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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Polymorphism and phase transitions in layered uranium(VI) hydroxides: Ab initio lattice dynamics simulations of UO 2 (OH) 2

The phase transitions and thermodynamics of stoichiometric α-, β-, and γ-UO 2 (OH) 2 polymorphs are investigated using density functional perturbation theory. The pressure-induced β(Pbca) → α(Cmca) phase transition is reproduced by calculations, with a volume reduction of ΔV/V = -14.7% similar to experiment. Consistent with observation, a temperature-driven γ(P2 1 /c) → β(Pbca) phase transition is predicted near 533 K. At 298.15K, the computed standard molar heat capacity of α-UO 2 (OH) 2 is C p 0 = 112.1 J mol -1 K -1 , only 1.6% smaller than the value of C p 0 = 113.96 ± 0.12 J mol -1 K -1 measured by calorimetry. C p 0 = 112.4 and 104.8 J mol -1 K -1 are predicted for the β- and γ-UO 2 (OH) 2 polymorphs, respectively. The calculated molar enthalpy and Gibbs energy functions of the α-, β-, and γ-UO 2 (OH) 2 polymorphs are also reported.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

The mechanics of nucleation and growth and the surface tensions of active matter

Homogeneous nucleation, a textbook transition path for phase transitions, is typically understood on thermodynamic grounds through the prism of classical nucleation theory. However, recent studies have suggested the applicability of classical nucleation theory to systems far from equilibrium. Here, in this article, we formulate a purely mechanical perspective of homogeneous nucleation and growth, elucidating the criteria for the properties of a critical nucleus without appealing to equilibrium notions. Applying this theory to active fluids undergoing motility-induced phase separation, we find that nucleation proceeds in a qualitatively similar fashion to equilibrium systems, with concepts such as the Gibbs–Thomson effect and nucleation barriers remaining valid. We further demonstrate that the recovery of such concepts allows us to extend classical theories of nucleation rates and coarsening dynamics to active systems upon using the mechanically derived definitions of the nucleation barrier and surface tensions. Three distinct surface tensions—the mechanical, capillary, and Ostwald tensions—play a central role in our theory. While these three surface tensions are identical in equilibrium, our work highlights the distinctive role of each tension in the stability of active interfaces and the nucleation and growth of motility-induced phases.

Capillary waves↗
DOE OSTI2025

Dual modulation of the anion-driven thermodynamic properties of aqueous choline halide-based deep eutectic solvents

Deep eutectic solvents (DESs) are considered tunable solvents because their specific properties can be achieved based on the choice of components and their relative concentrations in a mixture. In this article, we investigate the influence of the variation in halide ions (F − , Cl − , Br − , I − ) of choline salts used on the thermodynamic and physicochemical properties of choline halide-based DESs. Our findings show that the density of choline halide-based DESs decreases nonlinearly with an increasing mole fraction of water, following a trend based on the size of the halides, with choline iodide showing the highest density. Temperature-dependent density data reveal that the thermal expansion coefficient decreases slightly with increasing water content, indicating a more stable volume at a higher mole fraction of water. The excess molar volume (V E ) of the DES mixtures exhibits complex behavior depending on the choline halide used, with both negative and positive V E values observed across different water mole fractions. These variations are linked to the hydrogen bonding interactions between the DES components and water molecules. In addition, viscosities decrease with increasing water content, suggesting the disruption of hydrogen bonding networks and enhanced mobility of the ions, which contributes to the observed increase in conductivity. The excess molar Gibbs energies, enthalpies, and entropies of activation have also been determined.

Choline halide↗
DOE OSTI2025

A fluctuating hydrodynamics model for nanoscale surfactant-laden interfaces

A multispecies diffuse interface model is formulated in a fluctuating hydrodynamics framework for the purpose of simulating surfactant interfaces at the nanoscale. The model generalizes previous work to ternary mixtures, employing a Cahn-Hilliard free energy density combined with incompressible, isothermal fluctuating hydrodynamics where dissipative fluxes include both deterministic and stochastic terms. The intermolecular parameters in the free energy are chosen such that one species acts as a partially miscible surfactant. From Laplace pressure measurements, we show that in this model the surface tension decreases linearly with surfactant concentration, leading to Marangoni convection for interfaces with concentration gradients. In the capillary wave spectrum for interfaces with and without surfactant, we find that for the former, the spectrum deviates significantly from classical capillary wave theory, presumably due to Gibbs elasticity. In non-equilibrium simulations of the Rayleigh-Plateau instability, deterministic simulations showed that the surfactant delays pinching of a fluid cylinder into droplets. However, stochastic simulations indicate that thermal fluctuations disrupt the surfactant's stabilizing effect. Similarly, the spreading of a patch of surfactant, driven by Marangoni convection, was found to be partially suppressed by thermal fluctuations.

Capillary waves↗
DOE OSTI2022

On the mechanisms of ion adsorption to aqueous interfaces: air-water vs. oil-water

The adsorption of ions to water-hydrophobe interfaces influences a wide range of phenomena, including chemical reaction rates, ion transport across biological membranes, and electrochemical and many catalytic processes; hence, developing a detailed understanding of the behavior of ions at water-hydrophobe interfaces is of central interest. Here, we characterize the adsorption of the chaotropic thiocyanate anion (SCN − ) to two prototypical liquid hydrophobic surfaces, water-toluene and water-decane, by surface-sensitive nonlinear spectroscopy and compare the results against our previous studies of SCN − adsorption to the air-water interface. For these systems, we observe no spectral shift in the charge transfer to solvent spectrum of SCN − , and the Gibb’s free energies of adsorption for these three different interfaces all agree within error. We employed molecular dynamics simulations to develop a molecular-level understanding of the adsorption mechanism and found that the adsorption for SCN − to both water-toluene and water-decane interfaces is driven by an increase in entropy, with very little enthalpic contribution. This is a qualitatively different mechanism than reported for SCN − adsorption to the air-water and graphene-water interfaces, wherein a favorable enthalpy change was the main driving force, against an unfavorable entropy change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Strong adsorption of guanidinium cations to the air–water interface

Combining Deep-UV second harmonic generation spectroscopy with molecular simulations, we confirm and quantify the specific adsorption of guanidinium cations to the air–water interface. Using a Langmuir analysis of measurements at multiple concentrations, we extract the Gibbs free energy of adsorption, finding it larger than typical thermal energies. Molecular simulations clarify the role of polarizability in tuning the thermodynamics of adsorption, and establish the preferential parallel alignment of guanidinium at the air–water interface. As a polyatomic cation, guanidinium represents one of the few examples of a positively charged species to exhibit a propensity for the air-water interface. As such, these results expand on the growing body of work on specific ion adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multiphasic size-dependent growth dynamics of nanoparticle ensembles

Colloidal nanoparticles are of great interest in modern science and industry. However, the thermodynamic mechanism and dynamics of nanoparticle growth have yet to be understood. Addressing these issues, we tracked hundreds of in-situ growth trajectories of a nanoparticle ensemble using liquid-phase TEM and found that the nanoparticle growth, including coalescence, exhibits nanoparticle size-dependent multiphasic dynamics, unexplainable by current theories. Motivated by this finding, we developed a model and theory for an ensemble of growing nanoparticles, providing a unified, quantitative understanding of the time-dependent mean and fluctuation of nanoparticle size and size-dependent growth rate profiles across various nanoparticle systems and experimental conditions. Our work reveals that the chemical potential in a small nanoparticle strongly deviates from the Gibbs-Thomson equation, shedding light on how it governs the size-dependent growth dynamics of nanoparticles.

Kim, Ji-Hyun↗
DOE OSTI2021

Multiphysics Coupling Methods for Molten Salt Reactor Modeling and Simulation in VERA

New multiphysics coupling capabilities for molten salt reactor (MSR) analysis have been developed in the Virtual Environment for Reactor Applications (VERA). This development consisted of two main efforts. First, a generic species transport module was added in the CTF code, which is the thermal-hydraulics (TH) code for VERA. This module uses the velocity fields for which CTF solves during the TH calculation to transport species through the core and around the primary loop. Additionally, a gas sparging model has been added to CTF to model the movement of certain species, namely, fission products such as xenon gas, to transport between the molten salt and gas bubbles present in the salt. The second effort in this development was coupling this capability to VERA’s neutron transport code MPACT. This effort focused on coupling the detailed TH transport models in CTF to MPACT to account for feedback effects in the neutron transport calculations. Finally, the thermochemistry code Thermochimica has also been coupled to VERA. Thermochimica performs pointwise calculations for chemical potential and Gibbs free energy and determines what phases are produced by the temperature, pressure, and elemental concentrations at different locations in the primary loop. These capabilities are demonstrated using a model of the Molten Salt Reactor Experiment (MSRE). Furthermore, this reactor operated at Oak Ridge National Laboratory in the 1960s, providing sources of experimental data that were used to develop the model. Various combinations of species were modeled using VERA’s new multiphysics coupling capabilities. Species distributions and reactivity effects behaved as expected for the MSRE model, demonstrating that the coupling is behaving correctly and causing appropriate feedback. The results of these calculations show the potential for VERA to be used for a wide variety of MSR analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Application of MELCOR for Simulating Molten Salt Reactor Accident Source Terms

Molten Salt Reactor (MSR) systems can be divided into two basic categories: liquid-fueled MSRs in which the fuel is dissolved in the salt, and solid-fueled systems such as the Fluoride-salt-cooled High-temperature Reactor (FHR). The molten salt provides an impediment to fission product release as actinides and many fission products are soluble in molten salt. Nonetheless, under accident conditions, some radionuclides may escape the salt by vaporization and aerosol formation, which may lead to release into the environment. Here, we present recent enhancements to MELCOR to represent the transport of radionuclides in the salt and releases from the salt. Some soluble but volatile radionuclides may vaporize and subsequently condense to aerosol. Insoluble fission products can deposit on structures. Thermochimica, an open-source Gibbs Energy Minimization (GEM) code, has been integrated into MELCOR. With the appropriate thermochemical database, Thermochimica provides the solubility and vapor pressure of species as a function of temperature, pressure, and composition, which are needed to characterize the vaporization rate and the state of the salt with fission products. Since thermochemical databases are still under active development for molten salt systems, thermodynamic data for fission product solubility and vapor pressure may be user specified. This enables preliminary assessments of fission product transport in molten salt systems. In this paper, we discuss modeling of soluble and insoluble fission product releases in a MSR with Thermochimica incorporated into MELCOR. Separate-effects experiments performed as part of the Molten Salt Reactor Experiment in which radioactive aerosol was released are discussed as needed for determining the source term.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

The importance of accounting for the Tolman correction to surface tension for nucleation and growth modeling of Fe clusters

Gibbs free energies of clusters are required for predictive modeling of cluster growth during condensation of a cooling vapor. Here, we present a straightforward method of calculating free energies of cluster formation using the data from molecular dynamics (MD) simulations. We apply this method to iron clusters having from 2 to 100 atoms. The energies obtained are verified by comparing to an MD-simulated equilibrium cluster size distribution in a sub-saturated vapor. We show that these free energies differ significantly from those obtained with a commonly used spherical cluster approximation, which relies on a surface tension coefficient of a flat surface, as it is used in the classical nucleation theory (CNT). We show that the spherical cluster approximation in CNT can be improved by using a cluster-size-dependent Tolman correction for the surface tension. The Tolman length and effective surface tension values were derived for iron clusters, and they significantly differ from the commonly used experimentally measured values. This improved approximation does not account for geometric magic number effects responsible for spikes and troughs in densities of neighbor cluster sizes. Nonetheless, it allows to more accurately model cluster formation from a cooling vapor. It better reproduces the condensation timeline, overall shape of the cluster size distribution, average cluster size, and the distribution width. In contrast, using a constant surface tension coefficient (as done in CNT) resulted in incorrect condensation dynamics and cluster size distributions. The analytical expression for cluster nucleation rate from CNT was updated to account for the size-dependence of cluster surface tension.

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

Landmark-embedded Gaussian process with applications for functional data modeling

In practice, we often need to infer the value of a target variable from functional observation data. A challenge in this task is that the relationship between the functional data and the target variable is very complex: the target variable not only influences the shape but also the location of the functional data. In addition, due to the uncertainties in the environment, the relationship is probabilistic, that is, for a given fixed target variable value, we still see variations in the shape and location of the functional data. To address this challenge, we present a landmark-embedded Gaussian process model that describes the relationship between the functional data and the target variable. A unique feature of the model is that landmark information is embedded in the Gaussian process model so that both the shape and location information of the functional data are considered simultaneously in a unified manner. Gibbs-Metropolis-Hasting algorithm is used for model parameters estimation and target variable inference. The performance of the proposed framework is evaluated by extensive numerical studies and a case study of nano-sensor calibration.

42 ENGINEERING↗
DOE OSTI2024

Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localization

Abstract This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.

Tarpau, Cécilia (ORCID:0000000286539490)↗
DOE OSTI2021

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗
DOE OSTI2021

eQuilibrator 3.0: a database solution for thermodynamic constant estimation

Abstract eQuilibrator (equilibrator.weizmann.ac.il) is a database of biochemical equilibrium constants and Gibbs free energies, originally designed as a web-based interface. While the website now counts around 1,000 distinct monthly users, its design could not accommodate larger compound databases and it lacked a scalable Application Programming Interface (API) for integration into other tools developed by the systems biology community. Here, we report on the recent updates to the database as well as the addition of a new Python-based interface to eQuilibrator that adds many new features such as a 100-fold larger compound database, the ability to add novel compounds, improvements in speed and memory use, and correction for Mg2+ ion concentrations. Moreover, the new interface can compute the covariance matrix of the uncertainty between estimates, for which we show the advantages and describe the application in metabolic modelling. We foresee that these improvements will make thermodynamic modelling more accessible and facilitate the integration of eQuilibrator into other software platforms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Flux trapping in NbTiN strips

We use scanning superconducting quantum interference device (SQUID) microscopy to image vortices in superconducting structures fabricated from NbTiN thin films. We repeatedly cool superconducting strips with different width in an applied magnetic field and image the individual vortices. From these images we determine the threshold field at which the first vortex enters a strip and the number and configuration of vortices beyond this threshold field. We model the behavior of the vortices with and without considering the effect of pinning using numerical methods to minimize the Gibbs free energy of vortices in the strips. Our measurements provide a first benchmark to investigate the flux trapping properties of NbTiN thin films directly relevant to NbTiN-based superconducting digital circuits.

Bai, Ruiheng [Cornell University] (ORCID:000000025↗
DOE OSTI2025

Thermodynamic Modeling of Complex Solid Solutions in the Lu-H-N System via Graph Neural Network Accelerated Monte Carlo Simulations

Metal hydrides are important across diverse applications, such as hydrogen storage, batteries, gas sensors, nuclear reactions, and high-temperature superconductivity. Previous computational studies of metal hydrides under extreme pressures, e.g., 𝑂⁡(10 2 ) ⁢GPa, usually treat them as stoichiometric compounds without considering interstitial lattice disorder. As pressures become more moderate in the 𝑂⁡(10 0 ) ⁢GPa and below range, hydrogen disorder at interstitial lattice sites becomes prominent, e.g., in the N-doped Lu hydride that was recently claimed superconducting near 1 GPa. Further adding compositional complexity from alloying and/or multielement interstitial occupation makes elucidating pressure- and temperature-dependent observables intractable by first-principles calculations alone. We therefore propose a lattice graph neural-network surrogate modeling approach to predict configuration- and pressure-dependent equation-of-state properties. Their efficiency permits Monte Carlo simulations to calculate Gibbs energies and pressure-dependent phase diagrams, thereby revealing insights into the synthesis conditions required for achieving desired phase equilibria. We demonstrate this concept for the compositionally complex cubic Lu(H,N,Va) 3 system where three constituents (hydrogen, nitrogen and vacancy) have disordered multielement interstitial occupancies and insights into pressure-dependent phase equilibria are critically needed, e.g., N-doping levels can significantly lower dehydrogenation temperatures and provide a new strategy to optimize hydrogen-storage alloys. This work can improve the thermodynamic understanding of the Lu-H-N system and help rational synthesis of N-doped Lu hydrides, but more generally demonstrates an efficient approach to model pressure-dependent thermodynamics of multicomponent solid solutions.

Monte Carlo methods↗
DOE OSTI2024

Robust finite-temperature many-body scarring on a quantum computer

Mechanisms for suppressing thermalization in disorder-free many-body systems, such as Hilbert space fragmentation and quantum many-body scars, have recently attracted much interest in foundations of quantum statistical physics and potential quantum information processing applications. However, their sensitivity to realistic effects such as finite temperature remains largely unexplored. Here, we have utilized IBM's Kolkata quantum processor to demonstrate an unexpected robustness of quantum many-body scars at finite temperatures when the system is prepared in a thermal Gibbs ensemble. We identify such robustness in the PXP model, which describes quantum many-body scars in experimental systems of Rydberg atom arrays and ultracold atoms in tilted Bose-Hubbard optical lattices. By contrast, other theoretical models which host exact quantum many-body scars are found to lack such robustness and their scarring properties quickly decay with temperature. Our study sheds light on the important differences between scarred models in terms of their algebraic structures, which impacts their resilience to finite temperature. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Dominant effect of anharmonicity on the equation of state and thermal conductivity of MgO under extreme conditions

Understanding heat transfer in the earth mantle region is of great scientific interest but highly challenging due to dissimilar conditions from our daily lives. Thermal conductivity of highly pressured and thermally activated materials can be completely different from that at ambient condition. In this study we calculate the equation of state and thermal conductivity of cubic crystalline MgO, a major component of the mantle, in such an environment. It is shown that the material properties are not accurately captured unless rigorous treatment of anharmonicity of phonon vibrational motion is explicitly applied. To predict renormalized phonon dispersion relations, interatomic force constants of high-order expansion are required, especially at elevated temperature. The anharmonicity plays an increasingly substantial role for regulating volume expansion as temperature rises, because the Gibbs free energy of MgO considerably deviates from what was predicted by the quasiharmonic approximation. We find that the lattice thermal conductivity of MgO and the heat transfer of the earth's mantle are reliably estimated only when both the temperature-dependent renormalization of phonon frequencies and four-phonon scattering effects are taken into consideration. We map the characteristics at Geotherm into contour diagrams in which equilibrium volumes and the thermal conductivities are described as functions of temperature and pressure. Furthermore, the thermal conductivity values of MgO in this study are smaller than those in previous theoretical studies due to the additional incorporation of four-phonon scatterings in the calculations. Specifically, deviation between the values in previous studies and in this study becomes larger as thermodynamic variables reach those near the core-mantle boundary. For instance, thermal conductivities of 52.15 and 23.67 Wm -1 K -1 are estimated at ambient and extreme conditions (T = 4000K and P = 135 GPa), respectively.

36 MATERIALS SCIENCE↗