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Enzyme immobilized multi-walled carbon nanotubes on paper-based biosensor fabricated via mask-less hydrophilic and hydrophobic microchannels for cholesterol detection
- Publication Year :
- 2022
-
Abstract
- Despite the low cost of paper substrates, the lack of appropriate device fabrication techniques has hampered the overall efficacy of paper-based sensors. Addressing this issue, in this work, we develop a multi-walled carbon nanotube (MWCNTs) coated paper substrate-based biosensor using a novel method of wax deposition followed by vacuum filtration to design dedicated hydrophobic and hydrophilic channels for label-free, highly selective, and sensitive detection of cholesterol. Detailed morphological characterization studies reveal the uniform deposition of MWCNTs on the paper substrate (∼15–20 nm average diameter). Upon exposure to cholesterol, an excellent dynamic range of response over three orders of magnitude from 10 nM −75 µM and 100 µM–8 mM concentration range with a limit of detection of 3.2 nM (3 S/m) was obtained. The Michaelis–Menten constant (Km) was found to be 0.0093 µM. In addition, the fabricated biosensor exhibited excellent reproducibility, stability and high specificity to cholesterol with negligible response from interfering analytes. The excellent response of the fabricated biosensor can be attributed to the modulation of electrical properties due to electrostatic gating effect and direct electron transfer between MWCNTs and cholesterol due to the bioconjugation of Cholesterol oxidase (ChOx). The strategy employed here addresses some major challenges faced by the current methods of using rigid substrates and liquid electrolyte based analytical methods for detection of cholesterol. Furthermore, the sensor could successfully measure concentrations of cholesterol in saliva. This work provides a promising platform for developing low cost, interference free, disposable paper-based biosensors for point of care diagnostics. © 2022 The Korean Society of Industrial and Engineering Chemistry
Details
- Database :
- OAIster
- Notes :
- text, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1345036867
- Document Type :
- Electronic Resource