2D material helps new computer chip process and store data like a neuron

Engineers at EPFL have created a new computer chip that can both process and store data in the same circuit. It’s made using a two-dimensional material called molybdenum disulfide (MoS2), paving the way for smaller and more energy efficient electronics.

Traditional computers process data in one area – the CPU – then pass it off to another section, such as a hard disk or solid state drive, for storage. This system has worked for us for decades, but it’s not necessarily the most efficient way to do things.

For instance, in the brain – the most powerful computer in the world – neurons have the ability to both process and store information. In recent years engineers have tried to mimic this functionality, creating chips with logic-in-memory architecture, sometimes known as “memristors.” The idea is that without the need to shuttle data around so much, we could make smaller and faster devices that chew up less energy.

The EPFL study takes some new steps towards that goal. The team’s new logic-in-memory chip is the first to be made with a 2D material, comprising a single layer of MoS2 that’s just three atoms thick. Not only is this material’s ultra thinness perfect for shrinking devices down, but it makes a great semiconductor as well.

EPFL's new computer chip is made with a two-dimensional sheet of molybdenum disulfide that's just three atoms thick
EPFL’s new computer chip is made with a two-dimensional sheet of molybdenum disulfide that’s just three atoms thick


The new chip is what’s known as a floating-gate field-effect transistor (FGFET). Usually used in flash memory systems, such as SD cards, these transistors are good at retaining electric charges for long periods of time. MoS2 is particularly sensitive to these stored charges, allowing it to perform both logic and memory functions.

“Our circuit design has several advantages,” says Andras Kis, lead author of the study. “It can reduce the energy loss associated with transferring data between memory units and processors, cut the amount of time needed for computing operations and shrink the amount of space required. That opens the door to devices that are smaller, more powerful and more energy efficient.”

The research was published in the journal Nature.

Source: EPFL

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