Predicting Dinitrogen Activation and Coupling with Carbon Dioxide and Other Small Molecules by Methyleneborane: A...

Area of Science:

• Computational chemistry
• Materials science
• Catalysis

Background:

• The escalating greenhouse effect necessitates effective carbon dioxide (CO₂) capture.
• Converting abundant dinitrogen (N₂) into valuable nitrogen-carbon (N-C) compounds is a significant chemical challenge.

Purpose of the Study:

• To investigate the feasibility of coupling dinitrogen with carbon dioxide using methyleneborane.
• To explore the thermodynamic and kinetic factors governing this reaction.
• To identify strategies for optimizing the reaction energetics.

Main Methods:

• Density functional theory (DFT) calculations were employed to model the reaction.
• Machine learning (ML) analysis was used to correlate molecular descriptors with reaction energies.
• Computational screening of N₂ coupling with various small molecules was performed.

Main Results:

• Methyleneborane was predicted to enable thermodynamically and kinetically favorable coupling of N₂ with CO₂.
• Machine learning models identified key descriptors (HOMO-LUMO gap, atomic charges) influencing reaction energies.
• The N₂ coupling mechanism was characterized as a concerted step, with CO₂ acting as both a σ donor and π acceptor.
• N₂ coupling with other small molecules (formaldehyde, SO₂, acetonitrile, N-ethylidenemethylamine) was also assessed.

Conclusions:

• Methyleneborane presents a promising catalyst for dinitrogen and carbon dioxide conversion.
• Computational insights guide the rational design of catalysts for N₂ fixation.
• Main group species play a pivotal role in enabling N₂ coupling chemistry.