4 papers
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…
Machine Learning on Multiple Topological Materials Datasets
Yuqing He, Pierre-Paul De Breuck, Hongming Weng +2
A dataset of 35,608 materials with their topological properties is constructed by combining the density functional theory (DFT) results of Materiae and the Topological Materials Da…
A generative material transformer using Wyckoff representation
Pierre-Paul De Breuck, Hashim A. Piracha, Gian-Marco Rignanese +1
Materials play a critical role in various technological applications. Identifying and enumerating stable compounds, those near the convex hull, is therefore essential. Despite rece…