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At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2015

The impact of vertical shear on the sensitivity of tropical cyclogenesis to environmental rotation and thermodynamic state

Abstract The impact of vertical wind shear on the sensitivity of tropical cyclogenesis to environmental rotation and thermodynamic state is investigated through idealized cloud‐resolving simulations of the intensification of an incipient vortex. With vertical shear, tropical cyclones intensify faster with a higher Coriolis parameter, f , irrespective of the environmental thermodynamic state. The vertical shear develops a vertically tilted vortex, which undergoes a precession process with the midlevel vortices rotating cyclonically around the surface center. With a higher f , the midlevel vortices are able to rotate continuously against the vertical shear, leading to the realignment of the tilted vortex and rapid intensification. With a lower f , the rotation is too slow such that the midlevel vortices are advected away from the surface center and the intensification is suppressed. The parameter, χ b , measuring the effect from the low‐entropy downdraft air on the boundary layer entropy, is found to be a good indicator of the environmental thermodynamic favorability for tropical cyclogenesis in vertical shear. Without vertical shear, tropical cyclones are found to intensify faster with a lower f by previous studies. We show this dependency on f is sensitive to the environmental thermodynamic state. The thermodynamical favorability for convection can be measured by χ m , which estimates the time it takes for surface fluxes to moisten the midtroposphere. A smaller χ m not only leads to a faster intensification due to a shorter period for moist preconditioning of the inner region but also neutralizes the faster intensification with a lower f due to enhanced peripheral convection.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Thermodynamic Implementations of Quantum Processes

Abstract Recent understanding of the thermodynamics of small-scale systems have enabled the characterization of the thermodynamic requirements of implementing quantum processes for fixed input states. Here, we extend these results to construct optimal universal implementations of a given process, that is, implementations that are accurate for any possible input state even after many independent and identically distributed (i.i.d.) repetitions of the process. We find that the optimal work cost rate of such an implementation is given by the thermodynamic capacity of the process, which is a single-letter and additive quantity defined as the maximal difference in relative entropy to the thermal state between the input and the output of the channel. Beyond being a thermodynamic analogue of the reverse Shannon theorem for quantum channels, our results introduce a new notion of quantum typicality and present a thermodynamic application of convex-split methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

The impact of mixed solvents on the complexation thermodynamics of Eu(III) by simple carboxylate and amino carboxylate ligands

To gain insight on the role of mixed solvents on the thermodynamic driving forces for the complexation between trivalent f-elements and organic ligands, solution phase thermodynamic parameters were determined for Eu(III) complexation with 2-hydroxyisobutyric acid (HIBA) and 2-aminoisobutyric acid (AIBA) in mixed methanol (MeOH)-water and N,N-dimethylformamide (DMF)-water solvents. Included in this study were the determination of mixed solvent autoprotolysis constants (pK α ) as well as the thermodynamic formation constants: log β, ΔG, ΔH, and ΔS, for ligand protonation and Eu(III)-ligand complexation utilizing potentiometry and calorimetry techniques. The results presented are conditional thermodynamic values determined at an ionic strength of 1.0 M NaClO 4 and a temperature of 298 K. It was found that moving from an aqueous solution to a binary aqueous-organic solvent affected all solution equilibria to some degree and that the extent of change depended on both the type of mixed solvent and the ligand in each study. Here, the ability to understand and predict these changes in thermodynamic values as a function of solvent composition provides important information about the chemistry of the trivalent f-elements.

2-aminoisobutyric acid↗

DOE OSTI2013

Effects of A-site composition and oxygen nonstoichiometry on the thermodynamic stability of compounds in the Ba–Sr–Co–Fe–O system

The thermodynamic stability of the perovskite-type oxides in the Ba{sub x}Sr{sub 1−x}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} (BSCF) system was investigated with varying Ba:Sr ratios (x=0.2, 0.4, 0.5, 0.6, 0.8) and correlated with the charge compensation mechanism and the change in the oxygen stoichiometry of the materials. Thermodynamic properties represented by the relative partial molar free energies, enthalpies and entropies of oxygen dissolution in the perovskite phase, as well as the equilibrium partial pressures of oxygen have been obtained in the temperature range of 823–1273 K using solid electrolyte electrochemical cells (EMF) method. The influence of the oxygen stoichiometry change on the thermodynamic properties was examined using a coulometric titration technique coupled with EMF measurements. The temperature dependence of enthalpy increment (H{sub T}−H{sub 298}) in the temperature range of 700–900 K was measured by drop calorimetry. The energetic parameters allow for the correlation of the structural and electrical stability with the defect structures. - Graphical abstract: Partial molar energy of oxygen dissolution (ΔG{sup ¯}{sub O{sub 2}}) (EMF measurements) and enthalpy increment (H{sub T}−H{sub 298}) (drop calorimetry data) of perovskite materials with the composition Ba{sub x}Sr{sub 1−x}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} as a function of temperature and Barium content. Highlights: ► We report relevant data for thermodynamic stability of Ba{sub x}Sr{sub 1−x}Co{sub 1−y}Fe{sub y}O{sub 3−δ} compounds. ► Temperature of structural transformations is evidenced as a function of Ba content. ► Correlation between thermodynamic, electrical and structural data is investigated. ► The results are discussed based on the properties-defect structure relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Ab Initio Thermodynamic Model for Magnesium Carbonates and Hydrates

An ab initio thermodynamic framework for predicting properties of hydrated magnesium carbonate minerals has been developed using density-functional theory linked to macroscopic thermodynamics through the experimental chemical potentials for MgO, water, and CO2. Including semiempirical dispersion via the Grimme method and small corrections to the generalized gradient approximation of Perdew, Burke, and Ernzerhof for the heat of formation yields a model with quantitative agreement for the benchmark minerals brucite, magnesite, nesquehonite, and hydromagnesite. The model shows how small differences in experimental conditions determine whether nesquehonite, hydromagnesite, or magnesite is the result of laboratory synthesis from carbonation of brucite, and what transformations are expected to occur on geological time scales. Because of the reliance on parameter-free first principles methods, the model is reliably extensible to experimental conditions not readily accessible to experiment and to any mineral composition for which the structure is known or can be hypothesized, including structures containing defects, substitutions, or transitional structures during solid state transformations induced by temperature changes or processes such as water, CO2, or O2 diffusion. Demonstrated applications of the ab initio thermodynamic framework include an independent means to evaluate differences in thermodynamic data for lansfordite, predicting the properties of Mg analogs of Ca-based hydrated carbonates monohydrocalcite and ikaite which have not been observed in nature, and an estimation of the thermodynamics of barringtonite from the stoichiometry and a single experimental observation.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2024

Optimal thermodynamic conditions to minimize kinetic by-products in aqueous materials synthesis

Abstract Phase diagrams offer substantial predictive power for materials synthesis by identifying the stability regions of target phases. However, thermodynamic phase diagrams do not offer explicit information regarding the kinetic competitiveness of undesired by-product phases. Here we propose a quantitative and computable thermodynamic metric to identify synthesis conditions under which the propensity to form kinetically competing by-products is minimized. We hypothesize that thermodynamic competition is minimized when the difference in free energy between a target phase and the minimal energy of all other competing phases is maximized. We validate this hypothesis for aqueous materials synthesis through two empirical approaches: first, by analysing 331 aqueous synthesis recipes text-mined from the literature; and second, by systematic experimental synthesis of LiIn(IO 3 ) 4 and LiFePO 4 across a wide range of aqueous electrochemical conditions. Our results show that even for synthesis conditions that are within the stability region of a thermodynamic Pourbaix diagram, phase-pure synthesis occurs only when thermodynamic competition with undesired phases is minimized.

Wang, Zheren (ORCID:0000000227429451)↗

DOE OSTI2026

A mathematical framework for thermodynamic computing with applications to chemical reaction networks

The widespread adoption of energy-intensive computing applications has led to a growing need for energy-efficient computing approaches. Thermodynamic computing offers a promising approach for low-energy computation by leveraging the intrinsic computational capabilities of physical, chemical, or biological systems. However, the mathematical foundations of thermodynamic computing require further development to fully realize the potential energy efficiencies, as well as to assess factors like noise and operational speed. In this paper, we establish a mathematical framework for utilizing thermodynamic processes to perform fundamental operations, including addition, subtraction, multiplication, and division. We highlight the use of chemical reactions as potential computational units and explore synthetic chemical and biochemical systems as practical implementations. Additionally, we demonstrate how these principles can be applied to solving complex mathematical problems, such as ordinary differential equations (ODEs) and suggest the necessary components to implement the thermodynamic computing framework using chemical reactions based in a microfluidic device. This work enhances our understanding of thermodynamic processes for natural computing as a basis for scalable, energy-efficient computation in paradigm disruptive next-generation systems.

Cannon, William R. [Pacific Northwest National Lab↗

DOE OSTI2016

Solvent influence on the thermodynamics for hydride transfer from bis(diphosphine) complexes of nickel

The thermodynamic hydricity of a metal hydride can vary considerably between solvents. This parameter can be used to determine the favourability of a hydride-transfer reaction, such as the reaction between a metal hydride and CO 2 to produce formate. Because the hydricities of these species do not vary consist ently between solvents, reactions that are thermodynamically unfavourable in one solvent can be favour able in others. The hydricity of a water-soluble, bis-phosphine nickel hydride complex was compared to the hydricity of formate in water and in acetonitrile. Formate is a better hydride donor than [HNi(dmpe) 2 ] + by 7 kcal mol -1 in acetonitrile, and no hydride transfer from [HNi(dmpe) 2 ] + to CO 2 occurs in this solvent. The hydricity of [HNi(dmpe) 2 ] + is greatly improved in water relative to acetonitrile, in that reduction of CO 2 to formate by [HNi(dmpe) 2 ] + was found to be thermodynamically downhill by 8 kcal mol -1 . Catalysis for the hydrogenation of CO 2 was pursued; however, the regeneration of [HNi(dmpe) 2 ] under catalytic conditions was unfavourable. However, the present results demonstrate that the solvent dependence of thermodynamic parameters such as hydricity and acidity can be exploited in order to produce systems with balanced or favourable overall thermodynamics. This approach should be advantageous for the design of future water-soluble catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Generalizing thermodynamic properties of bulk single-walled carbon nanotubes

The enthalpy and Gibbs free energy thermodynamical potentials of single walled carbon nanotubes were studied of all types (armchairs, zig-zags, chirals (n>m), and chiral (n<m)). Bulk values of these thermodynamic potentials were obtained using a previously demonstrated robust method based on semi-empirical PM3 calculations and an extrapolated cluster approach. Those values were used to study the relationship between the thermodynamic potentials and the diameter of the nanotube. Results of this study led to the proposal of a single equation for the thermodynamical potential of ΔH{sub AB}{sup 298 K} or ΔG{sub AB}{sup 298 K} (assembly of nanotubes from atoms) versus the chiral vector indexes n and m for any given nanotube. The equations show a good level of accuracy in predicting thermodynamic potentials for practical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Thermodynamics of electrolyte solutions near charged surfaces: Constant surface charge vs constant surface potential

Electric double layers are ubiquitous in science and engineering and are of current interest, owing to their applications in the stabilization of colloidal suspensions and as supercapacitors. While the structure and properties of electric double layers in electrolyte solutions near a charged surface are well characterized, there are subtleties in calculating thermodynamic properties from the free energy of a system with charged surfaces. These subtleties arise from the difference in the free energy between systems with constant surface charge and constant surface potential. In this work, we present a systematic, pedagogical framework to properly account for the different specifications on charged bodies in electrolyte solutions. Our approach is fully variational—that is, all free energies, boundary conditions, relevant electrostatic equations, and thermodynamic quantities are systematically derived using variational principles of thermodynamics. We illustrate our approach by considering a simple electrolyte solution between two charged surfaces using the Poisson–Boltzmann theory. Our results highlight the importance of using the proper thermodynamic potential and provide a general framework for calculating thermodynamic properties of electrolyte solutions near charged surfaces. Specifically, we present the calculation of the pressure and the surface tension between two charged surfaces for different boundary conditions, including mixed boundary conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.

computation↗

DOE OSTI2019

Macroscopic Thermodynamic Reversibility in Quantum Many-Body Systems

The resource theory of thermal operations, an established model for small-scale thermodynamics, provides an extension of equilibrium thermodynamics to nonequilibrium situations. On a lattice of any dimension with any translation-invariant local Hamiltonian, we identify a large set of translation-invariant states that can be reversibly converted to and from the thermal state with thermal operations and a small amount of coherence. These are the spatially ergodic states, i.e., states that have sharp statistics for any translation-invariant observable, and mixtures of such states with the same thermodynamic potential. As an intermediate result, we show for a general state that if the gap between the min- and the max-relative entropies to the thermal state is small, then the state can be approximately reversibly converted to and from the thermal state with thermal operations and a small source of coherence. Our proof provides a quantum version of the Shannon-McMillan-Breiman theorem for the relative entropy and a quantum Stein’s lemma for ergodic states and local Gibbs states. In this work, our results provide a strong link between the abstract resource theory of thermodynamics and more realistic physical systems as we achieve a robust and operational characterization of the emergence of a thermodynamic potential in translation-invariant lattice systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Thermodynamic Assessment of the Ternary Alloy System Li-Sn-Zn

The goal of this project is to predict thermodynamics and structure-properties relationships of a series of Li-based alloys for the development of advanced tritium breeding materials that exhibit the beneficial properties of pure lithium while mitigating its chemical reactivity issues for fusion applications. This project makes use of phenomenological thermodynamics based on the CALPHAD (CALculation of PHAse Diagrams), and the use of the Thermo-Calc software (see Appendix A), and experimental calorimetric data and structural characterization for the purpose of validating the data. The initial selection of Sn and Zn as solutes is considered in this first report. Originally Li-Sn alloys have shown promise in meeting tritium breeding ratio (TBR) and energy multiplication requirements. However with the addition of Zn, we expect an improvement in the nuclear, thermal, and chemical requirements of the working fluid. Other substitutes will be considered once neutronic calculations are carried out. Hence the objective of this first task is to carry out a thermodynamic assessment of the Li-Sn-Zn alloy system, as part of the development of a self-consistent and validated thermodynamic database that will include other solute elements for optimizing the properties of blanket materials in fusion-based reactors. This obviously involves the thermodynamic assessment of the three binary subsystems, namely Li-Sn, Li-Zn, and Sn-Zn.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Coupled Mass and Heat Transport Models for Nuclear Fuels using Thermodynamic Calculations

We have developed a theoretical framework for incorporation of thermodynamic equilibrium calculations into engineering models of nuclear fuel problems based on the finite element method (FEM). The framework is based on linear irreversible thermodynamics and their incorporation into integral equations for balancing energy and mass. For coupled energy and mass transport, thermodynamic calculations are performed at the nodal points of the FEM mesh and are used at the integration points to calculate the driving forces and fluxes for irreversible thermodynamic problems. The consistent coupling of thermodynamic models with isotopic calculations and other nuclear fuel physics models has been described. The approach has been demonstrated on simple unit problems. Implementation in practical nuclear fuel problems will be developed follow-on research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Physical and Thermodynamic Properties of Secondary Organic Materials for Modeling (Final Technical Report)

Secondary organic material constitutes more than 50% of the submicron component of atmospheric aerosol particles. This organic material is produced by oxidation of biogenic and anthropogenic volatile organic compounds. The physicochemical properties of these aerosol particles and their variability with atmospheric conditions influence many climate-relevant endpoints, such as rates of chemical reactions, production of secondary organic material, number-diameter distributions, direct radiative forcing, and cloud condensation nuclei. The results of the project research highlight a nonlabile-to-labile transition for material representative of anthropogenic secondary organic particulate matter at a threshold humidity range. This behavior differs markedly from materials representing biogenic aerosol sources, which lack such a transition. More specifically, the mass lability of atmospheric organic particulate matter, meaning its tendency to evaporate, is an important property in the mechanisms governing the climate effects. This property is affected by both the volatility and the molecular diffusivity of the constituent organic species. Via a series of laboratory experiments, the project directly determined the mass labilities of films of secondary organic material representative of anthropogenic and biogenic organic particulate matter (PM). The evaporation rates for anthropogenic organic PM increased above a threshold relative humidity (RH) between 20% and 30%, indicating rapid partitioning above a transition RH. Below the threshold, the characteristic time for equilibration was estimated at up to 1 week for a typically sized particle. In contrast, for films representing biogenic PM, no RH threshold was observed, suggesting equilibrium partitioning is rapidly obtained for all RHs. The effective molecular diffusivity for the biogenic case was at least 1000 times greater than that of the anthropogenic case. The results allow for an improved representation of anthropogenic and biogenic secondary organic aerosol formation in climate models. The results of the project also provide new measurements on how organic aerosol particles take up water and serve as cloud condensation nuclei, thus explaining the observed complex thermodynamic behaviors using a simple thermodynamic model. The project results reconciled the discrepancy between sub-saturation hygroscopicity and super-saturation cloud condensation nuclei activity for organic aerosol particles. The key to the explanation is the phase separation between hydrophobic and hydrophilic organics and the induced surface tension lowering. The results are essential for the assessment of the aerosol indirect effect on climate. In more detail, hygroscopic growth and cloud condensation nuclei activation are key processes for accurately modeling the climate impacts of organic particulate matter. Nevertheless, the microphysical mechanisms of these processes remain unresolved. The project results focus on complex thermodynamic behaviors, including humidity-dependent hygroscopicity, diameter-dependent cloud condensation nuclei activity, and liquid-liquid phase separation in the laboratory for biogenically derived secondary organic material representative of similar atmospheric organic particulate matter. These behaviors can be explained by the non-ideal mixing of water with hydrophobic and hydrophilic organic components. The non-ideality-driven liquid-liquid phase separation further enhances water uptake and induces lowered surface tension at high relative humidity, which results in a lower barrier to cloud condensation nuclei activation. By comparison, secondary organic material representing anthropogenic sources does not exhibit complex thermodynamic behavior. The combined results highlight the importance of detailed thermodynamic representations of the hygroscopicity and cloud condensation nuclei activity in models of the Earth’s climate system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Evolution of the Thermodynamic Properties of Clusters of Galaxies out to Redshift of 1.8

The thermodynamic properties of the hot plasma in galaxy clusters retains information on the processes leading to the formation and evolution of the gas in their deep, dark matter potential wells. These processes are dictated not only by gravity but also by gas physics, e.g. AGN feedback and turbulence. Here, we study the thermodynamic properties, e.g. density, temperature, pressure, and entropy, of the most massive and the most distant (z > 1.2) SPT-selected clusters, and compare them with those of the nearby clusters (z < 0.1) to constrain their evolution as a function of time and radius. We find that thermodynamic properties in the outskirts of high redshift clusters are remarkably similar to the low redshift clusters, and their evolution follows the prediction of the self-similar model. Their intrinsic scatter is larger, indicating that the physical properties that lead to the formation and virialization of cluster outskirts show evolving variance. On the other hand, thermodynamic properties in the cluster cores deviates significantly from self-similarity indicating that the processes that regulate the core are already in place in these very high redshift clusters. This result is supported by the unevolving physical scatter of all thermodynamic quantities in cluster cores.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

NASA NTRS1972

Application of thermodynamics to silicate crystalline solutions

A review of thermodynamic relations is presented, describing Guggenheim's regular solution models, the simple mixture, the zeroth approximation, and the quasi-chemical model. The possibilities of retrieving useful thermodynamic quantities from phase equilibrium studies are discussed. Such quantities include the activity-composition relations and the free energy of mixing in crystalline solutions. Theory and results of the study of partitioning of elements in coexisting minerals are briefly reviewed. A thermodynamic study of the intercrystalline and intracrystalline ion exchange relations gives useful information on the thermodynamic behavior of the crystalline solutions involved. Such information is necessary for the solution of most petrogenic problems and for geothermometry. Thermodynamic quantities for tungstates (CaWO4-SrWO4) are calculated.

Saxena, S. K.↗