Adaptive Biosensing and Neuromorphic Classification Based on an Ambipolar Organic Mixed Ionic–Electronic Conductor. Issue 20 (17th April 2022) - Zhang, Yanxi; van Doremaele, Eveline R. W.; Ye, Gang; Stevens, Tim; Song, Jun; Chiechi, Ryan C.; van de Burgt, Yoeri
Abstract: 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. Abstract : An adaptive neuromorphic sensor system can locally process and classify biosignals based on a single high‐performance material. This material is an organic mixed ionic–electronic conductor (OMIEC) based on a conjugated polymer P‐3O, exhibiting exceptional ambipolar transistor properties and high stability. This versatile material enables straightforward fabrication and integration of electronic components, including transistors, ambipolar inverters, memory devices, and dopamine sensors.