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Thick nanoporous matrices of polystyrene nanoparticles and their potential for electrochemical biosensing
- 1.0539868 - ÚIACH 2022 RIV GB eng J - Journal Article
Sopoušek, J. - Humlíček, J. - Hlaváček, Antonín - Horáčková, V. - Skládal, P. - Lacina, K.
Thick nanoporous matrices of polystyrene nanoparticles and their potential for electrochemical biosensing.
Electrochimica acta. Roč. 368, FEB (2021), č. článku 137607. ISSN 0013-4686. E-ISSN 1873-3859
R&D Projects: GA ČR(CZ) GJ18-03367Y
Institutional support: RVO:68081715
Keywords : nanoparticles * multilayers * thin film interference * Biosensing
OECD category: Analytical chemistry
Impact factor: 7.336, year: 2021
Method of publishing: Limited access
Solid-state nanopores with diameter in units of nanometer can be formed by assembling spherical nanoparticles in a dense arrangement. In the current work, the properties of multi-layered highly ordered assemblies of polystyrene nanoparticles were studied, and their feasibility for electrochemical biosensing was probed. These thick matrices were built using a step-by-step deposition technique. Each individual layer of NPs exhibited distinct color which was caused by the thin film interference effect (a color of specific wavelength was characteristic for matrix of specific thickness). The electrochemical characteristics of matrices were investigated with impedance spectroscopy. The impedance spectra of multi-layered matrices exhibited formation of an additional semicircle (RC component additional to the one in a common Randles equivalent circuit). Further, model biosensing based on nanopore blocking was performed using human serum albumin as an antigen and the corresponding monoclonal antibody as an analyte (serology format). Resulting data disfavored the direct employment of the multi-layered matrices for biosensing purposes as the efficiency decreased with increasing thickness of matrices. However, the data revealed highly valuable information about the diffusion and redox processes in the thick nanoporous matrices. (C) 2020 Elsevier Ltd. All rights reserved.
Permanent Link: http://hdl.handle.net/11104/0317566
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