A material identified as a potential superconductor by the screening process.In materials science, a 'candidate' is a substance that shows promising properties for a specific application but has not yet been fully verified. In the context of superconductivity, a candidate might be a new compound that exhibits a drop in electrical resistance at low temperatures, but where the effect is not yet confirmed to be true superconductivity. The screening process involves computational and experimental methods to identify such candidates from a large pool of possibilities.
The concept of a 'candidate' in this sense is as old as materials discovery itself, but the systematic high-throughput screening of materials for superconductivity gained momentum in the 2000s with the advent of computational databases and machine learning.
The screening process typically starts with computational predictions — using density functional theory or machine learning to estimate a material's electronic structure and potential for superconductivity. Promising candidates are then synthesized and tested experimentally. Measurements of resistivity, magnetic susceptibility, and heat capacity are used to confirm whether the material truly enters a superconducting state, characterized by zero resistance and the Meissner effect.
Candidate screening is used in the search for room-temperature superconductors, better battery materials, and more efficient catalysts.
The first cuprate superconductor, discovered in 1986, was initially a candidate that took several years to be fully confirmed as a true superconductor.





