Transistors cannot enable very low-power IoT, could memristors do the job?

January 18, 2018 // By Jean-Pierre Joosting
The Internet of Things is on the horizon but handling the explosion of data that will follow poses a huge challenge, with predictions of 50 billion industrial internet sensors in place by 2020. Not all these sensors are low data rate – a single autonomous device – a smart watch, a cleaning robot, or a driverless car – can produce gigabytes of data each day, whereas an airbus may have over 10 000 sensors in one wing alone.

To build the IoT as envisioned by the the industry, power as well as data storage and analysis are key. Transistor-based technology faces two huge hurdles. First, current transistors in computer chips must be miniaturized to the size of only few nanometres – but at this line width they dont work anymore. Second, analysing and storing unprecedented amounts of data will require equally huge amounts of energy.

Sayani Majumdar, Academy Fellow at Aalto University, along with her colleagues, is designing technology to tackle both issues and create the basic building blocks for the components that will comprise future "neuromorphic" computers. It's a field of research on which the largest ICT companies in the world and also the EU are investing heavily.

"The technology and design of neuromorphic computing is advancing more rapidly than its rival revolution, quantum computing. There is already wide speculation both in academia and company R&D about ways to inscribe heavy computing capabilities in the hardware of smart phones, tablets and laptops. The key is to achieve the extreme energy-efficiency of a biological brain and mimic the way neural networks process information through electric impulses," explains Majumdar.

In their recent article in Advanced Functional Materials, Majumdar and her team show how they have fabricated a new breed of "ferroelectric tunnel junctions", that is, few-nanometre-thick ferroelectric thin films sandwiched between two electrodes. They have abilities beyond existing technologies and bode well for energy-efficient and stable neuromorphic computing.


The probe-station device (the full instrument, left, and a closer view of the device connection, right) which measures the electrical responses of the basic components for computers mimicking the human brain. The tunnel junctions are on a thin film on the substrate plate. Image courtesy of Tapio Reinekoski.


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