ArNeBOT - Artificial Neurons Based on Organic Electrochemical Transistors

• Applicants: Dr. Hans Kleemann; Dr.-Ing. Christian Matthus
• Subject Area: Experimental Condensed Matter Physics ; Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 522208759

ArNeBOT aims to demonstrate the first hardware implementation of advanced bio-inspired artificial spiking neuron (ASN) based on organic electrochemical transistors (OECT). We will describe the biomimetic properties of OECTs with a physics-based model serving as a starting point for modeling advanced bio-inspired neuron models based on sets of differential equations. This neuron model will be translated into a circuit design using the complementary OECT technology with an adjustable threshold voltage. We will demonstrate that such spiking neurons can show complex and adjustable excitation patterns (class 1 & class 2) as well as low power consumption (energy per spike). Ultimately, we will integrate the bio-inspired neuron into a spiking neural network (SNN) and carry out standardized classification tasks (e.g., heartbeat classification and time-series prediction) to underline the computation power of such networks. More specifically, we define the following three objectives for the project: (1) Understanding the device physics behind the biomimetic operation of OECTs. (2) Implement an advanced, bioinspired spiking neuron model based on a physics-based OECT model. (3) Demonstrate the first hardware implementation of a bioinspired artificial neuron with an adjustable state of excitability and superior power efficiency.

• DFG Programme: Research Grants