Spatial organization of glucose oxidase and catalase in layered polyethylenimine coated carbon nanotube electrodes affects coupled reaction kinetics and oxygen recycling in glucose biosensors.

Authors

Marcelinus Christwardana, Khanifa Aulia Rakhma, K Khoirunnisa, Cepi Kurniawan, Lina Mahardiani

Published in

Analytica chimica acta. Volume 1424. Pages 346205. Nov 22, 2026. Epub Aug 31, 2026.

Abstract

The buildup of H₂O₂ often diminishes the sensitivity and stability of glucose oxidase (GOx)-based glucose biosensors. This work assessed four carbon nanotubes (CNT) and polyethylenimine (PEI) - based biocatalyst configurations using a layer-by-layer approach (CNT/PEI/GOx; CNT/PEI/GOx-Cat; CNT/PEI/GOx/PEI/Cat; CNT/PEI/Cat/PEI/GOx) to modulate the H₂O₂ diffusion route and O₂ regeneration via catalase (Cat). Voltammetric and amperometric analyses were conducted in 0.1 M phosphate-buffered saline at pH 7.4 (aerobic conditions) at a potential of -0.45 V vs. Ag/AgCl. The optimal configuration was CNT/PEI/GOx/PEI/Cat, exhibiting analytical performance metrics of J_max of 22.0 μA cm^-2, K_m^app of 6.55 mM, sensitivity of 3.34 μA×cm^-2×mM^-1, and LOD of ≈ 44.84 μM. This structure exhibited an active enzyme coverage (as FADH₂) of 16.47 pM·cm^-2 and maintained signal retention of around 90% through the fourth cycle, showing that the rate-limiting factor under amperometric circumstances is governed by the generation, diffusion, and conversion of H₂O₂, as well as the availability of O₂, rather than exclusively by direct electron transfer (DET). Positioning catalase as the topmost layer above GOx (isolated from PEI) efficiently inhibits H₂O₂ buildup next to the electrode while regenerating local O₂, hence optimizing catalytic current and stability. This configuration also achieved the most accurate glucose recovery (average error ∼3%) in spiked solutions containing common electroactive interferents, confirming its practical reliability for complex sample analysis. These results provide a structured framework for the development of more sensitive and resilient glucose biosensors.

PMID:
42887961
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

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