Effect of perylene assembly shapes on photoelectrochemical properties and ultrasensitive biosensing behaviors toward dopamine

In this study, a photoelectrochemical (PEC) sensor based on perylene diimide derivatives (PDIs) was developed for the ultrasensitive quantification of dopamine (DA). PDIs were able to form self-assembled semiconductor nanostructures by strong π-π stacking, suitable for photoactive substances. Moreov...

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Veröffentlicht in:Analytical and bioanalytical chemistry 2023-09, Vol.415 (23), p.5845-5854
Hauptverfasser: Chi, Kuan-Neng, Liu, Jia-Wen, Guan, Yan, Li, Qiu-Xia, Yang, Tong, Hu, Rong, Yang, Yun-Hui
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Sprache:eng
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Zusammenfassung:In this study, a photoelectrochemical (PEC) sensor based on perylene diimide derivatives (PDIs) was developed for the ultrasensitive quantification of dopamine (DA). PDIs were able to form self-assembled semiconductor nanostructures by strong π-π stacking, suitable for photoactive substances. Moreover, the shape of the PDI significantly affected the PEC properties of these nanostructures. The results showed that amino PDI with two-dimensional (2D) wrinkled layered nanostructures exhibited superior PEC properties relative to one-dimensional (1D) nanorods and fiber-based nanostructures (methyl and carboxyl PDIs). Based on these results, a mechanism for PEC sensor action was then proposed. The presence of 2D amino-PDI resulted in accelerated charge separation and transport. Furthermore, dopamine acted as effective electron donor to cause an increase in photocurrent. The as-obtained sensor was then used to detect small molecules like DA. A blue light optimized sensor at an applied potential of 0.7 V showed a detection limit of 1.67 nM with a wide linear range of 5 nM to 10 μM. On the other hand, the sensor presented acceptable reliability in determining DA in real samples. A recovery rate between 97.99 and 101.0% was obtained. Overall, controlling the morphology of semiconductors can influence PEC performance, which is a useful finding for the future development of PEC sensors. Graphical Abstract
ISSN:1618-2642
1618-2650
DOI:10.1007/s00216-023-04865-7