graphene-based memory resistor (memristor) that can exist in many different states has been designed and demonstrated by Thomas Schranghamer, Aaryan Oberoi and Saptarshi Das at Pennsylvania State University in the US.

Using simulations and experiments, the team showed how the device can be used to substantially improve the performance of artificial neural networks – systems that could someday rival and even replace conventional computers.

Despite decades of relentless growth, advances in the semiconductor technologies used in digital computing are showing clear signs of slowing down. To keep up with a growing demand for computing power, researchers are developing new technologies that mimic the operation of neurons the human brain – which perform both the storage and processing of information. This has the potential of being much more efficient than current computer architectures, which require both time and energy to shuttle data between separate storage and processing components.

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