Nuclear Materials Science

Organisational unit: Institute

  1. Modelling radiation-induced phase changes in binary FeCu and ternary FeCuNi alloys using an artificial intelligence-based atomistic kinetic Monte Carlo approach

    Castin, N., Malerba, L., Bonny, G., Pascuet, I., Hou, M. & Terentyev, D., 15 Sep 2009, In: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 267, 18, p. 3002-3008

    Research output: Contribution to journalArticlepeer-review

  2. Modeling the first stages of Cu precipitation in α-Fe using a hybrid atomistic kinetic Monte Carlo approach

    Castin, N., Pascuet, M. I., Malerba, L., Terentyev, D. & Bonny, G., Aug 2011, In: The Journal of Chemical Physics. 135, 6, p. 064502-064502

    Research output: Contribution to journalArticlepeer-review

  3. Predicting vacancy migration energies in lattice-free environments using artificial neural networks

    Castin, N., J.R., F., R.C., P. & Malerba, L., 5 Dec 2013, In: Computational Materials Science. 84, p. 217-225

    Research output: Contribution to journalArticlepeer-review

  4. New Approach To Model Point Defects Migration Using A Monte-Carlo Paradigm Coupled With Artificial Intelligence.

    Castin, N., Malerba, L., Bonny, G. & Terentyev, D., Oct 2008, Proceedings of the Fourth International Conference on Multiscale Materials Modeling. Tallahassee, FL, United States

    Research output: Contribution to report/book/conference proceedingsIn-proceedings paperpeer-review

  5. Prediction of point-defect migration energy barriers in alloys using artificial intelligence for atomistic kinetic Monte Carlo applications

    Castin, N., Malerba, L. & Bonny, G., Jun 2009, In: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 267, p. 3148-3151

    Research output: Contribution to journalArticlepeer-review

  6. Calculation of proper energy barriers for atomistic kinetic Monte Carlo simulations on rigid lattice with chemical and strain field long-range effects using artificial neural networks

    Castin, N., Malerba, L., Terentyev, D. & Bonny, G., 21 Feb 2010, In: The Journal of Chemical Physics. 132, 7, p. 074507-074507

    Research output: Contribution to journalArticlepeer-review

  7. On the onset of void swelling in pure tungsten under neutron irradiation: An object kinetic Monte Carlo approach

    Castin, N., Bakaev, A., Bonny, G., Malerba, L. & Terentyev, D., 17 Jun 2017, In: Journal of Nuclear Materials.

    Research output: Contribution to journalArticlepeer-review

  8. Improved atomistic Monte Carlo models based on ab-initio-trained neural networks: Application to FeCu and FeCr alloys

    Castin, N., Messina, L., Domain, C., Pasianot, R. C. & Olsson, P., 29 Jun 2017, In: Physical Review B. 95, 214117.

    Research output: Contribution to journalArticlepeer-review

  9. Object kinetic Monte Carlo model for neutron and ion irradiation in tungsten: Impact of transmutation and carbon impurities

    Castin, N., Bonny, G., Bakaev, A., Ortiz, C. J., Sand, A. E. & Terentyev, D., 2018, In: Journal of Nuclear Materials. 500, p. 15-25 10 p.

    Research output: Contribution to journalArticlepeer-review

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