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Home » Institute » Departments & Research Groups » Artificial Intelligence for Integrated Material Science » Discovery and Characterization of Inorganic Stoichiometric Compounds » DCISC Publications

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  • 2025

  • P. De Breuck, H. Wang, G. Rignanese et al. Generative AI for crystal structures: a review. npj Computational Materials, 11, 370, (2025)
  • K. Gao, W. Cui, T. Cerqueira et al. Enhanced superconductivity in X4H15 compounds via hole-doping at ambient pressure. Advanced Science, 12, e08419, (2025)
  • J. Jacobs, C. Ritter, Ke. Xu et al. Structural and electronic tunability of Ruddlesden–Popper oxyfluorides through nickel–copper substitution in La2Ni1−xCuxO2.5F3 (0 ≤ x ≤ 1). Journal of Materials Chemistry A, 13, 32539–32550, (2025)
  • T. da Silva, T. Cerqueira, H. Wang et al. High-throughput study of kagome compounds in the AV3Sb5 family. Digital Discovery, 4, 2431–2438, (2025)
  • K. Gao, T. Cerqueira, A. Sanna et al. The maximum Tc of conventional superconductors at ambient pressure. Nature Communications, 16, 8253, (2025)
  • A. Loew, D. Sun, H. Wang et al. Universal machine learning interatomic potentials are ready for phonons. npj Computational Materials, 11, 178, (2025)
  • T. da Silva, T. Cavignac, T. Cerqueira et al. Machine-learning accelerated prediction of two-dimensional conventional superconductors. Materials Horizons, -, -, (2025)
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