In Silico Screening of Metal-Organic Frameworks for Formaldehyde Capture with and without Humidity by Molecular...

Area of Science:

• Materials Science
• Environmental Chemistry
• Computational Chemistry

Background:

• Formaldehyde (HCHO) removal from indoor air is critical due to health concerns.
• Porous adsorbents, particularly metal-organic frameworks (MOFs), show promise but face challenges with capacity, selectivity, and humidity.
• Water presence significantly impacts HCHO capture performance via competitive adsorption.

Purpose of the Study:

• To identify suitable MOFs for formaldehyde capture.
• To explore the relationship between MOF structure and HCHO capture performance in both dry and humid air.
• To develop screening methods for high-performing MOFs under varying humidity levels.

Main Methods:

• Grand Canonical Monte Carlo (GCMC) molecular simulations were employed.
• Working capacity and selectivity were calculated to evaluate HCHO capture performance.
• Henry's constant selectivity (SK_H) was used to screen MOFs under 80% humidity.

Main Results:

• Optimal MOFs for dry air exhibit small pore sizes (~5 Å) and moderate heat of adsorption (40-50 kJ/mol).
• 3D cage structures are superior to 2D channels for HCHO adsorption.
• Henry's constant (K_H) in the range of 10^-2-10¹ correlates with dry air performance.
• SK_H HCHO/H₂O effectively identifies MOFs for humid conditions, unlike SK_H for mixture components.
• ECATAT demonstrated high working capacity (0.64 mol/kg) and minimal water adsorption.

Conclusions:

• Small pore size, moderate adsorption enthalpy, and specific structural features (3D cages) are key for efficient HCHO capture by MOFs.
• SK_H HCHO/H₂O is a reliable metric for selecting MOFs effective in humid environments.
• ECATAT is a promising candidate MOF for formaldehyde removal from indoor air, even under humid conditions.