Blind Search for Complex Chemical Pathways Using Harmonic Linear Discriminant Analysis.

Area of Science:

• Computational Chemistry
• Chemical Dynamics
• Reaction Mechanism Discovery

Background:

• Elucidating chemical reaction mechanisms is challenging due to experimental limitations in observing short-lived intermediates and the reliance of simulations on initial guesses.
• Discovering reaction pathways often requires significant chemical intuition and can be serendipitous.

Purpose of the Study:

• To develop a systematic computational method for searching and identifying reaction mechanisms connecting reactant and product states.
• To overcome the limitations of traditional experimental and simulation approaches in reaction pathway discovery.

Main Methods:

• Utilizing enhanced molecular dynamics, specifically metadynamics, to explore the configuration space between reactant and product states.
• Employing harmonic linear discriminant analysis to construct collective variables from generic descriptors that distinguish between reactant and product states.
• Performing an initial search at a low level of theory, followed by refinement at a higher level of theory for discovered intermediates and transition states.

Main Results:

• The method successfully identified reaction intermediates and transition states by exploring the configuration space.
• Applied to two test reactions, the approach revealed complex mechanisms in seemingly simple systems.
• The discovered mechanisms can challenge established chemical paradigms.

Conclusions:

• The proposed method offers a time-efficient and systematic approach to reaction mechanism search.
• It has the potential to uncover unexpected reaction pathways and can be extended to larger, more complex systems like reactions in solution or catalysis.