ORGS4-0999
Cumulative sensing of low-level chemical analytes based on dual-mode organic electrochemical platform
Topic
GS4. Graduate Student Oral Session IV: Polymers for Electronics, Photonics, and Energy
When and Where
Sep 28, 2026
15:00 - 15:12
Room 104
Session Chairs
Hobeom KIM
Giwon LEE
Hyeong Jun KIM
Presenter(s)
Elvis K. Boahen (Hanyang University)
Co-Author(s)
Abstract
Hazardous chemical analytes such as nitrogen dioxide (NO2) can cause serious respiratory issues with prolonged exposure, even at low concentrations. However, existing gas sensors based on field-effect transistors (FETs), optimized for the detection of high gas concentrations, lack the required memory functionalities necessary for recognizing cumulative exposure to low concentrations. Moreover, they exhibit high power consumption, restricting their use in wearable technologies. Organic electrochemical transistor (OECT)-based sensors on the other hand, can monitor and record cumulative gas exposures while operating under low voltage conditions. However, current OECT-based sensors are limited by poor responsivity and high limit of detection, primarily due to the need for high doping thresholds to trigger electrochemical doping in the semiconductor channel.
Here, we present a dual-mode OECT-based chemosensory platform, designed to resolve both instantaneous NO2 concentrations and cumulative exposure. The sensor features two distinct interfacial modes, each capable of interacting with gas molecules, producing a coupled response under exposure. This configuration enables the detection of trace NO2 concentrations down to 100 ppb while retaining sensitivity to exposure history owing to excellent memory capability (> 1 h). In parallel, a machine learning-based classification framework is employed to quantify cumulative exposure under dynamic conditions. As a demonstration, a wearable sensing bracelet incorporating a 3 x 3 array is integrated with a Bluetooth-enabled system to provide real-time alerts when accumulated NO2 exposure exceeds recommended safety threshold.
Here, we present a dual-mode OECT-based chemosensory platform, designed to resolve both instantaneous NO2 concentrations and cumulative exposure. The sensor features two distinct interfacial modes, each capable of interacting with gas molecules, producing a coupled response under exposure. This configuration enables the detection of trace NO2 concentrations down to 100 ppb while retaining sensitivity to exposure history owing to excellent memory capability (> 1 h). In parallel, a machine learning-based classification framework is employed to quantify cumulative exposure under dynamic conditions. As a demonstration, a wearable sensing bracelet incorporating a 3 x 3 array is integrated with a Bluetooth-enabled system to provide real-time alerts when accumulated NO2 exposure exceeds recommended safety threshold.
