United Probabilistic Nature and Model of Chemical and Mechanical Reactions of Consecutive Destruction of Substance
Author(s) -
Vitaliy Pavlovich Malyshev
Publication year - 2015
Publication title -
american journal of physical chemistry
Language(s) - English
Resource type - Journals
eISSN - 2327-2449
pISSN - 2327-2430
DOI - 10.11648/j.ajpc.20150406.11
Subject(s) - probabilistic logic , chemical reaction , chemistry , thermodynamics , steric effects , molecule , statistical physics , representation (politics) , computational chemistry , mathematics , physics , stereochemistry , organic chemistry , statistics , politics , political science , law
Into development of mathematical methods of forecasting of grinding process materials based on different aspects of the application of systems theory, the authors propose to be likened to and summarize chemical and mechanical processes of sequential destruction of matter on the basis of a single probability of their nature. Expression for the rate of direct reaction of substances is opened taking into account sense of product of the mole fractions of reacting molecules as probabilities of their simultaneous presence at any point of reactionary space (a concentration factor P conc ), a steric factor of P st – as probabilities of successful mutual orientation of molecules, an activation factor of P a – as probabilities of overcoming of a power barrier of activation under the influence of the frequency of impacts of Z : V = Z ∙ P conc ∙ P st ∙ P а . Probabilistic representation of the rate of chemical reactions more directly reflects randomized the state of the reacting system and can be generalized to any of its variants, in particular, mechanical. This allowed us to consider the process of grinding material from new point of view, and moreover - to liken of its kinetics successive irreversible reactions to give the general expression for the output of the intermediates (fractions) at any time for any number of destruction stages. On this basis calculated the entropy of mixing of fractions and the dynamics of change corresponding to the log-normal distribution of fractions which known by data of practices.
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