Temperature dependence of chemical and biophysical rate processes: Phenomenological approach to deviations from Arrhenius law

Arrhenius plots, which are used to represent the effects of temperature on the rates of chemical and biophysical processes and on various transport phenomena in materials science, may exhibit deviations from linearity. Account of curvature is provided here by a formula which involves a deformation of the exponential function, of the kind recently encountered in treatments of non-extensivity in statistical mechanics. We present here examples on diverse topics – respiration rates of plants, speed of gliding of bacteria, quantum mechanical tunneling in a chemical reaction – illustrating the variety of possible applications and the additional insight that can be gained

Uniform description of non-Arrhenius temperature dependence of reaction rates, and a heuristic criterion for quantum tunneling vs classical non-extensive distribution

AbstractTo account for frequently documented low-temperature deviations from Arrhenius rate law, the proposed expansion of inverse activation energy against inverse temperature is shown to yield a first order linearizing parameter which is formally correlated with Tsallis non-extensive classical statistical mechanics. Its sign provides a heuristic criterion, especially appealing in biochemistry, for assigning deviations as due either: (i) to quantum mechanical under-barrier tunneling, or (ii) to 'classical' collective phenomena. For (i), an explicit relationship is here derived in terms of barrier features. Case (ii) typically occurs in enzymatic or heterogeneous catalysis, in membrane mediated processes and in those controlled by diffusion or by transport in general

Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing

The main goal of this study is to find the most effective set of parameters for the Simplified Generalized Simulated Annealing algorithm, SGSA, when applied to distinct cost function as well as to find a possible correlation between the values of these parameters sets and some topological characteristics of the hypersurface of the respective cost function. The SGSA algorithm is an extended and simplified derivative of the GSA algorithm, a Markovian stochastic process based on Tsallis statistics that has been used in many classes of problems, in particular, in biological molecular systems optimization. In all but one of the studied cost functions, the global minimum was found in 100% of the 50 runs. For these functions the best visiting parameter, qV, belongs to the interval [1.2, 1.7]. Also, the temperature decaying parameter, qT, should be increased when better precision is required. Moreover, the similarity in the locus of optimal parameter sets observed in some functions indicates that possibly one could extract topological information about the cost functions from these sets

Anticommuting space : an alternative formulation of the wavefunction antisymmetry description

We show the important role of the anticommuting algebra in quantum chemistry. We use the properties of the Multilinear Alternating Space in order to obtain the antisymmetry of the wave function and we calculate some molecular invariants.Nous montrons le rôle important joué par les algèbres antisymétriques en chimie quantique. Nous utilisons les propriétés des espaces multilinéaires alternés pour imposer l'antisymétrie de la fonction d'onde et calculons certains invariants moléculaires

A model for diffusive systems: Beyond the Arrhenius mechanism

Diffusivity in supercooled liquids was observed to exhibit a non-Arrhenius behavior near the glass-transition temperature. This process, which occurs where the activation energy depends on the temperature, suggests the possibility of a metastable equilibrium. This peculiar phenomenon cannot be explained using the usual Markovian stochastic models. Based on a non-linear Fokker-Planck equation, we propose a diffusion coefficient that is proportional to the supercooled-liquid concentration. The proposed model allows us to explain the anomalous behavior of the diffusivity robustly. We demonstrate that this new approach is consistent with experimental patterns. Besides, it could be applied to non-Arrhenius chemical kinetics.Fil: Rosa, A.C.P.. Programa de Modelagem Computacional; Brasil. Universidade Federal do Oeste da Bahia; BrasilFil: Vaveliuk, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Mundim, Kleber C.. Universidade de Brasília; BrasilFil: Moret, M.A.. Programa de Modelagem Computacional; Brasil. Universidade do Estado da Bahia; Brasi

Temperature coefficient (Q10) and its applications in biological systems: beyond the Arrhenius theory

The Q10 temperature coefficient, which is widely used in scientific literature, is a measure of the temperature sensitivity of chemical reaction rates or biological processes. However, the conclusions drawn from applying this coefficient to experimental data obtained from biological processes are not universal. In many biological processes, Q10 values are often discordant with the results predicted by the Arrhenius law. The hypothesis tested in the present study is that this problem arises mainly from the fact that the Q10 coefficient is defined by the ratio between rates described by exponential laws instead of power laws. Considering this hypothesis and the need to review the mathematical laws and models currently used to describe rates and Q10 coefficients, we propose a model beyond the usual Arrhenius theory or exponential decay law herein. The proposed mathematical model is based on the theory of deformed exponential functions, with the ordinary Q10 model representing the conventional exponential function. Therefore, all results following the standard model remain valid. Moreover, we include a Q10 free open-source code, written in Python, and compatible with Windows, Linux and macOS platforms. The validation of the proposed model and confirmation of the given hypothesis were performed based on the following temperature-dependent biological processes: soil organic carbon (SOC) decomposition (which is essential to forecast the impact of climate change on terrestrial ecosystems); the metabolism of Arctic zooplankton; physiological processes of the respiratory and cardiovascular systems; rate of oxygen consumption in mitochondria of the eurythermal killifish Fundulus heteroclitus, and leaf respiration

Atomistic study of interaction zone at copper-carbon interfaces

Formation of Cu-C composite is a difficult technological problem: carbon is practically insoluble in copper. We show that the heat treatment of the Cu-C composite leads to the formation of thin (approximately 50 nm) interface, which provides the bonding between fiber and matrix, The high-resolution scanning electron microscopy (HR SEM) study displays the formation of the interaction zone. Monte Carlo simulations with repulsive Cu-C interatomic potentials study this zone on the interface. (C) 2001 Elsevier Science B.V. All rights reserved.status: publishe

Atomistic study of interaction zone at copper-carbon interfaces

Formation of Cu-C composite is a difficult technological problem: carbon is practically insoluble in copper. We show that the heat treatment of the Cu-C composite leads to the formation of thin (approximately 50 nm) interface, which provides the bonding between fiber and matrix, The high-resolution scanning electron microscopy (HR SEM) study displays the formation of the interaction zone. Monte Carlo simulations with repulsive Cu-C interatomic potentials study this zone on the interface. (C) 2001 Elsevier Science B.V. All rights reserved.status: publishe