An Indian academic fellow has designed thin organic films which can take data for more than 10 years

Owing to data explosion which comes with Internet of Things, this academic fellow develops ultrathin films which can store unprecedented amount of data

An Indian-origin academy fellow has designed and fabricated easily printable, organic thin films that can retain data for more than 10 years without power, work with low voltages and handle the data explosion that comes with Internet of Things (IoT).

Representational image. Reuters.

Representational image. Reuters.

According to a study published in Advanced Functional Materials journal, these films can become the building block of future computers that mimic the human brain.

Sayani Majumdar from Aalto University, Finland, along with her colleagues, is designing this technology to reduce the dependency on current transistors in computer chips that won't work in future.

Secondly, these films do not require huge amount of energy to analyse and store unprecedented amounts of data.

"The technology and design of neuromorphic computing is advancing more rapidly than its rival revolution, quantum computing," explains Majumdar.

"The key is to achieve the extreme energy-efficiency of a biological brain and mimic the way neural networks process information through electric impulses," she added.

These "ferroelectric tunnel junctions" have a nano-scale hardware architecture that could be scaled to industrial manufacture and use and can be sandwiched between two electrodes.

The junctions work in low voltages of less than five volts and with a variety of electrode materials, including silicon used in chips in most of our electronics.

"Our junctions are made out of organic hydro-carbon materials and they would reduce the amount of toxic heavy metal waste in electronics. We can also make thousands of junctions a day in room temperature without them suffering from the water or oxygen in the air," Majumdar said.

"We are no longer talking of transistors, but 'memristors'. They are ideal for computation similar to that in biological brains," she added.

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