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DOE OSTI2022

Engineering of Form Factor in Rotationally Symmetric Photonic Cavities for Faster Axion Searches

Form factor can be engineered in photonic cavities such that it dramatically increases the scan speed of axion haloscope detectors. Using higher-order modes of a photonic cavity, we can probe axions at larger mass ranges beyond the reach of current detectors that rely on conventional copper cavities. The main idea is to produce a higher-order mode with longitudinal field distribution that has relatively high amplitude away from both the cavity axis and the cavity walls such that it results in a relatively large form factor and maintains a high-quality factor. The detector scan speed significantly increases as it is proportional to the square of the form factor multiplied by the quality factor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

High-Current Density Durability of Pt/C and PtCo/C Catalysts at Similar Particle Sizes in PEMFCs

The durability of carbon supported PtCo-alloy based nanoparticle catalysts play a key role in the longevity of proton-exchange membrane fuel cells (PEMFC) in electric vehicle applications. To improve its durability, it is important to understand and mitigate the various factors that cause PtCo-based cathode catalyst layers (CCL) to lose performance over time. These factors include i) electrochemical surface area (ECSA) loss, ii) specific activity loss, iii) H + /O 2 -transport changes and iv) Co 2+ contamination effects. We use a catalyst-specific accelerated stress test (AST) voltage cycling protocol to compare the durability of Pt and PtCo catalysts at similar average nanoparticle size and distribution. Our studies indicate that while Pt and PtCo nanoparticle catalysts suffer from similar magnitudes of electrochemical surface area (ECSA) losses, PtCo catalyst shows a significantly larger cell voltage loss at high current densities upon durability testing. The distinctive factor causing the large cell voltage loss of PtCo catalyst appears to be the secondary effects of the leached Co 2+ cations that contaminate the electrode ionomer. A 1D performance model has been used to quantify the cell voltage losses arising from various factors causing degradation of the membrane electrode assembly (MEA).

08 HYDROGEN↗

DOE OSTI2020

Photoproduction of three jets in the CGC: gluon TMDs and dilute limit

We study the process γA → $ q\overline{q}g $ + X in the Color Glass Condensate (CGC) effective theory. After obtaining the cross section, we consider two kinematic limits which are encompassed in our result. In the so-called correlation limit, the vector sum of the transverse momenta of the three outgoing particles is small with respect to the individual transverse momenta; the cross section then simplifies considerably and can be written in a factorized form, sensitive to both the unpolarized and linearly-polarized Weizsäcker-Williams transverse momentum dependent gluon distribution function (gluon TMD). The second limit of the CGC cross section that we consider is the dilute limit, which we obtain after performing a weak-field expansion; we recover a typical linear-regime expression, involving a single unintegrated gluon distribution function. Using numerical simulations of the small-x QCD evolution of the TMDs, we investigate the rapidity dependence of the cross section in the correlation limit.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Quantifying the Relationship Between Microstructure and Performance in Gadolinium-Doped Ceria Infiltrated Ni/YSZ Symmetric Cells

Infiltration of mixed ionic/electronic conducting (MIEC) nanocatalysts into the anodes of solid oxide fuel cells (SOFCs) allow the hydrogen oxidation reaction (HOR) to occur at double-phase boundaries (DPBs), rather than being confined only to the triple phase boundaries (TPBs). In this research, we use a combination of cross-sectional scanning electron microscopy (SEM), three-dimensional (3-D) reconstruction, and electrochemical methods to characterize both baseline and gadolinium-doped ceria (GDC)-infiltrated symmetric cells, with the goal of establishing a comparison between the density of electrochemically active sites in uninfiltrated and GDC-infiltrated cells. Here, electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) analysis showed GDC infiltration decreased the overall polarization of the anode by a factor of 8.78 X, and decreased the resistance associated with the reactions at the TPBs/DPBs by a factor of over 21 X. By quantifying expected GDC deposition morphology in the Ni/YSZ anode it is estimated that reactions occur in the baseline cell up to 84 nm from the active TPB lines.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Biocatalytic gateway to convert glycerol into 3-hydroxypropionic acid in waste-based biorefineries: Fundamentals, limitations, and potential research strategies

Microbial conversion of bioenergy-derived waste glycerol into value-added chemicals has emerged as an important bioprocessing technology due to its eco-friendliness, feasible technoeconomics, and potential to provide sustainability in biodiesel and bioethanol production. Glycerol is an abundant liquid waste from bioenergy plants with a projected volume of 6 million tons by 2025, accounting for about 10% of biodiesel and 2.5% of bioethanol yields. 3-Hydroxypropionic acid (3-HP) is a major product of glycerol bioconversion, which is the third largest biobased platform compound with expected market size and value of 3.6 million tons/year and USD 10 billion/year, respectively. Despite these biorefinery values, 3-HP biosynthesis from glycerol is still at an immature stage of commercial exploitation. The main challenges behind this immaturity are the toxic effects of 3-HPA on cells, the distribution of carbon flux to undesirable pathways, low tolerance of cells to glycerol and 3-HP, co-factor dependence of enzymes, low enzyme activity and stability, and the problems of substrate inhibition and specificity of enzymes. To address these challenges, it is necessary to understand the fundamentals of glycerol bioconversion and 3-HP production in terms of metabolic pathways, related enzymes, cell factories, midstream process configurations, and downstream 3-HP recovery, as discussed in this review critically and comprehensively. It is equally important to know the current challenges and limitations in 3-HP production, which are discussed in detail along with recent research efforts and remaining gaps. Finally, possible research strategies are outlined considering the recent technological advances in microbial biosynthesis, aiming to attract further research efforts to achieve a sustainable and industrially exploitable 3-HP production technology. Here, by discussing the use of advanced tools and strategies to overcome the existing challenges in 3-HP biosynthesis, this review will attract researchers from many other similar biosynthesis technologies and provide a common gateway for their further development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Compositional and structural control in LLZO solid electrolytes

Garnet-based solid-state electrolytes (SSEs) represent a promising class of materials for next-generation batteries with improved safety and performance. However, lack of control over the composition and crystal structure of the well-known Li 7 La 3 Zr 2 O 12 (LLZO) garnet material has led to poor reproducibility with a wide range of ionic conductivities reported in the literature. In this study, the role of precursor homogeneity in controlling the compositional and structural evolution of Al-doped LLZO is explored. A novel solution-based synthesis approach is employed to demonstrate enhanced atomic-scale mixing of the starting materials in comparison to conventional solid-state preparation methods. Through this technique, it is shown that the stability and formation temperature of the highly conductive cubic phase is directly impacted by the spatial distribution of the doping element and reactant species in the precursor mixture. Precursor homogeneity was also an important factor in mitigating the formation of unwanted secondary impurities. These findings can be used to guide the synthesis of SSEs with reproducible material characteristics and enhanced electrolytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

System-level performance and degradation of 21 GWDC of utility-scale PV plants in the United States

We assess the performance of a fleet of 411 utility-scale (i.e., >5 MWAC and ground-mounted) photovoltaic (PV) projects totaling 21.1 GWDC (16.3 GWAC) of capacity, which achieved commercial operations in the United States from 2007 to 2016. This fleet of projects contributed more than 50% of all solar electricity generated in the United States in 2017. Using detailed information on individual project characteristics, in conjunction with modeled irradiance data, we assess the extent to which actual first-year performance has lived up to both modeled and stated expectations. We then analyze system-level performance degradation in subsequent years by employing a “fixed effects” regression model to statistically isolate the impact of age on system performance. We find that this fleet of utility-scale PV projects has generally lived up to ex ante expectations for first-year performance but that subsequent system-level degradation—found to be −1.3%/year (±0.2%)—has, on average, been worse than both ex ante expectations (commonly −0.5%/year) and results from past studies (ranging from −0.8%/year to −1.0%/year). We emphasize that −1.3%/year is a system-level estimate that captures more than just module degradation (e.g., including soiling, balance of plant degradation, and downtime for maintenance and/or other events). A side analysis of a variety of project characteristics suggests that system-level degradation rates tend to be of lower magnitude among newer projects and larger projects and at sites with lower long-term average temperatures.

14 SOLAR ENERGY↗

DOE OSTI2026

Weak Lensing Mass Calibration of the ACT DR5 Galaxy Clusters with the DES Year 3 Weak Lensing Data

We use weak gravitational lensing measurements from Year 3 Dark Energy Survey data to calibrate the masses of 443 galaxy clusters selected via the Sunyaev-Zel'dovich effect from Atacama Cosmology Telescope Data Release 5 maps of the cosmic microwave background. We incorporate redshift and SZ measurements for individual clusters into a hierarchical model for the stacked lensing signals and perform Bayesian analyses to constrain the hydrostatic mass bias of the clusters. Our treatment of systematic uncertainties includes a prescription for measuring and accounting for the weak lensing boost factor, consideration of a miscentering effect, as well as marginalization over uncertainties in the source galaxy photometric redshift distributions and shear calibration. The resultant constraints on the normalization of the mass-observable relation have a precision of approximately 7%, with the mean WL halo mass of M $_{500c}$ = 5.4 × 10$^{14}$ M $_{⊙}$. We measure the bias between the true cluster mass and the mass estimated from the SZ signal based on an X-ray-calibrated scaling relation assuming hydrostatic equilibrium, to be 1 - b = 0.74$^{+0.06}$ $_{-0.05}$ over the full sample. When splitting the clusters into high (z = 0.43-0.70) and low (z = 0.15-0.43) redshift bins, we measure 1 - b = 0.58$^{+0.06}$ $_{-0.05}$ and 0.81$^{+0.08}$ $_{-0.06}$, respectively. When introducing additional freedom in redshift and mass to the hydrostatic bias model, we find that 1 - b decreases with redshift (with the power law of -1.8$^{+0.5}$ $_{-0.6}$, 99.95% confidence), consistent with findings from other recent studies, while we do not find any significant trend in mass. We also demonstrate that our result is robust against various systematics such as a scale cut, priors on baryonic and miscentering parameters, and degree of scatter in mass-observable relation. The weak-lensing mass calibration presented in this study will be a useful tool for using the ACT clusters as probes of astrophysics, and as a step towards using their abundance as a cosmological probe.

Shin, T. [Carnegie Mellon U.] (ORCID:0000000263895↗

DOE OSTI2020

Preliminary Study on TRISO Fuel Cross Section Generation

Cross section self-shielding methodologies for TRISO fuel were assessed to provide accurate multigroup cross sections for a high-fidelity reactor physics code so that the code is able to accurately model and simulate advanced reactors with TRISO fuel. Initially, the two existing methodologies (the SCALE method and the Sanchez-Pomraning method) were studied and implemented to MC2-3 for detailed performance tests. Additionally, a new spatial self-shielding method, named the iterative local spatial self-shielding (ILSS) method, for particulate fuels was developed based on the disadvantage factor and implemented to MC2-3 as well. The new method approximately accounts for the effect of randomly distributed particles on the particle shadowing effect using a homogenized compact region surrounding a particle of interest at the center. The self-shielded cross sections of the particle at the center are determined iteratively since the cross sections of the homogenized compact region are calculated using them. For the energy range above 100 keV where the fuel-to-moderator ratio is more important than the random distribution of particles, a single particle unit-cell model is used by preserving the average amount of moderator per fuel particle in the system. The three self-shielding methods implemented in MC2-3 were tested using numerical benchmark problems made based on fuel compact problems of a prismatic-type very high temperature reactor. Test results indicated that the ILSS method produced slightly better results than the SCALE and Sanchez-Pomraning methods, compared to the Serpent-2 Monte Carlo results obtained with 25 independent random particle configurations. The SCALE and Sanchez-Pomraning methods tend to underestimate the heterogeneity effect by 150 and 100 pcm, respectively, while the new ILSS method overestimates the heterogeneity effect by 70 pcm. In future, the new self-shielding method will be extended to perform pebble calculations and compare results with those from the SCALE and Sanchez-Pomraning methods. Furthermore, the new method will be optimized for practical applications to on-the-fly resonance treatment for lattice or whole-core calculations for advanced reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Statistical and Machine Learning Approaches to Analyzing Pipeline Incidents in the United States (2010–2024)

This study applies machine learning methods to analyze natural gas pipeline incidents in the United States using the Pipeline and Hazardous Materials Safety Administration (PHMSA) Gas Distribution Incident Dataset (2010–2024). The dataset includes over 600 variables describing incident characteristics, infrastructure attributes, and contributing factors associated with unintentional gas releases. The objective is to assess whether these features can reliably predict the underlying cause of pipeline failures. Multinomial logistic regression and Random Forest models were developed to classify incident causes, including excavation damage, corrosion, equipment failure, and natural forces. Results show that excavation damage is both the most frequent and most predictable cause, with models achieving strong performance for this category. However, when excavation damage is excluded, model accuracy declines significantly, with some models performing near random levels. Across all approaches, severe class imbalance and limited variability in key predictors constrain predictive performance. Pipeline age and diameter emerge as the most influential variables, but they provide insufficient discriminatory power to distinguish among less frequent failure types. These findings indicate that non-excavation-related incidents are rare, heterogeneous, and weakly represented in the dataset, limiting the effectiveness of machine learning classification. Overall, this study highlights the structural limitations of the PHMSA dataset for predictive modeling and underscores the need for improved data balance and feature enrichment. The results reinforce excavation damage prevention as the most impactful strategy for reducing pipeline incidents.

03 NATURAL GAS↗

DOE OSTI2025

The Cosmic Evolution of C IV Absorbers at 1.4 < z < 4.5: Insights from 100,000 Systems in DESI Quasars

We present the largest catalog to date of triply ionized carbon (C IV ) absorbers detected in quasar spectra from the Dark Energy Spectroscopic Instrument. Using an automated matched-kernel convolution method with adaptive signal-to-noise thresholds, we identify 101,487 C IV systems in the redshift range 1.4 < z < 4.5 from 300,637 quasar spectra. Completeness is estimated via Monte Carlo simulations, and the catalog is 50% complete at EW C IV ≥ 0.4 Å. The differential equivalent width frequency distribution declines exponentially and shows weak redshift evolution. The absorber incidence per unit comoving path increases by a factor of 2–5 from z ≈ 4.5 to z ≈ 1.4, with stronger redshift evolution for strong systems. Using column densities derived from the apparent optical depth method, we constrain the cosmic mass density of C IV , Ω C IV , which increases by a factor of ∼3.8 from (0.82 ± 0.05) × 10 −8 at z ≈ 4.5 to (3.16 ± 0.2) × 10 −8 at z ≈ 1.4. From Ω C IV , we estimate a lower limit on intergalactic medium metallicity ${\mathrm{log}}({Z}_{{\rm{IGM}}}/{Z}_{\odot })\gtrsim -3.25$ at z ∼ 2.3, with a smooth decline at higher redshifts. These trends trace the cosmic star formation history and He II photoheating rate, suggesting a link between C IV enrichment, star formation, and UV background over ∼3 Gyr. The catalog also provides a critical resource for future studies connecting circumgalactic metals to galaxy evolution, especially near cosmic noon.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Considerations for Long-Term Load Forecasting in Morocco

There are many factors that determine how demand for electricity may change over time. These factors include GDP, population size, and technology diffusion and adoption. We employ a simple extrapolation of current trends in Morocco GDP to estimate how the peak demand and annual consumption may change through the year 2030. We discuss the many factors that this approach does not take into account (such as adoption of air conditioning, electric vehicles, and distributed generation).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗

DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗

DOE OSTI2024

Polarized fragmenting jet functions in inclusive and exclusive jet production

Abstract In this work, we present a complete theoretical framework for analyzing the distribution of polarized hadrons within jets, with and without measuring the transverse momentum relative to the standard jet axis. Using soft-collinear effective theory (SCET), we derive the factorization and provide the theoretical calculation of both semi-inclusive and exclusive fragmenting jet functions (FJFs) under longitudinal and transverse polarization. With the polarized FJFs, one gains access to a variety of new observables that can be used for extracting both collinear and transverse momentum dependent parton distribution functions (PDFs) and fragmentation functions (FFs). As examples, we provide numerical results for the spin asymmetry$$ {A}_{TU,T}^{\cos \left({\phi}_S-{\hat{\phi}}_{S_h}\right)} $$ A TU , T cos ϕ S − ϕ ̂ S h from polarized semi-inclusive hadron-in-jet production in polarizedppcollisions at RHIC kinematics, where a transversely polarized quark would lead to the transverse spin of the final-state hadron inside the jet and is thus sensitive to the transversity fragmentation functions. Similarly, another spin asymmetry,$$ {A}_{TU,L}^{\cos \left({\phi}_q-{\phi}_S\right)} $$ A TU , L cos ϕ q − ϕ S from polarized exclusive hadron-in-jet production in polarizedepcollisions at EIC kinematics would allow us to access the helicity fragmentation functions. These observables demonstrate promising potential in investigating transverse momentum dependent PDFs and FFs and are worthwhile for further measurements.

Physics↗

DOE OSTI2023

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a μ ≡ ( g μ - 2 ) / 2 , from the Fermilab Muon g - 2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω ˜ p ′ , and of the anomalous precession frequency corrected for beam dynamics effects, ω a . From the ratio ω a / ω ˜ p ′ , together with precisely determined external parameters, we determine a μ = 116 592 057 ( 25 ) × 10 - 11 (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a μ ( FNAL ) = 116 592 055 ( 24 ) × 10 - 11 (0.20 ppm). The new experimental world average is a μ ( exp ) = 116 592 059 ( 22 ) × 10 - 11 (0.19 ppm), which represents a factor of 2 improvement in precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Distributions of Particles Accelerated by Strong Alfvénic Turbulence

This work presents a model for generating nonthermal power-law tails of particles’ energy probability density functions in turbulent collisionless plasmas, applicable to both nonrelativistic and relativistic scenarios. We propose that strong Alfvénic turbulence energizes plasma particles through curvature acceleration, particularly for particles with Larmor radii comparable to the scales of turbulence. When the energy density of the energized particles increases, the efficiency of the energy exchange process diminishes. As a result, the acceleration process saturates, leading to power-law distributions of particle momentum and energy. In the nonrelativistic case, the momentum probability density function scales as f(p)dp ∝ p −3 dp, while in the ultrarelativistic case, the energy probability density function scales as f(γ)dγ ∝ γ −3 dγ, where γ is the Lorentz factor. This model provides a unified framework for understanding particle acceleration in both energy regimes, complementing existing analytical approaches. The predicted scalings are consistent with available observations of energetic ion distributions in the heliosphere and with the findings from numerical simulations of ultrarelativistic particle acceleration in magnetically dominated plasma turbulence.

Alfven waves↗

DOE OSTI2025

Effect of likelihood misspecification in Gaussian process-driven autonomous experimentation

In recent years, several groups have designed Autonomous Experiment (AE) models with the aim of using them as an alternative method for neutron scattering scanning. In an AE, Gaussian processes (GPs) are most frequently used due to their interpretability, their non-parametric nature, their universal approximation, and their closed-form predictive distribution. GPs have two key components, namely, the model for the likelihood of a neutron count knowing the underlying dynamic structure factor and the acquisition function. In this paper, we investigate the impact, on the quality of an AE, of the likelihood and acquisition function choices, in energy scans and (Q, ω) ones, with respect to the signal-over-noise ratio. While we hypothesized that the quality of GP predictions would decrease when the normal to Poisson likelihood approximation breaks down at low count rates, we found that the use of the correct Poisson likelihood does not improve the quality of the data collected, as well as yields very poor results in (Q, ω) scans at low count rates. In fact, the best results are obtained with a combination of normal likelihood, including the observation noise, and the change in variance acquisition function. In addition, we find that the performance, or quality of the predictive distribution, is a misleading measure of efficiency, that is, of the quality of the data collected.

Perryman, David Elliott [Inst. Laue-Langevin (ILL)↗