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.
author keywords: adaptive sensing; ambipolar inverters; neuromorphic computing; organic mixed ionic-electronic conductors
MeSH headings : Biosensing Techniques; Electronics; Ions; Polymers; Transistors, Electronic
open access via onlinelibrary.wiley.com (publisher PDF)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(Web of Science)
Source: Web Of Science
Added: May 2, 2022
AbstractOrganic 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.