Organic Memcapacitors for Large-Area, Neuromorphic Pattern Recognition: Development of an Electronic Trap System



Prof. Frank Ellinger

Chair of Circuit Design and Network Theory , TU Dresden


Dr.-Ing. Bahman Kheradmand Boroujeni

Chair of Circuit Design and Network Theory , TU Dresden


Prof. Stefan Mannsfeld

Center for Advancing Electronics, TU Dresden


Project Description

In this proposal, we want to study the organic circuits integration of a recently developed, novel memory structure, dubbed “pinMOS”, that can be thought of as a hybrid of a conventional p-i-n diode OLED structure and a MOS capacitor. In preliminary experiments we already observe a distinct memcapacitive behavior with a double hysteresis loop in charge-voltage graphs and achieve highly reproducible bias history-dependent capacitive states

With this research, we also want to evaluate and further develop this new device with more complex, system-level applications in mind. In order to accomplish this goal, we will develop this technology in a tight feedback loop between the circuit and device fabrication partner (Mannsfeld) and the device modeling/ circuit design partner (Ellinger, Boroujeni). To steer this research towards a feasible system application, we chose an application that makes use of important technological aspects we want to develop and at the same time bears some societal significance. Since food is always a major need for human life, developing environmentally friendly technologies for enhancing agricultural yields while protecting nature will be a key factor for successful development.

The proposed system requires a large-area, distributed network of nano-Watt event-detector circuits with built-in tracking of the impedance history. Memcapacitors do not require static power like memristors and therefore are excellent memory elements for this purpose. During the phase I of this Priority program, we will focus on the development of the integration of memcapacitors and organic transistors (and passives) to form working event-detector circuits and circuit blocks for neuromorphic pattern-recognition in a single pixel. The circuit functionalities will be modeled using tools such as Verilog-A, circuit simulators, MATLAB, and SystemC; and theoretical optimization studies/simulations will be carried out.

Further involved scientists


Lautaro Petrauskas

Chair of Circuit Design and Network Theory , TU Dresden