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DOE OSTI2012

Spatio-temporal evolution of the L {yields} I {yields} H transition

We investigate the dynamics of the low(L) {yields} high(H) transition using a time-dependent, one dimensional (in radius) model which self-consistently describes the time evolution of zonal flows (ZFs), mean flows (MFs), poloidal spin-up, and density and pressure profiles. The model represents the physics of ZF and MF competition, turbulence suppression via E Multiplication-Sign B shearing, and poloidal flows driven by turbulence. Numerical solutions of this model show that the L{yields}H transition can occur via an intermediate phase (I-phase) which involves oscillations of profiles due to ZF and MF competition. The I-phase appears as a nonlinear transition wave originating at the edge boundary and propagates inward. Locally, I-phase exhibits the characteristics of a limit-cycle oscillation. All these observations are consistent with recent experimental results. We examine the trigger of the L{yields}H transition, by defining a ratio of the rate of energy transfer from the turbulence to the zonal flow to the rate of energy input into the turbulence. When the ratio exceeds order unity, ZF shear gains energy, and a net decay of the turbulence is possible, thus triggering the L{yields}H transition. Numerical calculations indicate that the L{yields}H transition is triggered by this peak of the normalized ZF shearing. Zonal flows act as 'reservoir,' in which to store increasing fluctuation energy without increasing transport, thus allowing the mean flow shear to increase and lock in the transition. A counterpart of the L {yields} I{yields}H transition, i.e., an L{yields}H transition without I-phase, is obtained in a fast power ramp, for which I-phase is compressed into a single burst of ZF, which triggers the transition. Effects of neutral charge exchange on the L{yields}H transition are studied by varying ZF damping and neoclassical viscosity. Results show that the predicted L{yields}H transition power increases when either ZF damping or viscosity increase, suggesting a link between recycling, ZF damping, and the L{yields}H threshold. Studies of fueling effects on the transition and pedestal structure with an emphasis on the particle pinch are reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Optimization for Bioenergy Systems

The Sustainable Aviation Fuel (SAF) Grand Challenge (Langholtz, 2024 ) seeks to generate 35 billion gallons of SAF each year by 2050, with corn stover, an agricultural byproduct, playing a key role as a feedstock. This study develops an optimization framework to enhance the quality and quantity of corn stover while ensuring economic and environmental viability. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model, we simulate the effects of cover crops on rotation yield, soil moisture balance, and nitrogen cycling across diverse climates and soils. The model outputs, including yield data and soil quality changes, inform a Mixed-Integer Linear Programming (MILP) optimization model. This model aims to maximize economic and environmental returns by incorporating production costs, direct and indirect income, and environmental incentives. The optimization model evaluates 280 agriculture management plans composed of various crop management strategies, including corn stover removal rates, cover crop adoption, and fertilization practices. It seeks to identify the optimal combination of crop and tillage decisions for each subfield, maximizing profits while enhancing soil carbon sequestration and reducing greenhouse gas emissions. Outputs include detailed subfield locations, optimal management plans, and profits per hectare and per acre, allowing for comparison with literature values on farm profits. This study provides a robust optimization framework supporting the SAF Grand Challenge by proposing economically viable and environmentally sustainable strategies for corn stover utilization. The findings highlight corn stover's potential as a sustainable feedstock for SAF production, offering practical solutions to enhance its quality and quantity while maintaining soil health. Idaho is used as a case study to demonstrate the framework's applicability and effectiveness in real-world scenarios. Langholtz, M. H., Davis, M., Hellwinckel, C., De La Torre Ugarte, D., Efroymson, R., Jacobson, R., Milbrandt, A., Coleman, A., Davis, R., Kline, K. L., Badgett, A., Curran, S., Schmidt, E., Theiss, T., Fried, J., English, B., Lambert, L., Cook, H., Field, J., ... Walker, L. (2024). 2023 Billion-Ton Report: An Assessment of U.S. Renewable Carbon Resources. https://doi.org/10.2172/2441098 DSSAT Foundation. (2025). Decision Support System for Agrotechnology Transfer (DSSAT). Retrieved from https://dssat.net/

09 - BIOMASS FUELS↗

DOE OSTI2016

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3 -N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

The Circular Velocity Curve of the Milky Way from 5–25 kpc Using Luminous Red Giant Branch Stars

We present a sample of 254,882 luminous red giant branch (LRGB) stars selected from the APOGEE and LAMOST surveys. By combining photometric and astrometric information from the Two Micron All Sky Survey and Gaia survey, the precise distances of the sample stars are determined by a supervised machine-learning algorithm: the gradient-boosted decision trees. To test the accuracy of the derived distances, member stars of globular clusters (GCs) and open clusters are used. The tests by cluster member stars show a precision of about 10% with negligible zero-point offsets, for the derived distances of our sample stars. The final sample covers a large volume of the Galactic disk(s) and halo of 0 < R < 30 kpc and |Z| ≤ 15 kpc. The rotation curve (RC) of the Milky Way across the radius of 5 ≲ R ≲ 25 kpc has been accurately measured with ~54,000 stars of the thin disk population selected from the LRGB sample. The derived RC shows a weak decline along R with a gradient of -1.83 ± 0.02 (stat.) ± 0.07 (sys.) km s -1 kpc -1 , in excellent agreement with the results measured by previous studies. The circular velocity at the solar position, yielded by our RC is 234.04 ± 0.08 (stat.) ± 1.36 (sys.) km s -1 , again in great consistency with other independent determinations. From the newly constructed RC, as well as constraints from other data, we have constructed a mass model for our Galaxy, yielding a mass of the dark matter halo of M 200 = (8.05 ± 1.15) × 10 11 M ⊙ with a corresponding radius of R 200 = 192.37 ± 9.24 kpc and a local dark matter density of 0.39 ± 0.03 GeV cm -3 .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to power use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2011

Consequences of the BABAR and KLOE e{sup +}e{sup -}{yields}{pi}{sup +}{pi}{sup -} data for the determination of model-dependent {rho}-{omega} mixing effects in {Pi}{sub {rho}{omega}}(m{sub {rho}}{sup 2}) and (g-2){sub {mu}}

We update our analysis of {rho}-{omega} mixing effects in the pion form factor to incorporate the recently published BABAR and KLOE e{sup +}e{sup -}{yields}{pi}{sup +}{pi}{sup -} cross sections. Implications for {tau}-decay-based standard model estimates of the leading order hadronic contribution to the muon anomalous magnetic moment, and for the extraction of the off-diagonal vector meson self-energy matrix element, {Pi}{sub {rho}{omega}}(m{sub {rho}}{sup 2}), are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Effects of drive pulse shape on graded metal pushered single shell capsule implosions on the National Ignition Facility

Graded metal pushered single shells (PSS) are a viable alternative to low-Z capsules (Z is the atomic number) for indirect drive inertial confinement fusion implosions due to enhanced core tamping and radiation trapping, but they can be compromised by the pusher mixing with the fuel. We compare 2-shock and 3-shock laser pulses for Be/Cr PSS capsules filled with deuterium–tritium gas fuel at 6 mg/cc density. 1D radiation-hydrodynamic simulations predict higher core compression and, hence, ∼2× higher fusion yield for the 3-shock drive than for 2-shock. Nevertheless, we observe similar core ion temperatures and fusion yields for both drives. The implosion burn duration is 25% shorter and the core volume is ∼2.5× smaller for the 3-shock drive than for 2-shock, consistent with a higher compression. 1D LASNEX mix simulations using a buoyancy-drag model matching the measured yields also agree with the observed core sizes and burn durations and suggest ∼40% and ∼70% yield degradations for 2-shock and 3-shock drives due to hydrodynamic instabilities and atomic mix at the pusher–fuel interface. At the same time, 2D HYDRA simulations show that mid-mode (2–250) instability degradations are negligible for the 2-shock implosion (9%) and significant (45%) for 3-shock. Subtracting these from the 1D mix simulations, we infer similar degradations from high-mode instabilities and atomic mix for both drives. Due to its robustness to mid-mode instabilities, future pusher–gas mix studies will use the 2-shock drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

Production of K* (892) 0 and Φ (1020) in pp collisions at $\sqrt{s}$ = 7 TeV

>The production of K*(892) 0 and Φ (1020) in pp collisions at $\sqrt{s}=7~\mathrm{TeV}$ was measured by the ALICE experiment at the LHC. The yields and the transverse momentum spectra d 2 N /d y d p T at midrapidity | y |<0.5 in the range 0< p T <6 GeV/ c for K * (892) 0 and 0.4< p T <6 GeV/ c for Φ (1020) are reported and compared to model predictions. Using the yield of pions, kaons, and Ω baryons measured previously by ALICE at $\sqrt{s}=7\ \mathrm{TeV}$ , the ratios K*/K – , Φ /K * , Φ /K – , Φ / π – , and $(\Omega + \overline{\Omega })/\phi$ are presented. The values of the K*K – , Φ /K * and Φ /K – ratios are similar to those found at lower centre-of-mass energies. In contrast, the Φ / π – ratio, which has been observed to increase with energy, seems to saturate above 200 GeV. The $(\Omega + \overline {\Omega })/\phi$ ratio in the p T range 1–5 GeV/ c is found to be in good agreement with the prediction of the $\mathrm{HIJING}/\mathrm{B}\overline{\mathrm{B}}$ v2.0 model with a strong colour field.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2012

Measurement of the W W cross section in root s=7 TeV pp collisions with the ATLAS detector and limits on anomalous gauge couplings

This Letter reports a measurement of the WW production cross section in {radical}s = 7 TeV pp collisions using data corresponding to an integrated luminosity of 1.02 fb{sup -1} collected with the ATLAS detector. Using leptonic decays of oppositely charged W bosons, the total measured cross section is {sigma}(pp {yields} WW) = 54.4 {+-} 4.0 (stat.) {+-} 3.9 (syst.) {+-} 2.0 (lumi.) pb, consistent with the Standard Model prediction of {sigma}(pp {yields} WW) = 44.4 {+-} 2.8 pb. Limits on anomalous electroweak triple-gauge couplings are extracted from a fit to the transverse-momentum distribution of the leading charged lepton in the event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Optimal Microgrid Networking for Maximal Load Delivery in Phase Unbalanced Distribution Grids: A Declarative Modeling Approach

Over the last several years, microgrids have increasingly become a part of the discussion about technologies that can improve the resilience of modern electrical grids. During extreme situations, microgrids have the capability to provide electrical service to customers within their boundaries when they would otherwise experience disruptions, and, when networked together, provide services to additional customers outside the microgrid boundaries. As a result, these technologies have motivated the community to develop new approaches for leveraging networked microgrid capabilities that utilize increasing levels of modeling sophistication. This has yielded a new challenge, where it has becoming increasingly difficult to fully quantify and evaluate the contribution of such detail. Here, the primary innovation presented in this paper is a method to standardize the approach to quantifying and evaluating these contributions via a declarative modeling approach that supports seamless mix-and-match of representations to ease comparison of modeling approaches and develop comprehensive understandings of how new contributions improve solutions to this problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2010

Supergravity Higgs inflation and shift symmetry in electroweak theory

We present a model of inflation in a supergravity framework in the Einstein frame where the Higgs field of the next to minimal supersymmetric standard model (NMSSM) plays the role of the inflaton. Previous attempts which assumed non-minimal coupling to gravity failed due to a tachyonic instability of the singlet field during inflation. A canonical Kähler potential with minimal coupling to gravity can resolve the tachyonic instability but runs into the η-problem. We suggest a model which is free of the η-problem due to an additional coupling in the Kähler potential which is allowed by the Standard Model gauge group. This induces directions in the potential which we call K-flat. For a certain value of the new coupling in the (N)MSSM, the Kähler potential is special, because it can be associated with a certain shift symmetry for the Higgs doublets, a generalization of the shift symmetry for singlets in earlier models. We find that K-flat direction has H{sub u}{sup 0} = −H{sub d}{sup 0*}. This shift symmetry is broken by interactions coming from the superpotential and gauge fields. This flat direction fails to produce successful inflation in the MSSM but yields a more interesting model in the NMSSM, even though it does not pass existing cosmological constraints. We point out that, in building more sophisticated models of this type, one may also need to take into account their implications for axion searches or other elementary particle constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

A cross-study analysis of drug response prediction in cancer cell lines

Abstract To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross-validation within a single study to assess model accuracy. While an essential first step, cross-validation within a biological data set typically provides an overly optimistic estimate of the prediction performance on independent test sets. To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: National Cancer Institute 60, ancer Therapeutics Response Portal (CTRP), Genomics of Drug Sensitivity in Cancer, Cancer Cell Line Encyclopedia and Genentech Cell Line Screening Initiative (gCSI). Based on observed experimental variability across studies, we explore estimates of prediction upper bounds. We report performance results of a variety of machine learning models, with a multitasking deep neural network achieving the best cross-study generalizability. By multiple measures, models trained on CTRP yield the most accurate predictions on the remaining testing data, and gCSI is the most predictable among the cell line data sets included in this study. With these experiments and further simulations on partial data, two lessons emerge: (1) differences in viability assays can limit model generalizability across studies and (2) drug diversity, more than tumor diversity, is crucial for raising model generalizability in preclinical screening.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Complete asymptotically safe embedding of the standard model

We introduce and discuss the “Tetrad Model”, a large color/flavor embedding of the Standard model which has an interacting ultraviolet fixed point. It is demonstrated that its extended-Pati-Salam symmetry is broken radiatively via the Coleman-Weinberg mechanism, while the remaining electroweak symmetry is broken when mass-squared terms run negative. In the IR the theory yields just the Standard Model, augmented by the fact that the Higgs fields carry the same generation indices as the matter fields. It is also shown that the Higgs mass-squareds develop a hierarchical structure in the IR, from a UV theory that is asymptotically flavor symmetric, opening up an interesting direction for explaining the emergence of the observed flavor structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2011

Crystal structure of the sweet-tasting protein thaumatin II at 1.27 A

Highlights: {yields} X-ray crystallographic structure of sweet-tasting protein, thaumatin II, was determined at a resolution of 1.27 A. {yields} The overall structure of thaumatin II is similar to that of thaumatin I, but a slight shift of the C{alpha} atom of G96 in thaumatin II was observed. {yields} The side chain of two critical residues, 67 and 82, for sweetness was modeled in two alternative conformations. {yields} The flexibility and fluctuation of side chains at 67 and 82 seems to be suitable for interaction of thaumatin molecules with sweet receptors. -- Abstract: Thaumatin, an intensely sweet-tasting protein, elicits a sweet taste sensation at 50 nM. Here the X-ray crystallographic structure of one of its variants, thaumatin II, was determined at a resolution of 1.27 A. Overall structure of thaumatin II is similar to thaumatin I, but a slight shift of the C{alpha} atom of G96 in thaumatin II was observed. Furthermore, the side chain of residue 67 in thaumatin II is highly disordered. Since residue 67 is one of two residues critical to the sweetness of thaumatin, the present results suggested that the critical positive charges at positions 67 and 82 are disordered and the flexibility and fluctuation of these side chains would be suitable for interaction of thaumatin molecules with sweet receptors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity

High-throughput and computational tools provide a new opportunity to calculate combined bioactivity of exposure to diverse chemicals acting through a common mechanism. We used high throughput in vitro bioactivity data and exposure predictions from the U.S. EPA’s Toxicity and Exposure Forecaster (ToxCast and ExpoCast) to estimate combined estrogen receptor (ER) agonist activity of non-pharmaceutical chemical exposures for the general U.S. population. High-throughput toxicokinetic (HTTK) data provide conversion factors that relate bioactive concentrations measured in vitro (µM), to predicted population geometric mean exposure rates (mg/kg/day). These data were available for 22 chemicals with ER agonist activity and were estimated for other ER bioactive chemicals based on the geometric mean of HTTK values across chemicals. For each chemical, ER bioactivity across ToxCast assays was compared to predicted population geometric mean exposure at different levels of in vitro potency and model certainty. Dose additivity was assumed in calculating a Combined Exposure-Bioactivity Index (CEBI), the sum of exposure/bioactivity ratios. Combined estrogen bioactivity was also calculated in terms of the percent maximum bioactivity of chemical mixtures in human plasma using a concentration-addition model. Estimated CEBIs vary greatly depending on assumptions used for exposure and bioactivity. In general, CEBI values were <1 when using median of the estimated general population chemical intake rates, while CEBI were ≥1 when using the upper 95th confidence bound for those same intake rates for all chemicals. Concentration-addition model predictions of mixture bioactivity yield comparable results. Based on current in vitro bioactivity data, HTTK methods, and exposure models, combined exposure scenarios sufficient to influence estrogen bioactivity in the general population cannot be ruled out. Future improvements in screening methods and computational models could reduce uncertainty and better inform the potential combined effects of estrogenic chemicals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A reduced order sulfuric acid decomposition model for a nuclear-powered hybrid sulfur cycle

A reduced order model of sulfuric acid decomposition within a bayonet chemical reactor was developed to support the U. S. Department of Energy Integrated Energy System program, and address the lack of knowledge in scaling and integration for joint chemical and nuclear processes. Sulfuric acid decomposition within a bayonet reactor was modeled to provide chemical and thermodynamic data relevant to advanced nuclear reactor-driven integrated energy systems based on desired operational scale and operational conditions. The temperature range required for high-temperature advanced nuclear reactor integrated energy systems, 750-850 °C, was shown to produce reasonable agreement (within a few percent relative error) with past models and experimental data, and yielded good efficiency results for bayonet reactor operations. The results of the reduced order model agreed with previous work from Savannah River National Labs within a maximum of 3.4% error on the decomposition of sulfur trioxide, and on previous Hybrid Sulfur flowsheets from Gorensek and Summers that showed operational temperature, pressure, and composition ranges for efficiency which made the Hybrid Sulfur cycle competitive with water electrolysis. Here, the agreement with previous high-fidelity models provided a framework for future Integrated Energy System grid evaluations with an advanced nuclear reactor and large-scale hydrogen production using a mathematical model to represent chemical operations.

08 HYDROGEN↗

DOE OSTI2024

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗

DOE OSTI2021

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↗