PPC-10 Smolenice Castle, Slovakia Sept. 5 - 9, 2011 Positron annihilation study of neutron-irradiated nuclear reactor pressure vessel (RPV) steels and their model alloys Y. Nagai1, A. Kuramoto1, T. Toyama1, T. Takeuchi2, M. Hasegawa3 1The Oarai Center, Institute for Materials Research, Tohoku University, Oarai, Ibaraki 311-1313, Japan 2Japan Atomic Energy Agency, Tokai, Ibaraki 319-1195, Japan 3Institute for Materials Research, Tohoku University, Sendai, Miyagi 980-8577, Japan hasegawa@imr.tohoku.ac.jp

2) Fe-Cu Model Alloys: Cu Nano-Clusters (Precipitates) Outline 1) Backｇround 2) Fe-Cu Model Alloys: Cu Nano-Clusters (Precipitates) a) Size: 2D-ACAR Momentum Smearing b) Number Density: AMOC 3) RPV Steel: Surveillance Test Specimen Materials Mechnisms: Nanostructural Features Irradiation Embrittlement & Hardening 1st & 2nd Generation A533B Post Irradiation Annealing (PIA) Experiments

Origin of irradiation-induced embrittlement Nuclear Reactor Pressure Vessel (RPV) Steel Origin of irradiation-induced embrittlement 1) Solute Nano-Clusters 2) Matrix Defects (vacancy-type defects, dislocation loops, ···) dislocation Grain boundary 3) P Segregation at Grain Boundary

Laser-Assisted Local Electrode Atom Probe Position sensitive ion detector Z Y X Local electrode Laser Vtotal Needle sample Vextraction ～100nm Time of Flight Mass 4 Energy-compensated type (with “Reflectron”) 4 4

Cu Nano-Particles in Fe Positron Quantum-Dot Confinement in a Precipitate of 59 Cu Atoms LEAP 3D-Atom Probe 2x107 Atoms, 1hour e+　Self-Searching: Cu Nano-Particles　in Fe 1nm Density isosurface of a quantum-dot confined positron in a Cu59 in Fe matrix. The isodensity value is 0.5% of the maximum. 60x60x170 nm

2a) Cu Nano-Precipitates (Clusters) : Size 2D-ACAR: Momentum Smearing Z. Tang et al.: J. Phys.: Condens. Matter 20 (2008) 445203, Size-dependent momentum smearing effect of positron annihilation radiation in embedded nano Cu clusters

2b) Cu Nano-Precipitates (Clusters) : Number Density AMOC: Time Evolution of HMCF (W-Parameter) 　　 Trapping Model A. Inoue et al.: Phys. Rev. B83 (2011) 115459

Fe-0.88at.%Cu: Thermal Aging @550˚C CDB Ratio Curve 3D-AP 2h 30nm 10nm 0.1h 0.2h 2h: Complete e+ Quantum-Dot Confinement Fig.1

Time Evolution of CDB HMCF (W-Parameter) Pure Cu Pure Fe

Positron Age-Momentum Correlation (AMOC) Using digital oscilloscope：Time resolution ~170ps Number density estimated by positron annihilation Time dependent HMCF　（W-parameter) Positron trapping rate Number density Number Density (×1017 cm-3) 3D-AP e+ Aging Time (h) 　　　Size Diameter (nm) 0.1 0.2 2 0.9 1.1 2.5 0.15 1.2 1.9 0.61 1.4 1.8 In this talk, firstly, I would like to briefly explain why we employ positron annihilation for elemental analysis rather than other technique, and introduce the site which positron probes. For defect scientists, positron is a tool of vacancy-type defects. But, not only the vacancy-type defects but also other sites, such as positron affinitive embedded clusters, polar groups in polymers, and so on, are also positron trapping sites. In this talk, I would like to concentrate on “positron affinitive embedded clusters in materials”. As examples, I introduce Cu clusters in Fe and solute clusters, so called GP zone, in Al. And I would like to comment two points on CDB data analysis and their interpretation from my personal experience. Finally, I show the competition between positron annihilation and other techniques in the study of embedded clusters.

3) RPV Steel: Surveillance Test Specimen Materials 1St & 2nd Generation A533B Irradiation –Induced Embrittlement (Hardening) Mechanisms Post Irradiation Annealing (PIA) Experiments PIA: 1st Gen A533B Kuramoto et al.: Submitted to J. Nucl. Mater. Fluence Dependence Takeuchi et al. : J. Nucl. Mater. 402 (2010) 93.

Reactor Pressure Vessel (RPV) Steel: A533B Chemical Composition wt.% A533B C Si Mn P S Ni Cr Cu Mo 1st. Gen. 0.19 0.30 1.30 0.015 0.010 0.68 0.17 0.16 0.53 2nd. Gen. 1.43 0.004 0.001 0.65 0.13 0.04 0.50 Purified: Cu, P, S JMTR Irradiation Fluence: 3.9x1019n/cm2 (0.061dpa) Flux: 1.8x1013n/cm2・sec Temperature: 2902C

Annealing Temperature [ ℃ ] Average Positron Lifetime [ps] V Annealing Behavior of Average Positron Lifetime 1st. Gen.(0.16Cu) & 2nd. Gen.(0.04Cu) A533B, 3.9×1019 n/cm2 200 300 400 500 600 100 120 140 160 180 Annealing Temperature [ ℃ ] Average Positron Lifetime [ps] V 1 Unirrad. (1st. Gen.) Fe bulk Unirrad. (2nd. Gen.) st. Gen. (0.16Cu) 2 nd. Gen. (0.04Cu) As-irrad.

CDB HMCF-LMCF Correlations 1st. Gen. (0.16Cu) & 2nd. Gen. (0.04Cu) A533B, 3.9×1019 n/cm2 450 °C 400 °C 300 °C As-irrad. (1st. Gen. ) 550 °C Unirrad. (1st. Gen. ) 600 °C 600 °C As-irrad. (2nd. Gen. ) Unirrad. (2nd. Gen. ) 450 °C 300 °C

Neutron Irradiation: 8.3×1018n/cm2 (1.2×10-2dpa, ~100ºC) Fe-Cu Model Alloys ( 0.3wt.%Cu, 0.05wt.%Cu ) 0.5 0.55 0.6 0.65 0.004 0.006 0.008 0.01 0.012 0.014 LMCF HMCF Pure Cu 500 0.3Cu 500 0.05Cu As-irrad. Pure Fe Unirrad. Unirrad. As-irrad.

Atom Maps of the Solutes: Annealing Behavior (As-irrad.~400℃) 1st. Gen. (0.16Cu) A533B, 3.9×1019 n/cm2 As-irrad. 350 °C 400 °C Cu Si Mn P Ni 10nm

Atom Maps of the Solutes: Annealing Behavior (As-irrad.~350 ℃) 2nd. Gen. (0.04Cu) A533B, 3.9×1019 n/cm2 As-irrad. 300 ℃ 350 ℃ Si Mn Ni P Cu 10nm

Average Chemical Compositions of Solute Clusters 3.9×1019 n/cm2 1st. Gen. (0.16Cu) A533B 2nd. Gen. (0.04Cu) A533B Cu Mn Si Composition [%] Ni Composition [%] Fe Annealing Temperature [°C] Annealing Temperature [°C]

Radius of Gyration (rg), Number Density (Nd) & Volume Fraction (Vf) A533B, 3.9×1019 n/cm2 rg Radius of Gyration 1st. Gen. (0.16Cu) CuMnSiNi Clusters 1st. Gen. 2nd. Gen. (0.04Cu) MnSiNi Clusters Nd Number Density 2nd. Gen. Hardening Russell-Brown Model Vf Volume Fraction

Annealing Behavior of Irradiation Hardening (∆Hv) 1st. Gen. (0.16Cu) A533B, 3.9×1019 n/cm2 e+ : Vac-Defects 3D-AP: CuMnSiNi Clusters As-irrad.

Av 3.9×1019n/cm2 LMCF HMCF Hv 1st. Gen. (0.16Cu) 2nd. Gen. (0.04Cu) As-irrad. Annealing Temperature [°C]

What & How Positron Annihilation Can Say on RPV-Embrittlement Mechnisms ? Unique Nano-Features 1) Cu-Rich Nano-Clusters Evolution, Recovery: Clear-Cut Info. Size, Number Density: Not Easy 2) Vacancy-Related Defects Correlation: Mech. Properties Integration: Other Methods, such as 3D-AP, SANS,TEM Quantative !!