Computational materials science, ‎0927-0256

Journal

ISSNs0927-0256
1 - 10 out of 42Page size: 10

Research output

  1. 2025
  2. Published

    Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: A case study of silicon nitride

    Nayak, G. K., Srinivasan, P., Todt, J., Daniel, R., Nicolini, P. & Holec, D., 6 Jan 2025, In: Computational materials science. 249.2025, 5 February, 11 p., 113629.

    Research output: Contribution to journal › Article › Research › peer-review

  3. 2024
  4. Published

    Descriptors based on the density of states for efficient machine learning of grain-boundary segregation energies

    Dösinger, C. A., Hammerschmidt, T., Peil, O. E., Scheiber, D. & Romaner, L., 13 Nov 2024, In: Computational materials science. 247.2025, 31 January 2025, 10 p., 113493.

    Research output: Contribution to journal › Article › Research › peer-review

  5. 2023
  6. Published

    Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture

    Steinberger, D., Issa, I., Strobl, R., Imrich, P. J., Kiener, D. & Sandfeld, S., 5 Jan 2023, In: Computational materials science. 216.2023, 5 January, 9 p., 111830.

    Research output: Contribution to journal › Article › Research › peer-review

  7. 2022
  8. E-pub ahead of print

    Stability and ordering of bcc and hcp TiAl+Mo phases: An ab initio study

    Dehghani, M., Ruban, A. V., Abdoshahi, N., Holec, D. & Spitaler, J., 18 Jan 2022, (E-pub ahead of print) In: Computational materials science. 205.2022, 1 April, 11 p., 111163.

    Research output: Contribution to journal › Article › Research › peer-review

  9. 2021
  10. Published

    An atomistic view on Oxygen, antisites and vacancies in the γ-TiAl phase

    Razumovskiy, V. I., Ecker, W., Wimler, D., Fischer, F-D., Appel, F., Mayer, S. & Clemens, H., Sept 2021, In: Computational materials science. 197.2021, September, 8 p., 110655.

    Research output: Contribution to journal › Article › Research › peer-review

  11. 2018
  12. Published

    Designing nanoindentation simulation studies by appropriate indenter choices: Case study on single crystal tungsten

    Goel, S., Cross, G., Stukowski, A., Gamsjäger, E., Beake, B. & Agrawal, A., 2018, In: Computational materials science. 152, p. 196-210 15 p.

    Research output: Contribution to journal › Article › Research › peer-review

  13. 2017
  14. E-pub ahead of print

    Structure and surface energy of Au55 nanoparticles: An ab initio study

    Holec, D., Fischer, F-D. & Vollath, D., 6 Apr 2017, (E-pub ahead of print) In: Computational materials science. 134.2017, 15 June, p. 137-144 8 p.

    Research output: Contribution to journal › Article › Research › peer-review

  15. Published

    Incorporation of vacancy generation/annihilation into reactive diffusion concept – Prediction of possible Kirkendall porosity

    Svoboda, J. & Fischer, F-D., 1 Feb 2017, In: Computational materials science. 127.2017, 1 February, p. 136-140 5 p.

    Research output: Contribution to journal › Article › Research › peer-review

  16. 2016
  17. Published

    Numerical analysis of macrosegregation in vertically solidified Pb-Sn test castings - Part I: Columnar solidification

    Wu, M., Zeng, Y., Kharicha, A. & Ludwig, A., 2016, In: Computational materials science.

    Research output: Contribution to journal › Article › Research › peer-review

  18. Published

    Numerical analysis of macrosegregation in vertically solidified Pb-Sn test castings – Part II : Equiaxed solidification

    Zheng, Y., Wu, M., Kharicha, A. & Ludwig, A., 2016, In: Computational materials science.

    Research output: Contribution to journal › Article › Research › peer-review

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