Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity

Area of Science:

• Catalysis
• Materials Science
• Organic Chemistry

Background:

• Selective transformation of inert chemical bonds (C-H, C-O, C-C, C-F) is crucial for synthesis and materials.
• Catalyst performance is modulated by electronic structure and intermolecular/interfacial interactions.
• Rational catalyst design for inert bond activation under mild conditions remains a significant challenge.

Purpose of the Study:

• To summarize strategies for controlling catalyst performance.
• To review the effects of electronic structures and interfacial interactions on catalysis.
• To highlight the role of computational and machine learning methods in catalyst discovery.

Main Methods:

• Review of electronic structure modulation (active site, ligands).
• Analysis of intermolecular and interfacial interactions (solvent, support effects).
• Discussion of catalyst types including molecular, metal-organic frameworks (MOFs), and natural minerals.
• Exploration of machine learning and high-throughput computational approaches.

Main Results:

• Electronic structure and interfacial interactions significantly impact catalyst activity and stability.
• Adjustable features like metal sites, crystal phase, ligands, solvents, and supports are key design elements.
• Machine learning, high-throughput computations, and automated pathway searches show promise for accelerating catalyst discovery.

Conclusions:

• Rational catalyst design requires a deep understanding of electronic and interfacial properties.
• Advanced computational and machine learning techniques are essential for future catalyst development.
• Further integration of high-throughput experiments and computations will drive innovation in catalysis.