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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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  • A. Loew, H. Wang, T. Cerqueira et al. Training machine learning interatomic potentials for accurate phonon properties. Machine Learning: Science and Technology, 5, 045019, (2024)
  • J. Schmidt, T. Cerqueira, A. Romero et al. Improving machine-learning models in materials science through large datasets. Materials Today Physics, 48, 101560, (2024)
  • H. Wang, T. Rauch, A. Tellez-Mora et al. Exploring flat-band properties in two-dimensional M3QX7 compounds. Physical Chemistry Chemical Physics, 26, 21558–21567, (2024)
  • J. Jacobs, H. Wang, M. Marques et al. Ruddlesden–Popper oxyfluorides La2Ni1–xCuxO3F2 (0 ≤ x ≤ 1): Impact of the Ni/Cu ratio on the thermal stability and magnetic properties. Inorganic Chemistry, 63, 11317-11324, (2024)
  • J. Jacobs, H. Wang, M. Marques et al. Ruddlesden–Popper oxyfluorides La2Ni1–xCuxO3F2 (0 ≤ x ≤ 1): Impact of the Ni/Cu ratio on the structure. Inorganic Chemistry, 63, 6075–6081, (2024)
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