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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A parametric study of slow dynamic nonlinear elasticity with comparisons to models

Several phenomenological models that aspire to quantitative description of anomalous nonlinear mesoscopic elasticity are reviewed and compared with laboratory measurements. This class of nonlinearity, best known perhaps for slow dynamics and aging, is seen widely in imperfectly consolidated granular solids but is not well understood. Typical slow dynamic tests show that a modest conditioning oscillatory "pump" strain depresses material stiffness, which then recovers like the logarithm of time after conditioning ceases. Several phenomenological models based on physical arguments have been proposed that predict the material stiffness response to arbitrary pump strain histories during conditioning and recovery. Approximate closed form and numerical solutions to the models are presented that predict the quantitative influence of three key pump parameters: the pump's strain amplitude, the pump's strain rate, and the pump’s duration. Laboratory measurements on Berea sandstone, concrete and a confined single aluminum bead find that slow dynamic responses are linear in pump strain and independent of pump frequency. Measurements also show that, after pump-off, stiffness recovers over times far longer than the pump duration. These observations and others are compared to model predictions. One of the considered models, based on a picture of fast brittle damage and slow healing, successfully matches all these behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On the various Cu-redox pathways and O 2 -mediated Bronsted-to-Lewis adsorbed-NH 3 redistribution under SCR half-cycle conditions

The Standard SCR reaction on Cu-SSZ-13 is a complex redox process facilitated by a reduction half cycle (RHC) and an oxidation half cycle (OHC). It is generally accepted that RHC requires the simultaneous presence of NO and NH 3 , while OHC requires both NO and O 2 ; however understanding of how these individual reactants impact the Cu redox cycle is limited. In this work, we provide experimental investigation of NO-only, NH 3 -only and NO+NH 3 RHC, and their relative rates. Simple kinetic models were developed to understand the dependance of NO-only and NH 3 -only RHC on Cu speciation. Various OHC routes including NO+O 2 and O 2 -only OHC, and a previously unreported H 2 O-mediated OHC pathway were also investigated. Detailed NH 3 temperature-programmed desorption studies showed that RHC selectively consumes NH 3 adsorbed on Lewis-acid sites, and that part of the remaining Bronsted-bound NH 3 moves to the Lewis-acid sites during subsequent OHC, thereby resulting in a repartitioning of adsorbed NH 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Why didn’t Oppenheimer ever win a Nobel Prize?

For his scientific achievement, he would be forever known as the father of the atomic bomb – but never as a Nobel laureate. The pinnacle of global recognition, the Nobel Prize was bestowed on 18 of J. Robert Oppenheimer’s colleagues with whom he worked at the Manhattan Project site in Los Alamos. There, in just 27 months and in a perceived race with Nazi Germany, the scientists created the first nuclear weapons. Their efforts brought the world into the Atomic Age and helped end World War II. Several were awarded the prize before coming to work at the wartime lab, while most would go on to win later in life. Oppenheimer was nominated for the Nobel Prize for Physics three times: in 1946, in 1951, and in 1967. Colleagues, scholars, and surely Oppenheimer himself pondered why he was never bestowed the honor. “To understand this,” said James Kunetka, historian and author of The General and the Genius, “you have to first examine the man’s academic life before and after the war.”

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Molecular Transducers of Physical Activity Consortium (MoTrPAC): Mapping the Dynamic Responses to Exercise

Exercise provides a robust physiological stimulus that evokes cross-talk between a wide range of tissues via hormonal, cellular and molecular signals that when repeated regularly over time (i.e., training) improves physiological capacity, benefits numerous organ systems and decreases the risk for premature mortality. In spite of its fundamental importance, a gap remains in identifying the detailed molecular signals and responses to exercise and its benefits for health and disease prevention. To further knowledge in this emerging area, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to generate a molecular map of the effects of acute and chronic exercise. MoTrPAC investigators are conducting preclinical and clinical studies to better understand the systemic effects of exercise across multiple tissues. The preclinical studies were performed on more than 700 rats with the analysis of twenty or more organs per rat. The clinical study involves a large cohort of ~2600 individuals with a range of ages and fitness levels (untrained, trained, highly trained) who will be evaluated physiologically and by molecular probing of blood, muscle and adipose tissues before and after acute and chronic endurance or resistance exercise. Multi-omic analyses (genomics, epigenomics, transcriptomics, proteomics and metabolomics/lipidomics) will be performed followed by state-of-the-art bioinformatics to create a molecular map of exercise. This mapping project will provide a public database that is expected to enhance our understanding of the health benefits of physical activity in many organ systems and potentially provide insight into mitigating diseases through activity.

Sanford, James A.↗
DOE OSTI2025

Structural and Dynamical Insights into the Formation Process of a Cross-Linked Polymer Network in Acrylic Adhesives During Thermal Curing

Many modern adhesives, sealants, and coatings rely on the controlled transition from a liquid to a solid state by forming a three-dimensional cross-linked polymer network, often referred to as curing. The curing process, which is initiated by the mixing of reactive components or an external trigger, defines the structure of a network and further controls the final mechanical properties of cured materials. However, the curing mechanism is not fully understood yet due to the lack of experimental tools capable of directly probing the structure and dynamics of a network over relevant time- and length scales. Here, in this paper, we report the curing process of a commercial two-component methyl methacrylate (MMA) adhesive using in operando X-ray photon correlation spectroscopy (XPCS), a method that closely simulates the target manufacturing environment of the adhesive. The results are then integrated with those obtained by rheology, differential scanning calorimetry (DSC), and transmission electron microscopy to establish the structure–dynamics–process–property relationship. The XPCS results identify four distinct stages in the curing process after the mixing, extrusion, and deposition of the acrylic adhesive: (i) At a cure time (or “aging time”, t age ) of less than 1 min, nanodomains of polymerized MMA are formed within a liquid monomeric MMA matrix. The average size is several nm and remains constant over t age , while the dynamics of the nanodomains are slowed down with t age due to an increase in the viscosity of the MMA matrix. (ii) After t age > 1 min, the size of the nanodomains increases with t age until the gel point (= 6.3 min after mixing as determined by rheology). The dynamics of the nanodomains also increase due to the heat generated by the exothermic reaction. (iii) At the gel point, the nanodomains begin to interconnect each other, resulting in a network structure with a characteristic length of about 100 nm. This characteristic network size does not change for the rest of the curing process up to t age = 500 min. The dynamics of the network structure, however, show a rapid slowing down with t age up to t age ≈ 12 min, corresponding to the onset of vitrification (as determined by rheology). (iv) At t age > 12 min, when the DSC and rheology data can no longer provide meaningful information, the XPCS data show a further slowing down of the network dynamics associated with vitrification. Our results provide rich and complex insights into the physics and material design of thermosets in commercially relevant processes, which are essential for future industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tungsten control in long pulse operation: feedback from WEST to ITER

The full W environment that is now foreseen for ITER puts strong emphasis on experimental results obtained in present devices in similar conditions. In this context, the WEST tokamak is well equipped to bring key contributions to the preparation of ITER operation, thanks to its capability to perform long pulses in dominant electron heating, torque-free scheme based on RF systems, and its ITER-grade actively cooled divertor. Recent results of interest cover the understanding of tungsten contamination and the evaluation of conditioning methods, the feedback on the current ramp-up phase, and the ageing of the ITER divertor components in L-mode attached condition. Further, new directions are being explored, in particular low divertor temperature operation that should be the normal operating regime of ITER. We also report on tungsten peaking physics, and the role of light impurity content.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Performance of the wavelength-shifting fiber upgrade for the Mu2e cosmic-ray veto detector

The Cosmic-Ray Veto detector for the muon-to-electron conversion experiment at Fermilab consists of four plastic scintillating counter layers read out by silicon photo-multipliers through embedded wavelength-shifting fibers. In order to increase the light yield in the most critical regions of the Cosmic-Ray Veto detector for improved background rejection, a 1.8 mm diameter fiber is being used in many of the detector's critical modules instead of the previously planned 1.4 mm diameter fiber. This paper reports the testing procedure and light properties of thirty-four 1.8 mm fiber spools, with measurements performed using a custom-built scanner. We compare these new results with previously published data from the 1.4 mm diameter fiber used for regions of the cosmic-ray veto where the increased light yield is not required. In addition, measurements of fiber aging were performed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Diabetes and hypertension are related to amyloid-beta burden in the population-based Rotterdam Study

Abstract Higher vascular disease burden increases the likelihood of developing dementia, including Alzheimer’s disease. Better understanding the association between vascular risk factors and Alzheimer’s disease pathology at the predementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (Aβ) plaques in participants from the population-based Rotterdam Study. Vascular risk factors (hypertension, hypercholesterolaemia, diabetes, obesity, physical inactivity and smoking) were assessed 13 (2004–2008) and 7 years (2009–2014) prior to 18F-florbetaben PET (2018–2021) in 635 dementia-free participants. Vascular risk factors were associated with binary amyloid PET status or continuous PET readouts (standard uptake value ratios, SUVrs) using logistic and linear regression models, respectively, adjusted for age, sex, education, APOE4 risk allele count and time between vascular risk and PET assessment. Participants’ mean age at time of amyloid PET was 69 years (range: 60–90), 325 (51.2%) were women and 190 (29.9%) carried at least one APOE4 risk allele. The adjusted prevalence estimates of an amyloid-positive PET status markedly increased with age [12.8% (95% CI 11.6; 14) in 60–69 years versus 35% (36; 40.8) in 80–89 years age groups] and APOE4 allele count [9.7% (8.8; 10.6) in non-carriers versus 38.4% (36; 40.8) to 60.4% (54; 66.8) in carriers of one or two risk allele(s)]. Diabetes 7 years prior to PET assessment was associated with a higher risk of a positive amyloid status [odds ratio (95% CI) = 3.68 (1.76; 7.61), P < 0.001] and higher standard uptake value ratios, indicating more severe Aβ pathology [standardized beta = 0.40 (0.17; 0.64), P = 0.001]. Hypertension was associated with higher SUVr values in APOE4 carriers (mean SUVr difference of 0.09), but not in non-carriers (mean SUVr difference 0.02; P = 0.005). In contrast, hypercholesterolaemia was related to lower SUVr values in APOE4 carriers (mean SUVr difference −0.06), but not in non-carriers (mean SUVr difference 0.02). Obesity, physical inactivity and smoking were not related to amyloid PET measures. The current findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer’s disease in a general population of older non-demented adults. As these conditions respond well to lifestyle modification and drug treatment, further research should focus on the preventative effect of early risk management on the development of Alzheimer’s disease neuropathology.

van Arendonk, Joyce (ORCID:0000000172941633)↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi physics simulation on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) by using Cardinal

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Separation of Lipoproteins for Quantitative Analysis of 14 C-Labeled Lipid-Soluble Compounds by Accelerator Mass Spectrometry

To date, 14 C tracer studies using accelerator mass spectrometry (AMS) have not yet resolved lipid-soluble analytes into individual lipoprotein density subclasses. The objective of this work was to develop a reliable method for lipoprotein separation and quantitative recovery for biokinetic modeling purposes. The novel method developed provides the means for use of small volumes (10–200 µL) of frozen plasma as a starting material for continuous isopycnic lipoprotein separation within a carbon- and pH-stable analyte matrix, which, following post-separation fraction clean up, created samples suitable for highly accurate 14 C/ 12 C isotope ratio determinations by AMS. Manual aspiration achieved 99.2 ± 0.41% recovery of [5- 14 CH 3 ]-(2R, 4'R, 8'R)-α-tocopherol contained within 25 µL plasma recovered in triacylglycerol rich lipoproteins (TRL = Chylomicrons + VLDL), LDL, HDL, and infranatant (INF) from each of 10 different sampling times for one male and one female subject, n = 20 total samples. Small sample volumes of previously frozen plasma and high analyte recoveries make this an attractive method for AMS studies using newer, smaller footprint AMS equipment to develop genuine tracer analyses of lipophilic nutrients or compounds in all human age ranges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Radial structure and formation of the Milky Way disc

The formation of the Galactic disc is an enthusiastically debated issue. Numerous studies and models seek to identify the dominant physical process(es) that shaped its observed properties; for example, satellite accretion, starburst, quenching, gas infall, and stellar radial migration. Taking advantage of the improved coverage of the inner Milky Way provided by the SDSS DR16 APOGEE catalogue and of the ages published in the APOGEE-AstroNN Value Added Catalogue (VAC), we examined the radial evolution of the chemical and age properties of the Galactic stellar disc with the aim of better constraining its formation. Using a sample of 199 307 giant stars with precise APOGEE abundances and APOGEE-AstroNN ages, selected in a ±2 kpc layer around the galactic plane, we assessed the dependency as a function of guiding radius of (i) the median metallicity, (ii) the ridge lines of the [Fe/H] – [Mg/Fe] and age–[Mg/Fe] distributions, and (iii) the age distribution function (ADF). The giant star sample allows us to probe the radial behaviour of the Galactic disc from R g = 0 to 14–16 kpc. The thick disc [Fe/H] – [Mg/Fe] ridge lines follow closely grouped parallel paths, supporting the idea that the thick disc did form from a well-mixed medium. However, the ridge lines present a small drift in [Mg/Fe], which decreases with increasing guiding radius. At sub-solar metallicity, the intermediate and outer thin disc [Fe/H] – [Mg/Fe] ridge lines follow parallel sequences shifted to lower metallicity as the guiding radius increases. We interpret this pattern as the signature of a dilution of the interstellar medium from R g ~ 6 kpc to the outskirts of the disc, which occurred before the onset of the thin disc formation. The APOGEE-AstroNN VAC provides stellar ages for statistically significant samples of thin disc stars from the Galactic centre up to R g ~ 14 kpc. An important result provided by this dataset is that the thin disc presents evidence of an inside-out formation up to R g ~ 10 – 12 kpc. Moreover, about ~7 Gyr ago, the [Mg/Fe] ratio in the outer thin disc (R g > 10 kpc) was higher by about ~0.03–0.05 dex than in the more internal regions of the thin disc. This could be the fossil record of a pollution of the outer disc gas reservoir by the thick disc during its starburst phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

On the origin of red spirals: does assembly bias play a role?

The formation of the red spirals is a puzzling issue in the standard picture of galaxy formation and evolution. Most studies attribute the colour of the red spirals to different environmental effects. We analyze a volume limited sample from the SDSS to study the roles of small-scale and large-scale environments on the colour of spiral galaxies. We compare the star formation rate, stellar age and stellar mass distributions of the red and blue spirals and find statistically significant differences between them at 99.9% confidence level. The red spirals inhabit significantly denser regions than the blue spirals, explaining some of the observed differences in their physical properties. However, the differences persist in all types of environments, indicating that the local density alone is not sufficient to explain the origin of the red spirals. Using an information theoretic framework, we find a small but non-zero mutual information between the colour of spiral galaxies and their large-scale environment that are statistically significant (99.9% confidence level) throughout the entire length scale probed. Such correlations between the colour and the large-scale environment of spiral galaxies may result from the assembly bias. Thus both the local environment and the assembly bias may play essential roles in forming the red spirals. The spiral galaxies may have different assembly history across all types of environments. We propose a picture where the differences in the assembly history may produce spiral galaxies with different cold gas content. Such a difference would make some spirals more susceptible to quenching. Finally, in all environments, the spirals with high cold gas content could delay the quenching and maintain a blue colour, whereas the spirals with low cold gas fractions would be easily quenched and become red.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Importance of a Moving Boundary Approach for Modeling the SEI Layer Growth to Predict Capacity Fade

One of the contributing factors to the aging of lithium-ion batteries is the growth of the solid-electrolyte interphase (SEI) layer. The growth of the SEI layer leads to the irreversible loss of lithium available for cycling and increases the resistance of the battery. Physics-based models in literature model the kinetically limited or solvent diffusion-limited growth. In such models, the interface resistance is a constant, and the contribution to the overpotential of the intercalation reaction from the SEI layer is considered to be ohmic. In this study, we propose a model that describes the growth of the SEI layer on the electrode surface as a moving interface. The transport of lithium ions and the solvent in the electrolyte are affected by this moving interface. The equations that govern the species transport and the potential drop across the SEI layer are derived from dilute solution theory and solved by transforming the coordinates of the moving boundary. The ion transport induces changes in the conductivity across the SEI layer, which affects the potential drop that arises due to its growth. The effects of this potential on capacity fade are studied over cycling the battery.

25 ENERGY STORAGE↗
DOE OSTI2021

Evaluation of Stripping Resistance of Organoclay-Modified Asphalt Binder and Aggregate Systems Using an Optical Contact Angle Analyzer

Organoclays, often referred to as nanoclays (NCs), are organically modified phyllosilicates. They are derived from naturally occurring clay minerals and possess unique characteristics in improving the physical and mechanical properties of polymers and rubbers. Recently, NCs have drawn interest in the modification of asphalt binders as micro-scale fillers. A few recent studies have revealed that the addition of NCs in asphalt binders improved binders’ stiffness, aging characteristics, and fatigue resistance. This study aims to evaluate the changes in moisture resistance of different NC-modified asphalt binders through the surface free energy (SFE) technique. This technique estimates SFE properties of binders and aggregates from static contact angle (SCA) data measured from an optical contact angle analyzer (OCA). Further, this study examines the changes in chemical compositions (functional groups) of binders due to the addition of selected NCs by using the Fourier Transformation Infrared (FTIR) technique. To this end, a commonly used performance grade (PG) binder (PG 64-22) modified with four different types (shape and size) of NCs, namely, Cloisite® 15 (C-15), Cloisite® 20 (C-20), Cloisite® Na+ (C-Na), and Cloisite® Ca++ (C-Ca) were evaluated in this study. The SFE data of five different types of aggregates from Oklahoma, namely, Davis Limestone (DL), Snyder Granite (SG), Dolese-Cooperton Limestone (DCL), Hanson-Davis Rhyolite (HDR), and Martin-Marietta-Mill-Creek Granite (MMMG), were used to perform their compatibility with the aforementioned NC-modified binders. The FTIR spectra revealed the presence of various alcohols, ethers, and esters in NC-modified asphalt binders. The moisture susceptibility analysis shows that the addition of NC results in an increase of SFE and cohesive energy of an asphalt binder, which are desired for improved moisture resistance. The addition of NC also shows improved compatibility in cases of all aggregates. Among the five aggregates, MMMCG showed the highest compatibility with all binders, followed by DCL, HDR, DL, and SG. In regard to NCs, the C-15 sample showed the highest compatibility followed by C-20, C-Na, and C-Ca.

Hossain, Zahid↗
DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗
DOE OSTI2024

Predicted Fracture Tendency of Naturally Occurring Aluminum Surface Coatings under Tensile Loading

Naturally occurring coatings on aluminum metal, such as its oxide or hydroxide, serve to protect the material from corrosion. Understanding the conditions under which these coatings mechanically fail is therefore expected to be an important aspect of predictive models for aluminum component lifetimes. To this end, we develop and apply a molecular dynamics (MD) modeling framework for conducting tension tests that is capable of isolating factors governing the mechanical strength as a function of coating chemistry, defect morphology, and variables associated with the loading path. We consider two representative materials, including γ-Al 2 O 3 and γ-Al(OH) 3 (i.e., oxide and hydroxide), both of which form readily as aluminum surface coatings. Our results indicate that defects have a significant bearing on the strength of aluminum oxide, with grain boundaries serving to reduce the strain at failure from ε zz = 0.300 to 0.219, relative to perfect single crystal. Our simulations also predict that porosity lowers the elastic stiffness and yield strength of the oxide. Relative to perfect crystal, we find porosity factors of 5%, 10% and 20% decrease the yield stress by 26%, 36% and 53%, respectively. MD predicts that perfect hydroxide and oxide single crystal have respective strains at failure of 0.08 and 0.31 under tensile uniaxial strain loading, and that the corresponding yield stresses are respectively 1.6 and 11.1 GPa. These data indicate that the hydroxide is substantially more susceptible to mechanical failure than the oxide. Our results, coupled with literature findings that indicate hot and humid conditions favor formation of hydroxide and defective oxide coatings, indicate the potential for a complicated dependence of aluminum corrosion susceptibility and stress corrosion cracking on aging history.

36 MATERIALS SCIENCE↗
DOE OSTI2021

National variability in Americans’ COVID-19 protective behaviors: Implications for vaccine roll-out

Protective behaviors such as mask wearing and physical distancing are critical to slow the spread of COVID-19, even in the context of vaccine scale-up. Understanding the variation in self-reported COVID-19 protective behaviors is critical to developing public health messaging. The purpose of the study is to provide nationally representative estimates of five self-reported COVID-19 protective behaviors and correlates of such behaviors. In this cross-sectional survey study of US adults, surveys were administered via internet and telephone. Adults were surveyed from April 30-May 4, 2020, a time of peaking COVID-19 incidence within the US. Participants were recruited from the probability-based AmeriSpeak® national panel. Brief surveys were completed by 994 adults, with 73.0% of respondents reported mask wearing, 82.7% reported physical distancing, 75.1% reported crowd avoidance, 89.8% reported increased hand-washing, and 7.7% reported having prior COVID-19 testing. Multivariate analysis (p critical value .05) indicates that women were more likely to report protective behaviors than men, as were those over age 60. Respondents who self-identified as having low incomes, histories of criminal justice involvement, and Republican Party affiliation, were less likely to report four protective behaviors, though Republicans and individuals with criminal justice histories were more likely to report having received COVID-19 testing. The majority of Americans engaged in COVID-19 protective behaviors, with low-income Americans, those with histories of criminal justice involvement, and self-identified Republicans less likely to engage in these preventive behaviors. Culturally competent public health messaging and interventions might focus on these latter groups to prevent future infections. These findings will remain highly relevant even with vaccines widely available, given the complementarities between vaccines and protective behaviors, as well as the many challenges in delivering vaccines.

60 APPLIED LIFE SCIENCES↗