datasets and properties chosen. Aging was quantified using quasi-static tensile properties measured on specimens artificially aged for up to 10 years. The major change relative to the most recent 2012 LANL assessment was that a more comprehensive body of U-Nb literature data was mined, in addition to being augmented by the latest LANL and UK AWE data. The tensile data compilation was published separately (LANL report LA-14493, December 2016). Recognizing the chemical banding of industrially produced U-6Nb, models were developed for the mid-range (6 wt.%) and extrema (4 and 8 wt.%) compositions. Lifetime estimates were calculated for all three alloy classes (4, 6, 8 wt.% nominal) and two measures of total tensile elongation (TE) to failure, namely TE-ext. — extensometer method, and TE-NCD — normalized crosshead displacement method. The conservative assumption was made that whichever composition (4, 6, or 8 wt.% Nb) and property (TE-ext or TE-NCD) was the first to cross the ductility failure threshold would limit the lifetime of the entire component. Tensile strength properties did not figure into the lifetime predictions, but could be useful as age-sensitive diagnostics and were also modeled. Of these, only first yield strength is expected to show a change at 40°C aging vs. time = 0 over the ~100-year timespan of engineering interest. Second yield strength evolves more slowly, and ultimate tensile strength slower still. Among all the models, the apparent activation energies for aging were mostly in the narrow 29– 37 kcal/mol range, which is close to that for diffusion of Nb in gamma-uranium. This agreement may be coincidental. The data from recent long-term aging studies substantially improved the model fit quality and robustness of the lifetimes. Appendices document sensitivity studies of the model fits and lifetimes with respect to using more limited datasets. These results highlight the limitations of relying solely on data from scattered literature studies and smaller datasets more generally.

36 MATERIALS SCIENCE↗

Standard Model prediction of the Bc lifetime

Applying an operator product expansion approach we update the Standard Model prediction of the B c lifetime from over 20 years ago. The non-perturbative velocity expansion is carried out up to third order in the relative velocity of the heavy quarks. The scheme dependence is studied using three different mass schemes for the b ¯ and c quarks, resulting in three different values consistent with each other and with experiment. Special focus has been laid on renormalon cancellation in the computation. Uncertainties resulting from scale dependence, neglecting the strange quark mass, non-perturbative matrix elements and parametric uncertainties are discussed in detail. The resulting uncertainties are still rather large compared to the experimental ones, and therefore do not allow for clear-cut conclusions concerning New Physics effects in the B c decay.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lifetime measurements of excited states in neutron-rich 53 Ti: Benchmarking effective shell-model interactions

Level lifetimes of the yrast (5/2 - ) to 13/2 - states in the neutron-rich nucleus 53 Ti, produced in a multinucleon-transfer reaction, have been measured for the first time. The recoil distance Doppler-shift method was employed and lifetimes of the excited states were extracted by a lineshape analysis aided by GEANT4-based Monte-Carlo simulations. The experiment was performed at the Grand Accelerateur National d'Ions Lourds facility in Caen, France, by using the Advanced Gamma Tracking Array for the gamma-ray detection coupled to the large-acceptance variable mode spectrometer for an event-by-event particle identification and the Cologne plunger for deep-inelastic reactions. Reduced transition probabilities, deduced from the lifetimes, give new information on the nuclear structure of 53 Ti, and are used to benchmark different shell-model calculations using established interactions in the fp shell.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics

Abstract. Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and black carbon (BC) particulate emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as particulate phase sulfate (SO4) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of −0.35 W m−2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8 d), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models.

54 ENVIRONMENTAL SCIENCES↗

Corrigendum to “The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics” published in Atmos. Chem. Phys., 23, 14779–14799, 2023

Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO 2 injection, seasonality of SO 2 and black carbon (BC) particulate emissions, and the assumed fraction of SO 2 emissions that is injected into the atmosphere as particulate phase sulfate (SO 4 ) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO 2 , SO 4 , and BC, with a particularly large relative variation for SO 2 , which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO 2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35?W?m-2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8?d), surface SO 2 concentration (up to 59?% decrease), and surface sulfate concentration (up to 23?% increase). Emitting SO 2 at height consistently increased SO 2 and SO 4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO 4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO 4 emission fraction are accurately and consistently represented in global models.

Ahsan, Hamza [Pacific Northwest National Laborator↗

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Heavy boron doping effects on biaxially tensile strained germanium (>1.5%) investigated via structural characterization, effective lifetime assessment and atomistic modeling

Highly tensile strained germanium (ε-Ge) represents an essential material system for emerging electronic and photonics applications. Moreover, adjusting the doping levels to moderate or high concentrations can effectively tailor the properties of ε-Ge for specific applications. This article combines experimental characterization with a theoretical framework to examine the effects of heavy elemental boron (B) doping on pseudomorphic sub-50 nm ε-Ge. High resolution X-ray diffractometry is used to validate tensile strain levels of 1.53% and 1.68% in Ge epilayers, surpassing the indirect-to-direct band gap crossover point at ∼1.5% biaxial tensile strain. Cross-sectional transmission electron microscopy revealed visual evidence of stacking faults and surface roughening in 1.68% ε-Ge, although a coherent and abrupt Ge/III–V heterointerface is observed, devoid of interfacial misfit dislocations. Effective lifetime measurements demonstrated approximately twofold enhancement in 1.53% B-doped ε-Ge (N B ∼7 × 10 19 cm −3 ) compared to its unstrained B-doped counterpart, while no such improvement was observed in 1.68% B-doped ε-Ge. This lack of enhancement is attributed to the presence of stacking faults and surface roughness within the ε-Ge epilayer. Through density functional theory calculations, we independently demonstrate that substitutional B atoms induce local deformation of Ge–Ge bonds in both unstrained Ge and ε-Ge epilayers, resulting in an additive tensile strain. This phenomenon could potentially lead to dynamic reduction and overcoming of the critical layer thickness for the system, facilitating the nucleation and subsequent glide of 90° leading Shockley partial dislocations, thereby generating stacking faults. In essence, these findings establish an upper limit on the B-doping concentration that can be achieved in highly ε-Ge epilayers, and collectively, offer valuable insights into the significance of heavy doping in Ge-based heterostructures. As such, this study delineates a fundamental constraint for integrating heavily doped ε-Ge in high-performance optoelectronic systems, necessitating precise strain-doping co-optimization to avoid performance degradation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Collider searches for scalar singlets across lifetimes

Spin-0 singlets arise in well-motivated extensions of the Standard Model. Their lifetime determines the best search strategies at hadron and lepton colliders. To cover a large range of singlet decay lengths, we investigate bounds from Higgs decays into a pair of singlets, considering signatures of invisible decays, displaced and delayed jets, and coupling fits of untagged decays. We examine the generic scalar singlet and the relaxion, and derive a matching as well as qualitative differences between them. For each model, we discuss its natural parameter space and the searches probing it.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Satellite-based evaluation of AeroCom model bias in biomass burning regions

Global models are widely used to simulate biomass burning aerosol (BBA). Exhaustive evaluations on model representation of aerosol distributions and properties are fundamental to assess health and climate impacts of BBA. Here we conducted a comprehensive comparison of Aerosol Comparisons between Observations and Models (AeroCom) project model simulations with satellite observations. A total of 59 runs by 18 models from three AeroCom Phase-III experiments (i.e., biomass burning emissions, CTRL16, and CTRL19) and 14 satellite products of aerosols were used in the study. Aerosol optical depth (AOD) at 550 nm was investigated during the fire season over three key fire regions reflecting different fire dynamics (i.e., deforestation-dominated Amazon, Southern Hemisphere Africa where savannas are the key source of emissions, and boreal forest burning in boreal North America). The 14 satellite products were first evaluated against AErosol RObotic NETwork (AERONET) observations, with large uncertainties found. But these uncertainties had small impacts on the model evaluation that was dominated by modeling bias. Through a comparison with Polarization and Directionality of the Earth’s Reflectances measurements with the Generalized Retrieval of Aerosol and Surface Properties algorithm (POLDER-GRASP), we found that the modeled AOD values were biased by –93 % to 152 %, with most models showing significant underestimations even for the state-of-the-art aerosol modeling techniques (i.e., CTRL19). By scaling up BBA emissions, the negative biases in modeled AOD were significantly mitigated, although it yielded only negligible improvements in the correlation between models and observations, and the spatial and temporal variations in AOD biases did not change much. For models in CTRL16 and CTRL19, the large diversity in modeled AOD was in almost equal measures caused by diversity in emissions, lifetime, and the mass extinction coefficient (MEC). We found that in the AeroCom ensemble, BBA lifetime correlated significantly with particle deposition (as expected) and in turn correlated strongly with precipitation. Additional analysis based on Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aerosol profiles suggested that the altitude of the aerosol layer in the current models was generally too low, which also contributed to the bias in modeled lifetime. Modeled MECs exhibited significant correlations with the Ångström exponent (AE, an indicator of particle size). Comparisons with the POLDER-GRASP-observed AE suggested that the models tended to overestimate the AE (underestimated particle size), indicating a possible underestimation of MECs in models. The hygroscopic growth in most models generally agreed with observations and might not explain the overall underestimation of modeled AOD. Our results imply that current global models contain biases in important aerosol processes for BBA (e.g., emissions, removal, and optical properties) that remain to be addressed in future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗

Power Electronics Materials and Bonded Interfaces - Reliability and Lifetime

The emergence of wide-bandgap (WBG) devices in power electronics packages has brought significant attention to the reliability and thermal performance of the bonded interfaces. These interfaces, such as die-attach and substrate-attach, need to withstand the severe stress induced on them by the high-temperature (> 200°C) operation of the WBG devices. Sintered silver and transient liquid phase alloys are key bonded interfaces that can enable the high-temperature operation of WBG devices, however it is essential to evaluate their reliability and study the possible failure mechanisms before they can be used in power electronics packages. Sintered silver is already being adopted in commercial packages as a die-attach, but large-area substrate-attach offers additional reliability challenges. In this project, we investigate the reliability of these interface materials under accelerated thermal cycling and correlate these results with finite element simulations to develop lifetime prediction models. The failure mechanisms of these bonded interfaces are also studied.

47 OTHER INSTRUMENTATION↗

BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py

Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.

Smith, Kandler↗

Rapid assessment of the creep rupture life of metals: A model enabling experimental design

Prediction of the creep rupture life of engineering metals is critical for qualification and design of new materials. The use of long-term creep tests and the need to quantify the performance variability in a priori similar systems hinder the rapid creep assessment of a given material. Therefore, it is essential to develop methods that can extrapolate the long-term performance of alloys and the associated variability from short-term experiments. To this end, this study introduces a new model which enables the estimation of the rupture life of a material for a given stress and temperature. This model relies on two components. First, a new relation for the minimum creep rate (MCR) of materials is introduced. It includes a stress dependent stress exponent allowing the model to capture the variation of MCR across a wide range of temperatures and stresses. Second, employing the Monkman-Grant (MG) law, we establish a relation between stress, temperature and creep rupture life. Together, these two elements yield a new closed-form mathematical expression for the Larson Miller parameter as a function of stress and temperature. This expression captures the creep rupture time for many metals (Gr91, Copper, Gr122 and 347H) and compares favorably with alternate empirical approaches. The model is then used to assess the minimum duration of creep rates necessary to qualify the material up to 100000h. Furthermore, it is found that depending on the material system, creep tests as few as five limited to 5000 h for steels (Gr91, Gr122, 347H) and 100 h for copper are sufficient to model creep lifetimes. Finally, using a Bayesian inference-based approach to calibrate the model, we demonstrate that variability in rupture life can be captured via the quantification of the uncertainty in the model parameters and extrapolated from a limited number of short to moderately short creep tests; thereby paving the way for accelerated creep testing.

36 MATERIALS SCIENCE↗

$\mathrm{PPT}$-Multicore: performance prediction of Open$\mathrm{MP}$ applications using reuse profiles and analytical modeling

In this report we present PPT-Multicore, an analytical model embedded in the Performance Prediction Toolkit (PPT) to predict parallel applications’ performance running on a multicore processor. PPT-Multicore builds upon our previous work towards a multicore cache model. We extract LLVM basic block labeled memory trace using an architecture-independent LLVM-based instrumentation tool only once in an application’s lifetime. The model uses the memory trace and other parameters from an instrumented sequentially executed binary. We use probabilistic and computationally efficient reuse profiles to predict the cache hit rates and runtimes of OpenMP programs’ parallel sections. We model Intel’s Broadwell, Haswell, and AMD’s Zen2 architectures and validate our framework using different applications from PolyBench and PARSEC benchmark suites. The results show that PPT-Multicore can predict cache hit rates with an overall average error rate of 1.23% while predicting the runtime with an error rate of 9.08%.

97 MATHEMATICS AND COMPUTING↗

Lifetime measurements probing collectivity in the ground-state band of 32 Mg

The signatures of inversion between normal and intruder configurations of particle-hole excitations across the N = 20 shell gap in the neutron-rich isotope 32 Mg have long been of keen interest. Electromagnetic transition rates in the ground-state band are key quantities that provide insights into collective properties associated with the contributions of the 2p2h and 4p4h intruder configurations. The combination of TRIPLEX, GRETINA, and the S800 spectrograph enables model-independent lifetime measurements to determine electromagnetic transition rates in rare isotopes. The reduced E2 transition rates in 32 Mg between the 2$^{+}_{1}$ and 0$^{+}_{1}$ states and between the 4$^{+}_{1}$ and 2$^{+}_{1}$ states have been measured, the latter representing the first experimental B(E2) value for this transition. Here, the B(E2) strengths indicate large collectivity and strong contributions from the 2p2h and 4p4h intruder configurations that may change with spin in the ground-state band of 32 Mg.

20 ≤ A ≤ 38↗

Electrorefiner Speciation and Phase Model for Prediction of Operation Lifetime

The Mk IV electrorefiner (ER) at Idaho National Laboratory has recovered uranium metal from used nuclear fuels for 27 years. Thus, large quantities of fission product chlorides more electropositive than uranium have accumulated in the ER salt, increasing the complexity of phase equilibria and salt speciation. Importantly, the melt temperature of the salt increases with ER operation and will ultimately exceed design limits without intervention. Methods to remove fission products from molten chloride salt are known, but their implementation at scale is not yet demonstrated. In this work, historical ER composition and differential scanning calorimetry (DSC) are utilized to develop coupled speciation and chloride salt solution thermochemistry models, which enable accurate present-day analysis of ER salt as well as forecast its future disposition. The developed thermochemical models are applicable to chloride salts generally and have been made available in the Molten Salt Thermal Properties Database – Thermochemical.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗