Pauli energy and information-theoretic approach for evaluating dynamic and nondynamic electron correlation

Reaction rate constant: a theoretical description from local temperature

Application of various descriptors based on electron density and its associated quantities to quantify chemical reactivity within the conceptual density functional theory has recently come into spotlight. Among others and particularly relevant to our study, local temperature based on electron density as well as kinetic energy density, as a measure of the kinetic energy of an electron moving in the Kohn-Sham potential of systems, should be mentioned. In this work, we propose to use the local temperature for describing the reaction rate constant, where our main idea originates from the point that the smaller the local temperature at the reaction center, the easier the electron removal, leading to a larger rate constant. On the basis of theoretical considerations, it is proved that the rate constant variations caused by the substituent effects can well be proportional to the local temperature at the reaction center. In order to numerically validate our proposed approach, we have taken the phenol derivatives with the available experimental rate constants of their O-methylation reaction as working models. The reason for this choice is that one of the most versatile approaches for labeling biologically active compounds with the 11C nuclide for positron emission tomography (PET) is methylation by methyl iodide including 11C nuclide, [11C]MeI, where methylation of phenolic oxygen with [11C]MeI is utilized to label some important tracers for PET studies. Our results unveil that the local temperature changes at the reaction center of the aforementioned reaction are reasonably correlated with the rate constant variations. Hopefully, incorporating the proposed correlations between the local temperature and the kinetics data into a computer control algorithm not only provides a simple tool for predicting the rate constant of the O-methylation reaction for other substituted phenols, but also, as a part of the chemical artificial intelligence, the optimum [11C]MeI labeling conditions for a wide variety of phenol derivatives can be controlled.

On the role of steric and exchange–correlation effects in halogenated complexes

Density functional theory formalisms of energy partitioning schemes are utilized to find out what energetic components govern interactions in halogenated complexes.