A General Predictive and Conceptual Model for Repulsive Electronic States in Valence Ionized Molecules

Area of Science:

• Physical Chemistry
• Chemical Physics
• Computational Chemistry

Background:

• Valence photoionization often results in statistical dissociation, predictable by RRKM theory.
• Small photoions with electronegative substituents (e.g., F, Cl, OH) can exhibit nonstatistical dissociation.
• This nonstatistical behavior involves direct dissociation from repulsive electronic states, forming radical fragments.

Purpose of the Study:

• To present a general and predictive model for nonstatistical dissociation in photoionized molecules.
• To rationalize the mechanism of direct dissociation involving electronegative substituents.
• To extend the understanding of photoionization dynamics to a broader range of molecules.

Main Methods:

• Development of a predictive model based on ionization of p- or π-localized orbitals on electronegative atoms.
• Identification of three key governing factors: excitation energy, ionized orbital character, and electronic degeneracy.
• Classification of potential energy surfaces into four distinct categories for predictive analysis.
• Extensive computational validation on over 50 molecules.

Main Results:

• The model accurately predicts nonstatistical dissociation arising from ionization of localized orbitals on electronegative atoms.
• Formation of radical-like fragments unbound to the cationic core is a key characteristic.
• The model successfully rationalizes dissociation pathways for molecules forming 2P (e.g., F•) or 2Π (e.g., OH•) radicals.
• Four classes of potential energy surfaces were defined, enabling accurate classification of dissociative behavior.

Conclusions:

• The developed model provides a general framework for understanding and predicting nonstatistical dissociation in photoionized molecules with electronegative substituents.
• Ionization of localized orbitals on electronegative atoms is a critical factor driving nonstatistical behavior.
• The model's accuracy and generality were confirmed through extensive computational studies, offering significant insights into molecular fragmentation dynamics.