The influence of the internal displacement cascades structure on the growth of point defect clusters in radiation enviro

1. EDF Electricité de France Recombination + Emission traps Interstitial loop Vacancy cluster Emission Ions Interstitial cluster + Annihilation Vacancy loop cascade Migration 8.46 10 16 10 keV cascades per cm3 per s • Only mono defects are mobile. • Em = 1.3 eV for vacancies • Em = 0.3 eV for interstitials 10-4 dpa/s (NRT) T = 573K thin foil : 100x100x300ao3 No traps, no loops Vacancy density (m-3) size ABSTRACT CONCLUSION The influence of the internal displacement cascades structure on the growth of point defect clusters in radiation environment • C.S. Becquart1, C. Domain2, L. Malerba3, M. Hou4 • (1) Laboratoire de Métalurgie Physique et Génie des Matériaux, UMR 8517, Université Lille-1, F-59655 Villeneuve d'Ascq Cédex, France • (2) EDF-R&D, Département Matériaux et Mécanique des Composants, Les renardières, F-77818 Moret sur Loing Cédex, France • (3) SCK•CEN, Reactor Materials Research Unit, B-2400 Mol, Belgium • (4) Physique des Solides Irradiés et des Nanostructures CP234, Université Libre de Bruxelles, Bd du Triomphe, B-1050 Brussels, Belgium THE PROBLEM THE OKMC MODEL • Displacement cascades are naturally modeled by • Molecular Dynamics (MD). • Displacement cascades are used as input for larger scale • modeling, e.g., by Kinetic Monte Carlo. • Cascade distributions are usually quite broad, and • realistic sampling for KMC thus requires large sets of • cascades. • But MD cascade calculation is time consuming. It is • thus tempting to use its Binary Collision Approximation • which is orders of magnitude faster. • But, even if the overall morphologies are similar, the • internal structure of cascades is different. • Hence the question: What is the importance of the • the internal structure of cascades in the long term • evolution? How sensitive the KMC is on the internal • cascade structure? • In order to evaluate this sensitivity, we run KMC • simulations with MD cascades, BCA cascades or • Random uniform point defect distributions as input. Displacement cascades obtained by full molecular dynamics and in its binary collision approximation, as well as random point defect distributions, all having similar overall morphologies, are used as input for long term radiation damage simulation by an object kinetic Monte Carlo method in α-iron. This model treats naturally point defect fluxes on cascades regions, resulting from cascades generated in other regions, in a realistic way. This study shows the significant effect of the internal structure of displacement cascades and, in particular, interstitial agglomeration on the long term evolution of defect cluster growth under irradiation. SIMILAR CASCADE DEBRIS CASCADE AGEING Frequency distributions of cascade volumes calculated in the Binary Collision for 10 keV PKA. (a) for the vacancies. (b) for the interstitials. The statistics were accumulated over 1000 cascades. The arrows indicate the volumes of the 5 10 keV MD cascades Component analysis allows associating an ellipsoid to each cascade. This way, it is possible to build volume distributions. Cascades are assumed to evolve without interacting with other sources of defects Green: MD Blueand pink: BCA Red: random On the basis of these distributions and distributions of ellipsoids elongation, it is possible to identify BCA cascades similar to MD cascades. It is also possible to make uniform and random distributions with similar associated ellipsoids. • Differences decrease after long times • Broad statistical dispersion Integral pair distribution functions for (a) vacancies (b) vacancy  interstitial (c) interstitial pairs From the integral pair correlation functions above, differences in internal structures of point defect distributions obtained by MD, in the BCA and at random can be compared. The most striking feature is the aggregation of interstitial which is much stronger in MD cascades. This difference is also found in the number of first and second neighbor clusters. Ln [t(s)] Ln [t(s)] Evolution versus time of (a) number of interstitials (b) percentage of interstitials in clusters (c) percentage of interstitials disappeared Evolution versus time of (a) number of vacancies (b) percentage of vacancies in clusters (c) percentage of vacancies disappeared DAMAGE EVOLUTION IN RADIATION ENVIRONMENT Interstitials only vacancies removed Vacancies only, interstitials removed Interstitials only, vacancies removed The comparison between cascade ageing and cascade evolution in irradiation environment revealed the importance of point defect –mostly interstitial- fluxes in the cluster growth kinetics. The role of the internal cascade structure is also demonstrated by comparing the long term evolution, starting with MD cascades, BCA cascades and random point defect distributions. In general, differences in the initial SIA distribution, due to the higher mobility of these defects, have larger effects in the long-term evolution than differences in the vacancy distributions. The next natural step in the study of cluster growth in radiation environment is to account for the mobility of small defect clusters and to identify its consequences. This, together with a systematic study of the importance of the parameters involved in the models is planned for future work. AFTER 0.1 dpa Vacancies and interstitials mobile Green: MD Blue: BCA pink: BCA Red: random (a) number of vacancies in clusters with sizes larger than “size”. (b) amount of vacancy clusters of size larger than “size”. (a) number of interstitials in clusters with sizes larger than “size”. (b) amount of interstitial clusters of size larger than size. (a) number of interstitials in clusters with sizes larger than “size”. (b) number of interstitial clusters of size larger than “size”. (a) number of vacancies in clusters with sizes larger than “size”. (b) number of vacancy clusters of size larger than “size”. MD predicts the largest number of interstitials in the smallest clusters. This is due to the largest number of interstitials clusters in the displacement cascades. These clusters are assumed to be immobile. MD predicts the largest number of vacancies in clusters in the largest vacancy clusters and the largest number of clustered interstitials in the smallest interstitial clusters.This is consistent with the following scheme: Intertitials are the most mobile. Their flux enhances the dissociation of vacancy clusters and vacancies become mobile again. These contribute to enhance the growth of other vacancy clusters in the close vicinity. Good matching between MD and BCA. Random distributions form a distinct class. Structural effects in cascades results in small vacancy clusters Acknowledgement: This work is part of the PERFECT Integrated Project supported by the European Communities