Supercurrent diodes in disordered quantum materials

Project funded by Research Council of Finland, grant 355056. Participating organisations named by the source: University of Jyväskylä. Funded amount: EUR 549,753, as stated by the source. Runs 2023-09-01 to 2027-08-31. Keywords: Physical sciences. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-07-23); national funding data, not CORDIS. Abstract given by the source: This project, carried out at the Condensed Matter Theory group of JYU, will theoretically investigate the recently discovered supercurrent diode effect (SDE) in new quantum materials. This effect shows up via a non-reciprocal current flow when both time-reversal and inversion symmetries are broken in the superconductor: supercurrent can flow in one direction, whereas only a regular dissipative Ohmic current can flow in the other. SDE is a useful new tool to probe microscopic properties of superconductors by simple electrical measurements, and it has a potential to provide a building block for the new generation of cryogenic electronics. SDE is currently a topic at the forefront of research in condensed matter physics. It is observed in a handful of systems, but many of its aspects are currently poorly understood. Our results will contribute to filling this knowledge gap, and will be of direct relevance for realization of new quantum technologies based on SDE.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Research Council of Finland. Retrieved 2026-10-28. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: Project funded by Research Council of Finland, EUR 549,753, 2023-2027. Investigates supercurrent diode effect in quantum materials at University of Jyväskylä. Suggested technology pillar: enabling. Generated by AI from the public source text; it may contain errors and the original source is authoritative.