Towards accurate porosity descriptors based on guest-host interactions

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• Geometry-based approaches are standard for characterizing nanoporous materials using descriptors like pore size and surface area.
• These methods rely on hard-sphere approximations, simplifying calculations but potentially limiting accuracy.
• Existing methods may struggle with accurately describing porosity in complex or small-pore systems.

Purpose of the Study:

• To quantify the shortcomings of traditional geometry-based methods for nanoporous material characterization.
• To develop and validate a novel energy-based approach for calculating pore descriptors.
• To assess the performance of the new method compared to existing techniques.

Main Methods:

• Developed algorithms to calculate pore descriptors (void fraction, accessible surface area, pore limiting diameters) using classical force field models.
• Employed an energy-based approach considering guest-framework interactions.
• Tested algorithms on diverse sets of metal-organic frameworks (MOFs) and zeolite structures.

Main Results:

• The energy-based method accurately calculates pore descriptors, offering an alternative to geometry-based approaches.
• Deviations were observed between energy-based and geometry-based methods, particularly for structures with small pore sizes.
• The developed method demonstrates high accuracy and computational performance.

Conclusions:

• Energy-based methods provide a more accurate characterization of nanoporous materials, especially for small pores.
• The new algorithms overcome limitations of geometry-based approaches, offering improved accuracy and efficiency.
• This method is suitable for high-throughput screening of large material databases.