Search Results (38)

1,3-Diphenylisobenzofuran (DPBF) is a widely used fluorescent probe for singlet oxygen (¹O₂) detection in photodynamic applications. In this work, we present an integrated experimental and computational analysis to describe its spectroscopic, photophysical, and reactive properties in ethanol, DMSO, and DMF. UV-Vis and fluorescence measurements across a wide concentration range show well-resolved S₀ → S₁ electronic transition of a π → π* nature with small red shifts in polar aprotic solvents. Fluorescence lifetimes increase slightly with solvent polarity, showing stabilization of the excited state. The 2D PES and Boltzmann populations analysis indicate two co-existing conformers (C_s and C₂), with C_s being slightly more stable at room temperature. TD-DFT calculations have been performed using several density functionals and the 6-311+G(2d,p) basis set to calculate absorption/emission wavelengths, oscillator strengths, transition dipole moments, and radiative lifetimes. Overall, cam-B3LYP and ωB97X-D provided the best agreement with experiments for the photophysical data across all solvents. The photophysical behavior of DPBF upon interaction with ¹O₂ can be explained by a small-barrier, two-step reaction pathway that goes through a zwitterionic intermediate, resulting in the formation of 2,5-endoperoxide. This work explains the photophysical properties and reactivity of DPBF, therefore providing a solid basis for future studies involving singlet oxygen. Full article

The thermal Doppler broadening of spectral profiles for particle populations in the absence or presence of potential fields can be described by kappa distributions. The kappa distribution provides a replacement for the Maxwell–Boltzmann distribution, which can be considered as a generalization for describing systems characterized by local correlations among their particles, as found in space and astrophysical plasmas. This paper presents all special cases of kappa distributions as members of a general pathway family of densities introduced by Mathai. The aim of the present paper is to bring to attention the application of various forms of the kappa distribution, its various special cases and its generalizations, which, in scalar-variable and multivariate situations, belong to a general family of distributions known as Mathai’s pathway models, comprising three different families of functions, namely the generalized type-1 beta, type-2 beta and gamma families. Through one parameter, known as the pathway parameter, one will be able to reach all the three families of functions and the stages of transitioning from one family to another. After pointing out the connection of multivariate (vector-variate) kappa distributions to the multivariate pathway model, the multivariate kappa distribution is extended to the real matrix-variate case by working out the various forms and by evaluating the normalizing constants of the various forms of the matrix-variate case explicitly. It is also pointed out that the pathway models are available for the scalar, vector and rectangular matrix-variate cases in the real domain as well as in the complex domain. Full article

We extend the 3D Lattice Boltzmann method with a deformable boundary (LBM-DB) for the computations of the full-volume colonic flow of the Newtonian fluid driven by the peristaltic segmented circular contractions which obey the three-step “intestinal law”: (i) deflation, (ii) inflation, and (iii) elastic relaxation. The key point is that the LBM-DB accurately prescribes a curved deforming surface on the regular computational grid through precise and compact Dirichlet velocity schemes, without the need to recover for an adaptive boundary mesh or surface remesh, and without constraint of fluid volume conservation. The population “refill” of “fresh” fluid nodes, including sharp corners, is reformulated with the improved reconstruction algorithms by combining bulk and advanced boundary LBM steps with a local sub-iterative collision update. The efficient parallel LBM-DB simulations in silico then extend the physical experiments performed in vitro on the Dynamic Colon Model (DCM, 2020) to highly occlusive contractile waves. The motility scenarios are modeled both in a cylindrical tube and in a new geometry of “parabolic” transverse shape, which mimics the dynamics of realistic triangular lumen aperture. We examine the role of cross-sectional shape, motility pattern, occlusion scenario, peristaltic wave speed, elasticity effect, kinematic viscosity, inlet/outlet conditions and numerical compressibility on the temporal localization of pressure and velocity oscillations, and especially the ratio of retrograde vs antegrade velocity amplitudes, in relation to the major contractile events. The developed numerical approach could contribute to a better understanding of the intestinal physiology and pathology due to a possibility of its straightforward extension to the non-Newtonian chyme rheology and anatomical geometry. Full article

The kinetics of the F₂ reaction with thiirane (C₂H₄S) was studied for the first time in a flow reactor combined with mass spectrometry at a total helium pressure of 2 Torr and in the temperature range of 220 to 800 K. The rate constant of the title reaction was determined under pseudo-first-order conditions, either monitoring the kinetics of F₂ or C₂H₄S consumption in excess of thiirane or of F₂, respectively: k₁ = (5.79 ± 0.17) × 10⁻¹² exp(−(16 ± 10)/T) cm³ molecule⁻¹ s⁻¹ (the uncertainties represent precision of the fit at the 2σ level, with the total 2σ relative uncertainty, including statistical and systematic errors on the rate constant being 15% at all temperatures). HF and CH₂CHSF were identified as primary products of the title reaction. The yield of HF was measured to be 100% (with an accuracy of 10%) across the entire temperature range of the study. Quantum computations revealed reaction enthalpies ranging from −409.9 to −509.1 kJ mol⁻¹ for all the isomers/conformers of the products, indicating a strong exothermicity. Boltzmann relative populations were then established for different temperatures. Full article

The first step in comprehending the properties of Au₁₀ clusters is understanding the lowest energy structure at low and high temperatures. Functional materials operate at finite temperatures; however, energy computations employing density functional theory (DFT) methodology are typically carried out at zero temperature, leaving many properties unexplored. This study explored the potential and free energy surface of the neutral Au₁₀ nanocluster at a finite temperature, employing a genetic algorithm coupled with DFT and nanothermodynamics. Furthermore, we computed the thermal population and infrared Boltzmann spectrum at a finite temperature and compared it with the validated experimental data. Moreover, we performed the chemical bonding analysis using the quantum theory of atoms in molecules (QTAIM) approach and the adaptive natural density partitioning method (AdNDP) to shed light on the bonding of Au atoms in the low-energy structures. In the calculations, we take into consideration the relativistic effects through the zero-order regular approximation (ZORA), the dispersion through Grimme’s dispersion with Becke–Johnson damping (D3BJ), and we employed nanothermodynamics to consider temperature contributions. Small Au clusters prefer the planar shape, and the transition from 2D to 3D could take place at atomic clusters consisting of ten atoms, which could be affected by temperature, relativistic effects, and dispersion. We analyzed the energetic ordering of structures calculated using DFT with ZORA and single-point energy calculation employing the DLPNO-CCSD(T) methodology. Our findings indicate that the planar lowest energy structure computed with DFT is not the lowest energy structure computed at the DLPN0-CCSD(T) level of theory. The computed thermal population indicates that the 2D elongated hexagon configuration strongly dominates at a temperature range of 50–800 K. Based on the thermal population, at a temperature of 100 K, the computed IR Boltzmann spectrum agrees with the experimental IR spectrum. The chemical bonding analysis on the lowest energy structure indicates that the cluster bond is due only to the electrons of the 6 s orbital, and the Au d orbitals do not participate in the bonding of this system. Full article

Since its inception, evolution theory has garnered much attention from the scientific community for a good reason: it theorizes how various living organisms came to be and what changes are to be expected in a certain environment. While many models of evolution have been proposed to track changes in species’ traits, not much has been said about how to calculate or estimate these traits. In this paper, using information theory, we propose an estimation method for trait parameters in a Darwinian evolution model for species with one or multiple traits. We propose estimating parameters by minimizing the relative information in a Darwinian evolution population model using either a classical gradient ascent or a stochastic gradient ascent. The proposed procedure is shown to be possible in a supervised or unsupervised learning environment, similarly to what occurs with Boltzmann machines. Simulations are provided to illustrate the method. Full article

A very important class of models widely used nowadays to describe and predict, at least in stochastic terms, the behavior of many-particle systems (where the word “particle” is not meant in the purely mechanical sense: particles can be cells of a living tissue, or cars in a traffic flow, or even members of an animal or human population) is the Kinetic Theory for Active Particles, i.e., a scheme of possible generalizations and re-interpretations of the Boltzmann equation. Now, though in the literature on the subject this point is systematically disregarded, this scheme is based on Markov Chains, which are special stochastic processes with important properties they share with many natural processes. This circumstance is here carefully discussed not only to suggest the different ways in which Markov Chains can intervene in equations describing the stochastic behavior of any many-particle system, but also, as a preliminary methodological step, to point out the way in which the notion of a Markov Chain can be suitably generalized to this aim. As a final result of the discussion, we find how to develop new very plausible and likely ways to take into account possible effects of the external world on a non-isolated many-particle system, with particular attention paid to socio-economic problems. Full article

Optical rotation (OR), the most frequently used chiroptical method, is used for the characterization of newly synthesized or isolated compounds. Computational predictions of OR are, however, mainly used for the determination of the absolute configurations of chiral compounds, but they may also be used for the verification of conformational analysis results if the experimental values are known. Our computational study deals with the conformational analysis of flexible salicylamide-based peptidomimetics, starting with a conformation search, then a low-level ab initio preoptimization of the hundreds of conformations found, and, finally, a higher-level DFT optimization. For the resulting minima structures, Boltzmann populations were calculated, followed by OR calculations for all the populated conformers using the DFT method with various basis sets with diffuse functions. Weighted averages of the ORs were compared with experimental values, and the agreement, which ranged from excellent to moderate for various compounds, served as a verification of the conformational analysis results. Full article

In non-equilibrium plasmas, the temperature cannot be uniquely determined unless the energy-distribution function is approximated as a Maxwell–Boltzmann distribution. To overcome this problem, we applied Tsallis statistics to determine the temperature with respect to the excited-state populations in non-equilibrium state hydrogen plasma, which enables the description of its entropy that obeys q-exponential population distribution in the non-equilibrium state. However, it is quite difficult to apply the q-exponential distribution because it is a self-consistent function that cannot be solved analytically. In this study, a self-consistent iterative scheme was adopted to calculate q-exponential distribution using the similar algorithm of the Hartree–Fock method. Results show that the excited-state population distribution based on Tsallis statistics well captures the non-equilibrium characteristics in the high-energy region, which is far from the equilibrium-Boltzmann distribution. The temperature was calculated using the partial derivative of entropy with respect to the mean energy based on Tsallis statistics and using the coefficient of q-exponential distribution. An analytical expression was derived and compared with Boltzmann statistics, and the distribution was discussed from the viewpoint of statistical physics. Full article

In the last few decades, the number of published papers that include search terms such as thermodynamics, entropy, ecology, and ecosystems has grown rapidly. Recently, background research carried out during the development of a paper on “thermodynamics in ecology” revealed huge variation in the understanding of the meaning and the use of some of the central terms in this field—in particular, entropy. This variation seems to be based primarily on the differing educational and scientific backgrounds of the researchers responsible for contributions to this field. Secondly, some ecological subdisciplines also seem to be better suited and applicable to certain interpretations of the concept than others. The most well-known seems to be the use of the Boltzmann–Gibbs equation in the guise of the Shannon–Weaver/Wiener index when applied to the estimation of biodiversity in ecology. Thirdly, this tendency also revealed that the use of entropy-like functions could be diverted into an area of statistical and distributional analyses as opposed to real thermodynamic approaches, which explicitly aim to describe and account for the energy fluxes and dissipations in the systems. Fourthly, these different ways of usage contribute to an increased confusion in discussions about efficiency and possible telos in nature, whether at the developmental level of the organism, a population, or an entire ecosystem. All the papers, in general, suffer from a lack of clear definitions of the thermodynamic functions used, and we, therefore, recommend that future publications in this area endeavor to achieve a more precise use of language. Only by increasing such efforts it is possible to understand and resolve some of the significant and possibly misleading discussions in this area. Full article

Remote sensing images are important data sources for land cover mapping. As one of the most important artificial features in remote sensing images, buildings play a critical role in many applications, such as population estimation and urban planning. Classifying buildings quickly and accurately ensures the reliability of the above applications. It is known that the classification accuracy of buildings (usually indicated by a comprehensive index called F1) is greatly affected by image quality. However, how image quality affects building classification accuracy is still unclear. In this study, Boltzmann entropy (an index considering both compositional and configurational information, simply called BE) is employed to describe image quality, and the potential relationships between BE and F1 are explored based on images from two open-source building datasets (i.e., the WHU and Inria datasets) in three cities (i.e., Christchurch, Chicago and Austin). Experimental results show that (1) F1 fluctuates greatly in images where building proportions are small (especially in images with building proportions smaller than 1%) and (2) BE has a negative relationship with F1 (i.e., when BE becomes larger, F1 tends to become smaller). The negative relationships are confirmed using Spearman correlation coefficients (SCCs) and various confidence intervals via bootstrapping (i.e., a nonparametric statistical method). Such discoveries are helpful in deepening our understanding of how image quality affects building classification accuracy. Full article

Grid refinement is used to reduce computing costs while maintaining the precision of fluid simulation. In the lattice Boltzmann method (LBM), grid refinement often uses interpolated values. Here, we developed a method in which interpolation in space and time is not required. For this purpose, we used the moment matching condition and rescaled the nonequilibrium part of the populations, thereby developing a recalibration procedure that allows for the transfer of information between different LBM stencils in the simulation domain. Then, we built a nonuniform lattice that uses stencils with different shapes on the transition. The resulting procedure was verified by performing benchmarks with the 2D Poisselle flow and the advected vortex. It is suggested that grids with adaptive geometry can be built with the proposed method. Full article

Most bubble breakage models have been developed for multiphase simulations using Euler-Euler (EE) approaches. Commonly, they are linked with population balance models (PBM) and are validated by making use of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The latter, however, may be replaced by alternate approaches such as Large Eddy simulations (LES) that play a pivotal role in current developments based on lattice Boltzmann (LBM) technologies. Consequently, this study investigates the possibility of transferring promising bubble breakage models from the EE framework into Euler-Lagrange (EL) settings aiming to perform LES. Using our own model, it was possible to reproduce similar bubble size distributions (BSDs) for EL and EE simulations. Therefore, the critical Weber (We_crit) number served as a threshold value for the occurrence of bubble breakage events. We_crit depended on the bubble daughter size distribution (DSD) and a set minimum time between two consecutive bubble breakage events. The commercial frameworks Ansys Fluent and M-Star were applied for EE and EL simulations, respectively. The latter enabled the implementation of LES, i.e., the use of a turbulence model with non-time averaged entities. By properly choosing We_crit, it was possible to successfully transfer two commonly applied bubble breakage models from EE to EL. Based on the mechanism of bubble breakage, We_crit values of 7 and 11 were determined, respectively. Optimum We_crit were identified as fitting the shape of DSDs, as this turned out to be a key criterion for reaching optimum prediction quality. Optimum We_crit values hold true for commonly applied operational conditions in aerated bioreactors, considering water as the matrix. Full article

Electron temperature is reconsidered for weakly-ionized oxygen and nitrogen plasmas with its discharge pressure of a few hundred Pa, with its electron density of the order of ${10}^{17}{\mathrm{m}}^{-3}$ and in a state of non-equilibrium, based on thermodynamics and statistical physics. The relationship between entropy and electron mean energy is focused on based on the electron energy distribution function (EEDF) calculated with the integro-differential Boltzmann equation for a given reduced electric field $E/N$. When the Boltzmann equation is solved, chemical kinetic equations are also simultaneously solved to determine essential excited species for the oxygen plasma, while vibrationally excited populations are solved for the nitrogen plasma, since the EEDF should be self-consistently found with the densities of collision counterparts of electrons. Next, the electron mean energy U and entropy S are calculated with the self-consistent EEDF obtained, where the entropy is calculated with the Gibbs’s formula. Then, the “statistical” electron temperature $T_{\mathrm{e}}^{\mathrm{st}}$ is calculated as $T_{\mathrm{e}}^{\mathrm{st}}={[\partial S/\partial U]}^{-1}$. The difference between $T_{\mathrm{e}}^{\mathrm{st}}$ and the electron kinetic temperature $T_{\mathrm{e}}^{\mathrm{kin}}$ is discussed, which is defined as $[2/(3k\left)\right]$ times of the mean electron energy $U=⟨ϵ⟩$, as well as the temperature given as a slope of the EEDF for each value of $E/N$ from the viewpoint of statistical physics as well as of elementary processes in the oxygen or nitrogen plasma. Full article

The isomerism of zinc complex [Zn(L)₂]²⁺ with tridentate ligand L having acetamide and pyridine groups on each side of the central amino- nitrogen atom has been investigated by DFT calculations, liquid state NMR and single-crystal X-ray diffraction. DFT was used for obtaining the ensembles of low-energy conformers of L and [Zn(L)₂]²⁺ and for the calculation of NMR parameters for all conformers. For all generated conformers of L and [Zn(L)₂]²⁺, the Mean Absolute Error [MAE(conf)] was tested as a structural quality parameter and compared with MAE(Bolz) for Boltzmann weighted ensembles. The most populated conformers had MAE(conf) values below 0.1 and 1 ppm for ¹H shifts and ¹³C shifts, respectively. For the [Zn(L)₂]²⁺ complex, the mer- C₂ symmetric isomer was the most stable, in accordance with the X-ray structure of [Zn(L)₂]₂[SiF₆][BF₄]₂. The cancellation of the magnetic equivalence of some nuclei valid for free L, when coordinated to the Zn²⁺ cation, was theoretically explained by the correct averaging of NMR parameters in the calculation procedure. Full article