Reactivity Prediction of Cu-Catalyzed Halogen Atom Transfer Reactions Using Data-Driven Techniques

Area of Science:

• Catalysis
• Organic Chemistry
• Physical Chemistry

Background:

• Linear free energy relationships (LFERs) are crucial for predicting reaction outcomes and designing catalysts in chemical reactions.
• Reductive cleavage of the C(sp3)-X bond in alkyl halides by copper (Cu) complexes is a key step in atom transfer radical polymerization and addition/cyclization reactions.

Purpose of the Study:

• To establish LFERs for the reductive cleavage of C(sp3)-X bonds by Cu complexes.
• To identify fundamental descriptors of Cu complexes and alkyl halides influencing reactivity.
• To develop predictive models for reaction rate constants (kact).

Main Methods:

• Established LFERs using the equation log kact = s(I + C + S) for 107 Cu complex/alkyl halide pairs across 5 solvents.
• Correlated LFER parameters (I, C, S, s) with descriptors like bond dissociation free energy, Tolman cone angle, electron affinity, radical stabilization energy, redox potential, solvent polarizability, and distortion energy.
• Employed multivariate linear regression (MLR) to develop a predictive model for kact.

Main Results:

• LFERs effectively interpolated kact values spanning over 13 orders of magnitude.
• Identified key descriptors influencing the reductive cleavage of C(sp3)-X bonds.
• The MLR model demonstrated superior predictive capability over the LFER equation.
• Predicted kact values for over 2000 Cu complex/alkyl halide pairs using the MLR model.

Conclusions:

• The established LFERs and identified descriptors provide fundamental insights into the reactivity of Cu complexes and alkyl halides in C(sp3)-X bond cleavage.
• The MLR model offers a powerful tool for predicting and optimizing catalyst performance in atom transfer radical reactions.
• This work facilitates the rational design of novel catalytic systems for various radical-mediated transformations.