Thermodynamic Space Research Articles

Tropical Thermodynamic–Convection Coupling in Observations and Reanalyses

Abstract This study examines thermodynamic–convection coupling in observations and reanalyses, and attempts to establish process-level benchmarks needed to guide model development. Thermodynamic profiles obtained from the NOAA Integrated Global Radiosonde Archive, COSMIC-1 GPS radio occultations, and several reanalyses are examined alongside Tropical Rainfall Measuring Mission precipitation estimates. Cyclical increases and decreases in a bulk measure of lower-tropospheric convective instability are shown to be coupled to the cyclical amplification and decay of convection. This cyclical flow emerges from conditional-mean analysis in a thermodynamic space composed of two components: a measure of “undiluted” instability, which neglects lower-free-tropospheric (LFT) entrainment, and a measure of the reduction of instability by LFT entrainment. The observational and reanalysis products examined share the following qualitatively robust characterization of these convective cycles: increases in undiluted instability tend to occur when the LFT is less saturated, are followed by increases in LFT saturation and precipitation rate, which are then followed by decreases in undiluted instability. Shallow, convective, and stratiform precipitation are coupled to these cycles in a manner consistent with meteorological expectations. In situ and satellite observations differ systematically from reanalyses in their depictions of lower-tropospheric temperature and moisture variations throughout these convective cycles. When using reanalysis thermodynamic fields, these systematic differences cause variations in lower-free-tropospheric saturation deficit to appear less influential in determining the strength of convection than is suggested by observations. Disagreements among reanalyses, as well as between reanalyses and observations, pose significant challenges to process-level assessments of thermodynamic–convection coupling.

Platinum equation of state to greater than two terapascals: Experimental data and analytical models

In order to develop a high impedance standard for shock physics applications, we investigated the equation of state (EOS) and shock compression of bulk platinum using canonical ab initio molecular dynamics (AIMD) simulations, coupled with experimental data on Sandia's Z machine. In simulations, we sampled the thermodynamic state space along isotherms ranging from 300 to 100 000 K for densities of 18 to 40 $\mathrm{g}/{\mathrm{cm}}^{3}$. While this rectilinear grid of EOS points was useful for preliminary experimental design, material going outside of the density/temperature space of the AIMD simulations required a SESAME-style, broad-range EOS, which we developed independently and subsequently compared to the AIMD simulations. In the final step we validated the SESAME EOS with experimental shock data to 2177 GPa on Sandia's Z machine. The theoretical and AIMD results are in excellent agreement with experiments.

Modeling atomically mixed graded density impactors

Graded density impactors (GDIs) are multi-material composite impactors used in gas gun experiments to tailor the drive conditions imparted to a sample test material. Previous graded density impactors generally rely on thin, but discrete, layers of different materials. The thinner and the greater number of layers will result in smoother compression. Taken to the limit of very thin layers would be pure material 1 at one surface, such as the front surface of an impactor, smoothly transitioning at the atomic scale to pure material 2 on the back surface. Such an impactor can initially shock, then smoothly compresses a material during a dynamic experiment. This type of experiment can serve to explore a larger region of thermodynamic space than a single or even multi-shock experiments. An overview of how graded density impactors are made is reviewed and sample results are given. A strategy for modeling these kinds of impactors is presented. The length scales of constituent mixing are given from the experimental build through electrochemical-deposition. Equation of state models for pure constituents and their subsequent mixtures are presented. It is demonstrated that the time scales for pressure and temperature equilibration, for atomically mixed GDIs, are short enough to be a justifiable closure for the resulting multiphase flow. Furthermore, we present simulation results of dynamic shock followed by a ramp compression, utilizing a silver/gold graded density impactor, onto a tantalum sample.

Geometric Bound on the Efficiency of Irreversible Thermodynamic Cycles.

Stochastic thermodynamics has revolutionized our understanding of heat engines operating in finite time. Recently, numerous studies have considered the optimal operation of thermodynamic cycles acting as heat engines with a given profile in thermodynamic space (e.g., P-V space in classical thermodynamics), with a particular focus on the Carnot engine. In this work, we use the lens of thermodynamic geometry to explore the full space of thermodynamic cycles with continuously varying bath temperature in search of optimally shaped cycles acting in the slow-driving regime. We apply classical isoperimetric inequalities to derive a universal geometric bound on the efficiency of any irreversible thermodynamic cycle and explicitly construct efficient heat engines operating in finite time that nearly saturate this bound for a specific model system. Given the bound, these optimal cycles perform more efficiently than all other thermodynamic cycles operating as heat engines in finite time, including notable cycles, such as those of Carnot, Stirling, and Otto. For example, in comparison to recent experiments, this corresponds to orders of magnitude improvement in the efficiency of engines operating in certain time regimes. Our results suggest novel design principles for future mesoscopic heat engines and are ripe for experimental investigation.

Thermodynamic geometry of spin-one lattice models. II. Criticality and coexistence in the mean-field approximation

We continue our study of the thermodynamic geometry of the spin one model from A. Sahay and R. Sanwari, Phys. Rev. E 105, 034134 (2022)10.1103/PhysRevE.105.034134. by probing the state space geometry of the Blume-Emery-Griffiths model and the Blume-Capel model in their mean-field approximation. By accounting for the stochastic variables involved we construct from the thermodynamic state space two complementary two-dimensional geometries with curvatures R_{m} and R_{q} which are shown to encode correlations in the model's two order parameters, the magnetization m and the quadrupole moment q. The geometry is investigated in the zero as well as the nonzero magnetic field region. We find that the relevant scalar curvatures diverge to negative infinity along the critical lines with the correct scaling and amplitude. We then probe the geometry of phase coexistence and find that the relevant curvatures predict the coexistence curve remarkably well via their respective R-crossing diagrams. We also briefly comment on the effectiveness of the geometric correlation length compared to the commonly used Ginzburg-Landau correlation length vis-à-vis their scaling properties.

Thermodynamic design space data-mining and multi-objective optimization of SCO2 Brayton cycles

This article implements the thermodynamic design space data-mining and multi-objective optimization of two typical supercritical carbon dioxide (SCO2) Brayton cycles: the recompression Brayton cycle (SCO2RBC) and the recompression reheating Brayton cycle (SCO2RRBC). Firstly, a mathematical model with more constraints has been established for the two Brayton cycles. The maximum errors of the mathematical model relative to the references for the SCO2RBC and SCO2RRBC are 2.5%, 3.5% respectively. Then, three data-mining techniques (global sensitivity analysis by ANOVA, single factor analysis, coupling analysis by SOM) are successively applied to explore the design space. As a result, four key design parameters have been identified: the maximum and the minimum cycle temperatures, the pressure ratio, and the shunt flow percentage. And they present different non-linear effects on the cycles’ performances (monotone increasing or decreasing, parabolic type with extreme point). It is also found that in order to achieve a global optimum, the maximum cycle temperature should be close to its upper bound, while the minimum cycle temperature tends to approach its lower bound, and a larger pressure ratio of compressor as well as a smaller shunt flow percentage is also required. Therefore, the data-mining methods are heuristic and can provide useful information for quickly searching the global optimums of SCO2 Brayton Cycles. Finally, a hybrid optimization algorithm is introduced to optimize the Brayton cycles. It shows that the search efficiency of the hybrid algorithm is 3 ∼ 4 times higher than the traditional stochastic algorithms. For the given design space, the cycle efficiency of the SCO2RRBC is improved by 10 percentage points. The hybrid algorithm coupled with the data-mining techniques are likely to speed up the design process of Brayton cycles, and have the potential to further improve the cycles’ performances.

Comparing Internal and Interparticle Space Effects of Metal-Organic Frameworks on Polysulfide Migration in Lithium-Sulfur Batteries.

One of the critical issues hindering the commercialization of lithium–sulfur (Li–S) batteries is the dissolution and migration of soluble polysulfides in electrolyte, which is called the ‘shuttle effect’. To address this issue, previous studies have focused on separators featuring specific chemical affinities or physical confinement by porous coating materials. However, there have been no studies on the complex effects of the simultaneous presence of the internal and interparticle spaces of porous materials in Li–S batteries. In this report, the stable Zr-based metal–organic frameworks (MOFs), UiO-66, have been used as a separator coating material to provide interparticle space via size-controlled MOF particles and thermodynamic internal space via amine functionality. The abundant interparticle space promoted mass transport, resulting in enhanced cycling performance. However, when amine functionalized UiO-66 was employed as the separator coating material, the initial specific capacity and capacity retention of Li–S batteries were superior to those materials based on the interparticle effect. Therefore, it is concluded that the thermodynamic interaction inside internal space is more important for preventing polysulfide migration than spatial condensation of the interparticle space.

Environments of Significant Tornadoes Occurring within the Warm Sector versus those Occurring along Surface Baroclinic Boundaries

Archived, hourly-analysis proximity soundings from the operational Rapid Update Cycle (RUC) model are used to examine the vertical wind profiles and thermodynamic parameter space associated with significant tornadoes (rated F2+/EF2+) occurring in the warm sector (33 events) of synoptic cyclones, as well as those occurring along surface baroclinic boundaries (52 events), during the period 1999-2010 over the central and eastern United States. These tornadoes were associated with either the warm sector or a surface baroclinic boundary through the use of subjective surface analyses, supplemented by visible satellite and WSR-88D imagery. A key finding is that measures of ground-relative wind speed, storm-relative helicity, and bulk wind difference are much stronger for warm-sector significant tornado events. In contrast, thermodynamic parameters did not distinguish between the two regimes. Among all of the parameters examined, the observed and predicted speed of the parent supercell showed the most substantial differences between warm-sector and boundary significant tornado environments.

Machine-learning integrated glassy defect from an intricate configurational-thermodynamic-dynamic space

Optimizing materials' properties and functions by controlling defects in the crystalline phase has been a cornerstone of materials science and condensed matter physics. However, this paradigm has yet to be established in the broadly defined amorphous materials, which implies the identification of very subtle structural features in an otherwise uniformly disordered medium. Here we propose and define a new integrated glassy defect (IGD), based on machine learning strategy informed by atomistic physics, and also by an extremely wide configurational, thermodynamic, and dynamic variables space of the disordered state. The IGD simultaneously includes positional topology and vibrational features, as well as the local morphology of the potential energy landscape. This unprecedented combination gives rise to a much more comprehensive and more effective definition of the ``glassy defect,'' much beyond the conventional, purely structural input. IGD can be used not only as an efficient predictor of athermal plasticity but is also transferable to detect both short-time vibrational anomalies (the boson peak), and long-time relaxation and diffusion dynamics in glasses. The integrated strategy is instrumental to build the long-sought structure-property relationship in complex media.

Geometrothermodynamics of black holes with a nonlinear source

We study thermodynamics and geometrothermodynamics of a particular black hole configuration with a nonlinear source. We use the mass as fundamental equation, from which it follows that the curvature radius must be considered as a thermodynamic variable, leading to an extended equilibrium space. Using the formalism of geometrothermodynamics, we show that the geometric properties of the thermodynamic equilibrium space can be used to obtain information about thermodynamic interaction, critical points and phase transitions. We show that these results are compatible with the results obtained from classical black hole thermodynamics.

Thermodynamic geometry of 5D R -charged black holes in extended thermodynamic space

We study a five-dimensional $R$-charged black hole in extended thermodynamic space. Here, we consider pressure and volume as conjugate thermodynamic variables. We begin with a thermodynamic study based on Maxwell's equal area rule and then compute the Ruppeiner scalar curvature for a number of different charge combinations. We mainly focus on three characteristic cases: an $R$-charged black hole with three equal charges, two equal charges, and three unequal charges. Based on our analysis, we make an attempt to relate the Ruppeiner scalar curvature with the phase structure of the black hole.

Probabilistic thermodynamic analysis of metabolic networks.

MotivationRandom sampling of metabolic fluxes can provide a comprehensive description of the capabilities of a metabolic network. However, current sampling approaches do not model thermodynamics explicitly, leading to inaccurate predictions of an organism’s potential or actual metabolic operations.ResultsWe present a probabilistic framework combining thermodynamic quantities with steady-state flux constraints to analyze the properties of a metabolic network. It includes methods for probabilistic metabolic optimization and for joint sampling of thermodynamic and flux spaces. Applied to a model of Escherichia coli, we use the methods to reveal known and novel mechanisms of substrate channeling, and to accurately predict reaction directions and metabolite concentrations. Interestingly, predicted flux distributions are multimodal, leading to discrete hypotheses on E.coli’s metabolic capabilities.Availability and implementationPython and MATLAB packages available at https://gitlab.com/csb.ethz/pta.Supplementary informationSupplementary data are available at Bioinformatics online.

Thermodynamic Discrimination between Energy Sources for Chemical Reactions

Summary Chemical transformations traverse large energy differences, yet the comparison of energy sources to drive a reaction is often done on a case-by-case basis; there is no fundamentally driven, universal framework with which to analyze and compare driving forces for chemical reactions. In this work, we present a reaction-independent expression for the equilibrium constant as a function of temperature, pressure, and voltage. With a specific set of axes, all reactions are represented by a single ( x , y ) point, and a quantitative divide between electrochemically and thermochemically driven reactions is visually evident. Additionally, we show that our expression has a strong physical basis in work and energy fluxes to the system, although specific data about operating conditions are necessary to provide a quantitative energy analysis. Overall, this universal equation and facile visualization of chemical reactions provides a consistent thermodynamic framework for comparing electrochemical versus thermochemical energy sources without knowledge of detailed process parameters.

Prediction of Failure in Ceramic Matrix Composites Using Damage-Based Failure Criterion

This paper presents a damage-based failure criterion and its implementation in order to predict failure in ceramic matrix composites (CMC) manufactured via filament winding. The material behavior of CMCs is anisotropic and strongly depends on the angle between fiber orientation and loading direction. The inelastic behavior of laminates with different fiber orientations under tension and shear is modeled with the help of continuum damage mechanics. The parameters required for the damage model are obtained from a standard tensile and shear test. An isotropic damage law determines the evolution of damage in thermodynamic space and considers the interaction of damage parameters in different principal material directions. A quadratic damage-based failure criterion inspired by the Tsai-Wu failure criterion is proposed. Failure stress and strain can be predicted with higher accuracy compared to the Tsai-Wu failure criterion in stress- or strain-space. The use of the proposed damage limits allows designing a CMC component based on the microstructural phenomenon of stiffness loss. With the help of results obtained from modeling and experiments, fracture mechanics during the Iosipescu-shear test of CMCs and its capability to determine the shear strength of the material is discussed.

Data-driven computational prediction and experimental realization of exotic perovskite-related polar magnets

Rational design of technologically important exotic perovskites is hampered by the insufficient geometrical descriptors and costly and extremely high-pressure synthesis, while the big-data driven compositional identification and precise prediction entangles full understanding of the possible polymorphs and complicated multidimensional calculations of the chemical and thermodynamic parameter space. Here we present a rapid systematic data-mining-driven approach to design exotic perovskites in a high-throughput and discovery speed of the A2BB’O6 family as exemplified in A3TeO6. The magnetoelectric polar magnet Co3TeO6, which is theoretically recognized and experimentally realized at 5 GPa from the six possible polymorphs, undergoes two magnetic transitions at 24 and 58 K and exhibits helical spin structure accompanied by magnetoelastic and magnetoelectric coupling. We expect the applied approach will accelerate the systematic and rapid discovery of new exotic perovskites in a high-throughput manner and can be extended to arbitrary applications in other families.

Reparametrizations and metric structures in thermodynamic phase space

We investigate the consequences of reparametrizations in the geometric description of thermodynamics analyzing the effects on the thermodynamic phase space. It is known that the contact and Riemannian structures of the thermodynamic phase space are related to thermodynamic equilibrium and statistical fluctuations in the Boltzmann–Gibbs statistical mechanics. The physical motivation for this analysis rests upon the possibility of having, instead of a direct control of the intensive parameters determining the state of the corresponding physical reservoirs, the control of a set of differentiable functions of the original variables. Likewise, we consider a set of differentiable functions of the extensive variables accounting for the possibility of not having direct access to the original variables. We find that the effect of reparametrizations on the thermodynamic phase space can be codified, in geometrical terms, in its contact and Riemannian structures. In particular, we single out a rank-two tensor that enters in the definition of the metric which geometrically comprises the information about such reparametrizations. We notice that even if these geometric structures are modified by the reparametrizations, the metric structure on the thermodynamic space of equilibrium states is preserved.

Relativistic quantum thermodynamics of moving systems

We analyse the thermodynamics of a quantum system in a trajectory of constant velocity that interacts with a static thermal bath. The latter is modeled by a massless scalar field in a thermal state. We consider two different couplings of the moving system to the heat bath, a coupling of the Unruh-DeWitt type and a coupling that involves the time derivative of the field. We derive the master equation for the reduced dynamics of the moving quantum system. It has the same form with the quantum optical master equation, but with different coefficients that depend on velocity. This master equation has a unique asymptotic state for each type of coupling, and it is characterized by a well-defined notion of heat-flow. Our analysis of the second law of thermodynamics leads to a surprising equivalence: a moving heat bath is physically equivalent to a mixture of heat baths at rest, each with a different temperature. There is no unique rule for the Lorentz transformation of temperature. We propose that Lorentz transformations of thermodynamic states are well defined in an extended thermodynamic space that is obtained as a convex hull of the standard thermodynamic space.

Thermodynamic geometry of Kaniadakis statistics

We consider the thermodynamic geometry of an ideal gas with particles obeying Kaniadakis statistics. We work out the thermodynamic curvature of κ-Maxwell–Boltzmann, κ-Bose and κ-Fermi gases. Curvature of thermodynamic parameters space of an ideal ordinary classical gas is zero while it is negative for κ-classical gas. Also, the thermodynamic curvature of an ideal κ-Fermi gas is negative such as ordinary fermion gas. For an ideal κ-Bose gas, two different regimes is found. In fact, we introduce a specified value of temperature; T*, where for T > T* (T < T*) the thermodynamic curvature is negative (positive) and intrinsic statistical interaction is repulsive (attractive) while for an ordinary ideal boson gas, the thermodynamic curvature is positive and the statistical interaction is attractive in full physical range. Therefore, we argue that the κ induces repulsive interaction to particles. Finally, we consider the singular points of thermodynamic curvature of κ-Bose gas and work out the condensation temperature.

Revisiting black hole thermodynamics in massive gravity: charged particle absorption and infalling shell of dust * * Supported by the Natural Science Foundation of China (11705161, 11675139, 11875220). Xiao-Mei Kuang is also partly Supported by Natural Science Foundation of Jiangsu Province (BK20170481) and Fok Ying Tung Education Foundation (171006). Shi-Qian Hu is also Supported by the Postgraduate Reaearch & Practice

In this study, we apply two methods to consider the variation of massive black holes in both normal and extended thermodynamic phase spaces. The first method considers a charged particle being absorbed by the black hole, whereas the second considers a shell of dust falling into it. With the former method, the first and second laws of thermodynamics are always satisfied in the normal phase space; however, in the extended phase space, the first law is satisfied but the validity of the second law of thermodynamics depends upon the model parameters. With the latter method, both laws are valid. We argue that the former method's violation of the second law of thermodynamics may be attributable to the assumption that the change of internal energy of the black hole is equal to the energy of the particle. Finally, we demonstrate that the event horizon always ensures the validity of weak cosmic censorship in both phase spaces; this means that the violation of the second law of thermodynamics, arising under the aforementioned assumption, does not affect the weak cosmic censorship conjecture. This further supports our argument that the assumption in the first method is responsible for the violation and requires deeper treatment.

Searching for optimal process routes: A reinforcement learning approach

Developing optimisation tools is a key target in supporting computer-aided process design as the complexity of the designed space grows beyond conventional unit operations. A process design problem can be formulated as a search of an optimal processing route in the thermodynamic state space, going from feedstock to products. This paper describes a design architecture that enables reinforcement learning agent to use trial-and-error to narrow its search to the most promising routes, rather than exhaustively enumerating solutions. In each iteration, the agent employs previously collected data to guide the search for new trajectories. This is successfully demonstrated in a hydrogen production process using both conventional and intensified process design principles. The agent outperformed standard nonlinear optimisation methods in competitive computational time. Limitations and future work are discussed.