The use of organic materials opens up possibilities in flexible, low-cost and low-energy neuromorphic computing. On top of that, the easy acces to a large linear and symmetric conductance range of these materials and devices offer opportunities for efficient implementation of hardware-based neural networks such as vector-matrix multiplication.
At the moment our research consists of optimising the material systems, stability and processability. At the same time we aim to develop a large (crossbar) array of organic neuromorphic devices to perform some basic neural network calculations. Finally, one of the specific applications could be found in dedicated smart brain-inspired point-of-care devices that can be trained to classify and recognise diseases or cells.