Electrochemical transistor resonance spectroscopy

Abstract

With the rise of smartphones and mobile devices, wearable sensors have garnered significant attention for their crucial role in enabling pervasive health monitoring. These devices not only mitigate the challenges of over-centralized and unequally distributed clinical resources but also provide valuable insights into real-time personal health condition. Moreover, wearable sensors serve as essential tools for generating datasets critical for building large-health-models in AI-driven medicine. Early advancements in wearable technology primarily focused on tracking movement and vital signs, such as step count, calorie expenditure, blood oxygen saturation, and heart rate. However, in recent years, wearable devices have evolved beyond tracking easily accessible physical activities to addressing critical healthcare challenges, such as cardiovascular disease prediction, cancer screening, metabolic disorder management, epidemiological control, and remote monitoring of the elderly. To meet these demands, there has been a growing research focus on wearable biochemical sensors, which integrate biorecognition elements (e.g., enzymes, antibodies, aptamers) with electrochemical, optical, or acoustic detection mechanisms. Despite significant progress, the field still faces challenges in achieving high sensitivity and specificity, particularly for biomarkers present in extremely low concentrations (pM to fM range), such as insulin and viral proteins. Organic electrochemical transistors (OECTs) have emerged as promising candidates for biosensing applications due to their ability to amplify signals directly within sensors. However, existing OECT-based sensors have shown mixed results and face challenges in achieving widespread adoption, primarily due to three major obstacles: (i) the absence of miniaturized readout systems tailored for wearable applications; (ii) the lack of large-scale, and cost-effective fabrication techniques for flexible OECT circuits, and (iii) the lack of standardized operational methods. To address these challenges, this thesis first introduces a fully integrated miniaturized analytical unit, the Personalized Electronic Reader for Electrochemical Transistors (PERfECT), for wireless characterizations of OECTs. PERfECT matches the performance of laboratory-scale equipment and is capable of measuring characteristics such as transfer, output, hysteresis, transient, and, most importantly, the ETRS with high resolution and sampling rate. Notably, PERfECT provides a critical missing component for the development of coin-sized ETRS systems for real-world wearable applications. Next, this thesis presents a scalable, low-cost fabrication strategy for flexible OECT circuits, facilitating their practical deployment. This approach combines flexible printed circuit board technology with inkjet printing, enabling high-yield and mass production of all-solid-state OECT circuits. Additionally, the introduction of ionic gels enhances device stability, enabling OECT circuits to serve as robust platforms for neuromorphic in-sensor computing applications. Finally, this thesis explores Electrochemical Transistor Resonance Spectroscopy (ETRS)—a novel electrochemical sensing concept that consolidates multiple characterization techniques into a single process. ETRS achieves unprecedented sensitivity by identifying a resonance frequency specific to each analyte through wide-range frequency scanning. This resonance represents the optimal synergy between sensing electrodes and semiconducting channels, enabling an ultra-low detection limit compared to conventional electrochemical methods. In summary, this thesis presents a systematic and comprehensive study of ETRS. The advancements collectively pave the way for next-generation wearable bioelectronics, facilitating real-time, high-sensitivity, AI-driven digital healthcare.