Search Results (241)

Although lithium-ion batteries are considered an ideal postulant for renewable energy harvesting, storage and applications, these batteries show promising performance; however, at the same time, these harvesting devices suffer from some major limitations, including scarce lithium resources, high cost, toxicity and safety concerns. Potassium ion batteries (PIBs) can be proven a favorable alternative to metal ion batteries because of their widespread potassium reserves, low costs and enhanced protection against sparks. In this study, DFT simulations were employed using the B3LYP/6-311⁺⁺g(d p) method to explore the application of graphene and its doped variants (N,B,P-graphene) as potential anode materials for PIBs. Various key parameters such as adsorption energy, Gibbs free energy, molecular orbital energies, non-covalent interactions, cell voltage, electron density distribution and density of states were computed as a means to evaluate the suitability of materials for PIB applications. Among the four structures, nitrogen- and phosphorus-doped graphene exhibited negative Gibbs free energy values of −0.020056 and −0.021117 hartree, indicating the thermodynamic favorability of charge transfer processes. Doping graphene with nitrogen and phosphorus decreases the HOMO-LUMO gap energy, facilitating efficient ion storage and charge transport. The doping of nitrogen and phosphorus increases the cell voltage from −1.05 V to 0.54 V and 0.57 V, respectively, while boron doping decreases the cell voltage. The cell voltage produced by graphene and its doped variants in potassium ion batteries has the following order: P-graphene (0.57 V) > N-graphene (0.54 V) > graphene (−1.05 V) > B-graphene (−1.54 V). This study illustrates how nitrogen- and phosphorus-doped graphene can be used as a propitious anode electrode for PIBs. Full article

In the present work, we suggest a new approach for studying the equilibrium states of an hydrodynamic isothermal turbulent self-gravitating system as a statistical model for a molecular cloud. The main hypothesis is that the local turbulent motion of the fluid elements is purely chaotic and can be regarded as a perfect gas. Then, the turbulent kinetic energy per fluid element can be substituted for the temperature of the chaotic motion of the fluid elements. Using this, we write down effective formulae for the internal and total the energy and for the first principal of thermodynamics. Then, we obtain expressions for the entropy, the free energy, and the Gibbs potential. Searching for equilibrium states, we explore two possible systems: the canonical ensemble and the grand canonical ensemble. Studying the former, we conclude that there is no extrema for the free energy. Through the latter system, we obtain a minimum of the Gibbs potential when the macro-temperature and pressure of the cloud are equal to those of the surrounding medium. This minimum corresponds to a possible stable local equilibrium state of our system. Full article

The practical implementation of transition state theory (TST) commonly assumes equivalence between theoretical and experimentally determined rate constants, represented by Arrhenius parameters—the activation energy and pre-exponential factor. Here, we employed the General Rate Equation (GRE) to analyse solid–gas-phase thermolysis in two paradigms: mass loss (e.g., calcite decomposition) and mass gain (e.g., methane pyrolysis leading to solid carbon formation). By partitioning the Gibbs free energy of activation into forwards and reverse contributions, plus an additional term accounting for concurrent physical phenomena (notably nucleation and diffusion-viscosity effects), we derived an empirical universal expression relating both Arrhenius parameters and $∆G^{+}$ across 500–1500 K. We further demonstrate the utility of the isokinetic temperature for interpreting cases where only Kinetic Compensation or Enthalpy–Entropy Compensation effects are observed. This framework unifies kinetic and thermodynamic descriptions of complex thermolysis processes. Full article

Geological storage of CO₂ in coal seam is an effective way for carbon emission reduction. Evaluating the adsorption-induced swelling behavior of confined coal is essential for this carbon emission reduction strategy. Based on the thermodynamic theory and the Gibbs adsorption model, a thermodynamic method for evaluating the gas adsorption-induced swelling behavior of confined coal was established. The influences of factors such as stress, gas pressure, and the state of gas on the adsorption-induced swelling behavior of confined coal were discussed. The predicted swelling deformation from the thermodynamic method based on the ideal gas hypothesis was consistent with the experimental result only under the condition of low-pressure CO₂ (<2 MPa). The predicted swelling deformation from that method was larger than the experimental result under the condition of high-pressure CO₂ (>2 MPa). However, the method based on the real gas hypothesis always had better prediction results under both the low- and high-pressure CO₂ conditions. From the perspective of phase equilibrium and transfer, in the process of CO₂ adsorption by the confined coal, gas molecules transfer from the adsorption site of high chemical potential to the low chemical potential. Taking the real gas as ideal gas will result in the surface energy increase in the established model. Consequently, the prediction result will be larger. Therefore, for geological storage of CO₂ in coal seam, it is necessary to take the real gas state to predict the adsorption-induced swelling behavior of the coal. In the process of CO₂ adsorption by the confined coal, when its pressure is being closed to the critical pressure, capillary condensation phenomenon will occur on the pore surface of the confined coal. This can make an excessive adsorption of CO₂ by the coal. With the increase in the applied stress, the adsorption capacity and adsorption-induced swelling deformation of the confined coal decrease. Compared to N₂ with CO₂, the coal by CO₂ adsorption always shows swelling deformation under the simulated condition of ultra-high-pressure injection. However, the coal by N₂ adsorption will shows shrinking deformation due to the pore pressure effect after the equilibrium pressure. Taking the difference in the adsorption-induced swelling behavior and pore compression effect, N₂ can be mixed to improve the injectivity of CO₂. This suggests that CO₂ storage in the deep burial coal seam can be carried out by its intermittent injection under high-pressure condition along with mixed N₂. Full article

The electrochemical CO₂ reduction reaction (eCO₂RR), driven by renewable energy, represents a promising strategy for mitigating atmospheric CO₂ levels while generating valuable fuels and chemicals. Its practical implementation hinges on the development of highly efficient electrocatalysts. In this study, a novel dual-metal atomic catalyst (DAC), composed of niobium and palladium single atoms anchored on a ferroelectric α-In₂Se₃ monolayer (Nb-Pd@In₂Se₃), is proposed based on density functional theory (DFT) calculations. The investigation encompassed analyses of structural and electronic characteristics, CO₂ adsorption configurations, transition-state energetics, and Gibbs free energy changes during the eCO₂RR process, elucidating a synergistic catalytic mechanism. The Nb-Pd@In₂Se₃ DAC system demonstrates enhanced CO₂ activation compared to single-atom counterparts, which is attributed to the complementary roles of Nb and Pd sites. Specifically, Nb atoms primarily drive carbon reduction, while neighboring Pd atoms facilitate oxygen species removal through proton-coupled electron transfer. This dual-site interaction lowers the overall reaction barrier, promoting efficient CO₂ conversion. Notably, the polarization switching of the In₂Se₃ substrate dynamically modulates energy barriers and reaction pathways, thereby influencing product selectivity. Our work provides theoretical guidance for designing ferroelectric-supported DACs for the eCO₂RR. Full article

A novel approach to the quantum version of $\kappa$-entropy that incorporates it into the conceptual, mathematical and operational framework of quantum computation is put forward. Various alternative expressions stemming from its definition emphasizing computational and algorithmic aspects are worked out: First, for the case of canonical Gibbs states, it is shown that $\kappa$-entropy is cast in the form of an expectation value for an observable that is determined. Also, an operational method named “the two-temperatures protocol” is introduced that provides a way to obtain the $\kappa$-entropy in terms of the partition functions of two auxiliary Gibbs states with temperatures $\kappa$-shifted above, the hot-system, and $\kappa$-shifted below, the cold-system, with respect to the original system temperature. That protocol provides physical procedures for evaluating entropy for any $\kappa$. Second, two novel additional ways of expressing the $\kappa$-entropy are further introduced. One determined by a non-negativity definite quantum channel, with Kraus-like operator sum representation and its extension to a unitary dilation via a qubit ancilla. Another given as a simulation of the $\kappa$-entropy via the quantum circuit of a generalized version of the Hadamard test. Third, a simple inter-relation of the von Neumann entropy and the quantum $\kappa$-entropy is worked out and a bound of their difference is evaluated and interpreted. Also the effect on the $\kappa$-entropy of quantum noise, implemented as a random unitary quantum channel acting in the system’s density matrix, is addressed and a bound on the entropy, depending on the spectral properties of the noisy channel and the system’s density matrix, is evaluated. The results obtained amount to a quantum computational tool-box for the $\kappa$-entropy that enhances its applicability in practical problems. Full article

In this work, we studied the main decomposition reactions on the ground state of nitromethane (CH₃NO₂) with the CASPT2 approach. The energetics of the main elementary reactions of the title molecule have been analyzed on the basis of Gibbs free energies obtained from standard expressions of statistical thermodynamics. In addition, we describe a mapping method (orthogonalized 3D representation) for the potential energy surfaces (PESs) by defining an orthonormal basis consisting of two $R^n$ orthonormal vectors (n, internal degrees of freedom) that allows us to obtain a set of ordered points in the plane (vector subspace) spanned by such a basis. Geometries and harmonic frequencies of all species and orthogonalized 3D representations of the PESs have been computed with the CASPT2 approach. It is found that all of the analyzed kinetically controlled reactions of nitromethane are endergonic. For such a class of reactions, the dissociation of nitromethane into CH₃ and NO₂ is the process with the lower activation energy barrier (ΔG); that is, the C-N bond cleavage is the most favorable process. In contrast, there exists a dynamically controlled process that evolves through a roaming reaction mechanism and is an exergonic reaction at high temperatures: CH₃NO₂ → [CH₃^…NO₂]* → [CH₃ONO]* → CH₃O + NO. The above assertions are supported by CASPT2 mappings of the potential energy surfaces (PESs) and classical trajectories obtained by “on-the fly” CASSCF molecular dynamics calculations. Full article

Based on the literature data, including our published paper on the thermal decomposition of solids, research regarding the possibility of balancing free energy of activation against Gibbs free energy was extended. The importance of nucleation accompanying the thermal decomposition reaction/process was established. For calcite, a symmetrical model was considered for the formation of the active state, followed by the formation into the solid, crystalline decomposition product CaO. When the decomposition is chemical in nature, we do not identify nucleation processes. This is determined by the forwards–backwards balance compatibility, and when an additional term appears, a reversible structural transformation is to be expected. An excess free energy model was proposed to determine the rate constant of activation. It is shown that the results of tests under dynamic conditions allow, with a good approximation, the determination of this quantity as tending towards a maximum rate constant equal to the Arrhenius pre-exponential factor. The solid product of the thermal decomposition of calcite is of great developmental importance, currently utilized for Calcium Looping (CaL) or for Carbon Capture and Storage (CCS) technologies using a reversible reaction of carbonation. Full article

Cisplatin is still a first-line agent in cancer treatment due to its effectiveness. Despite the large body of research concerning this drug, the role of explicit water molecules in its mechanism remains uncertain. We addressed the addition of cisplatin with the nitrogenous DNA bases adenine and guanine, with an emphasis on the impact of explicit microsolvation on every step of the action pathway of this pharmaceutical. We used electronic structure calculations to explore the energetics of the key reactions of this mechanism. We also exploited state-of-the-art methods of wave function analyses, namely, the Quantum Theory of Atoms in Molecules and the Interacting Quantum Atoms partition, to explore the chemical bonding throughout such chemical reactions. Our results reveal that microsolvation significantly differently affects electronic and Gibbs free activation energies, as previously reported (F.P. Cossio et al. ChemPhysChem, 17, 3932, 2016). The changes in activation energies are consistent with Hammond’s postulate in terms of the changes in the chemical bonding scenario between reactants and transition states. Overall, we provide an in-depth description of the importance of the surrounding water molecules of cisplatin, which aids in understanding the mechanism of pharmaceuticals in the pursuit of more effective cancer treatments. Full article

This work presents a comprehensive approach for the justification of the reagent regime of coal flotation by investigating the interfacial characteristics of flotation phases with various techniques. For the energy characterization of the surface processes in flotation systems, a method of establishing the components of the specific surface Gibbs energy on the basis of a numerical estimation of surface free energy change during the adsorption of flotation reagents using the Owens–Wendt–Rabel–Kaelble technique was proposed. Using the developed approach, the features of the kinetics of n-hexane sorption on the surface of coal samples were established. The substantiation of differences in the potential mechanisms of the fixation of strictly apolar and aromatic reagents is based on the results of the quantum–chemical modeling of the states of the coal–adsorbate system using the software packages Avogadro and Orca. The simulation shows the possibility of aliphatic and aromatic reagents’ synergetic effects on coal surface hydrophobization. Based on the results of quantum–chemical modeling, it was found that for the physical adsorption of an oxyethylated nonyl-phenol molecule on a molecular fragment of the coal surface, according to the Weiser model, the decrease in the energy of the system was 0.05562 eV, which indicates the high thermodynamic probability of the physical sorption of this compound. The parameters of the Langmuir monomolecular model for the sorption of oxyethylated nonyl-phenol on the surface of the studied coal samples were established. The criterion characterizing the interphase phenomena in the flotation system based on the results of potentiometric studies of the interfacial characteristics, E_f, was proposed. It was found that for the studied values of the flow rate of oxyethylated nonyl-phenol, the highest value of E_f was achieved when the value of the sorption of the reagent equaled 63.99% of the limiting sorption capacity. The performance of the proposed reagents for coal flotation was confirmed by flotation tests. Full article

Steam reforming is an important industrial process for hydrogen production. Acetone, the by-product of phenol production from cumene peroxidation, is a useful source of hydrogen due to its availability and low value compared to hydrogen fuel. This study aimed to utilize the Gibbs free energy minimization method using the Soave–Redlich–Kwong (SRK) equation of state (EOS) to conduct a thermodynamic analysis of the steam reforming process for pure component acetone. The steam reforming process is temperature dependent, with increasing temperatures leading to higher hydrogen production. Competing reactions, particularly the exothermic reverse water–gas shift, impact hydrogen yields beyond 650 °C. The study identified 600 °C as the optimum temperature to strike a balance between maximizing hydrogen production and minimizing the reverse water–gas shift’s impact. The optimal hydrogen yield (70 mol%) was achieved at a steam-to-oil ratio (STOR) of 12. High STOR values shift the equilibrium of the water–gas shift reaction towards hydrogen production due to increased steam, effectively consuming acetone and favoring the desired product. Atmospheric pressure is optimum for hydrogen production because the equilibrium of gas phase reactions shifts in favor of the lighter components at lower pressures. Full article

Biomass ironmaking is crucial for carbon reduction in the ironmaking industry. To understand this process better, the iron production capacity and energy requirements of biomass were studied. A thermodynamic equilibrium model and energy consumption model for the biomass and iron oxide reduction system at 100–1300 °C was established by the minimum free Gibbs energy method. The effects of factors such as biomass type, temperature, and initial amount of iron oxide on the system were analyzed. The research results indicated that the maximum ironmaking capacity of biomass was determined by the element content of carbon, hydrogen and oxygen in biomass and temperature. The equilibrium H₂/(H₂ + H₂O) and CO/(CO + CO₂) at the maximum iron yield were affected not by the biomass species and element content, but by temperature. The reduction capacity of the ten selected biomass types decreased with a temperature increase from 700 °C to 1300 °C. For the 1 kg of pine sawdust and iron oxide system, the maximum equilibrium state amount of metallic iron was 23.05 mol at 718 °C, and the minimum system energy consumption per ton Fe was 1.16 GJ at 800 °C and 1.18 GJ at 900 °C. These research results will provide a key basis for a deeper understanding of the intrinsic mechanism of biomass ironmaking. Full article

Today, the machining of heat-resistant alloys based on triple, quad, or penta equilibria high-entropy alloy systems of elements (ternary, quaternary, quinary iron-, titanium-, or nickel-rich alloys), including dual-phase by Gibb’s phase rule, steels of the austenite class, and nickel- and titanium-based alloys, are highly relevant for the airspace and aviation industry, especially for the production of gas turbine engines. Cutting tools in contact with those alloys should withstand intensive mechanical and thermal loads (tense state of 1.38·10⁸–1.54·10⁸ N/m², temperature up to 900–1200 °C). The most spread material for those tools is cutting ceramics based on oxides, nitrides of the transition and post-transition metals, and metalloids. This work considers the wear resistance of the cutting insert of silicon nitride with two unique development coatings — titanium–zirconium nitride coating (Ti,Zr)N and complex quad nitride coating with TiN content up to 70% (Ti,Al,Cr,Si)N with a thickness of 3.8–4.0 µm on which microtextures were produced by the assisted electric discharge machining with the electrode-tool of ø0.25 mm. The microtextures were three parallel microgrooves of R0.13^+0.02 mm at a depth of 0.025₋₀.₀₅. The operational life was increased by ~1.33 when the failure criterion in turning nickel alloy was 0.4 mm. Full article

This study develops a three-state Markov framework to estimate the transition rates between normal, preclinical screen-detectable phase (PCDP), and clinical breast cancer using simulated data. Two exponential models are explored: a five-mode transition model and a six-mode transition model, the latter incorporating exact cancer case timings. Each model is analyzed both with and without covariates to evaluate their influence on breast cancer progression. Parameters are estimated utilizing maximum likelihood estimation and Bayesian models with Gibbs sampling to ensure robustness and methodological rigor. Additionally, a nonhomogeneous model based on the Weibull distribution is introduced to account for time-varying transition rates, providing a more dynamic perspective on disease progression. While the analysis is conducted with simulated data, the framework is adaptable to real-world datasets, offering valuable insights for refining screening policies and optimizing inter-screening intervals. Full article

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory, Ergodic Theory and the Theory of Dynamical Systems. Specifically, we are referring to the classical entropies: the Boltzmann–Gibbs, von Neumann, Shannon, Kolmogorov–Sinai and topological entropies. In addition to their common name, which is historically justified (as we briefly describe in this review), another commonality of the classical entropies is the important role that they have played and are still playing in the theory and applications of their respective fields and beyond. Therefore, it is not surprising that, in the course of time, many other instances of the overarching concept of entropy have been proposed, most of them tailored to specific purposes. Following the current usage, we will refer to all of them, whether classical or new, simply as entropies. In particular, the subject of this review is their applications in data analysis and machine learning. The reason for these particular applications is that entropies are very well suited to characterize probability mass distributions, typically generated by finite-state processes or symbolized signals. Therefore, we will focus on entropies defined as positive functionals on probability mass distributions and provide an axiomatic characterization that goes back to Shannon and Khinchin. Given the plethora of entropies in the literature, we have selected a representative group, including the classical ones. The applications summarized in this review nicely illustrate the power and versatility of entropy in data analysis and machine learning. Full article