Search Results (976)

Due to their simplicity and ease of visualization, lattice models can be useful to illustrate basic concepts in thermodynamics. The recipe to obtain classical thermodynamic expressions from lattice models is usually based on invoking the thermodynamic limit, and the ideal gas law can easily be obtained as the density of non-interacting particles vanishes. We present a lattice-based analysis that shows that, when a gas consisting of non-interacting particles evolves towards mechanical equilibrium with the environment, the ideal gas law can be obtained with no recourse to unnecessary assumptions regarding the size or particle density of the lattice. We also present a statistical mechanical analysis that considers a quantized volume and reproduces the process obtained for the discrete lattice model. We show how the alternative use of a well-known and accessible model (the non-interacting lattice gas) can give microscopic insights into thermal systems and the assumptions that underlie the laws used to describe them, including local vs. global equilibrium, irreversible processes, and the sometimes subtle difference between physical assumptions and mathematically convenient approximations. Full article

The link between information and energy introduces the observer and their knowledge into the understanding of a fundamental quantity in physics. Two approaches compete to account for this link—Brillouin’s negentropy law of information and Landauer’s law on data erasure—which are often confused. The first, based on Clausius’ inequality and Shannon’s mathematical results, is very robust, whereas the second, based on the simple idea that information requires a material embodiment (data bits), is now perceived as more physical and therefore prevails. In this paper, we show that Landauer’s idea results from a confusion between information (a global emergent concept) and data (a local material object). This confusion leads to many inconsistencies and is incompatible with thermodynamics and information theory. The reason it prevails is interpreted as being due to a frequent tendency of materialism towards reductionism, neglecting emergence and seeking to eliminate the role of the observer. A paradoxical trend, considering that it is often accompanied by the materialist idea that all scientific knowledge, nevertheless, originates from observation. Information and entropy are actually emergent quantities introduced in the theory by convention. Full article

We analyze the effect of varying system conditions on the single-particle entanglement entropy for an arbitrary eigenstate of a complex system that can be described by a multiparametric Gaussian ensemble. Our theoretical analysis leads to the identification of a single functional of the system parameters that governs the entropy dynamics. This reveals a sensitivity of the entropy to collective information content, characterized by the functional, instead of the individual system details. The functional can further be used to identify the universality classes as well as a deep web of connection underlying different quantum states. Full article

We develop a data-driven framework for analyzing how scientific concepts evolve through their empirical in-text frequency distributions in large text corpora. For each concept, the observed distribution is paired with a maximum entropy equilibrium reference, which takes a generalized Boltzmann form determined by two measurable statistical moments. Using data from more than 500,000 physics papers (about 13,000 concepts, 2000–2018), we reconstruct the temporal trajectories of the associated MaxEnt parameters and entropy measures, and we identify two characteristic regimes of concept dynamics, stable and driven, separated by a transition point near criticality. Departures from equilibrium are quantified using a residual-information measure that captures how much structure a concept exhibits beyond its equilibrium baseline. To analyze temporal change, we adapt the Hatano–Sasa and Esposito–Van den Broeck decomposition to discrete time and separate maintenance-like contributions from externally driven reorganization. The proposed efficiency indicators describe how concepts sustain or reorganize their informational structure under a finite representational capacity. Together, these elements provide a unified and empirically grounded description of concept evolution in scientific communication, based on equilibrium references, nonequilibrium structure, and informational work. Full article

Conservatively perturbed equilibrium (CPE) experiments yield transient concentration extrema that surpass steady-state equilibrium values. A physics-informed neural network (PINN) framework is introduced to simulate these over-equilibrium dynamics in linear chemical reaction networks without reliance on extensive time-series data. The PINN incorporates the reaction kinetics, stoichiometric invariants, and equilibrium constraints directly into its loss function, ensuring that the learned solution strictly satisfies physical conservation laws. Applied to three- and four-species reversible mechanisms (both acyclic and cyclic), the PINN surrogate matches conventional ODE integration results, reproducing the characteristic early concentration extrema (maxima or minima) in unperturbed species and the subsequent relaxation to equilibrium. It captures the timing and magnitude of these extrema with high accuracy while inherently preserving total mass. Through the physics-informed approach, the model achieves accurate results with minimal data and a compact network architecture, highlighting its parameter efficiency. Full article

Continuous particle exchange thermal machines require no time-dependent driving, can be realised in solid-state electronic devices, and can be miniaturised to nanometre scale. Quantum dots, providing a narrow energy filter and allowing to manipulate particle flow between the hot and cold reservoirs are at the heart of such devices. It has been theoretically shown that through mitigating passive heat flow, Carnot efficiency can be approached arbitrarily closely in a quantum dot heat engine, and experimentally, values of 0.7${\eta }_C$ have been reached. However, for practical applications, other parameters of a thermal machine, such as maximum power, efficiency at maximum power, and noise—stability of the power output or heat extraction—take precedence over maximising efficiency. We explore the effect of the internal microscopic dynamics of a quantum dot on these quantities and demonstrate that its performance as a thermal machine depends on few parameters—the overall conductance and three inherent asymmetries of the dynamics: entropy difference between the charge states, tunnel coupling asymmetry, and the degree of detailed balance breaking. These parameters act as a guide to engineering the quantum states of the quantum dot, allowing to optimise its performance beyond that of the simplest case of a two-fold spin-degenerate transmission level. Full article

This work extends the steady flow Lenoir cycle within finite-time thermodynamics (FTT) by incorporating heat transfer irreversibilities through the $\epsilon -NTU$ formalism and a non-isentropic expansion modeled via the expander isentropic efficiency ${\eta }_E$. The total conductance $U_T$ (sum for the two heat exchangers) is partitioned between hot and cold units using $u_L=U_L/U_T$, with $U_T=U_H+U_L$. For each triplet ($\tau =T_H/T_L$, $U_L$, $U_T$), we closed the cycle by determining $T_1$, the working fluid temperature at the cooler outlet and heater inlet, $T_2$, the heater outlet and expander inlet, and $T_3$, the expander outlet and cooler inlet. Using these states, we compute the heat rates ${\dot{Q}}_{12}$, ${\dot{Q}}_{31}$ and the net power $P$. In addition to the thermal efficiency $\eta$, the following extended objective functions are evaluated: the efficient power $E_F$, the ecological efficiency $\varphi$, and the second law efficiency ${\eta }_{II}$. Parametric sweeps on $u_L$ for $\tau ϵ \left\{3.25,3.75\right\}$ and $U_{T }ϵ \left\{\mathrm{2.5,5.0},\mathrm{7.5,10}\right\} \mathrm{k}\mathrm{W}$ show unimodal curves for P($u_L$) and maxima. A robust result places the optima of $P$, $\eta$, $E_F$, $\varphi$, and ${\eta }_{II}$ in a distribution band at $u_L~0.6$. This guideline offers clear design guidance for allocating exchange area in heat recovery and microgeneration, maximizing power, high η, and exergetic utilization with contained entropic penalty. Full article

Serrin’s works provided a new perspective on classical thermodynamics through his statements of the first law and the accumulation function, and of the second law and the accumulation theorem, as well as the subsequent result by Huilgol that the work accomplished in a thermal cycle implies an inequality where the important temperatures of the thermal cycle and an integral similar to that of Clausius appears. Based on these pioneering works, explicit forms of the accumulation function have been derived for the Otto, Diesel, Stirling and Ericsson cycles. In this paper, a more straightforward derivation than that made by Huilgol is presented to obtain the inequality for the work accomplished in a cycle, following the theoretical framework of Serrin and Huilgol, and explicitly introducing that the temperature ranges in which the system exchanges heat are finite. This paper clearly shows the natural physical fact that heat exchange processes in a system have two defined extreme temperatures, corresponding to the beginning and end of the process, which can be equal in the isothermal limiting case. The derivation of the accumulation function for the ideal air-standard Brayton cycle is provided for the first time, extending Serrin’s thermodynamic framework, where the temperature constraints of the adiabatic compression and expansion processes under which it operates are analyzed. Finally, a practical example is included to illustrate the behavior of the accumulation function of the ideal air-standard Brayton cycle. Full article

It is well known that the Cahn–Hilliard equation satisfies the energy dissipation law and the mass conservation property. Recently, the radial basis function–finite difference (RBF–FD) approach and its numerous variants have garnered significant attention for the numerical solution of surface-related problems, owing to their intrinsic advantage in handling complex geometries. However, existing RBF–FD schemes generally fail to preserve mass conservation when solving the Cahn–Hilliard equation on smooth closed surfaces. In this paper, based on an $L^2$ projection method, two numerically efficient RBF–FD schemes are proposed to achieve mass-conservative numerical solutions, which are demonstrated to preserve the mass conservation law under relatively mild time-step constraints. Spatial discretization is performed using the RBF–FD method, while based on the convex splitting method and a linear stabilization technique, the first-order backward Euler formula (BDF1) and the second-order Crank–Nicolson (CN) scheme are employed for temporal integration. Extensive numerical experiments not only validate the performance of the proposed numerical schemes but also demonstrate their ability to utilize mild time steps for long-term phase-separation simulations. Full article

In agreement with the second law of thermodynamics, a new theoretical model for the description of the heat transfer at nanoscale in a rigid body is derived. The model introduces the concept of the Knudsen layer into non-equilibrium thermodynamics in order to better investigate how phonon–boundary scattering may influence the heat propagation at nanoscale. This paper, in particular, deepens the influence of the Knudsen layer on the speed of propagation of thermal waves. Full article

Organic Rankine Cycle (ORC) systems with complex configurations exhibit strong thermo-mechanical–electrical–magnetic coupling, making dynamic analysis computationally demanding. This study proposes a multi-time-scale modeling framework that partitions the system into second-, decisecond-, and hybrid-scale subsystems for separate computation, reducing simulation time while maintaining accuracy. Dynamic models are developed for heat exchangers, expanders, pumps, generators, and converters. The method is validated on a basic ORC system using operational data, achieving a mean absolute error of 2.12%, well within the ±5% tolerance. It is then applied to a series dual-loop ORC and a multi-heat-source ORC with series heat exchangers. Results indicate that the dual-loop configuration enhances disturbance rejection to both sink and heat-source fluctuations, while dual-heat-source system dynamics are predominantly governed by the second heat source. The framework enables efficient, accurate simulation of complex ORC architectures and provides a robust basis for advanced control strategy development. Full article

The growing demand for renewable energy positions biorefineries as key to enhancing biofuel competitiveness. This study proposes a novel MILP superstructure integrating resource seasonality, process selection, and heat integration to optimize biomethanol production in a sugarcane biorefinery. A multi-objective optimization balancing net present value (NPV) and avoided CO₂ emissions reveals that energy integration improves environmental performance with limited economic impact. The model estimates the production of up to 66.85 kg of biomethanol/ton sugarcane from bagasse gasification, 40.7 kg e-methanol/ton sugarcane via CO₂ hydrogenation, and 3.68 kg of biomethane/ton sugarcane from biogas upgrading. Hydrogen production through biomethane reforming and photovoltaic-powered electrolysis increases methanol output without raising emissions. The integrated system achieves energy efficiencies of up to 57.3% and enables the avoidance of up to 493 kg of CO₂/ton sugarcane over the planning horizon. When thermal integration is excluded, efficiency drops by 8% and net energy production per area falls by 11%, due to the need to divert bagasse to cogeneration. Although economic challenges remain, CO₂ remuneration ranging from USD 3.27 to USD 129.79 per ton could ensure project viability. These findings highlight the role of integrated energy systems in enabling sustainable and economically feasible sugarcane biorefineries. Full article

This paper innovatively presents an integrated nuclear-powered supercritical carbon dioxide (S-CO₂) system for aircraft carriers, replacing the conventional secondary-loop steam Rankine cycle with a regenerative S-CO₂ power cycle. The system comprises two modules: a nuclear reactor module and a S-CO₂ power module. Comprehensive thermodynamic, economic, and compactness analyses were conducted, using exergy efficiency, levelized energy cost (LEC), and heat transfer area per unit power output (APR) as objective functions for optimization. Parameter analysis revealed the influence of key operating parameters on system performance, and a multi-objective optimization approach based on genetic algorithms was employed to determine optimal system parameters. The results indicate that the system achieves an exergy efficiency of 45%, an APR of 0.168 m² kW⁻¹, and an LEC of 2.1 cents/(kW·h). This high compactness, combined with superior thermodynamic and economic performance, underscores the feasibility of the S-CO₂ system for integration into nuclear-powered aircraft carriers, offering significant potential to enhance their overall performance and operational efficiency. Full article

The article considers the description of a macrosystem in terms that do not depend on the nature of the macrosystem. The results obtained can be used to describe macrosystem models of thermodynamic processes, and to create interdisciplinary models that take into account interactions of various natures. The macrosystem model is based on its representation in the form of a self-similar oriented weighted graph where the equation of state is fulfilled for each node, which connects extensive variables. One of the extensive variables is entropy, the maximum of which corresponds to the state of equilibrium. For processes in which fluxes are linearly dependent on driving forces, Onsager’s relations are shown to be true, which makes it possible to prove that in the space of stationary processes, entropy production in a closed macrosystem is a metric similar to the Mahalanobis metric, which determines the distance between processes. Zero in such a space indicates reversible processes, and thus the production of entropy shows the degree of irreversibility as the distance from a researched process to a reversible one. Full article