Volatile organic compounds seriously endanger the environment and human health, so the identification and detection of organic vapors is of great significance. Traditional optical organic vapor sensors with solvatochromic shift mechanism have lower sensitivity and specific recognition performance due to weak intermolecular interactions.
Recently, the research group led by Prof. JIANG Lei at Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made a breakthrough in the construction of highly-sensitive optical organic vapor sensor through polymeric swelling induced variation of fluorescent intensity. The study was published in Nature Communications.
Researchers combined polymer and aggregation-induced emission (AIE) molecules. Then they fabricated polymer/AIE fluorescent microwire arrays as optical organic vapor sensor based on asymmetric-wettability micropillar template, to achieve higher sensitivity and specificity through polymeric swelling induced variation of fluorescent intensity.
The polymer/AIE fluorescent microwire arrays have the advantages of high stability, fast response time and higher sensitivity than traditional optical organic vapor sensors.
Researchers further revealed the mechanism for organic vapor sensing through theoretical calculation, and constructed sensor arrays using commercial polymers or AIE materials to successfully classify and identify various organic vapors, proving the universality of this strategy.
More importantly, researchers fabricated polymer/AIE microwires array derived from designable polyethersulfones, through regulating their side chains, to distinguish similar organic vapors of benzene and toluene.
Theoretical simulation proved that the interaction between polymer and vapor molecule was consistent with the theory of similar dissolve mutually.
This work will open new route to construct novel optical organic vapor sensor with higher sensitivity and specific recognition performance.
Proposed mechanism of polymer/AIE microwire for organic vapor sensing. (Image by ZHANG Xiqi)
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