ArticleSmall science2024
Nanosized Porphyrinic Metal-Organic Frameworks for the Construction of Transparent Membranes as a Multiresponsive Optical Gas Sensor.
Article in Small science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Facile and Fast Microwave-Assisted Synthesis of Metalated PCN-222 for Light-Driven Hydrogen Evolution Reaction.ACS omega · 2026Article
- DNA-mimic for Specific Surface Functionalization of Zr-MOFs for Bacterial Targeting.Angewandte Chemie (International ed. in English) · 2026Article
- Zr-based metal-organic frameworks for colorimetric sensing applications.RSC applied interfaces · 2026Review
- Tuning the Photoelectrochemical Properties of Ti/W-Modified PCN-222 Using Charge-Selective Interfaces.ACS applied materials & interfaces · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
The well-known and excellent colorimetric sensing capacity of porphyrins, along with the exceptional structural properties of metal-organic frameworks (MOFs), make porphyrin-based MOFs, such as PCN-222, ideal candidates for the construction of a chemical sensor based on absorbance. However, to the best of authors' knowledge, no high-quality porphyrin-based MOF gas sensors have been developed to date, most likely due to the difficulties in: 1) preparing nanosized porphyrin-MOFs to minimize scattering in absorbance measurements; and 2) incorporating MOFs into transparent membranes for practical use. Herein, a simple and fast microwave-assisted method for preparing high-quality nanosized PCN-222 crystals and their metalated derivatives PCN-222(M) is reported to finely tune the sensing response. Next, the successful dispersion of these PCN-222(M) nanoparticles into poly(dimethylsiloxane) to create flexible and transparent membranes is demonstrated. This integration yields a multiresponsive optical gas sensor exhibiting excellent sensitivity and the ability to discriminate between various volatile organic compounds via pattern recognition identification.
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Registered trials
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