Accurate computational electrochemistry from density functional theory and multiscale

Project: Academy of Finland: Other research funding

Research outputs

  1. 2019
  2. Published

    Understanding X-ray Spectroscopy of Carbonaceous Materials by Combining Experiments, Density Functional Theory, and Machine Learning. Part I: Fingerprint Spectra

    Aarva, A., Deringer, V. L., Sainio, S., Laurila, T. & Caro, M. A., 26 Nov 2019, In : Chemistry of Materials. 31, 22, p. 9243-9255 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. Published
  4. Published

    Machine Learning Interatomic Potentials as Emerging Tools for Materials Science

    Deringer, V. L., Caro, M. A. & Csányi, G., 5 Sep 2019, In : Advanced Materials. 1902765.

    Research output: Contribution to journalArticleScientificpeer-review

  5. Published

    Optimizing many-body atomic descriptors for enhanced computational performance of machine learning based interatomic potentials

    Caro, M. A., 30 Jul 2019, In : Physical Review B. 100, 2, 11 p., 024112.

    Research output: Contribution to journalArticleScientificpeer-review

  6. 2018
  7. Published

    Computational Surface Chemistry of Tetrahedral Amorphous Carbon by Combining Machine Learning and Density Functional Theory

    Deringer, V. L., Caro, M. A., Jana, R., Aarva, A., Elliott, S. R., Laurila, T., Csányi, G. & Pastewka, L., 2018, In : Chemistry of Materials. 30, 21, p. 7438–7445 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  8. Published

    Reactivity of Amorphous Carbon Surfaces: Rationalizing the Role of Structural Motifs in Functionalization Using Machine Learning

    Caro, M. A., Aarva, A., Deringer, V. L., Csányi, G. & Laurila, T., 2018, In : Chemistry of Materials. 10 p.

    Research output: Contribution to journalArticleScientificpeer-review

ID: 13261902