Ajinkya C. Hire

Jan 8, 2025 | nature.com | Jason Gibson |Ajinkya C. Hire |Philip Dee |Benjamin P. Geisler |Peter Hirschfeld

AbstractIntegrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research, where the primary challenge lies in the computational intensity of calculating the electron-phonon spectral function, α2F(ω), the essential ingredient of Midgal-Eliashberg theory of superconductivity. To overcome this challenge, we adopt a two-step approach. First, we compute α2F(ω) for 818 dynamically stable materials.