Sensing of KCl, NaCl, and Pyocyanin with a MOF-Decorated Electrospun Nitrocellulose Matrix

• Published in: ACS applied nano materials Vol. 6; no. 4; pp. 2854 - 2863
• Main Authors: Lüder, Lars, Nirmalraj, Peter Niraj, Neels, Antonia, Rossi, René Michel, Calame, Michel
• Format: Journal Article
• Language: English
• Published: American Chemical Society 24.02.2023
• Subjects: nanoscale; wearable sensor; Raman spectroscopy; electrospinning; metal−organic frameworks; particle integration
• ISSN: 2574-0970; 2574-0970
• DOI: 10.1021/acsanm.2c05252

Wearable sensors can provide important insight into a patient’s health status by monitoring the concentration of specific biomarkers in body fluids. Compared to biofluids such as blood or cerebrospinal fluid, which require an invasive acquisition process, other body fluids such as sweat or exhaled air can be easily collected using patches or masks, sufficient for the detection of metabolic and pathological changes. However, the successful integration of an efficient biosensor into textiles or polymer substrates is a challenge if flexibility and functionality are not to be compromised. Here, we demonstrate the integration of nanoporous metal–organic framework (MOF) particles with nitrocellulose (NC) fibrous layers using an electrospinning approach and validate the efficiency of our MOF@NC structure as biosensors. The chemical response of this hybrid nanomaterial upon exposure to different ionic sweat biomarkers such as NaCl and KCl as well as pyocyanin, a biomarker for the nosocomial pathogen Pseudomonas aeruginosa, was investigated using Raman spectroscopy. A change of the Raman intensity at distinct peaks of our MOF-containing architecture occurs after treatment of the material with the analyte solutions. Furthermore, we observed the sensitivities for pyocyanin at the normalized Raman intensity change to be up to −1120 au μm–1, about 4 orders of magnitude larger than for NaCl and KCl. The independence of our architecture from the type of MOF and the possibility of using different MOFs with individual chemistry make this approach a promising platform for versatile and adaptable sensing of biomarkers with high sensitivity and selectivity.