Search Results (5,064)

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

Headspace (HS) in anaerobic batch biodigesters is a critical design parameter that modulates pressure stability, gas–liquid equilibrium, and methanogenic productivity. This systematic review, guided by PRISMA 2020, analyzed 84 studies published between 2015 and 2025, of which 64 were included in the qualitative and quantitative synthesis. The interplay between headspace volume fraction ${\mathrm{V}}_{\mathrm{H}\mathrm{S}}/{\mathrm{V}}_{\mathrm{t}\mathrm{o}\mathrm{t}}$, operating pressure, and normalized methane yield was assessed, explicitly integrating safety and instrumentation requirements. In laboratory settings, maintaining a headspace volume fraction (HSVF) of 0.30–0.50 with continuous pressure monitoring P(t) and gas chromatography reduces volumetric uncertainty to below 5–8% and establishes reference yields of 300–430 NmL CH₄ g⁻¹ VS at 35 °C. At the pilot scale, operation at 3–4 bar absolute increases the CH₄ fraction by 10–20 percentage points relative to ~1 bar, while maintaining yields of 0.28–0.35 L CH₄ g COD⁻¹ and production rates of 0.8–1.5 Nm³ CH₄ m⁻³ d⁻¹ under OLRs of 4–30 kg COD m⁻³ d⁻¹, provided pH stabilizes at 7.2–7.6 and the free NH₃ fraction remains below inhibitory thresholds. At full scale, gas domes sized to buffer pressure peaks and equipped with continuous pressure and flow monitoring feed predictive models (AUC > 0.85) that reduce the incidence of foaming and unplanned shutdowns, while the integration of desulfurization and condensate management keep corrosion at acceptable levels. Rational sizing of HS is essential to standardize BMP tests, correctly interpret the physicochemical effects of HS on CO₂ solubility, and distinguish them from intrinsic methanogenesis. We recommend explicitly reporting standardized metrics (Nm³ CH₄ m⁻³ d⁻¹, NmL CH₄ g⁻¹ VS, L CH₄ g COD⁻¹), absolute or relative pressure, HSVF, and the analytical method as a basis for comparability and coupled thermodynamic modeling. While this review primarily focuses on batch (discontinuous) anaerobic digesters, insights from semi-continuous and continuous systems are cited for context where relevant to scale-up and headspace dynamics, without expanding the main scope beyond batch systems. Full article

Coal slime, a byproduct of coal processing with high ash content, poses significant challenges in terms of its efficient separation and resource utilization due to its fine particle size and complex composition. This study aims to optimize the oil agglomeration process for coal slime separation through systematic parameter investigation and predictive modeling. Response surface methodology (RSM) was employed to analyze the individual and interactive effects of pulp density, oil dosage, and agitation rate on three key performance indicators: combustible recovery, efficiency index, and ash rejection. Meanwhile, an artificial neural network (ANN) was developed to establish a robust prediction model for the efficiency index. The novelty of this work lies in the integration of thermodynamic analysis, multi-objective optimization, and machine learning approaches. The key findings include the identification of dodecane as the optimal bridging liquid due to its intermediate carbon chain length that balances interfacial tension and wettability. Under optimized conditions (14% pulp density, 22% oil dosage, and 1600 r/min), the process achieved a combustible recovery of 91.49%, ash rejection of 61.58%, and efficiency index of 53.07%. The ANN model demonstrated superior predictive capability with an overall R² of 0.9659 and RMSE of 1.12. This work provides comprehensive guidelines for the design, optimization, and scale-up of coal slime oil agglomeration processes in industrial applications. Full article

Recent advances in non-local thermodynamic equilibrium (non-LTE) plasma simulations, for example in modeling kilonova ejecta, have emphasized the need for consistent and reliable atomic data. Unlike LTE modeling, non-LTE calculations must include a consistent treatment of various photon-induced and collisional processes in order to describe realistic electron and photon distributions in the plasma. However, the available atomic data are often incomplete, inconsistently formatted, or even fail to indicate the main dependencies on the level structure and plasma parameters, thus limiting their practical use. To address these issues, we have extended Jac, the Jena Atomic Calculator (version v0.3.0), to provide direct access to relevant cross sections, plasma rates, and rate coefficients. Emphasis is placed on photoexcitation and ionization processes as well as their time-reversed counterparts—photo-de-excitation and photorecombination. Whereas most of these data are still based on empirical expressions, their dependence on the ionic level structure and plasma temperature is made explicit here. Moreover, the electron and photon distributions can be readily controlled and adjusted by the user. This transparent representation of atomic data for photon-mediated processes, together with a straightforward use, facilitates their integration into existing plasma codes and improves the interpretation of high-energy astrophysical phenomena. It may support also more accurate and flexible non-LTE plasma simulations. Full article

Ni–ySiC system (where y = 0.001, 0.005, and 0.015 wt.%) composite materials with enhanced mechanical properties have been fabricated and comprehensively investigated. The composites were synthesized using a combined technology involving preliminary mechanical activation of powder components in a planetary mill followed by consolidation via spark plasma sintering (SPS) at 850 °C. The microstructure and phase composition were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). The physico-mechanical properties were evaluated by density measurements (hydrostatic weighing), three-point bending tests (25 °C and 400 °C), and Young’s modulus measurement using an ultrasonic method (25–750 °C). It was found that the introduction of ultralow amounts of SiC nanoparticles (0.001 wt.%) leads to an extreme increase in flexural strength: by 115% at 20 °C (up to 1130 MPa) and by 86% at 400 °C (up to 976 MPa) compared to pure nickel. Microstructural analysis revealed the formation of an ultrafine-grained structure (0.15–0.4 µm) with the presence of pyrolytic carbon and probable nickel silicide interlayers at the grain boundaries. Thermodynamic and kinetic modeling, including the calculation of chemical potentials and diffusion coefficients, confirmed the possibility of reactions at the Ni/SiC interface with the formation of nickel silicides (Ni₂Si, NiSi) and free carbon. The scientific novelty of the work lies in establishing a synergistic strengthening mechanism combining the Hall–Petch, Orowan (dispersion), and solid solution strengthening effects, and in demonstrating the property extremum at an ultralow content of the dispersed phase (0.001 wt.%), explained from the standpoint of quantum-chemical analysis of phase stability. The obtained results are of practical importance for the development of high-strength and thermally stable nickel composites, promising for application in aerospace engineering. Full article

The increasing share of renewable energy sources (RES) in modern power systems necessitates the development of efficient, large-scale energy storage technologies capable of mitigating generation variability. Liquid Air Energy Storage (LAES), particularly in its adiabatic form, has emerged as a promising candidate by leveraging thermal energy storage and high-pressure air liquefaction and regasification processes. Although LAES has been widely studied, the impact of ambient temperature on its performance remains insufficiently explored. This study addresses that gap by examining the thermodynamic response of an adiabatic LAES system under varying ambient air temperatures, ranging from 0 °C to 35 °C. A detailed mathematical model was developed and implemented in Aspen Hysys to simulate the system, incorporating dual refrigeration loops (methanol and propane), thermal oil intercooling, and multi-stage compression/expansion. Simulations were conducted for a reference charging power of 42.4 MW at 15 °C. The influence of external temperature was evaluated on key parameters including mass flow rate, unit energy consumption during liquefaction, energy recovery during expansion, and round-trip efficiency. Results indicate that ambient temperature has a marginal effect on overall LAES performance. Round-trip efficiency varied by only ±0.1% across the temperature spectrum, remaining around 58.3%. Mass flow rates and power output varied slightly, with changes in discharging power attributed to temperature-driven improvements in expansion process efficiency. These findings suggest that LAES installations can operate reliably across diverse climate zones with negligible performance loss, reinforcing their suitability for global deployment in grid-scale energy storage applications. Full article

Despite substantial advances in turbofan engineering, a crucial gap persists: there remains the need for an all-inclusive comparative analysis that includes real-world operational data and evaluates the performance of modern turbofans used in aviation. Specifically, systematic investigations that examine the exergy and efficiency of turbofan engines for takeoff and cruise remain scarce. Further, the current literature needs to address rigorous performance assessments that include simultaneous consideration of the combined effects of ambient conditions (e.g., temperature, density, relative humidity), Mach number, and turbine inlet temperature on high-bypass turbofan engines used in modern, commercial aircraft. Energetic and exergetic analyses were conducted on five commercial high-bypass turbofan engines with different configurations for both takeoff and cruise flight modes. The computational thermodynamic models developed showed strong correlation with manufacturers’ specifications. Performance evaluations included variations in ambient conditions, altitude, Mach number, and turbine inlet temperature. Results demonstrate that three-spool engine architecture exhibits 70–71% reduction in exergy destruction between flight phases compared to 62.5% for two-spool designs, indicating greater operational adaptability. The combustion chamber emerged as the dominant contributor to irreversibilities, representing approximately 55–58% of overall exergy destruction during takeoff operations. Results demonstrate that increased ambient temperature and/or humidity increase both degraded exergetic efficiency and thrust-specific fuel consumption, and that Mach number and altitude influenced efficiency metrics through ram compression and density effects, while higher turbine inlet temperatures enhanced exhaust kinetic energy via increased thermal input. We show that cruise operations demonstrated superior exergetic efficiency (68–74%) compared with takeoff (47–60%) across all engine configurations. Our results confirm the fundamental trade-off in turbofan design: for long-range applications, high-bypass engines prioritize propulsive efficiency, while for power-intensive operations, moderate-bypass configurations deliver higher specific thrust. Full article

Background/Objectives: Advancing information on the key physicochemical properties of biologically active substances enables the development of formulations with reduced dosing, lower toxicity, and minimal adverse effects. This work addresses the knowledge gap concerning the pharmacologically relevant properties of harmaline (HML), with a focus on thermodynamic and kinetic aspects. New data were obtained on the compound’s solubility and distribution coefficients across a wide temperature range. Specifically, solubility was measured in aqueous buffers (pH 2.0 and 7.4), 1-octanol (OctOH), n-hexane (Hex), and isopropyl myristate (IPM), while distribution coefficients were determined in OctOH/pH 7.4, Hex/pH 7.4, and IPM/pH 7.4 systems. Methods: Three membranes—regenerated cellulose (RC), PermeaPad (PP) and polydimethylsiloxane-polycarbonate (PDS)—were used as barriers in permeability studies using a Franz diffusion cell. Results: At 310.15 K, the molar solubility of HML in the solvents decreased in the following order: OctOH > pH 2.0 > pH 7.4 > IPM > Hex. The distribution coefficient of HML showed a strong dependence on the nature of the organic phase, correlating with its solubility in the respective solvents. The OctOH/pH 7.4 distribution coefficient ranged from 0.973 at 293.15 K to 1.345 at 313.15 K, falling within the optimal range for potential drug bioavailability. The transfer of HML into OctOH (from either pH 7.4 or hexane) is thermodynamically spontaneous, whereas its transfer into Hex is unfavorable. Conclusions: Based on its permeability across the PP barrier, HML was classified as highly permeable. The distribution and permeation profiles of HML showed similar trends over 5 h in both the OctOH/pH 7.4–PP and IPM/pH 7.4–PDS systems. These systems were therefore proposed as suitable models for studying HML transport in vitro. Full article

Since there is limited information available in the literature about the thermodynamic properties of the Cu-Mg-Ti system, this work aims to determine the mixing enthalpy change for several liquid alloys from this system. To achieve the intended purpose, the applied methods were divided into two stages. The first one covered a high-temperature calorimetric measurement of the enthalpy of mixing performed at 1123–1402 K for liquid solutions in six measurement series (A–F). The obtained experimental results indicate that the liquid solutions are characterized by negative deviations from ideal solutions across the whole measured concentration range. The second stage of the study includes thermodynamic modeling. At first, based on the calorimetrically obtained experimental data and thermodynamic properties of the binary systems described by the Redlich–Kister model, a set of ternary optimized parameters for the Cu-Mg-Ti system were calculated. Then, for the calculation of the mixing enthalpy change, two models were used—the symmetrical Muggianu model and the asymmetrical Toop model. This study complements the information available in the literature and the obtained results aim to fill the gap in the current knowledge on thermodynamic properties. Full article

The article is devoted to analyzing the synthesis of mathematical models of metalworking processes by cutting for digital counterparts of metal-cutting machines. Despite the development of modern measuring instruments, data acquisition, and transmission systems, as well as the growth of computing power of modern computers, the problem with a high-quality mathematical description of the cutting process is urgent. Methods: When developing mathematical models of elastic–thermodynamic interaction, the authors relied on analytical methods of model construction, as well as on the analysis of experimental data obtained as a result of the conducted research. The STD.201-1 stand was used as measuring equipment; data processing was carried out using the MATLAB 2018 mathematical software package. Results: A comparison of the results of the mathematical modeling of the synthesized model and the results of measuring cutting processes on a metal-cutting machine show a high degree of convergence. The modeled and experimental graphs of the cutting force decomposed along the deformation axes and the graphs of the cutting temperature differ only in the area of the transient process (tool embedding). Conclusions: The models obtained during synthesis can become the basis for building a digital twin system. Full article

The contamination of water bodies by polycyclic aromatic hydrocarbons (PAHs) poses a significant concern for the ecological systems, along with public health. Magnetic adsorption stands out as a green and practical solution for treating polluted water. To make the process more efficient and economical, it is important to create materials that not only absorb contaminants effectively but also allow for easy recovery and reuse. This study proposes a simple yet effective method for coating Fe₃O₄ nanoparticles with hydroxypropyl-β-cyclodextrin polymer (HP-β-CDCP). The physicochemical properties of the synthesized sorbent were characterized using a transmission electron microscope (TEM), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and Vibrating Sample Magnetometer (VSM) analysis. The adsorption performance of HP-β-CDCP/Fe₃O₄ nanoparticles was well-described by the pseudo-second-order kinetic model, thermodynamic analysis, and the Freundlich isotherm model, indicating multiple interaction mechanisms with PAHs, such as π–π interactions, hydrogen bonding, and van der Waals forces. Using HP-β-CDCP/Fe₃O₄ nanoparticles as the adsorbent, the purification rates for the fifteen representative PAHs were achieved within the range of 33.9–93.1%, compared to 15.3–64.8% of the unmodified Fe₃O₄ nanoparticles. The adsorption of all studied PAHs onto HP-β-CDCP/Fe₃O₄ nanocomposites was governed by pH, time, and temperature. Equilibrium in the uptake mechanism was obtained within 15 min, with the largest adsorption capacities for PAHs in competitive adsorption mode being 6.46–19.0 mg·g⁻¹ at 20 °C, pH 7.0. This study points to the practical value of incorporating cyclodextrins into tailored polymer frameworks for improving the removal of PAHs from polluted water. Full article

We demonstrate that pulsed laser annealing induces plasmonic gold nanoparticles in ZnO thin films, monitored in real-time via pulse-by-pulse spectroscopy. Initially embedded gold nanoparticles (smaller than 5 nm) in sputtered ZnO films were annealed using 532 nm pulses from a Q-switched Nd:YAG laser while monitoring transmission spectra in situ. A plasmonic resonance dip emerged after ~100 pulses in the 530–550 nm region, progressively deepening with continued exposure. Remarkably, different incident energies converged to a thermodynamically stable optical state centered near 555 nm, indicating robust nanoparticle configurations. After several hundred laser shots, the process stabilized, producing larger nanoparticles (40–200 nm diameter) with significant surface protrusion. SEM analysis confirmed substantial gold nanoparticle growth. Theoretical modeling supports these observations, correlating spectral evolution with particle size and embedding depth. The protruding gold nanoparticles can be functionalized to detect specific biomolecules, offering significant advantages for biosensing applications. This approach offers superior spatial selectivity and real-time process monitoring compared to conventional thermal annealing, with potential for optimizing uniform nanoparticle distributions with pronounced plasmonic resonances for biosensing applications. Full article

Indium-doped SnTe (Sn_1−xIn_xTe) provides a model platform for exploring the emergence of superconductivity within a topological crystalline insulator. Here, we present a systematic investigation of the structural, transport, and thermodynamic properties of high-quality single crystals with 0.0 ≤ x ≤ 0.5. All compositions up to x = 0.4 form a single-phase cubic structure, enabling a controlled study of the superconducting state. Electrical resistivity and specific heat measurements reveal a bulk, fully gapped s-wave superconducting phase whose transition temperature increases monotonically with In concentration, reaching Tc ≈ 4.7 K at x = 0.5. Analysis of the electronic specific heat and McMillan formalism shows that the electron–phonon coupling constant λ_el-ph systematically increases with doping, while the Debye temperature systematically decreases, resulting in the lattice softening. This behavior, together with the observed evolution of the normal-state resistivity exponent from Fermi-liquid (n ≈ 2.04) toward non-Fermi-liquid values (n ≈ 1.72), demonstrates a clear crossover from weak to strong interaction with increasing In content. These results establish Sn_1−xIn_xTe as a tunable superconducting system in which coupling strength can be continuously controlled, offering a promising platform for future studies on the interplay between phonon-mediated superconductivity and crystalline topological band structure. Full article

Turbocharged diesel engines are widely used for the propulsion and as the generators for powering auxiliary systems in marine applications. Many works were published on the development of diagnosis tools for the engines using data from simulation models or from experiments on a sophisticated engine test bench. However, the simulation data varies a lot with actual operational data, and the available sensor data on the actual vessel is much less compared to the data from test benches. Therefore, it is necessary to develop anomaly prediction and fault diagnosis models from limited data available from the engines. In this paper, an artificial intelligence (AI)-based anomaly detection model and machine learning (ML)-based fault diagnosis model were developed using the actual data acquired from a diesel engine of a cargo vessel. Unlike the previous works, the study uses operational, thermodynamic, and vibration data for the anomaly detection and fault diagnosis. The paper provides the overall architecture of the proposed predictive maintenance system including details on the sensorization of assets, data acquisition, edge computation, and AI model for anomaly prediction and ML algorithm for fault diagnosis. Faults with varying severity levels were induced in the subcomponents of the engine to validate the accuracy of the anomaly detection and fault diagnosis models. The unsupervised stacked autoencoder AI model predicts the engine anomalies with 87.6% accuracy. The balanced accuracy of supervised fault diagnosis model using Support Vector Machine algorithm is 99.7%. The proposed models are vital in marching towards sustainable shipping and have potential to deploy across various applications. Full article

This study examines the activity coefficients of benzene, toluene, and di-(2-ethylhexyl)phosphoric acid (D2EHPA) in binary benzene–D2EHPA and toluene–D2EHPA systems, as well as the ternary n-hexane–toluene–D2EHPA system, using gas chromatography at 293.0 K. The primary objective was to determine UNIFAC model interaction parameters and validate their accuracy for predicting thermodynamic behavior in these systems. Experimental measurements revealed activity coefficient maxima for benzene and toluene at mole fractions of 0.8–0.9, decreasing to 0.46–0.67 in dilute solutions. The UNIFAC interaction parameters were calculated as follows: ACH–HPO₄ (−334, 4605), ACCH₃–HPO₄ (680, 467), and refined CH₂–HPO₄ (54, 1199). The UNIFAC model achieved deviations of less than 2% from experimental data in both binary and ternary systems. A novel methodology incorporating intermediate standards for gas chromatography was developed to overcome challenges in measuring volatile solvent concentrations, enhancing measurement precision. These findings enable accurate prediction of activity coefficients in mixtures of alkanes, cycloalkanes, and monoaromatic hydrocarbons with D2EHPA, offering significant implications for optimizing metal liquid–liquid extraction processes. Full article