A joint international research team has developed ultra-sensitive graphene-based sensors that can detect microwaves with the highest theoretically possible sensitivity.
Currently, microwave power can be detected using a device called bolometer, a device which usually consists of three materials: an electromagnetic absorption material, a material that converts electromagnetic waves into heat, and a material that converts the generated heat into electrical resistance. The bolometer calculates the amount of electromagnetic waves absorbed using the changes in the electrical resistance. Using the semiconductor-based diodes such as silicon and gallium arsenide in the bolometer, the sensitivity of the state-of-the-art commercial bolometer operating at room temperature is limited at 1 nanowatt by averaging for a second.
The research team broke through this limit by innovating the aspect of materials and structure of the device. Firstly, the team used graphene as the material for absorbing electromagnetic waves. Graphene is made up of one layer of carbon atoms and has a very small electronic heat capacity. The small heat capacity signifies that even if little energy is absorbed, it causes a big temperature change. Microwave photons have very little energy, but if absorbed by graphene, they can cause considerable temperature rise. The problem is that the temperature increase in graphene cools down very quickly, making it difficult to measure the change.
To solve this problem, the research team adopted a device called the Josephson junction. This quantum device, composed of Superconductor-Graphene-Superconductor (SGS), can detect temperature changes within 10 picoseconds via an electrical process. This makes it possible to detect the temperature changes in graphene and the resulting electrical resistance.
Combining these key ingredients, researchers reached to develop a device that can resolve 1 aW (1 trillionth of a watt) within a second.
This technology may maximize the measuring efficiency of quantum computing and drastically reduce the indirect resources to enable large-scale quantum computers that will be of great use. (SciTechDaily)
The paper has been published in Nature.