According to the researchers, the technology offers an energy-efficient platform for personal computing and artificial intelligence applications.
The digital revolution that began in the 1950s will soon be replaced by another giant leap in technology based on artificial intelligence and machine learning.
Many researchers are exploring ways to prepare for the upcoming fourth industrial revolution, which will integrate personal computing technologies that are so advanced they will obscure the line between virtual and physical realty.
“It is important for us to understand that the computing platforms of today will not be able to sustain at-scale implementations of AI algorithms on massive datasets,” said study co-author Thirumalai Venkatesan.
“Today’s computing is way too energy-intensive to handle big data. We need to rethink our approaches to computation on all levels: materials, devices and architecture that can enable ultralow energy computing.”
Venkatesan explained that brain-inspired electronics with organic memristors could offer a functionally promising and cost-effective platform.
Memristive devices possess an inherent memory and are capable of both storing data and retaining memory even without power. Memristors function in much the same way as neurons, the computing units in the brain, and the devices are the perfect candidates for personalized computing platforms.
“Over the last 20 years, there have been several attempts to come up with organic memristors, but none of those have shown any promise,” said study lead author Sreetosh Goswami. “The primary reason behind this failure is their lack of stability, reproducibility and ambiguity in mechanistic understanding. At a device level, we are now able to solve most of these problems.”
The new organic memristors are based on metal azo complex devices, which were developed by study co-author Professor Sreebata Goswami.
“In thin films, the molecules are so robust and stable that these devices can eventually be the right choice for many wearable and implantable technologies or a body net, because these could be bendable and stretchable,” said Professor Goswami.
According to Venkatesan, the next challenge will be to produce these organic memristors at scale.”Now we are making individual devices in the laboratory. We need to make circuits for large-scale functional implementation of these devices.”
The research is published in the journal Applied Physics Reviews.