Entropy Variation Research Articles

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

Radiomic Gradient in Peritumoural Tissue of Liver Metastases: A Biomarker for Clinical Practice? Analysing Density, Entropy, and Uniformity Variations with Distance from the Tumour.

The radiomic analysis of the tissue surrounding colorectal liver metastases (CRLM) enhances the prediction accuracy of pathology data and survival. We explored the variation of the textural features in the peritumoural tissue as the distance from CRLM increases. We considered patients with hypodense CRLMs >10 mm and high-quality computed tomography (CT). In the portal phase, we segmented (1) the tumour, (2) a series of concentric rims at a progressively increasing distance from CRLM (from one to ten millimetres), and (3) a cylinder of normal parenchyma (Liver-VOI). Sixty-three CRLMs in 51 patients were analysed. Median peritumoural HU values were similar to Liver-VOI, except for the first millimetre around the CRLM. Entropy progressively decreased (from 3.11 of CRLM to 2.54 of Liver-VOI), while uniformity increased (from 0.135 to 0.199, p < 0.001). At 10 mm from CRLM, entropy was similar to the Liver-VOI in 62% of cases and uniformity in 46%. In small CRLMs (≤30 mm) and responders to chemotherapy, normalisation of entropy and uniformity values occurred in a higher proportion of cases and at a shorter distance. The radiomic analysis of the parenchyma surrounding CRLMs unveiled a wide halo of progressively decreasing entropy and increasing uniformity despite a normal radiological aspect. Underlying pathology data should be investigated.

Slow pyrolysis of Agave americana L. fibers: Analysis of kinetics and thermodynamics using the coats-redfern method at different heating rates

This study employed thermogravimetric analysis (TGA) alongside the Coats-Redfern method (CRM) to investigate the thermal degradation's kinetics and thermodynamics of fibers extracted from the flower stalk of Agave americana (FSAA). We explored FSAA fibers' thermal behavior across varying heating rates (HRs) to elucidate complex reaction mechanisms and estimate critical parameters. TGA experiments at 5, 10, and 20 °C/min HRs reveal a multi-step breakdown process supported by solid coefficients of determination (R2 > 0.99). Activation energy values, ranging from 83.6 to 210.1 kJ/mol, vary with HR, providing insights into thermal decomposition kinetics. Thermodynamic parameters, including variations in entropy (ΔS), Gibb's free energy, and enthalpy, shed light on spontaneity and energy transfer during the process. Negative ΔS values suggested reduced disorder during thermal decomposition. This study represented a novel investigation into the thermal behavior of fibers extracted from the FSAA for the first time, using CRM in conjunction with TGA. Through comprehensive analysis, we elucidated the kinetics and thermodynamics of FSAA fiber degradation across various HRs. Our findings shed light on the intricate reaction mechanisms underlying FSAA fiber decomposition, providing valuable insights for potential applications in biofuel production and composite materials.

Pressure-induced semiconductor to metal transition and its impact on the electronic, optical, and thermodynamic properties of the new Kitaev spin liquid candidate CoI2

We investigate the recently identified Kitaev candidate, the unconventional two-dimensional (2D) crystalline material van der Waals CoI2. Our approach involves employing ab-initio calculations to study the effects of applied pressure on its physical properties. CoI2 was found to be a semiconductor with a band gap energy of 2.1 eV. By applying pressure up to 13 GPa, a transition from a semiconductor to a metallic state takes place. This transition was explained by the displacement of the initially filled 5p-iodide band, overlapping with partially filled Co-3d states, leading to the formation of a hybridized conduction band and the emergence of a metallic ground state. Furthermore, by subjecting the CoI2 to pressure, a significant increase of the optical conductivity from 9900 to 11600 (Ω cm)−1, and the refractive index increases from 2.75 to 3.5. Our thermodynamic calculations reveal a captivating tale of CoI2; detecting a peak at 55 K in the temperature-normalized heat capacity which suggests the presence of entropy variation in the material, indicating a shift in the spin configuration within CoI2. In addition, a low thermal conductivity (ranging from 5 to 0.1 W m−1 K−1) underscores the strong interactions among quantum spins.

Analysis of a new three-dimensional jerk chaotic system with transient chaos and its adaptive backstepping synchronous control

A new three-dimensional Jerk chaotic system with line equilibrium points is proposed. The system is researched in detail by the Lyapunov exponent graph, bifurcation diagram, phase diagram, and time domain waveform diagram, which show that the system has rich dynamical behaviors, such as eight types of coexisting attractors, extreme multistability of four different attractor states, and offset boosting in two directions. In addition, the system also has six types of transient chaos, which greatly increase the complexity of the system. We study the variation of the spectral entropy (SE) and C0 complexity when the system takes different initial values. Also, in this paper, the initial conditions under which the system is in a synchronized state are determined by initial values with higher complexity. The correctness of the theoretical analysis and numerical simulation is verified by circuit simulation and hardware experiments. Finally, the new system achieves synchronization control utilizing a designed adaptive backstepping controller, laying the foundation for its subsequent use in secure communications.

On the Supposed Mass of Entropy and That of Information.

In the theory of special relativity, energy can be found in two forms: kinetic energy and rest mass. The potential energy of a body is actually stored in the form of rest mass, the interaction energy too, but temperature is not. Information acquired about a dynamical system can be potentially used to extract useful work from it. Hence, the "mass-energy-information equivalence principle" that has been recently proposed. In this paper, it is first recalled that for a thermodynamic system made of non-interacting entities at constant temperature, the internal energy is also constant. So, the energy involved in a variation in entropy (TΔS) differs from a change in the potential energy stored or released and cannot be associated to a corresponding variation in mass of the system, even if it is expressed in terms of the quantity of information. This debate gives us the opportunity to deepen the notion of entropy seen as a quantity of information, to highlight the difference between logical irreversibility (a state-dependent property) and thermodynamical irreversibility (a path-dependent property), and to return to the nature of the link between energy and information that is dynamical.

Performance analysis of indirect contact heat pipe radiator for space nuclear power system

The heat pipe radiator, with excellent thermal conductivity and anti-collision performance, is expected very suitable for heat emission in nuclear-power spacecraft. Indirect contact heat pipe radiator could operate longer life with lower capital cost. In this paper, the fluid-solid coupling heat transfer method is integrated to solve the energy model and S–S radiation model based on the k-epsilon model. Optimization objectives, heat dissipation performance and temperature uniformity are adopted to optimize the radiator structure. A comparison analysis between the ordinary and optimized radiator is conducted based on energy and entropy variation. The results show that the temperature uniformity and heat dissipation characteristic of the radiator after the optimization of connection mode of heat pipe and coolant pipe, fin shape, and fins welding direction have been improved without changing the area of fins and the weight of radiator. Through the comparative of radiators after changing the working conditions, some useful conclusions are drawn, which provide the theoretical foundation for the experimental research and engineering practice.

Exploration of structural, magnetic, and magnetocaloric characteristics of double perovskites HoRCoMnO6 (R=Ho, Gd, Eu or Nd)

A conventional solid-state process was used to synthesize the double perovskite materials HoRCoMnO6 (R=Ho, Gd, Eu, Nd). The structural properties of the compounds were investigated using X-ray powder diffraction (XRD). The results revealed that Ho₂CoMnO₆ crystallizes in a monoclinic structure with the P21/n space group. In contrast, the other compounds HoRCoMnO6 (R=Gd, Eu, or Nd) exhibit an orthorhombic structure with the Pnma space group. As a result, the average crystallite size also changes as a function of rare-earth element doping. This investigation reveals that the magnetic properties of the compounds studied are significantly dependent on the doping elements. The Curie temperature TC, for example, increases from 80 to 118 °C with the ionic radii of rare earths increasing. Furthermore, the study of the magnetocaloric effect (MCE) shows that the maximum of the entropy variation (−ΔSMmax) increases from 4.97 to 6.06 J/(kg∙K) under a magnetic field of 5 T with substitution by rare-earth ions. To examine the efficiency of MCE materials, the relative cooling power (RCP) was evaluated and is found to increase with increment of rare-earth radius till 406.69 J/kg for Nd. The mean entropy variation with temperature (TEC) was also studied. Due to their significant magnetocaloric performance, HoRCoMnO6 (noted as HRCMO) compounds (with R=Ho, Gd, Eu or Nd) could be good candidates for low-temperature magnetic cooling applications

Small-scale variation of atmospheric dynamics applying chaos theory, case study

Characterization and knowledge of the variability of atmospheric dynamics on a small scale in the city of Riobamba, Ecuador, are achieved through the chaos theory. Meteorological data is taken every hour during four years, including variables such as wind speed, wind direction, incident radiation, temperature, and humidity, from the ESPOCH, SAN JUAN, and QUIMIAG weather stations in the canton of Riobamba. The van Ulden and Hostlang models are used to calculate the Obukhov length, surface heat fluxes, and latent heat flux. The chaos theory is applied to study the variation of atmospheric microdynamics. The Lyapunov coefficients, Kolmogorov-Sinai entropy, and Kaplan-Yorke fractal dimension are determined. Before analysis, noise reduction is necessary due to the lack of correlation, especially in the Obukhov length. This research follows a longitudinal design and employs quantitative and explanatory methods based on data analysis, statistical-mathematical techniques, and inductive-deductive approaches. The results indicate a highly variable system, reflected in a high number of Lyapunov coefficients, fractional dimensions, and entropy variations. The microdynamic parameters exhibit hyperchaotic behavior, as indicated by the presence of more than one positive Lyapunov coefficient. The variables also demonstrate a fractional fractal dimension, highlighting the irregularity in the geometric representation of the system.

First-principles study on hydrogen storage properties of the new hydride perovskite XAlH3 (X=Na, K)

First-principles were employed to research the hydrogen storage capacities and structure, mechanic, electronic, optical, dynamical, thermodynamic properties of XAlH3 (X = Na, K) compounds. The investigation of elastic constants, formation energy and phonon dispersion curve reveals that the XAlH3 compounds possesses mechanical, thermodynamic and dynamic stability. By calculating the B/G, it is evident that NaAlH3 has ductility and KAlH3 has brittleness. Moreover, the chemical bonding of XAlH3 compounds is ionic. According to the results obtained from the electronic property analysis, these compounds are metal nature. Additionally, the internal charge transfer of the two compounds was studied by Bader partial charge analysis. The optical properties show that the NaAlH3 hydride has higher static dielectric function than that of KAlH3. The thermodynamic properties of these hydrides have been studied, including energy, heat capacity, free energy, and the entropy variation with temperature. Furthermore, NaAlH3 and KAlH3 have high hydrogen storage capacities, which are 5.40 wt% and 4.19 wt%, respectively. This study has revealed for the first time the characteristics of XAlH3 hydrides, bringing new potential options for hydrogen storage materials.

Life as the Explanation of the Measurement Problem

This study argues that a biological cell, a dissipative structure, is the smallest agent capable of processing quantum information through its triangulated, holographic sphere of perception, where this mechanism has been extended by natural evolution to endo and exosemiosis in multicellular organisms and further to the language of Homo sapiens. Thus, life explains the measurement problem of quantum theory within the framework of the holographic principle, emergent gravity, and emergent dimensionality. Each Planck triangle on a black hole surface corresponds to a qubit in an equal superposition, attaining known bounds on the products of its energies and orthogonalization interval. Black holes generate entropy variation shells through the solid-angle correspondence. The entropic work introduces the bounds on the number of active Planck triangles dependent on the information capacity of the black hole generator. The velocity and dissipativity bounds and the bounds on the theoretical probabilities for active, energy-carrying Planck triangles were derived. In particular, this study shows that black holes, Turing machines, and viruses cannot assume the role of an observer. The entropy variation shells and black-body objects may hint at solutions to ball lightning and sonoluminescence unexplained physical spherical phenomena.“It is also possible that we learned that the principal problem is no longer the fight with the adversities of nature but the difficulty of understanding ourselves if we want to survive” [1].

Variance of entropy for testing time-varying regimes with an application to meme stocks

Shannon entropy is the most common metric for assessing the degree of randomness of time series in many fields, ranging from physics and finance to medicine and biology. Real-world systems are typically non-stationary, leading to entropy values fluctuating over time. This paper proposes a hypothesis testing procedure to test the null hypothesis of constant Shannon entropy in time series data. The alternative hypothesis is a significant variation in entropy between successive periods. To this end, we derive an unbiased sample entropy variance, accurate up to the order O(n-4)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(n^{-4})$$\\end{document} with n the sample size. To characterize the variance of the sample entropy, we first provide explicit formulas for the central moments of both binomial and multinomial distributions describing the distribution of the sample entropy. Second, we identify the optimal rolling window length to estimate time-varying Shannon entropy. We optimize this choice using a novel self-consistent criterion based on counting significant entropy variations over time. We corroborate our findings using the novel methodology to assess time-varying regimes of entropy for stock price dynamics by presenting a comparative analysis between meme and IT stocks in 2020 and 2021. We show that low entropy values correspond to periods when profitable trading strategies can be devised starting from the symbolic dynamics used for entropy computation, namely periods of market inefficiency.

The impact of chemical properties of the solid-liquid-adsorbate interfaces on the entropy-enthalpy compensation involved in adsorption.

Despite extensive studies on the thermodynamic mechanism governing molecular adsorption at the solid-water interface, a comprehensive understanding of the crucial role of interface properties in mediating the entropy-enthalpy compensation during adsorption is lacking, particularly at a quantitative level. Herein, we employed two types of surface models (hydroxyapatite and graphene) along with a series of amino acids to successfully elucidate how distinct interfacial features dictate the delicate balance between entropy and enthalpy variations. The adsorption of all amino acids on the hydroxyapatite surface is an enthalpy-dominated process, where the water-induced enthalpic component of the free energy and the surface-adsorbate electrostatic interaction term alternatively act as the driving force for adsorption in different regions of the surface. Although favorable interactions are observed between amino acids and the graphene surface, the entropy-enthalpy compensation exhibits dependence on the molecular size of the adsorbates. For small amino acids, favorable enthalpy changes predominantly determine their adsorption behavior; however, larger amino acids tend to bind more tightly with the graphene surface, which is thermodynamically dominated by the entropy variations despite the structural characteristics of amino acids. This study reveals specific entropy-enthalpy mechanisms underlying amino acid adsorption at the solid-liquid interface, providing guidance for surface design and synthesis of new biomolecules.

A combination weighting method for debris flow risk assessment based on t-distribution and linear programming optimization algorithm.

Debris flow risk assessment can provide some reference for debris flow prevention and control projects. In risk assessment, researchers often only focus on the impact of objective or subjective indicators. For this purpose, this paper proposed a weight calculation method based on t-distribution and linear programming optimization algorithm (LPOA). Taking 72 mudslides in Beichuan County as an example, this paper used analytic hierarchy process (AHP), entropy weight method (EWM) and variation coefficient method (VCM) to obtain the initial weights. Based on the initial weights, weight intervals with different confidence levels were obtained by t-distribution. Subsequently, the final weights were obtained by LOPA in the 90% confidence interval. Finally, the final weights were used to calculate the risk score for each debris flow, thus delineating the level of risk for each debris flow. The results showed that this paper's method can avoid overemphasizing the importance of a particular indicator compared to EWM and VCM. In contrast, EWM and VCM ignored the effect of debris flow frequency on debris flow risk. The assessment results showed that the 72 debris flows in Beichuan County were mainly dominated by moderate and light risks. Of these, there were 8 high risk debris flows, 24 medium risk debris flows, and 40 light risk debris flows. The excellent triggering conditions provide favorable conditions for the formation of high-risk debris flows. Slightly and moderate risk debris flows are mainly located on both sides of highways and rivers, still posing a minor threat to Beichuan County. The proposed fusion weighting method effectively avoids the limitations of single weight calculating method. Through comparison and data analysis, the rationality of the proposed method is verified, which can provide some reference for combination weighting method and debris flow risk assessment.

An evaluation of quality of college student training based on combination of entropy weight and variation coefficient weights

An evaluation of quality of college student training based on combination of entropy weight and variation coefficient weights

Advancing humidity sensing and magnetocaloric properties of spinel structural CoCr2O4 nanoparticles achieved via innovative bismuth doping by combustion synthesis

This study explores the influence of Bi-doping on Co1-xBixCr2O4 (x = 0–0.2) nanoparticles synthesized via the solution combustion method, focusing on humidity sensing and magnetocaloric effects. The investigation reveals two magnetic transitions: the Curie temperature (TC) marks the paramagnetic to ferrimagnetic shift, while the spiral transition temperature (TS) indicates a spiral spin order transition. Magnetization measurements demonstrate that −ΔSM and relative cooling power (RCP) values vary with Bi concentration, making these nanoparticles viable for magnetic refrigeration above liquid nitrogen temperatures. Analyzing magnetic entropy variation, the modified Arrott plots and Kouvel-Fisher approach affirm second-order phase transitions. The sensing response exhibits growth alongside relative humidity (RH) and Bi concentration, culminating in an impressive ∼97.56 % sensing response for the 20 % Bi-doped sample. This heightened humidity sensing performance with increased Bi content can be attributed to synergistic effects. These results highlight the potential of 20 % Bi-doped Co1-xBixCr2O4 nanoparticles as promising contenders for enduring and practical humidity sensing applications.

Fast Estimation of Entropy Profiles for Lithium-Ion Batteries

The operating temperature of a lithium-ion battery (LIB) has strong effects on its electrochemical performance, safety, and lifetime. Reliable predictions of cell temperature and heat generation are required for the design and thermal management of battery systems. During the normal operation of LIBs, heat sources can be classified into irreversible heat from resistive losses such as ohmic resistance, charge-transfer overpotentials, and mass-transfer limitations; and reversible heat from entropy change . The irreversible heat generation is related to the cell's internal resistance and the applied current. The reversible heat depends on the entropy variation of electrode materials, the state of charge (SoC), and the temperature. An accurate measurement of entropy-variation will not only help to improve the battery operation under optimal thermal conditions but can also be used to diagnose the battery aging since it can reveal crystal structure changes in the electrodes [1, 2].Techniques for measuring the entropy of a battery can mainly be classified into potentiometric [3] and calorimetric methods. The potentiometric method measures the open circuit voltage (OCV) changes while the cell temperature is varied at different SoCs. This method requires a long relaxation time to obtain the OCV equilibrium state following each SoC point and temperature step. The calorimetric method [4-6] is based on measuring the heat generation during charge and discharge, and various models are applied to differentiate between and quantify the reversible and irreversible heat sources. The entropy variation with SOC is obtained via the reversible heat rate.Recent improved methods include e.g., Schmidt et al. [4] who proposed a reversible heat extraction method based on electrothermal impedance spectroscopy (ETIS) and Damay et al. [5] proposing a fast calorimetric method to obtain a continuous entropy profile. The cell surface temperature is monitored while the battery is charged and discharged continuously. A thermal balance is used to estimate the heat generation from the monitored cell temperature changes during charge and discharge. The benefit of this method can be low cost, fast and high resolution. Bedürftig et al. [6] proposed a calorimetric method named ‘Double Pulse Method’ to measure reversible heat in lithium-ion battery cells by exciting the cell with charge and discharge current pulses.Here we present a new entropy characterization method via charge and discharge cycles of a LIB at low constant C-rates using simple insulating condition. Through monitoring the variations of cell surface temperature and voltage with the state of charge, the continuous variation of entropy with the state of charge can be extracted. These results were compared to classical entropy measurements obtained through the potentiometric method as shown in Figure 1. In addition, the extracted entropy variation data is input into a LIB modelling approach, combining a P2D-electrochemical sub-model for battery operation and a 3D-finite-element sub-model for thermal behavior while battery charge and discharge. The model predictions on the cell outer surface temperature variation while charge and discharge under different C-rates are compared with the data obtained in the battery characterization tests as shown in Figure 2. Good agreements between the model predictions and tests are achieved.

3D Electrothermal Model for Internal Temperature Distribution in Lithium-Ion Battery Cell and Module

In recent years, lithium-ion batteries (LIBs) have been massively developed in many applications as they provide high energy and power densities, high efficiency and long lifespan compared to other battery technologies. Despite remarkable improvements, Li-ion batteries still face thermal issues, which cause performance drop, limited calendar life, safety concerns and temperature-caused degradation. Therefore, proper thermal management for a LIB is necessary to control its temperature and to extend its lifetime. Internal temperature measurement remains very challenging for LIB. So, electrothermal LIB models, developed to forecast both electrical performances and temperature distributions, seems to be a powerful and complementary tool to experiments, in particular to obtain battery temperatures in use. Most of models, assume simplified approach considering that heat sources are either located in the center of the cell or uniformly distributed in the volume of the cell and so do not consider the real internal geometry of the cells.In this work, a 3D electrothermal model of a large commercial prismatic NMC-type lithium-ion cell (25 Ah) is developed based on the internal geometry reconstructed from tomography. The electrothermal model, developed with the COMSOL Multiphysics® software with the real internal geometry as well as the anisotropy of the thermal properties, accounts for irreversible and reversible heat sources. The entropy variation profiles were estimated by Entroview™ using their patented method. The validation of the model is performed thank to temperature measurement during charge and discharge at several currents in a climatic chamber at 25°C. Simulation results highlight exothermal and endothermal behaviors related to the entropy change along with the charge and discharge stages. Moreover, the internal temperature distribution is thoroughly impacted by the internal geometry of the cell and the anisotropy of the thermal properties.Finally, the 3D electrothermal model is extended to a module of 12 cells in series (12S) to evaluate the heterogeneities of internal temperatures considering the real geometry of each cell. Once validated, simulation (as shown of figure 1) underline the heterogeneous temperature distribution at the module scale and the importance of having an efficient battery thermal management system to limit an excessive increase of the temperatures which can cause performance drops until irreversible degradations. Figure 1

Assessment of heat and entropy balance of an OWC wave energy converter

This paper deals with the thermodynamic processes governing an Oscillating Water Column (OWC) device, focusing on the entropy variation and the energy and heat budgets over the expansion–compression cycles. The influence of the thermodynamic performance on the Levelized Cost of Energy (LCOE) and the carbon footprint is analysed. The research deals with an experimental research on a simple OWC off-shore model for the purpose, with the open gas system inside the chamber formulated by a real gas model, and conceptually represented by an equivalent closed one in order to apply the First Principle of Thermodynamics appropriately. Analysed results show that the compression process is an active process, while the expansion process is a passive one. In addition, the observed non-adiabatic performance of the complete cycle implies a efficiency reduction, with consequences on the LCOE. Furthermore, an approach to emergy (embodied energy) analysis is considered, providing with concluding remarks on OWC renewability and possible impacts on the biosphere and GHG emissions. An utter approach on OWC energy and emergy assessment will be develop on future researches.

Entropy-Enthalpy Compensation in Ti-V-Mn-Cr BCC Alloys Used as Hydrogen Storage Materials

In this paper, we report the effect of the Cr/Mn ratio on the thermodynamic properties of Ti30V60Mn(10−x)Crx (x = 0, 3.3, 6.6 and 10) + 4 wt.% Zr alloys. It was found that the enthalpy and entropy change with the Cr/MN ratio and that the entropy and entropy variation is coupled in an enthalpy-entropy compensation fashion. Using a compensation quality factor, it was established that the enthalpy-entropy compensation is not due to a statistical origin, with a confidence of more than 95%.