Work

An Empirical Model of Ion‐Selective Organic Electrochemical Transistors

Year: 2025

Type: article

Abstract: Frequent monitoring of body fluids such as blood, sweat, saliva, and urine is essential for the early detection of various diseases. Ion‐selective organic electrochemical transistors (IS‐OECTs) offer a low‐cost, highly sensitive, and easily fabricated platform for detecting ion concentration changes. Their inherent flexibility and biocompatibility make them well‐suited for integration into wearable systems for continuous, point‐of‐care health monitoring. However, optimizing IS‐OECT design and circuit performance requires accurate modeling of their concentration‐dependent behavior, which is complicated by complex electrochemical interactions and charge transport dynamics. In this work, it introduces an empirical model that extends the Friedlein framework to incorporate ion concentration effects, enabling accurate prediction of steady‐state device characteristics in the presence of both target and interfering ions. Validation of this model with IS‐OECTs fabricated to detect ammonium (NH 4 ⁺) and sodium (Na⁺) ions shows an excellent agreement with experimental measurements, underscoring its reliability for electrochemical sensing applications.

Source: Advanced Materials Technologies

DOI: 10.1002/admt.202501217

Authors: Shishir Deb Nath, Pinok Chowdhury Manik, Mohammad Shafiqul Islam, Mainul Hossain, Yasser Khan

Institutions: Bangladesh University of Engineering and Technology, University of Dhaka, University of Southern California

Language: English

Topic: Conducting polymers and applications

Subfield: Polymers and Plastics

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funder: National Institutes of Health

Award: Novel multimodal neural, physiological, and behavioral sensing and machine learning for mental states