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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effects of Microstructural Composition, Porosity, and Microcracks on the Elastic Moduli of Nuclear Graphites

The elastic responses of nuclear graphite not only depend on the graphitic content itself but are largely dictated by the microstructural constitution of the material. The types of raw materials combined with the manufacturing processes used to produce the graphite yield the microstructural content that primarily includes graphite filler, graphitized pitch binder, and voids/defects that typically occupy approximately 20% of the volume. Among these microstructural components, porosity and microcracking (considered to be part of voids/defects) heavily influence the overall properties of the material, including the elastic moduli. It is widely accepted that the primary effect of oxidation is to increase porosity, but the related effect on the moduli cannot be explained satisfactorily by simply noting changes to porosity. Models describing the elastic moduli of porous, polycrystalline graphite materials have been developed to interpret experimental determinations of Young's modulus and shear modulus in oxidized graphites. Beyond porosity, the moduli are heavily influenced by microcracks, and their effects can be assessed using physical property models based on orientation distribution coefficients and microcrack-modified, single-crystal moduli to represent the combined effects of crystallite orientation and microcracking. This work demonstrates how most modulus measurements in nuclear graphites can be understood using relatively simple models that describe the effects of porosity and microcracking. We also present directions to be pursued to account for microstructure-related effects that occur as a result of neutron irradiation.

Spicer, James B.↗
DOE OSTI2026

CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery

Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but existing methods rely on scalar rewards that provide limited information about why candidate solutions fail, leading agents to repeatedly explore invalid regions. We introduce Certification-Driven Reinforcement Learning (CDRL), a framework that leverages structured feedback from symbolic reasoning tools. When a candidate violates domain constraints, these tools produce certificates identifying the actions responsible for failure. CDRL converts these certificates into reusable constraints that eliminate classes of invalid solutions and guide exploration toward valid regions. We evaluate CDRL on neutrino flavor model discovery in theoretical particle physics, where the hypothesis space exceeds $10^{26}$ possible models, and compare it with the state-of-the-art RL approach previously used for this task. Across three theory spaces, CDRL achieves up to 1.95$\times$ higher valid model rates and up to 6.33$\times$ higher neutrino model rates while evaluating up to 4$\times$ fewer candidates. We further extract 40 interpretable rules from search trajectories using a post-hoc decision-tree framework and show that reusing them as soft constraints yields gains of up to 2$\times$ in valid model rates and 3$\times$ in neutrino model discovery across all three theory spaces. These results suggest that CDRL uncovers reusable structure in combinatorial search spaces and provides a general framework for scientific model discovery.

Jha, Piyush [Georgia Tech., Atlanta; Georgia Tech]↗
DOE OSTI2021

Investigating the Accuracy of Water Models through the Van Hove Correlation Function

In this study, we present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

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

Quantitative and interpretable order parameters for phase transitions from persistent homology

Here, we apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and fully frustrated XY models. In particular, we use persistent homology, which computes the births and deaths of individual topological features as a coarse-graining scale or sublevel threshold is increased, to summarize multiscale and high-point correlations in a spin configuration. We employ vector representations of this information called persistence images to formulate and perform the statistical task of distinguishing phases. For the models we consider, a simple logistic regression on these images is sufficient to identify the phase transition. Interpretable order parameters are then read from the weights of the regression. This method suffices to identify magnetization, frustration, and vortex-antivortex structure as relevant features for phase transitions in our models. We also define “persistence” critical exponents and study how they are related to those critical exponents usually considered.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A stochastic solver based on the residence time algorithm for crystal plasticity models

Abstract The deformation of crystalline materials by dislocation motion takes place in discrete amounts determined by the Burgers vector. Dislocations may move individually or in bundles, potentially giving rise to intermittent slip. This confers plastic deformation with a certain degree of variability that can be interpreted as being caused by stochastic fluctuations in dislocation behavior. However, crystal plasticity (CP) models are almost always formulated in a continuum sense, assuming that fluctuations average out over large material volumes and/or cancel out due to multi-slip contributions. Nevertheless, plastic fluctuations are known to be important in confined volumes at or below the micron scale, at high temperatures, and under low strain rate/stress deformation conditions. Here, we develop a stochastic solver for CP models based on the residence-time algorithm that naturally captures plastic fluctuations by sampling among the set of active slip systems in the crystal. The method solves the evolution equations of explicit CP formulations, which are recast as stochastic ordinary differential equations and integrated discretely in time. The stochastic CP model is numerically stable by design and naturally breaks the symmetry of plastic slip by sampling among the active plastic shear rates with the correct probability. This can lead to phenomena such as intermittent slip or plastic localization without adding external symmetry-breaking operations to the model. The method is applied to body-centered cubic tungsten single crystals under a variety of temperatures, loading orientations, and imposed strain rates.

42 ENGINEERING↗
DOE OSTI2023

Improving Mathematical Exposition of an Industrial-Scale Linear Program

Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. Furthermore, the computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Search for a heavy Higgs boson decaying into a Z boson and another heavy Higgs boson in the $\ell \ell bb$ and $\ell \ell WW$ final states in pp collisions at $\sqrt{s}=13$ $\text {TeV}$ with the ATLAS detector

A search for a heavy neutral Higgs boson, A decaying into a Z boson and another heavy Higgs boson, H, is performed using a data sample corresponding to an integrated luminosity of 139 fb-1 from proton–proton collisions at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector at the LHC. The search considers the Z boson decaying into electrons or muons and the H boson into a pair of b-quarks or W bosons. The mass range considered is 230–800 $\text {GeV}$ for the A boson and 130–700 $\text {GeV}$ for the H boson. The data are in good agreement with the background predicted by the Standard Model, and therefore 95% confidence-level upper limits for $\sigma \times B(A\rightarrow ZH)\times B(H\rightarrow bb \; \text {or} \; H \rightarrow WW)$ are set. The upper limits are in the range 0.0062–0.380 pb for the $H\rightarrow bb$ channel and in the range 0.023–8.9 pb for the $H\rightarrow WW$ channel. An interpretation of the results in the context of two-Higgs-doublet models is also given.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Measurement of the associated production of a Higgs boson decaying into b-quarks with a vector boson at high transverse momentum in pp collisions at s=13 TeV with the ATLAS detector

The associated production of a Higgs boson with a W or Z boson decaying into leptons and where the Higgs boson decays to a $b\bar{b}$ pair is measured in the high vector-boson transverse momentum regime, above 250 GeV, with the ATLAS detector. The analysed data, corresponding to an integrated luminosity of 139 fb -1 , were collected in proton–proton collisions at the Large Hadron Collider between 2015 and 2018 at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The measured signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model, is $0.72^{+0.39}_{-0.36}$ corresponding to an observed (expected) significance of 2.1 (2.7) standard deviations. Cross-sections of associated production of a Higgs boson decaying into b quark pairs with a W or Z gauge boson, decaying into leptons, are measured in two exclusive vector boson transverse momentum regions, 250–400 GeV and above 400 GeV, and interpreted as constraints on anomalous couplings in the framework of a Standard Model effective field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Mathematical modeling and parameter estimation of MFI membranes for para/ortho‐xylene separation

Abstract A mathematical model of a membrane with a thin, oriented, and selective MFI layer, which also includes contributions from defects, pore blockages, support layer, and external mass transfer, was formulated based on the Maxwell‐Stefan equations. It was validated using reported (Kim et al., Angew Chemie Int Ed, 2018, 57:480–485; Jeon et al., Nature, 2017, 543:690–694) para/ortho‐xylene separation data from five MFI membranes. The diffusivities of the xylenes were considered to be the same for all membranes, while the thickness and the density of defects and pore blockage were treated as unique properties of each membrane, and their contributions were estimated by fitting the model to the corresponding separation data. The effects of these properties and the role of permeate pressure on the separation performance were subsequently analyzed. The proposed modeling, parameter estimation, and analysis framework allow one to quantitatively interpret the variation of separation performance, to understand separation bottlenecks, and to provide guidance for designing membranes with desired performance.

Liu, Jingjun↗
DOE OSTI2020

Effect of Anode Porosity and Temperature on the Performance and Lithium Plating During Fast-Charging of Lithium-Ion Cells

Twenty-four single-layer approximate to 32 mAh pouch cells are tested to determine the effect of electrode porosity on lithium plating. Twelve cells contain a graphite electrode that is 26% porous, and 47% for the other twelve. The cells are cycled using a 6-C charge and a C/2 discharge protocol at temperatures in the range of 20-50 degrees C. A macro-homogeneous electrochemical model and microstructure analysis tool set are used to help interpret experimental observations for the effect of anode porosity and ambient temperature on fast-charging performance. Additionally, comparison between the two also highlights gaps in current theoretical understanding that need to be addressed. In post-test examination, lithium plating is seen in all cells, regardless of porosity. Elevated temperature is shown to reduce the amount of lithium plating and improve initial fast-charge capacity, but also changes the rate of other, less well-understood degradation mechanisms. Apparent kinetic rate laws, At + Bt 1/2 , where A and B are constants, can be fit to most of the capacity loss and resistance increase data. The relative magnitudes of A and B change with temperature and porosity. The capacity loss data at 50 degrees C from the high-porosity cells are fit by a logistics rate law.

25 ENERGY STORAGE↗
DOE OSTI2021

Search for squarks and gluinos in final states with jets and missing transverse momentum using 139 fb -1 of $ \sqrt{s} $ = 13 TeV pp collision data with the ATLAS detector

A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb -1 . The results are interpreted in the context of various R -parity-conserving models where squarks and gluinos are produced in pairs or in association and a neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.30 TeV for a simplified model containing only a gluino and the lightest neutralino, assuming the latter is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.85 TeV are excluded if the lightest neutralino is massless. These limits extend substantially beyond the region of supersymmetric parameter space excluded previously by similar searches with the ATLAS detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A search for R-parity-violating supersymmetry in final states containing many jets in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for R-parity-violating supersymmetry in final states with high jet multiplicity is presented. The search uses 140 fb –1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature prompt gluino-pair production decaying directly to three jets each or decaying to two jets and a neutralino which subsequently decays promptly to three jets. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence level are extracted. Gluinos with masses up to 1800 GeV are excluded when decaying directly to three jets. In the cascade scenario, gluinos with masses up to 2340 GeV are excluded for a neutralino with mass up to 1250 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Data-driven discovery of a formation prediction rule on high-entropy ceramics

The interest in high entropy ceramics (HECs) has increased steadily due to their superior properties. However, the prediction of their formation still poses challenges for the discovery of new systems. Here, we discover a rational rule for designing single-phase high entropy metal diborides (HEBs) using data-driven approach. The machine learning (ML) model is trained on data collected via high-throughput experiments (HTEs). K nearest neighbor (KNN) model shows an experimental validation accuracy of 93.75%. By implementing interpretable ML method, we demonstrate that a mismatch of the bonds between boron and transition metals (δ B-TM ) dominates the formation of HEBs. We propose an empirical rule that HEBs favor forming a single phase when δ B-TM < 3.66; otherwise, multiphase. The rule has a high accuracy of 93.33% for new HEBs predictions. In addition, we contribute 165 high quality HEBs data in total, which can promote the development of materials informatics in HEBs. Furthermore, this data-driven strategy can be expanded to accelerate the search for new HECs, paving a pathway to design novel HECs with superior properties rapidly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the competitive antagonism effect in combined chloride-sulfate attack: A numerical exploration

Highlights: • A chemo-physical-mechanical method based on thermodynamic modelling is implemented. • The contradicting findings from reported experiments are numerically explored. • The competitive antagonism effect is time-dependent rather than a conclusive term. • The competitive antagonism effect is quantifiable with a novel assessment criterion. It is of tremendous difficulty to draw a conclusive verdict on the complex process of mutual interference regarding the combined chloride-sulfate attack on concrete, where many have explored the topic, but contradicting results have been reported. In this paper, by taking advantages of the chemo-physical-mechanical method, based on the robust technique of thermodynamic modelling, the competitive antagonism effect in combined chloride-sulfate attack is investigated. Firstly, a range of reported tests are numerically modelled to demonstrate the effectiveness of the employed method in interpreting those opposing and diverse experimental outcomes. More importantly, a fresh conjecture incorporating a novel assessment criterion for the competitive antagonism effect is proposed and supported through a carefully designed illustrative example. Based on the numerical exploration, unique findings and implications for future engineering practices are revealed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spectral line identification from a photoionised silicon plasma in emission

Next-generation X-ray satellite telescopes such as XRISM, NewAthena and Lynx will enable observations of exotic astrophysical sources at unprecedented spectral and spatial resolution. Proper interpretation of these data demands that the accuracy of the models is at least within the uncertainty of the observations. One set of quantities that might not currently meet this requirement is transition energies of various astrophysically relevant ions. Current databases are populated with many untested theoretical calculations. Accurate laboratory benchmarks are required to better understand the coming data. We obtained laboratory spectra of X-ray lines from a silicon plasma at an average spectral resolving power of ∼7500 with a spherically bent crystal spectrometer on the Z facility at Sandia National Laboratories. Many of the lines in the data are measured here for the first time. We report measurements of 53 transitions originating from the K-shells of He-like to B-like silicon in the energy range between ∼1795 and 1880 eV (6.6–6.9 Å). The lines were identified by qualitative comparison against a full synthetic spectrum calculated with ATOMIC. The average fractional uncertainty (uncertainty/energy) for all reported lines is ∼5.4 × 10 −5 . We compare the measured quantities against transition energies calculated with RATS and FAC as well as those reported in the NIST ASD and XSTAR’s uaDB. Average absolute differences relative to experimentally measured values are 0.20, 0.32, 0.17 and 0.38 eV, respectively. All calculations/databases show good agreement with the experimental values; NIST ASD shows the closest match overall.

astrophysical plasmas↗
DOE OSTI2025

Accurate and Efficient Prediction of p K w in Aqueous Electrolytes Using Local Electrostatic Potentials

The K w =10 -pK w in aqueous electrolytes exhibit significant variations as a function of ion concentration. This behavior is not well-described by the Pitzer model, particularly at high concentrations. Here, we provide a molecular interpretation of the concentration dependent trends in p K w and develop a new method that accurately predicts the dissociation constant based upon the local electrostatic potential of the water oxygen that is determined by its nearest neighbors. The method is computationally efficient, relying only upon sampling of the local configurations (via molecular dynamics) and a small set of experimentally measured p K w . It is extensible to a range of salt compositions and the molecular understanding of the local potentials provides new routes toward the development of electrolytes with tailored physicochemical properties like p K w .

anions↗
DOE OSTI2026

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗