Scientists have developed a novel transistor based on organic materials that has the ability to learn, paving the way for technology that mimics the human brain.
The transistor developed by scientists at Linkoping University in Sweden is equipped with both short-term and long-term memory. Until now, brains have been unique in being able to create connections where there were none before.
In the organic electrochemical transistor that the researchers have developed, the channel in the transistor consists of an electropolymerised conducting polymer. The channel can be formed, grown or shrunk, or completely eliminated during operation.
It can also be trained to react to a certain stimulus, a certain input signal, such that the transistor channel becomes more conductive and the output signal larger.
“It is the first time that real time formation of new electronic components is shown in neuromorphic devices,” said Simone Fabiano, from Linkoping University.
By changing the input signal, the strength of the transistor response can be modulated across a wide range, and connections can be created where none previously existed. This gives the transistor a behavior that is comparable with that of the synapse, or the communication interface between two brain cells.
It is also a major step towards machine learning using organic electronics. Software-based artificial neural networks are currently used in machine learning to achieve what is known as “deep learning”.
Software requires that the signals are transmitted between a huge number of nodes to simulate a single synapse, which takes considerable computing power and thus consumes considerable energy.
“We have developed hardware that does the same thing, using a single electronic component,” said Gerasimov.
“Our organic electrochemical transistor can therefore carry out the work of thousands of normal transistors with an energy consumption that approaches the energy consumed when a human brain transmits signals between two cells,” said Fabiano.