We develop novel computational methods to understand the properties of solids from their basic ingredients. We apply them to unveil the mysteries hidden in materials and to predict new exciting compounds.

Research

We use first-principles quantum mechanical methods to understand and predict the properties of materials.

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Latest publications

Search for thermodynamically stable ambient-pressure superconducting hydrides in the GNoME database

Antonio Sanna, Tiago F. T. Cerqueira, Ekin Dogus Cubuk, Ion Errea and Yue-Wen Fang
Communications Physics 9, 94 (2026)

Machine learning driven exploration of hydride superconductors at ambient pressure

Paulo R. Pires, Thalis H.B. da Silva, Kun Gao, Kaja H. Hiorth, Tiago F. T. Cerqueira, Théo Cavignac, Pierre-Paul De Breuck, Hai-Chen Wang, Đorđe Dangić, Yue-Wen Fang, Antonio Sanna, Wenwen Cui, Ion Errea, Päivi Törmä and Miguel A. L. Marques
Computational Materials Today 10, 100052 (2026)

A chemical bonding based descriptor for predicting the role of anharmonicity induced by quantum nuclear effects in hydride superconductors

Francesco Belli, Eva Zurek and Ion Errea
npj Computational Materials 12, 100 (2026)