Precision-engineered metal-organic frameworks: fine-tuning reverse topological structure prediction and design

Area of Science:

• Materials Science
• Computational Chemistry
• Chemical Engineering

Background:

• The reverse topological approach (RTA) advances digital discovery of metal-organic frameworks (MOFs).
• Node-and-linker assembly allows predictable MOF reticulations using computational templates.
• However, the vast design space of building units (BUs) causes combinatorial explosion.

Purpose of the Study:

• To develop a fine-tuned RTA for MOF structure prediction.
• To integrate topological constraints and reticular chemistry for efficient design.
• To overcome limitations of traditional trial-and-error methods.

Main Methods:

• A refined RTA was developed with precise topological constraints.
• A database of 94,823 precision-engineered MOFs (PE-MOFs) was designed from realistic BUs.
• PE-MOFs were optimized and assessed for post-combustion CO2 capture stability.

Main Results:

• A database of 94,823 PE-MOFs was generated.
• Top-performing MOFs for CO2 capture were identified.
• Integration of activation, water, and thermal stability criteria was employed.

Conclusions:

• Synergizing precision engineering (PE) with RTA enhances efficiency and precision in MOF computational design.
• This approach offers a powerful strategy for discovering novel MOFs for applications like carbon capture.
• The developed methodology transcends traditional exhaustive methods in materials discovery.