Computational Screening of MOFs for Acetylene Separation

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Chemistry

Background:

• Efficient separation of acetylene (C2H2) from CO2 and CH4 is crucial for industrial applications requiring high-purity C2H2.
• Metal-organic frameworks (MOFs) offer tunable properties for adsorption-based gas separations, showing promise in experimental studies.

Purpose of the Study:

• To conduct a large-scale molecular simulation study on the separation performance of 174 MOF structures for C2H2/CO2 and C2H2/CH4 mixtures.
• To identify optimal MOF adsorbents for selective C2H2 separation based on multiple performance metrics.

Main Methods:

• Employed large-scale molecular simulations to evaluate 174 different MOF structures.
• Calculated key performance metrics including selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability.
• Analyzed structure-performance relationships to determine optimal MOF characteristics.

Main Results:

• Identified top MOF candidates exhibiting unprecedented C2H2/CO2 and C2H2/CH4 selectivities at 1 bar and 298 K.
• The highest selectivities reported were 49 for C2H2/CO2 and 824 for C2H2/CH4.
• Optimal MOFs possess pore sizes between 4-11 Å, surface areas of 600-1,200 m²/g, and porosities of 0.4-0.6.

Conclusions:

• This simulation study provides a comprehensive evaluation of MOFs for C2H2 separation.
• The identified MOFs and structure-performance insights will guide the design of next-generation adsorbents for efficient acetylene purification.