A mesh network of MnO nanowires and CNTs reinforced by molecularly imprinted structures for the selective detection of para-nitrophenol

Advanced material architecture can be used to develop tailor-made interfaces for innovative and selective sensor platforms. An intricate mesh structure of manganese oxide nanowires and carbon nanotubes was synthesized. Further, the mesh was strengthened by a molecularly imprinted network to generate template cavities and impart selective recognition. Termed as MIP@MnO:CNT, this mesh structure was used as the receptor interface for microarray transducers. The unique hybrid composition and morphology enhanced binding performance for detection of para-nitrophenol (P-NP), an important pollutant. The sensor showed exceptional sensitivity towards P-NP monitoring with a limit of detection of 3 nM (S/N = 3). Benefitted from the imprinting strategy, the designed sensor exhibited 85–99% selectivity when compared to other aromatic compounds. Moreover, the designed interface was able to detect P-NP in water samples. As demonstrated in this study, other chemical compositions and morphology of multi-dimensional materials can be crafted for the improved and specific detection of analytes.