Artículos SCI

Parametrization of mechanochemical reactions, or relating the evolution of the reaction progress to the supplied input power, is required both to establish protocols and to gain insight into mechanochemical reactions. Thus, results could be compared, replicated, or scaled up even under different milling conditions, enlarging the domains of application of mechanochemistry. Here, we propose a procedure that allows the parametrization of mechanochemical reactions as a function of the supplied input power from the direct analysis of the milling experiments in a model-free approach, where neither the kinetic model function nor the rate constant equation are previously assumed. This procedure has been successfully tested with the mechanochemical reaction of CH3NH3PbCl3, enabling the possibility to make predictions regardless of the milling device as well as gaining insight into the reaction dynamic. This methodology can work for any other mechanical reaction and definitely paves the way to establish mechanochemistry as a standard synthetic procedure.

In this work, it is proposed a method for studying kinetics of complex processes composed of non-independent stages. In this method, the variable contribution of the different stages as a function of the heating schedule is taken into account. The method involves the simultaneous kinetic analysis of a set of experimental data registered under linear heating rate conditions, without any previous assumptions regarding the kinetic models followed by the stages or their corresponding activation energies.
The method has been tested with the kinetic analysis of the pyrolysis of natural rubber, since the kinetics of this process is complex and depends on temperature and heating schedule. It is demonstrated that the behavior of the experimental curves can be accurately predicted with the kinetic parameters calculated by the proposed methodology.
The kinetic analysis presented here could be applied to other complex processes as those found in pyrolysis, without the need of using oversimplified kinetic models that could yield significant errors when used in real applications.