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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Transient Modeling and Simulation of a Generic Stable Salt Reactor

A SAM system-level model of a generic stable salt reactor has been developed to investigate thermal-hydraulic behavior and safety performance under steady and transient conditions. The model integrates information generated from a reactor physics analysis using PROTEUS and PERSENT, and a computation fluid dynamics (CFD) analysis using STAR-CCM+. A loose, iterative coupling scheme between PROTEUS and SAM is implemented to calculate the equilibrium power and temperature distributions in the steady-state critical core condition. The converged steady-state model is then used in PERSENT to calculate the four reactivity feedback temperature coefficients (Doppler, fuel density, coolant density, and core radial expansion) and kinetic parameters that are needed in SAM to model the temperature feedback effects in transient simulations. Within the fully enclosed liquid fuel pins, natural convection is the dominant heat transfer mechanism. The STAR-CCM+ model of the fuel pin considers conjugate heat transfer from the liquid fuel salt to the pin cladding and external reactor coolant. The CFD results of the axial and radial temperature profiles are used to empirically determine an effective fuel salt thermal conductivity in the SAM fuel pin model so that the temperatures predicted by the SAM model match as closely as possible the CFD results. In the central region of the fuel pin, the effective thermal conductivity is as high as similar to 60 times the physical fuel salt thermal conductivity. The whole-plant SAM model is then used to simulate an unprotected station blackout transient. The results of this simulation showed that the large negative fuel axial expansion reactivity feedback reduces fission power to similar to 2.4% nominal power. The core is cooled by natural circulation, which removes heat in the core to the emergency heat removal system, and ultimately, to the ambient. However, peak fuel salt and cladding temperatures can potentially reach as high as 1500 K, albeit briefly, if the shutdown mechanism fails to operate.

stable salt reactor; transient simulations; system↗
DOE OSTI2024

Hidden quantum criticality and entanglement in quench dynamics

Entanglement exhibits universal behavior near the ground-state critical point where correlations are long ranged and the thermodynamic entropy is vanishing. On the other hand, a quantum quench imparts extensive energy and results in a build up of entropy, hence no critical behavior is expected at long times. In this work, we present a new paradigm in the quench dynamics of integrable spin chains which exhibit a ground-state order-disorder phase transition at a critical line. Specifically, we consider a quench along the critical line which displays a volume-law behavior of the entropy and exponentially decaying correlations; however, we show that quantum criticality is hidden in higher-order correlations and becomes manifest via measures such as the mutual information and logarithmic negativity. Furthermore, we showcase the scale invariance of the Rényi mutual information between disjoint regions as further evidence for genuine critical behavior. We attribute the emergent quantum criticality to the soft mode not getting excited in spite of the quench. Moreover, the results presented here are universal to models whose low-energy or long-wavelength dynamics are well described by a free-fermionic field theory. Our results are amenable to an experimental realization on different quantum simulator platforms, particularly the Rydberg simulators. Published by the American Physical Society 2024

Paul, Sanku↗
DOE OSTI2023

Solid-state batteries: The critical role of mechanics

Solid-state batteries with lithium metal anodes have the potential for higher energy density, longer lifetime, wider operating temperature, and increased safety. Although the bulk of the research has focused on improving transport kinetics and electrochemical stability of the materials and interfaces, there are also critical challenges that require investigation of the mechanics of materials. In batteries with solid-solid interfaces, mechanical contacts, and the development of stresses during operation of the solid-state batteries, become as critical as the electrochemical stability to keep steady charge transfer at these interfaces. In conclusion, this review will focus on stress and strain that result from normal and extended battery cycling and the associated mechanisms for stress relief, some of which lead to failure of these batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Navigating thermal stability intricacies of high-nickel cathodes for high-energy lithium batteries

High-nickel oxide cathodes, LiNi x M 1−x O 2 (x ≥ 0.8), are preferred in automotive lithium batteries, but they face thermal instability challenges. Inconsistent literature reports and unstandardized testing protocols further complicate quantitative assessments of the thermal stability of these cathodes. Here, we present here a statistical thermal analysis based on the differential scanning calorimetry measurements of 15 representative cathode materials with different compositions, morphologies and states of charge. The findings reveal that each cathode has a critical state of charge that defines its safe operating limit, which is affected by the metal–oxygen bond strength and surface reactivity. The thermal runaway temperature is dictated by the layered Li 1−x NiO 2 to LiNi 2 O 4 spinel-like phase transition, which is thermodynamically determined by the metal–oxygen bond covalency and kinetically influenced by the cation mixing and particle size. Raman spectroscopy is used to predict the thermal runaway temperature on the basis of the linear relationship between them. Finally, we propose a thermal stability index to quantify cathode thermal stability as a guide for developing safer high-nickel cathodes.

batteries↗
DOE OSTI2023

Recalculating Dissolver Curves for Critical Parameters for Nuclear Criticality Safety

The dissolver paradox is a phenomenon in criticality safety whereby a high density fissile material is being dissolved in a low fissile density solution and is subcritical before and after dissolution. However, as the metal is being dissolved, there may be an intermediate concentration that leads to a critical state. CCG-184 is a Y-12 report written in 1980 that provided critical parameter data for two separate dissolver paradox scenarios: solid metal spheres and hollow metal spheres with internal moderation effects. The sphere and shell are both surrounded by solution, however the shell contains solution of the same concentration within itself. In 1980, there are limitations to the computational methods to determine critical parameters. These are due to the lower number of energy groups utilized (16-group) at the time, smaller number of established cross-sectional data, as well as a larger uncertainty within the resonance region of neutron energies. With these constraints in mind, these critical parameters are recalculated with newer cross-sectional data, a newer Monte Carlo code: SCALE 6.1.3 using KENO V.a, and a larger number of energy bins.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Nuclear Criticality Experiments Research Center Futures: A Report of a Workshop held September 6-9, 2022, Los Alamos, NM, November, 2022

Experiments and training with critical assemblies and fissionable material (at or near the critical state) that explore reactivity phenomena are central to a number of national security challenges. From fission energy to nuclear weapons to a broad suite of scientific challenges, it is clear that additional capacity and capability are needed. The National Criticality Experiments Research Center (NCERC) marked 10 years of operations in 2021. This anniversary was an opportune time to celebrate our successes and progress, and to evaluate the remaining and emergent challenges. Against this backdrop, a workshop of approximately 140 national and international leaders in nuclear research was convened in Los Alamos, New Mexico to explore “NCERC Futures.” Therefore, the present workshop focused specifically on needed capabilities and tools to meet the research challenges in eight topical mission areas served by NCERC. As each Topical Group summarized their discussions in the out brief, it was recognized that key challenges could be met through enabling infrastructure investments and new critical assemblies. Enabling infrastructure includes staffing, additional space/buildings, developing an agile bounding safety basis, the ability to keep pace with technological advances in detectors and data acquisition systems (allowing use of those with Bluetooth™ and similar technologies), an expanded set of materials options (especially plutonium), a “Plug and Play” design and implementation mindset, and a facility that enabled free-field measurements. The new critical assemblies that were identified as having the most impact were a bare plutonium (Pu) Critical Assembly, a Horizontal Split Table (HST), a Super Comet, and a Uranium Solution Burst Assembly. NECRC is a unique, one-of-a-kind facility in the United States. If all the improvements were to be made, NCERC would enable the United States and its partners to address many important research questions related to criticality. These include but are not limited to: (1) Covering the entire neutron energy spectrum for both highly enriched uranium (HEU) and Pu in configurations for virtually all conceivable applications; (2) Performing multi-physics solution experiments and irradiations with a Uranium Solution Burst Assembly, which more closely resembles actual criticality accidents; (3) Conducting free-field experiments to make basic fission physics measurements and much cleaner benchmarks with various experimental observables; and (4) Providing more training classes and more experiments annually at greater cost efficiency enabled by additional buildings and machines and an agile, bounding, risk-balanced Safety Basis. In the end, workshop attendees enthusiastically concluded that NCERC Futures are bright and the workshop helped to identify a roadmap of capability gaps that need to be addressed. This report documents the results of those efforts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Non-equilibrium critical scaling and universality in a quantum simulator

Universality and scaling laws are hallmarks of equilibrium phase transitions and critical phenomena. However, extending these concepts to non-equilibrium systems is an outstanding challenge. Despite recent progress in the study of dynamical phases, the universality classes and scaling laws for non-equilibrium phenomena are far less understood than those in equilibrium. In this work, using a trapped-ion quantum simulator with single-spin resolution, we investigate the non-equilibrium nature of critical fluctuations following a quantum quench to the critical point. We probe the scaling of spin fluctuations after a series of quenches to the critical Hamiltonian of a long-range Ising model. With systems of up to 50 spins, we show that the amplitude and timescale of the post-quench fluctuations scale with system size with distinct universal critical exponents, depending on the quench protocol. While a generic quench can lead to thermal critical behavior, we find that a second quench from one critical state to another (i.e. a double quench) results in a new universal non-equilibrium behavior, identified by a set of critical exponents distinct from their equilibrium counterparts. Our results demonstrate the ability of quantum simulators to explore universal scaling beyond equilibrium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Compendium of Cyber Incident Notification Requirements for Critical Infrastructure Utilities by State

Cyber attacks targeting critical infrastructure in the United States are on the rise and pose serious risks to the economy and health and safety of its citizens. Experts suggest a sound cyber risk mitigation strategy includes constant monitoring for signs of cyber intrusions and rapid reporting of incidents so that other critical infrastructure operators may benefit from early warnings. Reporting incidents to Public Utility Commissions (PUCs) and other state agencies who have roles in energy emergency planning and incident response and recovery is essential for them to maintain situational awareness and provide necessary support to ensure rapid restoration of utility services, should disruptions occur.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Neural Network Sampling of the Free Energy Landscape for Nitrogen Dissociation on Ruthenium

In heterogeneous catalysis, free energy profiles of reactions govern the mechanisms, rates, and equilibria. Energetics are conventionally computed using the harmonic approximation (HA), which requires determination of critical states a priori. Here, we use neural networks to efficiently sample and directly calculate the free energy surface (FES) of a prototypical heterogeneous catalysis reaction—the dissociation of molecular nitrogen on ruthenium—at density-functional-theory-level accuracy. We find that the vibrational entropy of surface atoms, often neglected in HA for transition metal catalysts, contributes significantly to the reaction barrier. The minimum free energy path for dissociation reveals an “on-top” adsorbed molecular state prior to the transition state. While a previously reported flat-lying molecular metastable state can be identified in the potential energy surface, it is absent in the FES at relevant reaction temperatures. Finally, these findings demonstrate the importance of identifying critical points self-consistently on the FES for reactions that involve considerable entropic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Assessing the Consequences of Postclosure Criticality in Spent Nuclear Fuel

The U.S. Department of Energy is funding research into studying the consequences of postclosure criticality on the performance of a generic repository by (1) identifying the features, events, and processes (FEPs) that need to be considered in such an analysis, (2) developing the tools needed to model the relevant FEPs in a postclosure performance assessment, and (3) conducting analyses both with and without the occurrence of a postclosure criticality and comparing the results. Here, this paper describes progress in this area of research and presents the results to date of analyzing the consequences of a postulated steady-state criticality in a hypothetical saturated shale repository. Preliminary results indicate that postclosure criticality would not affect repository performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

On the trapped magnetic moment in type-II superconductors

In this article, measurements of the trapped (remanent) magnetic moment, M trap (H) , when a small magnetic field H is turned off after cooling below the superconducting transition temperature, T c , or ramping a magnetic field up and down after cooling in a zero magnetic field, offer substantial advantages in difficult cases of small samples and large field-dependent backgrounds, which is relevant for hydrogen-based ultra-high-T c superconductors (UHTS). Until recently, there was no need for a separate paper on the trapped magnetic flux for well-known critical-state models due to the simplicity of the physics involved. However, recent publications showed the need for such an analysis. This note summarizes the expectations for the Bean model with constant critical current density and the Kim model with field-dependent critical currents. It is shown that if the trapped moment is fitted to the power law, M trap $\propto$ H a , the fixed exponent α = 2 is exact for the Bean model, while Kim models show a wide interval of possible values, 2$\leqslant$a$\leqslant$4. Furthermore, accounting for reversible magnetization expands the range of possible exponents to 1$\leqslant$a$\leqslant$4. In addition, demagnetizing factors are essential and make the trapped moment orientation dependent even in isotropic materials. As a concrete application, it is shown that flux trapping experiments performed on H 3 S UHTS compounds can be well described using this generalized approach, lending further support to the type-II superconducting nature of H 3 S under ultra-high pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

The effect of local chemical ordering on Frank-Read source activation in a refractory multi-principal element alloy

In this work, we investigate the operation of Frank-Read (FR) sources in a refractory multi-principal element alloy (MPEA). Simulations of discrete dislocation motion in MPEAs is enabled by the development of a phase field dislocation dynamics model that treats the atomic-scale fluctuations in lattice energies across the glide plane, present due to local ordering in the chemical composition within the nominally random MPEA atomic structure. We consider, through simulation, a range of length scales over which ordering occurs, varying from short-range lengths, a few times dislocation core width, to long-range lengths, an order of magnitude longer than the core. Characteristic of this body-centered cubic MPEA, the simulations also include screw/edge character dependence in glide resistance, as informed by atomic scale simulation. The critical stresses to activate the source for the same source size are found to be statistically distributed, as a direct consequence of the underlying variation in lattice energy. Furthermore, analysis of critical state for activating edge and screw FR sources in the MPEA reveals that FR source operation occurs via a two-step mechanism, involving athermal kink-pair formation, unlike the conventional FR source operation in a material with no composition fluctuations. This mechanism lowers the average critical stress required to activate the FR source and causes the statistical dispersion in critical stress to depend on the range of composition ordering. More importantly, it leads to a more severe dependence of source strength on FR source length than predicted by line tension alone.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synchronization of Alternative Models in a Supermodel and the Learning of Critical Behavior

“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, interscale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the midlatitudes and a pair of ECHAM5 models of the tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with intermodel connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. In conclusion, for supermodels of both types, power spectra indicate enhanced interscale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗
DOE OSTI2023

Assessing continuum plasticity postulates with grain stress and local strain measurements in triaxially compressed sand

Critical state and continuum plasticity theories have been used in research and engineering practice in soil and rock mechanics for decades. These theories rely on postulated relationships between material stresses and strains. Some classical postulates include coaxiality between stress and strain rates, stress–dilatancy relationships, and kinematic assumptions in shear bands. Although numerical and experimental data have quantified the strains and grain kinematics in such experiments, little data quantifying grain stresses are available. Here, we report the first-known grain stress and local strain measurements in triaxial compression tests on synthetic quartz sands using synchrotron X-ray tomography and 3D X-ray diffraction. We use these data to examine the micromechanics of shear banding, with a focus on coaxiality, stress-dilatancy, and kinematics within bands. Our results indicate the following: 1) elevated deviatoric stress, strain, and stress ratios in shear bands throughout experiments; 2) coaxial principal compressive stresses and strains throughout samples; 3) significant contraction along shear bands; 4) vanishing volumetric strain but nonvanishing stress fluctuations throughout samples at all stages of deformation. Our results provide some of the first-known in situ stress and strain measurements able to aid in critically evaluating postulates employed in continuum plasticity and strain localization theories for sands.

42 ENGINEERING↗
DOE OSTI2023

Mapping out the thermodynamic stability of a QCD equation of state with a critical point using active learning

The Beam Energy Scan Theory (BEST) collaboration's equation of state (EoS) incorporates a three-dimensional Ising model critical point into the quantum chromodynamics (QCD) equation of state from lattice simulations. Furthermore, it contains four free parameters related to the size and location of the critical region in the QCD phase diagram. Certain combinations of the free parameters lead to acausal or unstable realizations of the EoS that should not be considered. In this work, we use an active learning framework to rule out pathological EoS efficiently. We find that checking stability and causality for a small portion of the parameters' range is sufficient to construct algorithms that perform with > 96 % accuracy across the entire parameter space. Though in this work we focus on a specific case, our approach can be generalized to any EoS containing a parameter space-class correspondence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Catalytic Bias in Enzymatic Metal Cofactor-Based Oxidation-Reduction Catalysis

Catalytic bias refers to the relative rate preference of a catalyst for either the forward or reverse direction. In enzymatic metal cofactor-based oxidation-reduction catalysis, the tuning of catalytic bias plays an underlying role in controlling rates of reactivity. For this, enzymes have evolved complex active sites that can exist in multiple oxidation states with differing reduction potentials in order to achieve challenging multi-step, oxidation-reduction reactions. Conceivably, the relative stability of the intermediates that contribute to determining the rate-limiting step of the catalytic cycle could impose catalytic bias, although mechanisms for this concept are just beginning to be realized. As one example, recent work on Clostridium pasteurianum [FeFe]-hydrogenases which catalyze reversible hydrogen oxidation have shown that the differential stabilization/destabilization of active site oxidation states through either static or dynamic protein interactions can preferentially promote either the hydrogen oxidation or proton reduction direction of the reaction. This revealed how an enzymatic cofactor can impose bias in oxidation-reduction catalysis through various tuning mechanisms by protein scaffold interactions. The hypothesis based on achieving catalytic bias through the modulation of cofactor oxidation states critical for the reaction cycle can be extended more generally to other cofactor-based oxidation-reductions catalysts. The current understanding of catalytic bias has significant implications for the design of synthetic catalysts used in industrial settings, as well as providing a greater fundamental understanding of the factors that control metabolic processes in all life.

catalysis↗
DOE OSTI2023

Synergizing a Large Ordinary Nernst Effect and Axis‐Dependent Conduction Polarity in Flat Band KMgBi Crystals

The exploration of quantum materials in which an applied thermo/electrical/magnetic field along one crystallographic direction produces an anisotropic response has led to unique functionalities. Along these lines, KMgBi is a layered, narrow gap semiconductor near a critical state between multiple Dirac phases due to the presence of a flat band near the Fermi level. The valence band is highly anisotropic with minimal cross-plane dispersion, which, in combination with an isotropic conduction band, enables axis-dependent conduction polarity. Thermopower and Hall measurements indicate dominant p-type conduction along the cross-plane direction, and n-type conduction along the in-plane direction, leading to a significant zero-field transverse thermoelectric response when the heat flux is at an angle to the principal crystallographic directions. Additionally, a large Ordinary Nernst effect (ONE) is observed with an applied field. It arises from the ambipolar term in the Nernst effect, whereby the Lorentz force on electrons and holes makes them drift in opposite directions so that the resulting Nernst voltage becomes a function of the difference between their partial thermopowers, greatly enhancing the ONE. It is proven that axis-dependent polarity can synergistically enhance the ONE, in addition to leading to a zero-field transverse thermoelectric performance.

36 MATERIALS SCIENCE↗