Energy Equilibrium Research Articles

Role of the complexity factor and Karmarkar condition in constructing new wormhole models in dRGT gravity

This study delves into the distinctive characteristics of wormhole models in the context of de Rham-Gabadadze-Tolley (dRGT) massive gravity, providing insights into their theoretical behavior and stability. We use a null zero complexity factor to find the wormhole shape function for Model I. Additionally, we solve analytically the modified field equations describing wormhole for a given choice of logarithmic redshift function, exploiting the Karmarkar condition for embedding class one metrics for Model II. To achieve this, we analyze the wormhole geometry in a static spherical spacetime with an anisotropic matter configuration. The study investigates a number of parameters, including density, energy conditions, equation of state parameter, adiabatic sound velocity, and equilibrium condition. The solution shows a traversable wormhole that violates the null energy criterion and equilibrium state for certain ranges of free parameters. We employ adiabatic sound velocity analysis to concentrate on the stability of the wormhole. Furthermore, by using the equation of state parameter (ω), we conclude that both models end up in the phantom dark energy region. Finally, our findings highlight distinct photon deflection behaviors in dRTG massive gravity, with Model II showing negative angles indicative of repulsive gravity, while Model I exhibits positive angles, underscoring significant differences in gravitational dynamics.

Optimisation of photovoltaic storage and charging system operation based on photovoltaic power generation prediction analysis

Abstract The power generation of photovoltaic power generation systems has more influencing factors. Accurate PV power prediction data is needed in order to maintain the stable operation of the power system. In this paper, a photovoltaic power generation prediction scheme combining the integrated weather-similar day clustering method is designed with reference to the weather characteristics in the northeast region. The training samples are classified into three generalized weather small sample datasets. The radial basis (RBF) neural network prediction optimized with the Fruit Fly Algorithm (FOA) is chosen as the main body of the prediction system model. The prediction model is established. The power prediction is compared with the power prediction using the BP neural network model. The simulated prediction results are analyzed. The results indicate that the FOA-RBF neural network model exhibits superior performance in approximating nonlinear functions compared to the BP neural network. Ultimately, the forecasted data is utilized for operational enhancement, aiming for peak economic efficiency as the goal of optimization. This process considers limitations like energy equilibrium to enhance the financial viability of the optical storage charging facility, which improves the economic efficiency of the photovoltaic storage charging station, enhances the reliability of the system, and verifies the usability of the small-sample PV power prediction strategy based on FOA-RBF neural network designed in this paper for the northeastern region.

Comparison of the Reaction Characteristics of Different Fuels in the Supercritical Multicomponent Thermal Fluid Generation Process

Supercritical multicomponent thermal fluid technology is a new technology with obvious advantages in offshore heavy oil recovery. However, there is currently insufficient understanding of the generation characteristics of the supercritical multicomponent thermal fluid, which is not conducive to the promotion and application of this technology. In order to improve the economic benefits and applicability of the supercritical multicomponent thermal fluid thermal recovery technology, this article reports on indoor supercritical multicomponent thermal fluid generation experiments and compares the reaction characteristics of different fuels in the supercritical multicomponent thermal fluid generation process. The research results indicate that the main components of the products obtained from the supercritical water–crude oil/diesel reaction are similar. Compared to the supercritical water–crude oil reaction, the total enthalpy value of the supercritical multicomponent thermal fluid generated by the supercritical water–diesel reaction is higher, and the specific enthalpy is lower. When the thermal efficiency of the boiler is the same, the energy equilibrium concentration of crude oil is lower than that of diesel. The feasibility of using crude oil instead of diesel to prepare supercritical multicomponent thermal fluids is analyzed from three aspects: reaction mechanism, economic benefits, and technical conditions. It is believed that using crude oil instead of diesel to prepare supercritical multicomponent thermal fluids has good feasibility.

Model and Energy Bounds for a Two-Dimensional System of Electrons Localized in Concentric Rings.

We study a two-dimensional system of interacting electrons confined in equidistant planar circular rings. The electrons are considered spinless and each of them is localized in one ring. While confined to such ring orbits, each electron interacts with the remaining ones by means of a standard Coulomb interaction potential. The classical version of this two-dimensional quantum model can be viewed as representing a system of electrons orbiting planar equidistant concentric rings where the kinetic energy may be discarded when one is searching for the lowest possible energy. Within this framework, the lowest possible energy of the system is the one that minimizes the total Coulomb interaction energy. This is the equilibrium energy that is numerically determined with high accuracy by using the simulated annealing method. This process allows us to obtain both the equilibrium energy and position configuration for different system sizes. The adopted semi-classical approach allows us to provide reliable approximations for the quantum ground state energy of the corresponding quantum system. The model considered in this work represents an interesting problem for studies of low-dimensional systems, with echoes that resonate with developments in nanoscience and nanomaterials.

Magnesium Regulates RNA Ring Dynamics and Folding in Subgenomic Flaviviral RNA.

Mosquito-borne flaviviruses including dengue, Zika, yellow fever, and regional encephalitis produce a large amount of short subgenomic flaviviral RNAs during infection. A segment of these RNAs named as xrRNA1 features a multi-pseudoknot (PK)-associated structure, which resists the host cell enzyme (XRN1) from degrading the viral RNA. We investigate how this long-range RNA PK folds in the presence of counterions, specifically in a mix of monovalent (K+) and divalent (Mg2+) salts at physiological concentrations. In this study, we use extensive explicit solvent molecular dynamics (MD) simulations to characterize the RNA ion environment of the folded RNA conformation, as determined by the crystal structure. This allowed us to identify the precise locations of various coordinated RNA-Mg2+ interactions, including inner-sphere/chelated and outer-sphere coordinated Mg2+. Given that RNA folding involves large-scale conformational changes, making it challenging to explore through classical MD simulations, we investigate the folding mechanism of xrRNA1 using an all-atom structure-based RNA model with a hybrid implicit-explicit treatment of the ion environment via the dynamic counterion condensation model, both with and without physiological Mg2+ concentration. The study reveals potential folding pathways for this xrRNA1, which is consistent with the results obtained from optical tweezer experiments. The equilibrium and free energy simulations both capture a dynamic equilibrium between the ring-open and ring-close states of the RNA, driven by a long-range PK interaction. Free energy calculations reveal that with the addition of Mg2+ ions, the equilibrium shifts more toward the ring-close state. A detailed analysis of the free energy pathways and ion-mediated contact probability map highlights the critical role of Mg2+ in bridging G50 and A33. This Mg2+-mediated connection helps form the long-range PK which in turn controls the transition between the ring-open and ring-close states. The study underscores the critical role of Mg2+ in the RNA folding transition, highlighting specific locations of Mg2+ contributing to the stabilization of long-range PK connections likely to enhance the robustness of Xrn1 resistance of flaviviral xrRNAs.

Molecular simulation on competitive adsorption of ethanol, acetaldehyde and acetic acid on zeolites in humid conditions

Adsorption is a key technique for purifying volatile organic compounds (VOCs) from indoor air. Due to the complexity of multi-component VOCs and humid environment, the competitive adsorption among VOCs under the influence of water vapor remains unclear, which limits adsorbent selection and performance prediction. In this work, adsorption characteristics of typical indoor VOCs (ethanol, acetaldehyde, and acetic acid) on commercial zeolites (BETA-25 and ZSM5-300) under varying humidity were studied through molecular simulation. The simulation based on charge-corrected molecular structures and force field was validated by experiments. The unary, binary and ternary adsorption isotherms of three VOCs were obtained. At both dry and wet conditions, the VOCs with higher polarity shows greater adsorption capacity: acetic acid > ethanol > acetaldehyde. BETA-25 exhibits stronger adsorption on all three gases under dry conditions, while under wet conditions ZSM5-300 shows greater adsorption capacity of ethanol and acetaldehyde with lower polarity as compared to BETA-25. Simulation of adsorption energy and adsorbate density distribution in ternary equilibrium demonstrates the presence of water vapor alters the sorbate-sorbent interaction, particularly for ethanol and acetaldehyde showing stronger adsorption on BETA-25 than on ZSM5-300 at dry conditions but reversely at wet conditions. The lower-silica zeolite favors the adsorption of highly-polar VOC regardless of water, and the higher-silica counterpart with greater hydrophobicity facilitates adsorption of less-polar compounds in competing with water. The findings in this work can provide methodological reference for adsorbent screening and data basis for real VOCs purification applications.

The Staggered Mesh Method: Accurate Exact Exchange Toward the Thermodynamic Limit for Solids.

In periodic systems, the Hartree-Fock (HF) exchange energy exhibits the slowest convergence of all HF energy components as the system size approaches the thermodynamic limit. We demonstrate that the recently proposed staggered mesh method for Fock exchange energy [Xing, Li, and Lin, Math. Comp., 2024], which is specifically designed to sidestep certain singularities in exchange energy evaluation, can expedite the finite-size convergence rate for the exact exchange energy across a range of insulators and semiconductors when compared to the regular and truncated Coulomb methods. This remains true even for two computationally cheaper versions of this new method, which we call non-SCF and split-SCF staggered mesh. Additionally, a sequence of numerical tests on simple solids showcases the staggered mesh method's ability to improve convergence toward the thermodynamic limit for band gaps, bulk moduli, equilibrium lattice dimensions, energies, and phonon force constants.

FP-LMTO simulation of the physical properties of arsenic-based binary XAs(X = Sc, and Al) compounds

This paper presents a simulation of the structural and optoelectronic properties of Scandium Arsenide (ScAs) and Aluminum Arsenide (AlAs) compounds. Theoretical modeling was performed using ab initio first-principles calculations, specifically the density functional theory (DFT), and the Mindlab numerical software. The software used two methods: the full-potential muffin-tin orbital method (FP-LMTO) and the full-potential plane-wave method (FP-LAPW). These two methods are employed to solve the Schrödinger equation. The exchange correlation effects have been computed using two different approximations: the generalized gradient approximation (GGA) and the local density approximation (LDA). Our findings indicate that the zinc blende structure (B3) is the stable phase, while the Wurtzite phase (B4) is metastable for the AlAs compound. On the other hand, the ScAs compound crystallizes in the NaCl phase (B1). The AlAs compounds undergo three phase transitions: [Formula: see text], [Formula: see text] and [Formula: see text]. In contrast, ScAs does not undergo any transition. The obtained results for equilibrium energies, lattice parameters and gap energies are in closer agreement with the experimental and theoretical data. The AlAs compound exhibits a semiconducting character, while ScAs exhibits a semi-metallic character. Additionally, the refractive index of these two compounds is similar to that of silicon, which is crucial for their application in photovoltaic cells.

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories.

The accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH3) molecule and the nucleophilic substitution (SN2) reaction F- + CH3F → FCH3 + F-. We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Dual-layer control strategy based on economic characterization of lifetime state and frequency regulation limit partition of hybrid energy storage

Compared with a single type of energy storage, hybrid energy storage system (HESS) has a better performance in improving the frequency safety of the grid. However, the combination of hybrid energy storage with different resource characteristics and thermal power units will significantly increase the difficulty of coordinated control. In view of the life decay of battery energy storage system (BESS) and the insufficient frequency regulation capability of the system, this paper proposes a dual-layer control strategy based on the economic characterization of hybrid energy storage life state and the frequency regulation limit partition. Real-time state of charge (SOC) is used to establish dynamic equilibrium quotation and energy storage performance characterization as the upper-layer model. Meanwhile, the optimal life evaluation of energy storage is proposed, and the charging and discharging switching model of energy storage is constructed to limit the frequent switching of energy storage and extend its life. The lower-layer model constructs the limit standard of frequency regulation of flywheel energy storage system (FESS), introduces multi-objective constraints, proposes a hybrid energy storage operation scheme suitable for the whole scene, and uses “two rules” as the evaluation index to evaluate the frequency regulation effect of the proposed frequency regulation control model from the regulation rate, accuracy and response time. Finally, taking the actual data of a local thermal power unit as an example, the validity and economy of the frequency regulation effect of the proposed model are verified.

Design and Optimization of Molecularly Imprinted Polymer Targeting Epinephrine Molecule: A Theoretical Approach.

Molecularly imprinted polymers (MIPs) are a growing highlight in polymer chemistry. They are chemically and thermally stable, may be used in a variety of environments, and fulfill a wide range of applications. Computer-aided studies of MIPs often involve the use of computational techniques to design, analyze, and optimize the production of MIPs. Limited information is available on the computational study of interactions between the epinephrine (EPI) MIP and its target molecule. A rational design for EPI-MIP preparation was performed in this study. First, density functional theory (DFT) and molecular dynamic (MD) simulation were used for the screening of functional monomers suitable for the design of MIPs of EPI in the presence of a crosslinker and a solvent environment. Among the tested functional monomers, acrylic acid (AA) was the most appropriate monomer for EPI-MIP formulation. The trends observed for five out of six DFT functionals assessed confirmed AA as the suitable monomer. The theoretical optimal molar ratio was 1:4 EPI:AA in the presence of ethylene glycol dimethacrylate (EGDMA) and acetonitrile. The effect of temperature was analyzed at this ratio of EPI:AA on mean square displacement, X-ray diffraction, density distribution, specific volume, radius of gyration, and equilibrium energies. The stability observed for all these parameters is much better, ranging from 338 to 353 K. This temperature may determine the processing and operating temperature range of EPI-MIP development using AA as a functional monomer. For cost-effectiveness and to reduce time used to prepare MIPs in the laboratory, these results could serve as a useful template for designing and developing EPI-MIPs.

Optimizing multi-energy systems with enhanced robust planning for cost-effective and reliable operation

This paper introduces a comprehensive and resilient multi-energy system (MES) designed for independent planning and real-time implementation. A robust daily coordinated planning model is proposed, incorporating adjustable optimization with fundamental operational and uncertainty constraints. The model integrates various energy sources and systems, including photovoltaics, wind turbines, combined heat and power (CHP) units, energy storage system (ESS), electric vehicle (EV), electric boilers, and power-to-gas (P2G) facilities, to manage electricity, natural gas, and heat demands. The objective is to minimize MES operational costs while meeting electricity and heat requirements, considering renewable energy uncertainties. It includes the development of a two-stage flexible robust optimization model that accounts for energy equilibrium, capacity constraints, and demand response mechanisms. The model incorporates price-based demand response with both switchable and interruptible loads, enhancing system controllability and flexibility. Additionally, a scenario generation and reduction technique based on the Kantorovich distance is employed to effectively manage forecast errors and uncertainties. A novel modified Slime Mold Algorithm (SMA) is utilized to solve the optimization problem, demonstrating superior convergence and computational efficiency compared to traditional meta-heuristics. The slime mold algorithm is further enhanced with chaos theory, using a sine map to introduce dynamic exploration capabilities. The findings indicate that the proposed multi-energy system model effectively balances electricity, natural gas, and heat loads while accommodating renewable energy fluctuations. The enhanced slime mold algorithm provides optimal solutions swiftly, ensuring reliable and cost-effective multi-energy system operation.

The implications of policy modeling assumptions for the projected impact of sugar-sweetened beverage taxation on body weight and type 2 diabetes in Germany

BackgroundEvaluating sugar-sweetened beverage (SSB) taxation often relies on simulation models. We assess how assumptions about the response to SSB taxation affect the projected body weight change and subsequent health and economic impacts related to type 2 diabetes mellitus (T2DM) using Germany as an example.MethodsIn the main analysis, we estimated changes in energy intake by age and sex under a 20% value-added tax on SSBs in Germany using marginal price elasticities (PE) and applied an energy equilibrium model to predict body weight changes. We then quantified the impact of several assumption modifications: SSB own-PE adjusted for consumption (M1)/based on alternative meta-analysis (M2); SSB consumption adjusted for underreporting (M3); substitution via marginal (M4a) or adjusted (M4b) cross-PE/as % of calorie change (M4c). We also assessed scenarios with alternative tax rates of 10% (S1) or 30% (S2) and including fruit juice (S3). We calculated overweight and obesity rates per modification and scenario. We simulated the impact on T2DM, associated healthcare costs, and disability-adjusted life years (DALYs) over the lifetime of the 2011 German adult population with a Markov model. Data included official demographics, national surveys, and meta-analyses.ResultsA 20% value-added tax in Germany could reduce the number of men and women with obesity by 210,800 [138,800; 294,100] and 80,800 [45,100; 123,300], respectively. Over the population’s lifetime, this would lead to modest T2DM-related health and economic impacts (76,700 DALYs [42,500; 120,600] averted; €2.37 billion [1.33; 3.71] costs saved). Policy impacts varied highly across modifications (all in DALYs averted): (M1) 94,800 [51,500; 150,700]; (M2) 164,200 [99,500; 243,500]; (M3) 52,600 [22,500; 91,100]; (M4a) -18,100 [-111,500; 68,300]; (M4b) 25,800 [-31,400; 81,500]; (M4c) 46,700 [25,300; 77,200]. The variability in policy impact related to modifications was similar to the variability between alternative policy scenarios (all in DALYs averted): (S1) 26,400 [9,300; 47,600]; (S2) 126,200 [73,600; 194,500]; (S3) 342,200 [234,200; 430,400].ConclusionsPredicted body weight reductions under SSB taxation are sensitive to assumptions by researchers often needed due to data limitations. Because this variability propagates to estimates of health and economic impacts, the resulting structural uncertainty should be considered when using results in decision-making.

Biogas-to-Power Systems Based on Solid Oxide Fuel Cells: Thermodynamic Analysis of Stack Integration Strategies

Biogas presents a renewable fuel source with substantial potential for reducing carbon emissions in the energy sector. Exploring this potential in the farming sector is crucial for fostering the development of small-scale distributed biogas facilities, leveraging indigenous resources while enhancing energy efficiency. The establishment of distributed biogas plants bolsters the proportion of renewable energy in the energy matrix, necessitating efficient power generation technologies. Given their proximity to bio-waste production sites like farms and digesters, optimising combined heat and power generation systems is imperative for energy self-sufficiency. Small-scale biogas facilities demand specific power generation technologies capable of achieving notable efficiencies, ranging from 40% to 55%. This study focuses on employing Solid Oxide Fuel Cells (SOFCs) in biogas-to-power systems and investigates the theoretical operation of SOFCs with fuel mixtures resulting from different biogas lean upgrading pathways. Therefore, starting from ten mixtures including CH4, CO2, H2, H2O, N2, and O2, the study proposes a method to assess their impact on the electrochemical performance, degradation, and energy equilibrium of SOFC units. The model embeds thermodynamic equilibrium, the Nernst potential, and energy balance, enabling a comprehensive comparison across these three analytical domains. The findings underscore the unsuitability of dry biogas and dry biomethane due to the potential risk of carbon deposition. Moreover, mixtures incorporating CO2, with or without H2, present significant thermal balance challenges.

The role of an in-plane electric field during the merging formation of spherical tokamak plasmas

Axial merging of two torus plasmas is utilized as a center-solenoid free start-up scheme for a high-beta spherical tokamak (ST) plasma, in which magnetic reconnection under a strong guide field plays dominant roles in energy conversion and equilibrium formation. The ion heating source in magnetic reconnection is the plasma outflow with E×B drift velocity in the downstream region where the reconnected field lines flow out. Since the inductive reconnection electric field is almost parallel to the magnetic field, particularly in the inboard-side downstream region of magnetic reconnection under a strong guide field, a large electrostatic field in the poloidal plane is spontaneously formed to sustain steady plasma outflow motion in the downstream region. In ST plasma merging experiments, the self-generated electrostatic field in the downstream region does not always balance with the inductive electric field to make the total electric field strictly perpendicular to the total magnetic field. The excess electrostatic field will provide an even faster outflow plasma velocity than the magnetic field line motion and a quick reversal of the toroidal plasma current to form convex flux surfaces.

FP-LAPW calculations of the structural, and optoelectronic properties of vanadium silicide compound for optoelectronic applications

Optoelectronic devices play an essential part in our daily lives by seamlessly integrating optics and electronics, leading to technologies such as smartphones, solar cells, and optical communication. In this study, the structural and optoelectronic characteristics of the hexagonal vanadium silicide are determined using the density functional theory (DFT). The structural parameters such as the zero-pressure bulk modulus B0, its pressure derivative B0′; equilibrium energy, and the volume of the primitive cell at equilibrium V0 are compared with experiment results. The metallic character of VSi2 is confirmed by calculating the density of states and band structure. Moreover, the optical properties like the dielectric function, reflectivity, energy loss function, refractive index, absorption coefficient, and optical conductivity are studied deeply, using the Drude model, within the energy interval from 0 to 14 eV and they are compared with experiment results of a polycrystalline and single crystal. However, the phonon dispersion spectrum shows the presence of imaginary modes, which indicates instability in the structure of vanadium silicide. The results indicate that the VSi2 material has the potential to be used in many applications, including mirrors, glass coatings, optoelectronic devices, optical networks, electronics, optical communications, and waveguide components.

Impact of boron substitution on the thermoelectric, mechanical stability, electronic and optical properties of InP alloys

Density Functional Theory (DFT) calculations, utilizing the full potential linearized augmented plane wave (FP-LAPW) method, were performed to investigate the effect of boron (B) substitution on the InP system through GGA and mBJ-GGA formalisms, aiming to improve its band gap energy. Lattice equilibrium optimization determined that the stable structure of the alloys at equilibrium energy shows a decrease in lattice constants with increasing boron concentration (x). The calculated formation enthalpies, which are negative, indicate that these systems are experimentally synthesizable. The elastic analysis confirms that the doped alloys are elastically stable and exhibit ductile properties. The optical parameter analysis reveals that the optical energy loss functions are minimal or zero in the infrared, visible, and ultraviolet ranges, suggesting their suitability for optical applications across these energy ranges. Specifically, the band gaps were found to range from 0.878 eV for x = 0.25–1.920 eV for x = 0.75 using the mBJ-GGA formalism. Furthermore, the role of B-doping in the InP system for thermoelectric technology was systematically investigated, revealing that our alloys possess good thermoelectric properties with a figure of merit (ZT) reaching up to 0.7 for x = 0.75. These results demonstrate that accurate tuning of the energy band gap through doping is an effective technique for discovering novel materials suitable for both thermoelectric and optoelectronic applications.

A direct FE2 method for concurrent multilevel modeling of a coupled thermoelectric problem – Joule heating effect – in multiscale materials and structures

Coupled thermoelectric problem significantly affects the performance of electric devices, while there seems to be no method for concurrent multiscale modeling of such problems, which significantly limits the development of advanced electric devices consisting of multiscale structures. To this end, a Direct FE2 (D-FE2) method is proposed for concurrent multiscale modeling of a typical type of coupled thermoelectric problems, i.e., Joule heating effect, in heterogeneous materials and structures. To enforce energy equilibrium and realize information transfer between the macro- and meso‑scales, the Hill-Mandel homogenization condition was generalized to account for both thermal and electric energy, while periodic boundary conditions derived from kinematic constraints were prescribed to both electric potential and temperature to link meso‑scale RVEs to macro-elements in the D-FE2 model. The proposed D-FE2 method can be easily implemented using the available feature “Multiple Points Constraint (MPC)” in many commercial FE software. A series of numerical examples including steady-state analysis and transient analysis of fiber composites, porous materials and lattice structures validate the favorable accuracy and efficiency of the proposed D-FE2 method in modeling the Joule heating phenomenon in multiscale materials and structures. This also implies the promising potential of the proposed D-FE2 method in modeling and design of large-scale electric devices with multiscale structures.

Novel perspectives on autophagy-oxidative stress-inflammation axis in the orchestration of adipogenesis.

Adipose tissue, an indispensable organ, fulfils the pivotal role of energy storage and metabolism and is instrumental in maintaining the dynamic equilibrium of energy and health of the organism. Adipocyte hypertrophy and adipocyte hyperplasia (adipogenesis) are the two primary mechanisms of fat deposition. Mature adipocytes are obtained by differentiating mesenchymal stem cells into preadipocytes and redifferentiation. However, the mechanisms orchestrating adipogenesis remain unclear. Autophagy, an alternative cell death pathway that sustains intracellular energy homeostasis through the degradation of cellular components, is implicated in regulating adipogenesis. Furthermore, adipose tissue functions as an endocrine organ, producing various cytokines, and certain inflammatory factors, in turn, modulate autophagy and adipogenesis. Additionally, autophagy influences intracellular redox homeostasis by regulating reactive oxygen species, which play pivotal roles in adipogenesis. There is a growing interest in exploring the involvement of autophagy, inflammation, and oxidative stress in adipogenesis. The present manuscript reviews the impact of autophagy, oxidative stress, and inflammation on the regulation of adipogenesis and, for the first time, discusses their interactions during adipogenesis. An integrated analysis of the role of autophagy, inflammation and oxidative stress will contribute to elucidating the mechanisms of adipogenesis and expediting the exploration of molecular targets for treating obesity-related metabolic disorders.

Structural characterization and keto-enol tautomerization of 4-substituted pyrazolone derivatives with DFT approach

The synthesis of two pyrazolone derivative compounds, PYR-I(4-Acetyl-1-(4-chlorophenyl)-3-isopropyl-1H-pyrazol-5(4H)-one) and PYR-II1-(4-Chlorophenyl))-3-isopropyl-5-oxo-4,5-5-dihydro-1H-pyrazole-4-carbaldehyde, their characterization by FT-IR, NMR, UV–Vis and GC-MS techniques, and the evaluation of the keto-enol tautomerization process of the structures along with the DFT approach and spectral data were reported in this paper. Spectral findings indicated that PYR-I was stable at the keto state. The IR spectrum recorded in solid form showed that the PYR-II structure was stable in the enol state, while the NMR spectrum in the solution medium showed that it was stable in the keto state. DFT-based analyses were realized with the B3LYP hybrid functional and the 6–311++G(d,p) basis set. The modelled keto, transition and enol state molecular geometries of structures were optimized in the gas phase and different solvent media and the total energy and dipole moment values were investigated at the specified theoretical level. The possible keto-enol tautomerism mechanism of the structures was evaluated through some thermodynamic parameters such as the difference in free Gibbs energy (ΔG), enthalpy (ΔH), entropy (ΔS), and predictive tautomeric equilibrium constants (Keq), acidity constants (pKa) and percentages of tautomers at 298.15 K and 1 atm pressure. The results of these analyses based on the DFT approach indicated that the keto-enol tautomer equilibrium heavily favours the keto form for PYR-I and the enol form for PYR-II in all cases. Moreover, natural bond orbital (NBO) analysis was performed for the tautomers, and the chemical reactivity profiles of the most stable tautomers were examined with the values of frontier molecular orbital energy and some reactivity descriptors.