Researchers are creating efficient systems using neural networks and charge density waves to reduce supercomputing's massive energy use.
An ultrafast electron microscope was used to observe nanosecond dynamics in 1T-TaS2, a tantalum sulfide with charge density waves at room temperature.Researchers have made use of novel ultrafast electron microscopy techniques to track millisecond changes in a material during electrical pulsing.
According to the team, the “melting response mimics how neurons are activated in the brain, while the vibrational response could generate neuron-like firing signals in a neural network,” said Daniel Durham, a postdoctoral researcher at ANL, in aSupercomputers of today need so much energy that it would be enough to power thousands of households. In response, scientists are using artificial
The resistance to electron mobility in the material is increased by the charge density waves. The resistance could be turned on and off quickly if the waves could be controlled. The team attached two electrodes to a flake of 1T-TaS2 to generate electrical pulses. Contrary to previous assumptions, the ultrafast electron microscope revealed two unexpected findings.melted due to the heat from the injected current, rather than the charge current itself, even during nanosecond pulses. Second, the electrical pulses induced drum-like vibrations in the material, altering the arrangement of the waves.
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