Reusable interface-decoupled organic photoelectrochemical transistor biosensing for acetylcholinesterase activity and its inhibitor detection

Abstract

Organic photoelectrochemical transistors (OPECTs) have garnered considerable attention in next-generation bioanalysis, offering inherent signal amplification and facile integration with diverse recognition elements. However, their practical application remains hindered by issues such as irreversible physicochemical alterations, electrode fouling, and limited reusability in complex biological matrices. Herein, we propose an innovative interface-decoupled organic photoelectrochemical transistor (ID-OPECT) sensor featuring an external photon-gating module for highly responsive and reusable biodetection. This physical decoupling strategy allows the colorimetric reaction to occur independently from the photogate interface, which not only achieves effective photon filtering to modulate the photoelectric response but also preserves the photosensitive surface from interference and contamination, thereby enabling repeated use. By integrating an I2-starch colorimetric module coupled with a multi-enzyme cascade, the incident light transmission can be modulated in response to acetylcholinesterase (AChE) activity and its inhibition by chlorpyrifos (CPF). Under optimized conditions, the developed ID-OPECT platform enables sensitive detection of AChE and CPF, with limits of detection of 14.60 U•L -1 and 16.94 ppb, respectively, by monitoring distinct channel current responses. This work presents a conceptually new paradigm for designing advanced optoelectronic sensors with enhanced stability and reusability.

Supplementary files

Article information

Article type
Paper
Submitted
23 Mar 2026
Accepted
15 Apr 2026
First published
17 Apr 2026

Analyst, 2026, Accepted Manuscript

Reusable interface-decoupled organic photoelectrochemical transistor biosensing for acetylcholinesterase activity and its inhibitor detection

H. Lin, H. Cai, H. Xiong, J. Sun, D. Han, F. Chen and C. Huang, Analyst, 2026, Accepted Manuscript , DOI: 10.1039/D6AN00315J

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