From Cages to Sheets: Computational Elucidation of Methylaluminoxane Structure and Reactivity

Area of Science:

• Polymer Chemistry
• Computational Chemistry
• Materials Science

Background:

• Methylaluminoxane (MAO) is crucial for single-site olefin polymerization.
• MAO's complex molecular structure has historically hindered characterization.
• Computational chemistry has been vital in proposing and refining MAO structural models.

Purpose of the Study:

• To review the computational journey in characterizing MAO structures.
• To highlight methodological advances and limitations in MAO modeling.
• To establish a structural foundation for understanding MAO and designing new cocatalysts.

Main Methods:

• Review of computational chemistry studies on MAO.
• Analysis of density functional theory (DFT) method performance for Al-O environments.
• Consideration of vibrational entropy's role in thermodynamic stability.
• Validation against experimental data (ESI-MS, NMR, X-ray, PDF).

Main Results:

• Identified systematic errors in common DFT methods for MAO.
• Established vibrational entropy as critical for thermodynamic stability.
• Proposed a dominant two-dimensional ovalene-based sheet model for the main MAO anion.
• Model is consistent with multiple experimental techniques.

Conclusions:

• The established sheet model provides a structural basis for MAO.
• This understanding facilitates comprehending MAO mixture complexity.
• Enables rational design of advanced aluminum-based cocatalysts for olefin polymerization.