Hasil untuk "Thermodynamics"

E. Lima, A. Hosseini-Bandegharaei, J. Moreno-Piraján et al.

Abstract In the adsorption literature, the Van't Hoff equation is used in different manners without any criteria about the concepts of physical-chemistry of equilibrium for calculation of thermodynamic parameters of adsorption. Indeed, the equilibrium constant (K) should be dimensionless for being used in the Van't Hoff equation. However, this is not a simple adjustment of units, as being spread in the literature, to become K dimensionless. In this paper, it will be calculated the equilibrium constants using numeric examples and show the flaws of the thermodynamics calculations, when the value of K is wrongly calculated, and what are the expected results of the changes in enthalpy (ΔH°) and changes in the entropy (ΔS°) that are spread in the literature.

S. Pfahl, P. O’Gorman, E. Fischer

D. Kastor, Sourya Ray, Jennie Traschen

We present geometric derivations of the Smarr formula for static AdS black holes and an expanded first law that includes variations in the cosmological constant. These two results are further related by a scaling argument based on Euler's theorem. The key new ingredient in the constructions is a two-form potential for the static Killing field. Surface integrals of the Killing potential determine the coefficient of the variation of Λ in the first law. This coefficient is proportional to a finite, effective volume for the region outside the AdS black hole horizon, which can also be interpreted as minus the volume excluded from a spatial slice by the black hole horizon. This effective volume also contributes to the Smarr formula. Since Λ is naturally thought of as a pressure, the new term in the first law has the form of effective volume times change in pressure that arises in the variation of the enthalpy in classical thermodynamics. This and related arguments suggest that the mass of an AdS black hole should be interpreted as the enthalpy of the spacetime.

D. Evans, G. Morriss

S. Singhal, K. Kendall

J. E. Dunn, R. Fosdick

C. Lupis

Ana L. Azevedo Costa, Mareike Liebertseder, Tatiana Gambaryan-Roisman et al.

Silicon (Si) is a promising anode material for next-generation lithium-ion batteries (LIBs) due to its high theoretical capacity. However, its practical application is hindered by significant volume changes during cycling, leading to particle pulverization, loss of electrical contact, and rapid capacity fading. To address these challenges, we study the effect of dry particle coating with nanostructured fumed metal oxides (TiO2, MgO, ZrO2, and Al2O3) on enhancing the electrochemical performance of SiOx/C anodes. The dry coating process, a facile and scalable technique, effectively attaches the metal oxide nanoparticles onto the SiOx/C surface, forming a protective layer. The coated anode active materials (AAMs) exhibit improved cycling stability and rate capability compared to the uncoated SiOx/C, with the Al2O3-coated anode demonstrating the most promising overall performance. The effective and uniform distribution of the porous coating acts as a protective layer, reducing side reactions while simultaneously enhancing ion diffusion kinetics and improving electrolyte accessibility. Detailed characterization reveals that the Al2O3 coating promotes the controlled formation of a LiF-rich solid electrolyte interphase (SEI) layer, contributing to enhanced ionic conductivity and stability. This study highlights the potential of dry particle coating with different metal oxides as a promising strategy for developing high-performance Si-based anodes for next-generation LIBs.

Yadong Han, Bingfu Han, Ming Liu et al.

Cavitating flows are of great interest in the fields of hydraulic machineries, which can significantly affect mechanical performance and safety. Despite various efforts being dedicated to figuring out the interaction between flow and cavitation fields, their correlation has not been clearly addressed. To this end, in this study, a convolutional neural network, U-Net, was adopted to build a model that can predict the vapor volume fraction from velocity fields. Large eddy simulations of cavitating flows around a Clark-Y hydrofoil were conducted, and the simulated snapshots with velocity and vapor volume fraction were adopted as a dataset for training the network. The predicted vapor volume fraction shows good agreement with the referred simulation results, with a <i>L</i>₁ deviation lower than 2 × 10⁻⁴, considering all the snapshots. The comparable <i>L</i>₁ deviation between the training and validation datasets suggests the existence of a strong correlation between velocity and cavitation fields. The cavitation–velocity interaction derived from using U-Net suggests that the location with zero velocity indicates the interior part of attached and cloud cavitations, and the local vortical velocity fields usually suggest the existence of cavitation shedding.

Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler

Reliably identifying and understanding temporal precursors to extreme wind gusts is crucial for early warning and mitigation. This study proposes a simple data-driven approach to extract key predictors from a dataset of historical extreme European winter windstorms and derive simple equations linking these precursors to extreme gusts over land. A major challenge is the limited training data for extreme events, increasing the risk of model overfitting. Testing various mitigation strategies, we find that combining dimensionality reduction, careful cross-validation, feature selection, and a nonlinear transformation of maximum wind gusts informed by Generalized Extreme Value distributions successfully reduces overfitting. These measures yield interpretable equations that generalize across regions while maintaining satisfactory predictive skill. The discovered equations reveal the association between a steady drying low-troposphere before landfall and wind gust intensity in Northwestern Europe.

Vito Antonio Cimmelli

We present a model of superfluidity based on the internal variable theory. We consider a two-component fluid endowed with a scalar internal variable whose gradient is the counterflow velocity. The restrictions imposed by the second law of thermodynamics are obtained by applying a generalized Coleman–Noll procedure. A set of constitutive equations of the Landau type, with entropy, entropy flux and stress tensor depending on the counterflow velocity, is obtained. The propagation of acceleration waves is investigated as well. It is shown that the first-and-second sound waves may propagate along the system with speeds depending on the physical parameters of the two fluids. First sound waves may propagate in the same direction or in the opposite direction of the counterflow velocity, depending on the concentration of normal and superfluid components. The speeds of second sound waves have the same mathematical form of those propagating in dielectric crystals.

Feier Chen, Yi Sha, Huaxiao Ji et al.

This study investigates the multifractal characteristics of the tanker freight market from 1998 to 2024. Using multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrending moving average (MF-DMA), we analyze temporal correlations and volatility, revealing subtle differences in multifractal features before and after 2010. We further examine the influence of key external factors—including economic disturbances (the 2008 financial crisis), technological innovations (the 2014 Shale Oil Revolution), supply chain disruptions (the COVID-19 pandemic), and geopolitical uncertainties (the Russia–Ukraine conflict)—on market complexity. Building on this, a predictive framework is introduced, leveraging the Baltic Dirty Tanker Index (BDTI) to forecast Brent oil prices. By integrating multifractal analysis with machine learning models (e.g., XGBoost, LightGBM, and CatBoost), our framework fully exploits the predictability from the freight index to oil prices across the above four major global events. The results demonstrate the potential of combining multifractal analysis with advanced machine learning models to improve forecasting accuracy and provide actionable insights during periods of heightened market volatility. On average, the coefficient of determination (<i>R</i>²) increases by approximately 62.65% to 182.54% for training and 55.20% to 167.62% for testing, while the mean squared error (MSE) reduces by 60.83% to 92.71%. This highlights the effectiveness of multifractal analysis in enhancing model performance, especially in more complex market conditions post-2010.

Sergio Barbosa, Sylvain Fichet, Eugenio Megías et al.

Abstract We study holographic entanglement entropy and revisit thermodynamics and confinement in the dilaton-gravity system. Our analysis focuses on a solvable class of backgrounds that includes AdS and linear dilaton spacetimes as particular cases, with some results extended to general warped metrics. A general lesson is that the behavior of the holographic theory is tied to the bulk curvature singularities. We find that a singular background is confining if and only if i) the singularity coincides with a boundary or ii) it is the linear dilaton. In the former case, for which the singularity cuts off spacetime, we demonstrate that both entanglement entropy and thermodynamics exhibit a first order phase transition. In the linear dilaton case we find instead that both entanglement entropy and thermal phase transitions are of second order. Additionally, along the process we thoroughly derive the radion effective action at quadratic order.

Ayah Marwan Rabi’, Jovana Radulovic, James M. Buick

In recent years, packed-bed systems have emerged as an attractive design for thermal energy storage systems due to their high thermal efficiency and economic feasibility. As integral components of numerous large-scale applications systems, packed-bed thermal energy stores can be successfully paired with renewable energy and waste heat to improve energy efficiency. An analysis of the thermal performances of two packed beds (hot and cold) during six-hour charging and discharging cycles has been conducted in this paper using COMSOL Multiphysics software, utilizing the optimal design parameters that have been determined in previous studies, including porosity (0.2), particle diameters (4 mm) for porous media, air as a heat transfer fluid, magnesia as a storage medium, mass flow rate (13.7 kg/s), and aspect ratio (1). The performance has been evaluated during both the charging and discharging cycles, in terms of the system’s capacity factor, the energy stored, and the thermal power, in order to understand the system’s performance and draw operational recommendations. Based on the results, operating the hot/cold storage in the range of 20–80% of the full charge was found to be a suitable range for the packed-bed system, ensuring that the charging/discharging power remains within 80% of the maximum.

Liran Wei, Mingzhu Tang, Na Li et al.

Accurate carbon market price prediction is crucial for promoting a low-carbon economy and sustainable engineering. Traditional models often face challenges in effectively capturing the multifractality inherent in carbon market prices. Inspired by the self-similarity and scale invariance inherent in fractal structures, this study proposes a novel multifractal-aware model, MF-Transformer-DEC, for carbon market price prediction. The multi-scale convolution (MSC) module employs multi-layer dilated convolutions constrained by shared convolution kernel weights to construct a scale-invariant convolutional network. By projecting and reconstructing time series data within a multi-scale fractal space, MSC enhances the model’s ability to adapt to complex nonlinear fluctuations while significantly suppressing noise interference. The fractal attention (FA) module calculates similarity matrices within a multi-scale feature space through multi-head attention, adaptively integrating multifractal market dynamics and implicit associations. The dynamic error correction (DEC) module models error commonality through variational autoencoder (VAE), and uncertainty-guided dynamic weighting achieves robust error correction. The proposed model achieved an average R² of 0.9777 and 0.9942 for 7-step ahead predictions on the Shanghai and Guangdong carbon price datasets, respectively. This study pioneers the interdisciplinary integration of fractal theory and artificial intelligence methods for complex engineering analysis, enhancing the accuracy of carbon market price prediction. The proposed technical pathway of “multi-scale deconstruction and similarity mining” offers a valuable reference for AI-driven fractal modeling.

Ming Zhang, Wen-Di Tan, Mengqi Lu et al.

We develop a framework for holographic thermodynamics in finite-cutoff holography, extending the anti-de Sitter/conformal field theory (AdS/CFT) correspondence to incorporate a finite radial cutoff in the bulk and a $T^2$-deformed CFT on the boundary. We formulate the first laws of thermodynamics for a Schwarzschild-AdS (SAdS) black hole with a Dirichlet cutoff on the quasilocal boundary and its dual deformed CFT, introducing the deformation parameter as a thermodynamic variable. The holographic Euler relation for the deformed CFT and its equation of state are derived, alongside the Smarr relation for the bulk. We show that the Rupert teardrop coexistence curve defines a phase space island where deformation flow alters states, with up to three deformed CFTs or cut-off SAdS sharing a same phase transition temperature, one matching the seed CFT or original SAdS. These results offer insights into gravitational thermodynamics with boundary constraints and quantum gravity in finite spacetime regions.

Archie Mingze Yao, Amal Sebastian, Venkatasubramaian Viswanathan

Batteries are critical for electrified transportation and aviation, yet thermodynamic understanding of electrode materials remains lacking, as indicated by the often-seen violation of the second law of thermodynamics of open-circuit voltage (OCV) models. On the other hand, thermodynamic modeling rarely utilizes electrochemical data such as OCV, entropic heat (dOCV/dT), which contains rich thermodynamic information. This work introduces a framework of thermodynamic modeling of materials for electrochemical energy storage, using differentiable programming and gradient-based optimization of thermodynamic parameters. Using a modified Debye model that accounts for the phonon density of states, the thermodynamics of pure substances is modeled from experimental measurements of specific heat ($c_p$) as well as the phonon density of states $g(ω)$. Thermodynamics of mixing is modeled with measured entropic heat and OCV data. We demonstrate the differentiable thermodynamic modeling framework with forward and inverse problems. In the forward problem, i.e. determining phase diagram of graphite anode given thermochemical and electrochemical data, we show that in addition to accurate reproduction of phase diagram of LixC6, the fitted temperature-dependent OCV of graphite reaches 3.8 mV mean absolute error (MAE) for test set data measured at 10$^\circ$C, compared with 2.9-3.6 mV MAE for training set data measured at 25$^\circ$C - 57$^\circ$C. In the inverse problem, i.e. determining OCV of lithium iron phosphate (LFP) cathode from phase diagram constrained by thermochemical and electrochemical data, we demonstrate accurate reproduction of LFP OCV as well as phase diagram. This framework offers a unified treatment of chemical and electrochemical thermodynamic data for electrode materials.

Luis F. Santos, Victor Hugo M. Ramos, Danilo Cius et al.

We formulate a canonical quantization of Equilibrium Thermodynamics by applying Dirac's theory of constrained systems. Thermodynamic variables are treated as conjugate pairs of coordinates and momenta, allowing extensive and intensive quantities to be promoted to operators in a Hilbert space. The formalism is applied to the ideal gas, the van der Waals gas, and the photon gas, illustrating both first- and second-class quantization procedures. For the ideal gas, a Schrödinger-like equation emerges in which entropy plays the role of time, and the wave function acquires a phase determined by the internal energy. A pseudo-Hermitian framework restores Hermiticity of the temperature operator and establishes the equivalence among constraint realizations. The approach naturally leads to thermodynamic uncertainty relations and suggests extensions to quantum and topological phase transitions, as well as black-hole and non-equilibrium thermodynamics.

Sajad Rasouli, Amirreza Zabihi, Mohammad Fasihi

Abstract Nano-silicon carbide (SiC) as a high thermal conductive material with an intrinsic thermal conductivity of ~ 490 W/m K was used to improve the cure characteristics, kinetics, and thermodynamics of curing reaction of styrene-butadiene rubber/butadiene rubber (SBR/BR) compounds. The considerations were carried out by non-isothermal differential scanning calorimetry (DSC). Results revealed that the presence of SiC shifted the peak and end temperatures of the curing peak to lower temperatures. The calculated activation energy of the curing reaction based on the Kissinger approach showed a descent from 409.8 to 93.8 kJ/mol by adding SiC from 0 to 7.5 phr (part per hundred rubber). Moreover, the obtained Gibbs free energy variation and equilibrium constant of the curing reaction proved that the reaction was absolutely forced and irreversible, which can be increasingly characterized as a one-way process. According to the results, SiC accelerated the curing reaction because of the increment of heat transfer into the compound. This phenomenon caused the increment of enthalpy variation of the vulcanization reaction, particularly at the SiC content of 5 phr. The achieved kinetic parameters via fitting an autocatalytic model based on the Sestàk–Berggren model by the Màlek method to describe the kinetics of the curing reaction indicated that the SiC filler had a catalytic effect on the curing reaction of SBR/BR-SiC, particularly after 2.5 phr of the filler.

Munirah A. Almulhim, Muneerah Al Nuwairan

The current work is devoted to studying the dynamical behavior of the Sakovich equation with beta derivatives. We announce the conditions of problem parameters leading to the existence of periodic, solitary, and kink solutions by applying the qualitative theory of planar dynamical systems. Based on these conditions, we construct some new solutions by integrating the conserved quantity along the possible interval of real wave propagation in order to obtain real solutions that are significant and desirable in real-world applications. We illustrate the dependence of the solutions on the initial conditions by examining the phase plane orbit. We graphically show the fractional order beta effects on the width of the solutions and keep their amplitude approximately unchanged. The graphical representations of some 3D and 2D solutions are introduced.