23 citations · 23 across the 7 of their papers we have counts for
5 papers · 1 filter
AI-Driven Expansion and Application of the Alexandria Database
Théo Cavignac, Jonathan Schmidt, Pierre-Paul De Breuck +9
We present a novel multi-stage workflow for computational materials discovery that achieves a 99% success rate in identifying compounds within 100 meV/atom of thermodynamic stabili…
Generative AI for Crystal Structures: A Review
Pierre-Paul De Breuck, Hai-Chen Wang, Gian-Marco Rignanese +2
As in many other fields, the rapid rise of generative artificial intelligence is reshaping materials discovery by offering new ways to propose crystal structures and, in some cases…
Enhanced superconductivity in X4H15compounds via hole-doping at ambient pressure
Kun Gao, Wenwen Cui, Tiago F. T. Cerqueira +3
This study presents a computational investigation of X4H15 compounds (where X represents a metal) as potential superconductors at ambient conditions or under pressure. Through syst…
High-throughput study of kagome compounds in the AV3Sb5 family
Thalis H. B. da Silva, Tiago F. T. Cerqueira, Hai-Chen Wang +1
The kagome lattice has emerged as a fertile ground for exotic quantum phenomena, including superconductivity, charge density waves, and topologically nontrivial states. While AV3Sb…
The Maximum of Conventional Superconductors at Ambient Pressure
Kun Gao, Tiago F. T. Cerqueira, Antonio Sanna +6
The theoretical maximum critical temperature () for conventional superconductors at ambient pressure remains a fundamental question in condensed matter physics. Through analys…