Are there any High-Throughput studies that aim to discover High Tc superconductors?

Question

High-Throughput materials modeling based on Density Functional Theory has become very popular recently. If, for example, we search "High-Throughput Perovskites" in Google Scholar, we get over ~14,000 results. Not all are computational and not all are peer-reviewed publications but it shows just how important High Performance Computing is in current materials research. Needless to say, The Materials Project and AFLOW are big players in the High-Throughput Materials Simulation game. There is even a database for Topological Insulators and Weyl Semimetals

However I am not aware of a database or High-Throughput study that is completely focused on the discovery of high $T_C$ superconductors. Can anyone point me toward some references? Are there any studies of this kind at all?

Answer 1

There are several such studies, particularly focusing on the machine-learning of critical temperatures.

• "Machine learning modeling of superconducting critical temperature"
• "An acceleration search method of higher T c superconductors by a machine learning algorithm"
• "Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery"

They all rely on the "Supercon" database of ~12,000 critical temperatures, which has also been extracted as supporting information for the first paper to GitHub.

In general, the ML methods offer suggestions for new compositions, but I'm not sure if any have yet been attempted.