Thermodynamic Model Research Articles

Integrated Experimental and Thermodynamic Modelling Study of Phase Equilibria in the PbO-AlO1.5-SiO2 System in Air

Abstract The present study focused on phase equilibria in the PbO–AlO1.5 and PbO–AlO1.5–SiO2 systems. The equilibration and quenching technique followed by the electron probe X-ray microanalysis (EPMA) was used in the present study. The liquidus of the PbO–AlO1.5–SiO2 system in air, including corundum (Al2O3), cristobalite/tridymite/quartz (SiO2), feldspar (PbAl2Si2+x O8+2x ), massicot (PbO), mullite (Al6+2x Si2−2x O13−x ), PbAl12O19, PbAl2O4, Pb9Al8O21, Pb6Al2Si6O21, Pb4Al2Si2O11, Pb4Al4Si3O16, Pb3Al10SiO20 and Pb12Al2Si20O55 primary phase fields, has been characterised. New lead aluminosilicate compounds, Pb13Al4Si6O31, Pb12Al6Si10O31, Pb9Al4Si8O31, Pb7Al2Si8O26 and Pb7Al2Si10O30 were found to coexist with oxide liquid. The PbO–AlO1.5 binary and PbO–AlO1.5–SiO2 ternary systems in air were reoptimized based on the obtained experimental data. New experimental results together with phase equilibria and thermodynamic literature data were used to obtain a self-consistent set of parameters of the thermodynamic model for all phases of the PbO–AlO1.5–SiO2 system in air. The predicted liquidus projection of the PbO–AlO1.5–SiO2 system was presented for the first time in the full range of temperatures and compositions. Graphical Abstract

Physiochemical synthesis of hydroxyapatite adsorbents from chicken and camel bone waste for removing Cd and Pb ions from polluted water

The utilization of waste resources to synthesize functional materials is crucial for achieving environmentally sustainable development. In this context, the current investigation aims to develop a new material using waste chicken and camel bones as adsorbents for the removal of Pb2+ and Cd2 from polluted water. The Hydroxyapatite (HA) adsorbents of chicken (HB) and camel (CB) bones were prepared via chemical treatment with NaOH, HNO3, H2O2, and ethanol, and also those followed by carbonization. The physicochemical and microscopic characteristics of the adsorbents were analyzed via SEM, XRD, FT-IR, and BET surface area analyses. Adsorption studies of Pb2+ and Cd2+ were performed in a batch style that included initial metal concentration, pH, pHpzc, solution temperature, contact time, and adsorbent dose. The results revealed that the bone chemically activated with 0.1 M NaOH had greater adsorption of Cd2+ ion (99.7% for HB and 99.89% for CB) and Pb2+ ions (99.85% for HB and 99.79% for CB) than the other activators did. Adsorption isotherms, adsorption kinetics, and thermodynamic models have been used to confirm the fit conditions that improve the adsorption technique. Maximum adsorption removal percentages for Pb2+ and Cd2+ were obtained under constant operation conditions (initial metal concentration 10 ppm, pH 6, adsorbent dose 0.05 g, contact time 30 min and solution temperature 328 K. Adsorption of Pb2+ and Cd2+ obeyed a pseudo-second-order model and fit well with the Langmuir isotherm.The metals adsorption using the prepared adsorbent was a spontaneous and exothermic process. Overall, the prepared adsorbents from chicken and camel bone waste are highly effective and promising as low-cost materials for the remediation of heavy metals-contaminated waters.

Height Control Method for Air Suspension Systems Based on Model-Free Adaptive Control and Improved Genetic Algorithm

<div>This article presents a height control method for air suspension systems, which are influenced by strong nonlinearity and multiple coupling factors, based on model-free adaptive control (MFAC) using full-form dynamic linearization (FFDL). To address the impact of different damping coefficients of the shock absorber on the height control effect, an improved genetic algorithm is employed to globally optimize the relevant parameters involved in the design of the control law, thereby enhancing the height control performance. The precision of modeling the air suspension system has a direct impact on the simulation of both static and dynamic vehicle models, as well as the accuracy of height control. In this article, an equivalent thermodynamic model of the air suspension system is established based on the principle of energy conservation for height control research. Considering the nonlinearity of the air suspension system and the need to make additional assumptions before modeling, a MFAC method using FFDL is adopted for controller design. Traditional height control methods do not consider the impact of changes in the shock absorber damping coefficient on the height control effect. For different damping coefficients, the body height tracking error is large when using the same height control law initialization parameters. Therefore, an improved genetic algorithm is employed to globally optimize the MFAC parameters under different damping states. The effectiveness of the thermodynamic model of the air suspension system and the MFAC method for height control, with parameters tuned using the improved genetic algorithm, was validated through MATLAB/Simulink simulations.</div>

Comprehensive Thermodynamic Performance Evaluation of a Novel Dual-Shaft Solid Oxide Fuel Cell Hybrid Propulsion System

With the rapid growth of air travel, reducing carbon emissions in aviation is imperative. Electric aircraft play a key role in achieving sustainable aviation, especially for large civil aircraft, where reducing emissions, improving the fuel efficiency, and enabling flexible power regulation are essential. This study proposes a dual-shaft, separated-exhaust fuel cell hybrid aircraft propulsion system (HAPS), using a solid oxide fuel cell (SOFC) to replace the conventional turbine-driven compressor. The independent speed control of the high- and low-pressure spools is realized via a power distribution system. A thermodynamic model is developed, and performance evaluations, including parametric, exergy, and sensitivity analyses, are conducted. At the design point, the system delivers 36.304 kN thrust, 16.775 g/(kN·s) specific fuel consumption, 15.931 MW SOFC power, and 54.759% SOFC efficiency. The exergy analysis highlights the optimization of components like the heat exchanger and fan to reduce energy losses. The sensitivity analysis reveals that the spool speeds and fuel utilization significantly impact the performance. The findings provide valuable insights into optimizing control strategies and offer a novel, efficient, and low-carbon power solution for aviation, supporting the industry’s transition towards sustainability.

Operational Flexibility Evaluation and Techno-Economic Analysis on Hot Primary Air Temperature Boosting by Reheated Steam in a Lignite-Fired Power Plant

Abstract Coal-fired power plants are commonly used as adjustable power sources to complement the fluctuating output of wind and solar energy. The investigation is required to determine the flexible peak-shaving capabilities of coal-fired boilers. A modified scheme for a lignite-fired power plant to further improve the primary air temperature using the outlet steam from the low-temperature reheater is studied while increasing the inlet flue gas temperature of the air preheater is considered the conventional scheme. Thermodynamic models of the power plant are constructed using ebsilon software. The operational characteristics of both schemes are compared under 30% turbine heat acceptance (THA)–100%THA conditions and the economic performance of the modified scheme is also evaluated. Results indicate that the modified scheme exhibits superior thermodynamic and economic performances compared to the conventional scheme. The disparity in power generation efficiency between the conventional and modified schemes reaches a maximum of 0.23 percentage points under 75%THA conditions. The net present value of the modified scheme amounts to 4.51 million dollars over the power plant lifespan of 30 years. The modified scheme allows the conventional denitrification catalyst to maintain an optimal temperature range even under 30%THA conditions, resulting in a power generation efficiency only 4.8 percentage points lower than that under 100%THA conditions, thus demonstrating remarkable operational flexibility. This study presents an efficient, cost-effective, and adaptable approach for lignite-fired power plants.

Artificial neural network modeling of dye adsorption kinetics and thermodynamics with magnetic nanoparticle-activated carbon from Allium cepa peels

Artificial neural network modeling of dye adsorption kinetics and thermodynamics with magnetic nanoparticle-activated carbon from Allium cepa peels

Mutations to transcription factor MAX allosterically increase DNA selectivity by altering folding and binding pathways

Understanding how proteins discriminate between preferred and non-preferred ligands (‘selectivity’) is essential for predicting biological function and a central goal of protein engineering efforts, yet the biophysical mechanisms underpinning selectivity remain poorly understood. Towards this end, we study how variants of the promiscuous transcription factor (TF) MAX (H. sapiens) alter DNA specificity and selectivity, yielding >1700 Kds and >500 rate constants in complex with multiple DNA sequences. Twenty-two of the 240 assayed MAX point mutations enhance selectivity, yet none of these mutations occur at residues that contact nucleotides in published structures. By applying thermodynamic and kinetic models to these results and previous observations for the highly similar yet far more selective TF Pho4 (S. cerevisiae), we find that these mutations enhance selectivity by altering partitioning between or affinity within conformations with different intrinsic selectivity, providing a mechanistic basis for allosteric modulation of ligand selectivity. These results highlight the importance of conformational heterogeneity in determining sequence selectivity and can guide future efforts to engineer selective proteins.

Equation of State of a Fluid H2O-CO2 at Temperatures 50–350 °C and Pressures 0.2–3.5 kbar

An equation of state (EOS) was obtained that accurately describes the thermodynamics of the system H2O–CO2 at temperatures of 50-350°C and pressures of 0.2-3.5 kbar. The equation is based on experimental data on the compositions of the coexisting liquid and gas phases and the Van Laar model, within which the values of the Van Laar parameters A12 and A21 were found for each experimental P-T point. For the resulting sets A12(P,T), A21(P,T), approximation formulas describing the dependences of these quantities on temperature and pressure were found and the parameters contained in the formulas were fitted. This two-stage approach made it possible to obtain an adequate thermodynamic description of the system, which allows, in addition to determining the phase state of the system (homogeneous or heterogeneous), to calculate the excess free energy of mixing of H2O and CO2, the activities of H2O and CO2, and other thermodynamic characteristics of the system. The possibility of such calculations creates the basis for using the obtained EOS in thermodynamic models of more complicated fluid systems in P-T conditions of the middle and upper crust. These fluids play an important role in many geological processes including the transport of ore matter and forming hydrothermal ore deposits, in particular, the most of the world's gold deposits. The knowledge of thermodynamics of these fluids is important in the technology of drilling oil and gas wells. In particular, this concerns the prevention of precipitation of solid salts in the well.

Thermodynamics of nucleosome breathing and positioning.

Nucleosomes are fundamental units of chromatin in which a length of genomic DNA is wrapped around a histone octamer spool in a left-handed superhelix. Large-scale nucleosome maps show a wide distribution of DNA wrapping lengths, which in some cases are tens of base pairs (bp) shorter than the 147bp canonical wrapping length observed in nucleosome crystal structures. Here, we develop a thermodynamic model that assumes a constant free energy cost of unwrapping a nucleosomal bp. Our model also incorporates linker DNA-short DNA segments between neighboring nucleosomes imposed by the folding of nucleosome arrays into chromatin fibers and other higher-order chromatin structures. We use this model to study nucleosome positioning and occupancy in the presence of nucleosome "breathing"-partial unwrapping and rewrapping of nucleosomal DNA due to interactions with the neighboring particles. We find that, as the unwrapping cost per bp and the chemical potential are varied, the nucleosome arrays are characterized by three distinct states, with low, intermediate, and high densities. The transition between the latter two states proceeds through an equiprobable state in which all nucleosome wrapping lengths are equally likely. We study the equiprobable state theoretically using a mean-field approach, obtaining an excellent agreement with numerical simulations. Finally, we use our model to reproduce S. cerevisiae nucleosome occupancy profiles observed in the vicinity of transcription start sites, as well as genome-wide distributions of nucleosome wrapping lengths. Overall, our results highlight the key role of partial nucleosome unwrapping in shaping the genome-wide patterns of nucleosome positioning and occupancy.

Thermodynamic Data of Copiapite-Group Minerals

Abstract Copiapite-group minerals are common products of weathering of sulfides, especially pyrite and pyrrhotite. They have a general formula AFe3+4(SO4)6(OH)2·20H2O and all crystallize in the triclinic crystal system (space group P). In this work, we have determined the thermodynamic properties of copiapite (A = Fe2+), ferricopiapite (A = 2/3Fe3+), magnesiocopiapite (A = Mg), and aluminocopiapite (A = 2/3Al). Enthalpies of formation were calculated from enthalpies of dissolution in 5 mol/dm3 HCl (measured by acid-solution calorimetry) and entropies from low-temperature heat capacity data (measured by relaxation calorimetry). Differential scanning calorimetry was used in a restricted temperature range to verify the accuracy of the heat capacity measurements. We also present calculated molar volumes and densities for the copiapite-group phases. The calculated Gibbs free energies of formation are (all values in kJ/mol) −10,322.6 ± 11.8 (A = Mg), −9862.7 ± 12.4 (A = 2/3Fe3+), −10,177.4 ± 10.9 (A = 2/3Al), and −9949.0 ± 12.1 (A = Fe2+). They correspond to solubility products (log Ksp) of −21.24 (A = Mg), −18.55 (A = 2/3Fe3+), −18.17 (A = 2/3Al), and −19.66 (A = Fe2+). They all relate to the dissolution reaction AxFe3+4(SO4)6(OH)2·20H2O + 2H+ → xA + 4Fe3+ + 6SO42− + 22H2O. Using an extended Pitzer model for highly concentrated ferric iron-sulfate solutions, positions of solubility curves for several ferric sulfates were calculated. The shape of the solubility envelope was reproduced, but the position of the curves was not matched. It seems that there is a considerable way to go before a satisfactory thermodynamic model can be constructed for this particular system.

The influence of feed molar flow rate on key streams properties and duties in ethanol-water azeotropic distillation process

Investigation on the influence of near azeotropic feed molar flow rate on properties of key streams connecting main process units of an ethanol-water azeotropic distillation pilot processis presented. The heterogeneous azeotropic distillation model with cyclohexane entrainer was configured in Aspen Plus® V10 commercial simulation software. Property analysis and prediction of plant’s performancewere achieved using Non-Random Two Liquid Redlich-Kwong thermodynamic model. Both residual curve maps and ternary diagrams were used to determineseparation possibility and presence of ethanol-water azeotrope in the formed ternary mixtureduring distillation synthesis. The process convergence was addressed using flowsheet convergence and balance node. Distillation of ethanol- water azeotropic mixture was simulated at constant recycle ratio (R = 5), numberof stages (N = 12) and pressure (P = 1 atm). Data obtained were analysed in MS Excel 2013. Results showed that simultaneous increase ofmolar flow rate of the near azeotropic feed and feed ethanol concentration improves ethanol purity but results in retrograde phenomenon which may humper plant’s performance and increase stream flow rates and therefore increase energy duties. The condenser duty of the main column wasaround 90.94% higher than the recycle column’scondenser duty. Also, reboiler duty of the main column were nearly 90.25% higher than the recycle column’s reboiler duty.It was concluded that setting 18 to 20 kmol/h feed molar flow rate enhances higher energy efficiency and improves ethanol product purity. Careful distillation synthesis and plant’s monitoring are recommended to improve ethanol-water azeotropic distillation plant’s performance and address retrograde phenomena.

Key phase diagram experiment of the ZnO-SnO2 system and thermodynamic modeling of the ZnO-SnO2-TiO2 system

Key phase diagram experiment of the ZnO-SnO2 system and thermodynamic modeling of the ZnO-SnO2-TiO2 system

Computational Modeling and Experimental Investigation of CO2-Hydrocarbon System Within Cross-Scale Porous Media.

CO2 flooding plays a crucial role in enhancing oil recovery and achieving carbon reduction targets, particularly in unconventional reservoirs with complex pore structures. The phase behavior of CO2 and hydrocarbons at different scales significantly affects oil recovery efficiency, yet its underlying mechanisms remain insufficiently understood. This study improves existing thermodynamic models by introducing Helmholtz free energy as a convergence criterion and incorporating adsorption effects in micro- and nano-scale pores. This study refines existing thermodynamic models by incorporating Helmholtz free energy as a convergence criterion, offering a more accurate representation of confined phase behavior. Unlike conventional Gibbs free energy-based models, this approach effectively accounts for confinement-induced deviations in phase equilibrium, ensuring improved predictive accuracy for nanoscale reservoirs. Additionally, adsorption effects in micro- and nano-scale pores are explicitly integrated to enhance model reliability. A multi-scale thermodynamic model for CO2-hydrocarbon systems is developed and validated through physical simulations. Key findings indicate that as the scale decreases from bulk to 10 nm, the bubble point pressure shows a deviation of 5% to 23%, while the density of confined fluids increases by approximately 2%. The results also reveal that smaller pores restrict gas expansion, leading to an enhanced CO2 solubility effect and stronger phase mixing behavior. Through phase diagram analysis, density expansion, multi-stage contact, and differential separation simulations, we further clarify how confinement influences CO2 injection efficiency. These findings provide new insights into phase behavior changes in confined porous media, improving the accuracy of CO2 flooding predictions. The proposed model offers a more precise framework for evaluating phase transitions in unconventional reservoirs, aiding in the optimization of CO2-based enhanced oil recovery strategies.

Probing Single-Cell Adhesion Kinetics and Nanomechanical Force with Surface Plasmon Resonance Imaging.

Single cell adhesion plays a significant role in numerous physiological and pathological processes. Real-time imaging and quantification of single cell adhesion kinetics and corresponding cell-substrate mechanical interaction forces are crucial for elucidating the cellular mechanisms involved in tissue formation, immune responses, and cancer metastasis. Here, we present the development of a plasmonic-based nanomechanical sensing and imaging system (PNMSi) for the real-time measurement of single cell adhesion kinetics and associated nanomechanical forces with plasmonic tracking and monitoring of cell-substrate interactions and the accompanying nanoscale fluctuations. Both the slow binding and dynamic nanomechanical interaction processes were tracked and analyzed with a thermodynamic model to determine the adhesion kinetic parameters and quantity the mechanical forces. To demonstrate the capabilities of the PNMSi platform, we examined single cell binding interactions across four different surface modifications, and obvious alterations in binding kinetics and corresponding nanomechanical forces were observed, influenced by surface charges and interfacial hydrophilicity. Additionally, we investigated changes in mechanical interaction forces of single cells during cytoskeleton modification, revealing the cross-linking-induced cell adhesion changes. Furthermore, to demonstrate the application capability of the system, the adhesion profiling of primary tumor and metastatic tumor cells was explored, and obvious alterations were observed in the kinetic forces of single cell-substrate interaction. The PNMSi platform facilitates high-throughput single cell adhesion imaging and the quantification of adhesion interaction kinetics and nanomechanical forces with high sensitivity and serves as a promising platform for identifying biomarkers for tumor metastasis and for screening potential therapeutic agents.

Graph-Based Deep Learning Models for Thermodynamic Property Prediction: The Interplay between Target Definition, Data Distribution, Featurization, and Model Architecture.

In this contribution, we examine the interplay between target definition, data distribution, featurization approaches, and model architectures on graph-based deep learning models for thermodynamic property prediction. Through consideration of five curated data sets, exhibiting diversity in elemental composition, multiplicity, charge state, and size, we examine the impact of each of these factors on model accuracy. We observe that target definition, i.e., using formation instead of atomization energy/enthalpy, is a decisive factor, and so is a careful selection of the featurization approach. Our attempts at directly modifying model architectures result in more modest, though not negligible, accuracy gains. Remarkably, we observe that molecule-level predictions tend to outperform atom-level increment predictions, in contrast to previous findings. Overall, this work paves the way toward the development of robust graph-based thermodynamic model architectures with more universal capabilities, i.e., architectures that can reach excellent accuracy across data sets and compound domains.

Outdoor exposure of a heavy metal doped concrete -Measuring and modelling of substance release.

Many construction products are in contact with, e.g., rain and seepage water during their service life. As a result, they may leach and release potentially harmful substances into the environment. Harmonized laboratory tests are available to assess the potential environmental impact, but the evaluation of leaching test results remains challenging because releases found in laboratory experiments cannot be directly extrapolated to field conditions. Particularly complex is the case of irrigated and therefore intermittently wetted components. This paper presents the leaching results of a one-year outdoor irrigation of a fly ash concrete doped with heavy metals (arsenic, lead, cadmium, chromium, copper, nickel, thallium, vanadium, and zinc). The results are compared with those of two other outdoor irrigation studies: a high-density concrete and a facing masonry mortar. Two modeling approaches, a statistical method by Weiler et al. and a thermodynamic model of Vega Garcia et al. are used to model the incremental and cumulative releases and to compare their applicability and predictive value. The experimental data of this work confirm the well-known fact that cementitious phases effectively incorporate many potentially environmentally harmful substances. However, increased leaching, particularly outdoors, is observed for the oxyanion-forming elements arsenic, chromium, vanadium, and sulfur. Both models seem sufficient for depicting and, in the case of statistics, also to predict the magnitude of the measured values. However, while the statistical approach focuses only on the results and requires further verification data and factor development for different materials, the thermodynamic approach describes the geochemical processes and therefore requires more background knowledge of the operator; it also lacks predictive accuracy for the irrigation case. Further research is needed.

Thermodynamic Model of Glass Ceramics Crystallization

The increase in the economic efficiency in many industries (energy, mineral resources, metallurgy, chemical coal, construction) is associated with new materials with unusual combination of physical, mechanical and chemical properties. Glass-ceramic materials obtained by directional glass crystallization rank first among others. Compared to crystalline substances, glass has increased internal energy (latent energy of crystallization). Therefore, the substance in the glassy state is metastable (thermodynamically unstable). Ordinary glass under certain conditions begins to crystallize, sometimes, spontaneously. This process is called drying or devitrification. A thermodynamic model is proposed based on the concept of dynamic equilibrium of energy and matter flows during phase transitions in non-equilibrium open systems. The model considers thermal force of the metasilicate crystal growth. Some of the main dependencies of kinetic parameters on thermodynamic properties are suggested for М2М1[Si2O6] metasilicate composition. The crystallization temperature growth occurs as the overall basicity ∆Ζо298 increases against relative increase in the basicity of ions in the cationic sublattice M2 and, especially, in the octahedral sublattice M1.

Aqueous Alteration as an Origin of Martian Magnetization

AbstractStrong magnetic fields have been measured from orbit around Mars over parts of the ancient southern highlands crust and on the surface at the InSight landing site. The geological processes that are responsible for generating strong magnetization within the crust remain poorly understood. One possibility is that intense aqueous alteration of crustal materials, through the process of serpentinization, could have produced magnetite that was magnetized in the presence of a global core‐generated magnetic field. Here, we test this idea with geophysical and geochemical models. We first determine the magnetizations required to account for the observed magnetic field strengths and then estimate the amount of magnetite necessary to account for these magnetizations. For the strongest orbital magnetic field strengths, about 7 wt% magnetite is required if the magnetic layer is 10 km thick. For the surface field strength observed at the InSight landing site, 0.4–1.1 wt% magnetite is required if the magnetic layer corresponds to one or more of the three crustal layers observed in the InSight seismic data (with thicknesses from 8 to 39 km). We then investigate the minerals that are produced by aqueous alteration for various possible crustal compositions and water‐to‐rock ratios using a thermodynamic model. Magnetite abundances up to 6 wt% can be generated for dunitic compositions that could account for the strongest magnetic anomalies. For more representative basaltic starting compositions, however, more than 0.4 wt% can only be generated when using high water‐to‐rock ratios, which could account for the weaker magnetizations beneath the InSight landing site.

Modeling the influence of bainite transformation on the flow behavior of steel using a macroscale finite element analysis

This study comprehensively investigates the kinetics of bainitic ferrite transformation in steel alloys by integrating experimental results, finite element analysis, and thermodynamic modeling. Using a dilatometer and Gleeble tests, empirical data were acquired to calibrate the Bhadeshia and Hensel-Spittel models, forming the basis for subsequent finite element simulations. Owing to the high importance of temperature in bainite transformation, the accuracy of the predicted temperature fields was validated precisely against experimental measurements, confirming the reliability of the methodology. A modified Bhadeshia model was proposed incorporating the influence of the applied shear stress on the activation energy, thereby emphasizing the temperature-dependent Cstress coefficient. The electron backscatter diffraction results validate the finite element model, and further exploration reveals the implications for fracture patterns and density changes due to bainitic transformation. This study contributes to a nuanced understanding of bainitic ferrite kinetics, offering valuable insights for alloy design and optimization under various thermomechanical conditions, and paving the way for advanced research on phase transformation kinetics and material behavior.

Molybdenum speciation in magmatic-hydrothermal fluids: Constraints from molybdenite solubility experiments and thermodynamic modeling

Molybdenum speciation in magmatic-hydrothermal fluids: Constraints from molybdenite solubility experiments and thermodynamic modeling