NANOPARTICLE ORGANIC MEMORY FIELD-EFFECT TRANSISTOR

For the first time, CNRS (Centre National de la Recherche Scientifique; National Center for Scientific Research) and CEA researchers have developed a unique transistor that can simulate the main functionalities of a synapse.

This organic transistor, based on pentacene and gold nanoparticles and known as a NOMFET (Nanoparticle Organic Memory Field-Effect Transistor), has revolutionized modern computing world and inspired the researchers to create new generations of neuro-inspired computers, capable of responding in a manner similar to the nervous system.

In the development of new information processing strategies, one approach consists in mimicking the way biological systems such as neuron networks operate to produce electronic circuits with new features. In the nervous system, a synapse is the junction between two neurons, enabling the transmission of electric messages from one neuron to another and the adaptation of the message as a function of the nature of the incoming signal. For example, if the synapse receives very closely packed pulses of incoming signals, it will transmit a more intense action potential. Conversely, if the pulses are spaced farther apart, the action potential will be weaker. It is exactly the nature what researchers succeeded to have copied in the NOMFET.

A transistor, the basic building block of an electronic circuit, can be used as a simple switch - it can then transmit, or not, a signal - or instead offer numerous functionalities for example :amplification, modulation, encoding, etc.

The innovation of the NOMFET resides in the original combination of an organic transistor and gold nanoparticles. These encapsulated nanoparticles, fixed in the channel of the transistor and coated with pentacene, have a memory effect that allows them to transmit in a way a synapse does during the transmission of action potentials between two neurons. This property therefore makes the electronic component capable of evolving as a function of the system in which it is placed. Its performance is comparable to the seven CMOS transistors that have been needed until now to achieve this plasticity.

The devices produced have been optimized to nanometric sizes in order to be able to integrate them on a large scale. Neuro-inspired computers, produced using this technology, are capable of functions comparable to those of the human brain.

Unlike silicon computers, widely used in high performance computing, neuro-inspired computers can resolve much more complex problems, such as visual recognition.