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IMAGE: The postage-stamp sized chip at the heart of an iPhone 5 has around one billion transistors. view more
Credit: Errol Hunt (FLEET)
New FLEET research confirms the potential for topological materials to substantially reduce the energy consumed by computing.
The collaboration of FLEET researchers from University of Wollongong, Monash University and UNSW have shown in a theoretical study that using topological insulators rather than conventional semiconductors to make transistors could reduce the gate voltage by half, and the energy used by each transistor by a factor of four.
To accomplish this, they had to find a way to overcome the famous Boltzmann s tyranny that puts a lower limit on transistor switching energy.
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Credit: FLEET
Just as James Cameron s Terminator-800 was able to discriminate between clothes, boots, and a motorcycle , machine-learning could identify different areas of interest on 2D materials.
The simple, automated optical identification of fundamentally different physical areas on these materials (eg, areas displaying doping, strain, and electronic disorder) could significantly accelerate the science of atomically-thin materials.
Atomically-thin (or 2D) layers of matter are a new, emerging class of materials that will serve as the basis for next-generation energy-efficient computing, optoelectronics and future smart-phones. Without any supervision, machine-learning algorithms were able to discriminate between differently perturbed areas on a 2D semiconducting material, explains lead author Dr Pavel Kolesnichenko. This can lead to fast, machine-aided characterization of 2D materials in the future, accelerating application of these materials in next-generation low-energy