NOMAD CoE
Publications

 


 

  1. C. Draxl, M. Kuban, S. Rigamonti, and M. Scheidgen

    Challenges and perspectives for interoperability and reuse of heterogenous data collections

    Section 4.1 in H. J. Kulik, et al.
    Roadmap on Machine Learning in Electronic Structure

    Electronic Structure 4, 023004 (2022).  [Download]
  2. M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H.-J. Bungartz, C.Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. E. Nagel, M. Scheidgen, C. Wöll, and C. Draxl

    FAIR data enabling new horizons for materials research

    Nature 604, 635 (2022). [DOI] [Download]
  3. M. Kuban, Š. Gabaj, W. Aggoune, C. Vona, S. Rigamonti, and C. Draxl

    Similarity of materials and data‑quality assessment by fingerprinting

    MRS Bulletin Impact , (2022). [DOI] [Download]
  4. Y. Luo, S. Bag, O. Zaremba, A. Cierpka, J. Andreo, S. Wuttke, P. Friederich, and M. Tsotsalas

    MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning

    Angew. Chem. Int. Ed. 61, (2022). [DOI]
  5. M. Jalali, M.  Tsotsalas, and C. Wöll

    MOFSocialNet: Exploiting Metal-Organic Framework Relationships via Social Network Analysis

    Nanomaterials 12, 704 (2022). [DOI]