2022 article

Adaptive Biosensing and Neuromorphic Classification Based on an Ambipolar Organic Mixed Ionic-Electronic Conductor

Zhang, Y., Doremaele, E. R. W., Ye, G., Stevens, T., Song, J., Chiechi, R. C., & Burgt, Y. (2022, April 17). ADVANCED MATERIALS.

co-author countries: China 🇨🇳 Netherlands 🇳🇱 United States of America 🇺🇸
author keywords: adaptive sensing; ambipolar inverters; neuromorphic computing; organic mixed ionic-electronic conductors
MeSH headings : Biosensing Techniques; Electronics; Ions; Polymers; Transistors, Electronic
Source: Web Of Science
Added: May 2, 2022

Organic mixed ionic-electronic conductors (OMIECs) are central to bioelectronic applications such as biosensors, health-monitoring devices, and neural interfaces, and have facilitated efficient next-generation brain-inspired computing and biohybrid systems. Despite these examples, smart and adaptive circuits that can locally process and optimize biosignals have not yet been realized. Here, a tunable sensing circuit is shown that can locally modulate biologically relevant signals like electromyograms (EMGs) and electrocardiograms (ECGs), that is based on a complementary logic inverter combined with a neuromorphic memory element, and that is constructed from a single polymer mixed conductor. It is demonstrated that a small neuromorphic array based on this material effects high classification accuracy in heartbeat anomaly detection. This high-performance material allows for straightforward monolithic integration, which reduces fabrication complexity while also achieving high on/off ratios with excellent ambient p- and n-type stability in transistor performance. This material opens a route toward simple and straightforward fabrication and integration of more sophisticated adaptive circuits for future smart bioelectronics.