379522 Computational Analysis and Screening of Materials for Capture of Toxic Compounds
Porous materials play an important role in the capture of toxic compounds. Advances in nanotechnology have enabled the development of novel materials by a targeted molecular design approach. This has led to the emergence of numerous functional materials over the past decade. Among them, metal-organic frameworks (MOFs) are promising materials, as they allow for design of new structures from a building-block approach permitting the design of a wide variety of adsorbents tailored for specific adsorption separations.
Development of selective adsorbents for target molecules would be greatly accelerated if we had a better understanding of how target sorbates interact with surface functional groups. Molecular simulations can provide valuable information to predict interaction energies with sufficient accuracy for screening and to provide insights about the detailed nature of molecular-level interactions. The objective of this work has been to computationally discover the best functional groups and surface chemistries for the removal of toxic chemicals from air.
An inherent challenge in the capture of toxic compounds in humid conditions is the competitive adsorption of water. We have explored two approaches for overcoming this problem. In the first approach, we have used quantum chemical methods to search for functional groups or surfaces that could bind toxic molecules more strongly than water. In the second approach, we have targeted hydrophobic MOFs. Using classical Monte Carlo simulations, we have investigated the effect of perfluoroalkane chains on ammonia and water adsorption in MOFs and performed high-throughput computational screening of hydrophobic MOFs. The results suggest that if materials are too hydrophilic, they adsorb too much water. On the other hand, if they are too hydrophobic, they adsorb too little ammonia.
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