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DOE OSTI2025

Physics-Informed Gaussian Process Inference of Liquid Structure from Scattering Data

We present a nonparametric Bayesian framework to infer radial distribution functions from experimental scattering measurements with uncertainty quantification using nonstationary Gaussian processes. The Gaussian process prior mean and kernel functions are designed to mitigate well-known numerical challenges with the Fourier transform, including discrete measurement binning and detector windowing, while encoding fundamental yet minimal physical knowledge of the liquid structure. We demonstrate uncertainty propagation of the Gaussian process posterior to unmeasured quantities of interest. Experimental radial distribution functions of liquid argon and water with uncertainty quantification are provided as both a proof of principle for the method and a benchmark for molecular models.

Chemical structure↗

DOE OSTI2024

Machine learning-guided discovery of gas evolving electrode bubble inactivation

The adverse effects of electrochemical bubbles on the performance of gas-evolving electrodes are well known, but studies on the degree of adhered bubble-caused inactivation, and how inactivation changes during bubble evolution are limited. We study electrode inactivation caused by oxygen evolution while using surface engineering to control bubble formation. We find that the inactivation of the entire projected area, as is currently believed, is a poor approximation which leads to non-physical results. Using a machine learning-based image-based bubble detection method to analyze large quantities of experimental data, we show that bubble impacts are small for surface engineered electrodes which promote high bubble projected areas while maintaining low direct bubble contact. We thus propose a simple methodology for more accurately estimating the true extent of bubble inactivation, which is closer to the area which is directly in contact with the bubbles.

Lake, Jack R.↗

DOE OSTI2023

The star-formation history in the last 10 billion years from CIB cross-correlations

ABSTRACT The cosmic infrared background (CIB) traces the emission of star-forming galaxies throughout all cosmic epochs. Breaking down the contribution from galaxies at different redshifts to the observed CIB maps would allow us to probe the history of star formation. In this paper, we cross-correlate maps of the CIB with galaxy samples covering the range z ≲ 2 to measure the bias-weighted star-formation rate (SFR) density 〈bρSFR〉 as a function of time in a model independent way. This quantity is complementary to direct measurements of the SFR density ρSFR, giving a higher weight to more massive haloes, and thus provides additional information to constrain the physical properties of star formation. Using cross-correlations of the CIB with galaxies from the DESI Legacy Survey and the extended Baryon Oscillation Spectroscopic Survey, we obtain high signal-to-noise ratio measurements of 〈bρSFR〉, which we then use to place constraints on halo-based models of the star-formation history. We fit halo-based SFR models to our data and compare the recovered ρSFR with direct measurements of this quantity. We find a qualitatively good agreement between both independent data sets, although the details depend on the specific halo model assumed. This constitutes a useful robustness test for the physical interpretation of the CIB, and reinforces the role of CIB maps as valuable astrophysical probes of the large-scale structure. We report our measurements of 〈bρSFR〉 as well as a thorough account of their statistical uncertainties, which can be used to constrain star-formation models in combination with other data.

Astronomy & Astrophysics↗

DOE OSTI2021

Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Fission Evaluation Tools and Analytics (FETA)

This living document presents the Python package FETA. FETA computes observables resulting from the fission process. This document provides the definition of these observables as well as the physics models that are implemented to compute them. Some of these models are used to determine the initial conditions of fission fragments, e.g., the excitation energy E* and spin distribution p(J, π) at scission for prompt decay, while others are related to the nuclear structure and decay properties of the fragments, e.g. the ground-state properties, level density and low-lying excitation spectrum, γ-strength functions and electromagnetic transitions, and neutron transmission coefficients. The end goal for FETA is to enable users to substitute every one of these models by their own files providing these quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Challenges of standard halo models in constraining galaxy properties from cosmic infrared background anisotropies

The halo model, combined with halo occupation distribution (HOD) prescriptions, is widely used to interpret cosmic infrared background (CIB) anisotropies and extract physical information about star-forming galaxies and their connection to large-scale structures. Recent CIB-specific implementations of the halo model have adopted more physical parameterizations. However, the extent to which these models can reliably recover meaningful physical parameters remains uncertain. We assessed whether the current parameterization of CIB halo models is sufficient to recover astrophysical quantities, such as star formation efficiency, η(M h , z), and halo mass at which the peak of star formation efficiency occurs, M max , when fit to mock data. We also assessed whether discrepancies arise from assumptions about galaxy emission (the HOD ingredients) or from more fundamental components in the halo model, such as bias and matter clustering. We fit the M21 CIB HOD model, implemented within the halo model framework, to mock CIB power spectra and star formation rate density (SFRD) data generated from the SIDES-Uchuu simulation, and compared the best-fit parameters to the known simulation inputs. We then repeated the analysis using a simplified version of the simulation (SSU), explicitly designed to match the HOD assumptions. A detailed comparison of model and simulation outputs was carried out to trace the origin of observed discrepancies. While the M21 HOD model provides a good fit to the mock data, it failed to recover the intrinsic parameters accurately, particularly the halo mass at which star formation efficiency peaks. This mismatch persists even when fitting data generated with the same model assumptions. We find strong agreement (within 5%) in the emission-related components (SFRD, emissivity), but observe a scale- and redshift-dependent offset exceeding 20% in the two-halo term of the CIB power spectrum. This likely arises from limitations in the treatment of halo bias and matter clustering within the linear approximation. Additionally, incorporating scatter in the SFR–halo mass relation and the spectral energy distribution (SED) templates significantly affects the shot noise (∼50%), but has only a modest impact (less than 10%) on the clustered component. These results suggest that recovering physical parameters from CIB clustering requires improvements to the cosmological ingredients of the halo model framework, such as adopting scale-dependent halo bias and nonlinear matter power spectra in addition to careful modeling of emission physics.

cosmic background radiation↗

DOE OSTI2021

Swelling-Induced Symmetry Breaking: A Versatile Approach to the Scalable Production of Colloidal Particles with a Janus Structure

Janus particles are widely sought for applications related to colloidal assembly, stabilization of emulsions, and development of active colloids, among others. Here we report a versatile route to the fabrication of well-controlled Janus particles by simply breaking the symmetry of spherical particles with swelling. When a polystyrene (PS) sphere covered by a rigid shell made of silica or polydopamine is exposed to a good solvent for PS, a gradually increased pressure will be created inside the shell. If the pressure becomes high enough to poke a hole in the shell, the spherical symmetry will break while pushing out the swollen PS through the opening to generate a Janus particle comprised of two distinct components. One of the components is made of PS and its size is controlled by the extent of swelling. The other component is comprised of the rigid shell and remaining PS, with its overall diameter determined by the original PS sphere and the rigid shell. This solution-based route holds promises for the scalable production of complex Janus particles with a variety of compositions and in large quantities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Phonon dynamics in the chiral Kitaev spin liquid

Here, we investigate the effect of a magnetic field on the extended Kitaev spin-liquid state through phonon dynamics. Using a constrained fermionic self-consistent mean field method, we analyze the quantum spin liquid (QSL) ground state for the extended Kitaev model with both the Zeeman term and the perturbative three-spin interaction term 𝜅. Our results demonstrate the dependence of the stability of the Kitaev QSL state on the field direction, consistent with findings in the literature. Additionally, we calculate the phonon dynamics for acoustic phonons coupled to the Majorana fermion excitations of the Kitaev spin-liquid state, discussing the temperature and field evolution of these quantities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Sensitivity of EDM experiments in paramagnetic atoms and molecules to hadronic CP violation

Experiments searching for the electric dipole moment (EDM) of the electron d e utilize atomic/molecular states with one or more uncompensated electron spins, and these paramagnetic systems have recently achieved remarkable sensitivity to d e . If the source of CP violation resides entirely in the hadronic sector, the two-photon exchange processes between electrons and the nucleus induce CP-odd semileptonic interactions, parametrised by the Wilson coefficient C SP , and provide the dominant source of EDMs in paramagnetic systems instead of d e . We evaluate the C SP coefficients induced by the leading hadronic sources of CP violation, namely nucleon EDMs and CP-odd pion-nucleon couplings, by calculating the nucleon-number-enhanced CP-odd nuclear scalar polarisability, employing chiral perturbation theory at the nucleon level and the Fermi-gas model for the nucleus. This allows us to translate the ACME EDM limits from paramagnetic ThO into novel independent constraints on the QCD theta term |$\bar θ$| < 3 × 10 –8 , proton EDM |d p | < 2 × 10 –23 e cm, isoscalar CP-odd pion-nucleon coupling |$\bar g$$^{(1)}_{πNN}$| < 4 × 10 –10 , and color EDMs of quarks |$\tilde d$ u -$\tilde $d d | < 2 × 10 –24 cm. We note that further experimental progress with EDM experiments in paramagnetic systems may allow them to rival the sensitivity of EDM experiments with neutrons and diamagnetic atoms to these quantities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Entanglement entropy across the lattice-continuum correspondence

This paper revisits the standard calculations of free field entanglement entropy in light of the newly developed lattice-continuum correspondence. This correspondence prescribes an explicit method to extract an approximately continuum quantum field theory out of a fully regularized lattice theory. This prescription will here be extended to subregion algebras, and it will be shown how entropies of continuum boson and fermion theories can be computed by working purely with lattice quantities. This gives a clear picture of the origin of divergences in entanglement entropy while also presenting a concise and detailed recipe for calculating this important quantity in continuum theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Fuel performance uncertainty quantification and sensitivity analysis in the presence of epistemic and aleatoric sources of uncertainties

Fuel performance modeling and simulation includes many uncertain parameters from models to boundary conditions, manufacturing parameters and material properties. These parameters exhibit large uncertainties and can have an epistemic or aleatoric nature, something that renders fuel performance code-to-code and code-to-measurements comparisons for complex phenomena such as the pellet cladding mechanical interaction (PCMI) very challenging. Additionally, PCMI and other complex phenomena found in fuel performance modeling and simulation induce strong discontinuities and non-linearities that can render difficult to extract meaningful conclusions form uncertainty quantification (UQ) and sensitivity analysis (SA) studies. In this work, we develop and apply a consistent treatment of epistemic and aleatoric uncertainties for both UQ and SA in fuel performance calculations and use historical benchmark-quality measurement data to demonstrate it. More specifically, the developed methodology is applied to the OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation benchmark. A cold ramp test leading to PCMI is modeled. Two measured quantities of interest are considered: the cladding axial elongation during the irradiations and the cladding outer diameter after the cold ramp. The fuel performance code used to perform the simulation is FAST. The developed methodology involves various steps including a Morris screening to decrease the number of uncertain inputs, a nested loop approach for propagating the epistemic and aleatoric sources of uncertainties, and a global SA using Sobol indices. The obtained results indicate that the fuel and cladding thermal conductivities as well as the cladding outer diameter uncertainties are the three inputs having the largest impact on the measured quantities. More importantly, it was found that the epistemic uncertainties can have a significant impact on the measured quantities and can affect the outcome of the global sensitivity analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Determining Design Criteria for Feeding Biomass into a Fluidized Bed Using a Feed Screw

Many pathways have been discovered for the thermochemical conversion of biomass to products. These pathways often show very promising results on the benchtop scale and could be economical with the appropriate scale up. However, many of the fundamental challenges of scaling up thermochemical reactions are not well understood. One primary problem area that rarely receives much upfront attention is feeding large quantities of biomass into thermochemical reactors. As biomass transitions from ambient to reactor conditions, it undergoes chemical and physical changes that affect its flowability. Often these changes lead to agglomeration of feed particles within the transfer screw, leading to large clumps of feed entering and disrupting the fluidized bed, or more critically leading to a plug in the feed screw causing costly downtime and maintenance to remove. This transitional phase must be better understood for scale up of conversion technologies to be successful. The Feedstock-Conversion Interface Consortium (FCIC) is a collaboration of eight National Laboratories. FCIC is currently conducting research on screw feeding of biomass into thermochemical fluidized bed reactors. Heat transfer models have been constructed for the screw/reactor interface. Mechanical forces on biomass within screw feeder are being determined, as well as how those forces change by varying feed screw design. Feedstock physical and chemical properties are then being measured along these temperature and mechanical force gradients. This work will better inform feed screw design for scale up, increasing the success rate of future biorefineries. Discussion will include research approach, testing, and preliminary results.

09 BIOMASS FUELS↗

DOE OSTI2023

Robust Statistical Approach for Determination of Graphite Nitridation Using Bayesian Model Comparison

A better estimation of surface reaction efficiency of semiconductor-grade graphite with atomic nitrogen, as well as the calibration error are calculated using Bayesian updating based on experimental data. Compared with a conventional deterministic model, the stochastic model approach is a powerful tool in the sense that the model is capable of taking into account underlying error correlations among the data quantities. In this paper, we investigate four different stochastic models (called “stochastic system model classes” herein) corresponding to different descriptions of modeling and measurement error structures, given one deterministic physical model. These stochastic system model classes differ in the covariance matrix structure that is used in the uncertainty model to represent uncertainties associated with the physical model and experimental measurements. For each model class, Bayesian inference is used to estimate the posterior probabilities of the physical model parameters as well as of the stochastic model parameters. Model comparison and selection are then applied based on two measures including Bayesian evidence and Bayesian information criterion, as well as the deviance information criterion. Both measures suggest the stochastic model class, which considers that a correlation between errors in two data quantities among different data points is the most plausible. With the stochastic model class, the range of uncertainty in surface reaction efficiency is estimated to be about two orders of magnitude at [Formula: see text].

Engineering↗

DOE OSTI2026

Reduced-Order Modeling of Hydrogen Releases from Vent Stacks and with Wind Effects

Here, the physical release behavior of hydrogen is important to understand from a safety and design perspective. The consequences of unignited pressurized gaseous hydrogen plumes exiting vent stacks were considered by extending and modifying existing general hydrogen plume models. Entrainment, vent stack backpressure, and the flow regime of hydrogen exiting the vent were found to be significant factors affecting plume shape and size, but further investigation and validation with unchoked, low-Froude-number flows is recommended to improve the model’s robustness. Additionally, models for the effects of wind on unignited plume momentum and entrainment were added to explore this behavior. Wind was assumed to increase mixing of hydrogen with the ambient air, and to affect the momentum of the released jet. Introducing wind into the plume model led to a shorter plume for all wind and jet directions. A high counter-flowing wind led to non-physical results and challenges in interpreting the visualization. The proposed jet plume wind sub-models (specifically entrainment coefficients) were fit and compared to experimental data of different releases of hydrogen into a wind tunnel, but the quantity of data available and experimental conditions were limited. Thus, collection of more empirical data and for a wider range of conditions is recommended for improvement of the proposed computational models. Developing reduced-order models for these physical phenomena can improve accessibility to predicted physical behavior and the rate at which hydrogen systems can be safely designed and deployed.

entrainment↗

DOE OSTI2023

Influence of the symmetry energy on the nuclear binding energies and the neutron drip line position

A clear connection can be established between properties of nuclear matter and finite-nuclei observables, such as the correlation between the slope of the symmetry energy and the dipole polarizability, or between compressibility and the isoscalar monopole giant resonance excitation energy. Establishing a connection between realistic atomic nuclei and an idealized infinite nuclear matter leads to a better understanding of underlying physical mechanisms that govern nuclear dynamics. In this work, we aim to study the dependence of the binding energies and related quantities (e.g., location of drip lines, the total number of bound even-even nuclei) on the symmetry energy S 2 (ρ). The properties of finite nuclei are calculated by employing the relativistic Hartree-Bogoliubov model, assuming even-even axial and reflection symmetric nuclei. Calculations are performed by employing two families of relativistic energy density functionals, based on different effective Lagrangians, constrained to a specific symmetry energy at the saturation density J within the interval of 30–36 MeV. Nuclear binding energies and related quantities of bound nuclei are calculated between 8 ≤ Z ≤ 104 from the two-proton to the two-neutron drip line. As the neutron drip line is approached, the interactions with stiffer J tend to predict more bound nuclei, resulting in a systematic shift of the two-neutron drip line towards more neutron-rich nuclei. Consequentially, a correlation between the number of bound nuclei N nucl and S 2 (ρ) is established for a set of functionals constrained using the similar optimization procedures. Furthermore the direction of the relationship between the number of bound nuclei and the symmetry energy highly depends on the density under consideration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Nuclear spin features relevant to ab initio nucleon-nucleus elastic scattering

Effective interactions for elastic nucleon-nucleus scattering from first principles require the use of the same nucleon-nucleon interaction in the structure and reaction calculations, as well as a consistent treatment of the relevant operators at each order. Previous work using these interactions has shown good agreement with available data. Here, we study the physical relevance of one of these operators, which involves the spin of the struck nucleon, and examine the interpretation of this quantity in a nuclear structure context. Using the framework of the spectator expansion and the underlying framework of the no-core shell model, we calculate and examine spin-projected, one-body momentum distributions required for effective nucleon-nucleus interactions in $J=0$ nuclear states. The calculated spin-projected, one-body momentum distributions for $^4$He, $^6$He, and $^8$He display characteristic behavior based on the occupation of protons and neutrons in single particle levels, with more nucleons of one type yielding momentum distributions with larger values. Additionally, we find this quantity is strongly correlated to the magnetic moment of the $2^+$ excited state in the ground state rotational band for each nucleus considered. In conclusion, we find that spin-projected, one-body momentum distributions can probe the spin content of a $J=0$ wave function. This feature may allow future ab initio nucleon-nucleus scattering studies to inform spin properties of the underlying nucleon-nucleon interactions. The observed correlation to the magnetic moment of excited states illustrates a previously unknown connection between reaction observables such as the analyzing power and structure observables like the magnetic moment.

6 ≤ A ≤ 19↗

DOE OSTI2020

Effect of Impurity Atoms on Thermonuclear Yield

The presence of impurity atoms in an inertial confinement fusion (ICF) implosion can greatly affect the burning of the thermonuclear fuel. This is a serious concern for attaining ignition as high atomic number atoms, such as carbon, can mix into the hot spot and reach the deuterium–tritium (DT) fuel, absorb energy from the implosion, and radiate away that energy. The temperature of the DT fuel drops and reduces the reactivity of the fuel resulting in lower thermonuclear yield. Fuel impurities can also be a useful diagnostic as when higher-Z atoms, such as Ar, Kr, and Xe, are purposefully mixed into the fuel. From the spectra emitted by these atoms, the temperature and density of the fuel can be deduced. The long history of using such tracer atoms by the national ICF program shows the great advances in experimental technique, diagnostic instruments, and atomic-physics modeling over the past 50 years. A particular set of experiments, the “High-Z” campaign, is reviewed in depth as this was the most systematic study of tracer element composition and quantity ever reported. Difficulties in interpreting the results of those experiments due to the limited code capabilities at that time are discussed. A main concern for the High-Z campaign was the then current state of non-Local Thermodynamic Equilibrium (nLTE) atomic physics models. The present state of nLTE modeling and its implementation in Los Alamos’s multi-physics codes is discussed in this report. To further the understanding of the complex interaction of high-Z atoms in the gas, a survey of relevant existing experimental platforms at the National Ignition Facility (NIF) and the Omega Laser Facility are presented along with the current state of pertinent diagnostics at NIF and Omega. This review concludes with a discussion of the trade-off available between temperature and volume of the imploded ICF capsule with the goal of maximizing the total yield.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗