Fully computational lead-development of fluoro-olefin polymerization catalysts

Area of Science:

• Organometallic Chemistry
• Polymer Science
• Computational Chemistry

Background:

• Coordinative polymerization of fluorinated olefins presents significant challenges in catalysis.
• Developing efficient catalysts is crucial for synthesizing advanced fluoropolymers.

Purpose of the Study:

• To computationally analyze the catalytic properties of diimido chromium VI compounds for fluorinated olefin polymerization.
• To identify key structural parameters influencing catalytic activity and propose novel catalyst candidates.

Main Methods:

• Density functional theory (DFT) calculations were employed to study chromium VI complexes.
• DFT methods were calibrated against high-level wave function theory calculations for accuracy.
• Systematic scanning of ligand-tunable geometrical parameters was performed.
• A fragment database was used for automated assembly and screening of chromium complexes.

Main Results:

• Reactivity predictions were found to be highly dependent on the chosen density functional.
• Calibration of DFT calculations improved the reliability of reactivity predictions.
• Optimal geometrical parameters influencing catalytic activity were identified.
• Three promising chromium-based catalyst candidates were proposed through automated screening.

Conclusions:

• Computational methods, when properly calibrated, can effectively guide the discovery of new catalysts.
• Diimido chromium VI compounds show potential for catalyzing fluorinated olefin polymerization.
• The proposed catalyst candidates warrant experimental investigation for practical applications.