Am Montag, den 11. Dezember 2023, um 12:00 Uhr c.t., findet der nächste Termin unseres Physikalischen Kolloquiums statt.
Referent ist Prof. Dr. Miguel Marques (RUB) zum Thema „Machine Learning Conventional Superconductors“.
We perform a large scale study of conventional superconducting materials using a machine-learning accelerated high-throughput workflow. We start by creating a comprehensive dataset of around 7000 electron-phonon calculations performed with reasonable convergence parameters. This dataset is then used to train a robust machine learning model capable of predicting the electron-phonon and superconducting properties based on structural, compositional, and electronic ground-state properties. Using this machine, we evaluate the transition temperature (Tc) of approximately 200000 metallic compounds, all of which on the convex hull of thermodynamic stability (or close to it) to maximize the probability of synthesizability. Compounds predicted to have Tc values exceeding 5 K are further validated using density-functional perturbation theory.
As a result, we identify 541 compounds with Tc values surpassing 10 K, encompassing a variety of crystal structures and chemical compositions. We also identified a series of (thermodynamically unstable) hydride compounds that superconduct at temperatures reaching more than 80 K at ambient pressure.
Abstract des Vortrags von Prof. Marques
Die Einführung erfolgt durch Prof. Dr. Ilya Eremin.
Die Fakultät lädt alle Interessierten herzlich ein. Die Veranstaltung findet im Hörsaal HZO 20 statt. Vor dem Kolloquium bieten wir Ihnen Kaffee und Kekse an.
Alle Termine des Physikalischen Kolloquiums finden Sie hier.