Metal-organic framework MIL-100(Fe) as a promising sensor for COVID-19 biomarkers detection

Microporous Mesoporous Mater. 2022 Sep;343:112187. doi: 10.1016/j.micromeso.2022.112187. Epub 2022 Aug 19.

ABSTRACT

The development of fast and non-invasive techniques to detect SARS-CoV-2 virus at the early stage of the infection would be highly desirable to control the COVID-19 outbreak. Metal-organic frameworks (MOFs) are porous materials with uniform porous structures and tunable pore surfaces, which would be essential for the selective sensing of the specific COVID-19 biomarkers. However, the use of MOFs materials to detect COVID-19 biomarkers has not been demonstrated so far. In this work, for the first time, we employed the density functional theory calculations to investigate the specific interactions of MOFs and the targeted biomarkers, in which the interactions were confirmed by experiment. The five dominant COVID-19 biomarkers and common exhaled gases are comparatively studied by exposing them to MOFs, namely MIL-100(Al) and MIL-100(Fe). The adsorption mechanism, binding site, adsorption energy, recovery time, charge transfer, sensing response, and electronic structures are systematically investigated. We found that MIL-100(Fe) has a higher sensing performance than MIL-100(Al) in terms of sensitivity and selectivity. MIL-100(Fe) shows sensitive to COVID-19 biomarkers, namely 2-methylpent-2-enal and 2,4-octadiene with high sensing responses as 7.44 x 105 and 9 x 107 which are exceptionally higher than those of the common gases which are less than 6. The calculated recovery times of 0.19 and 1.84 x 10-4 s are short enough to be a resuable sensor. An experimental study also showed that the MIL-100(Fe) provides a sensitivity toward 2-methylpent-2-enal. In conclusion, we suggest that MIL-100(Fe) could be used as a potential sensor for the exhaled breath analysis. We hope that our research can aid in the development of a biosensor for quick and easy COVID-19 biomarker detection in order to control the current pandemic.

PMID:35999991 | PMC:PMC9389852 | DOI:10.1016/j.micromeso.2022.112187

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