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ICTP/CAS/IAEA School and Workshop Plasma-Material Interaction in Fusion Devices Hefei, China Ion Radiation Albedo Effect: Influence of Surface Roughness on Ion Retention and Sputtering of Materials Yong-gang Li and Zhi Zeng Research Laboratory for Computational Materials Sciences, Institute of Solid State Physics, Chinese Academy of Sciences June 23rd, 2016 ygli@theory.issp.ac.cn Outline •  Background •  Monte Carlo simulation of primary radiation damage •  Influence of surface roughness on ion retention and sputtering of materials •  Summary to years) scales be addressed simultaneously, and that extensive physical processes across the plasma–surface-bulk materials interfaces be integrated Figs and illustrate phenomena that govern the response of the materials surface to plasma exposure [9], and the computational models that must be accurately integrated While vastly different length scales characterize the surface ($nm) and plasma processes ($mm) as indicated in Fig 1, the plasma and the material’s surface are strongly coupled to each other, mediated by an electrostatic and magnetic sheath, through the nearly continuous exchange and recycling of incident ion and neutral species and the re-deposition of eroded particles These interactions are more explicitly shown in Fig 2, along with the corresponding time scales upon which they occur These physical processes occur over a disparate range of time scales, which poses a challenge both to modeling, and experimental characterization of both the individual and coupled processes As one example, the high probability (>90%) of prompt local ionization and re-deposition of sputtered material atoms means that the surface material that is in contact with the plasma is itself a plasma-deposited surface, as opposed to the original well-ordered surface of the material that existed at the beginning of operation [9] Likewise, the recycling of hydrogen plasma (fuel) is self-regulated through processes involving near-surface diffusion, trapping, and gas bubble formation, coupled to the ionization that results from interactions with the plasma The multitude of time and length scales controlling material evolution and device performance requires the development not only of detailed physics models and computational Background the implantation depth is generally only a few nanome more implanted particles accumulate within the surfac eventually a steady-state condition can result, in which t of species implanted into the materials is balanced by that r from the material The extent to which both surface morp and sub-surface defect creation and evolution processes by neutron-induced damage influence the diffusion, trapp precipitation of hydrogen and helium species into gas bu an outstanding question that impacts the tritium perm retention and near-surface saturation levels Tungsten has recently been selected as the sole diverto rial in ITER [10,11], and is the leading candidate material fo and future fusion reactors Laboratory experiments perfor linear plasma devices indicate the possibility of substantial modification in tungsten exposed to low-energy, helium pla mixed helium–hydrogen plasma, although the observed response is strongly temperature-dependent and likely dep on the ion energy and flux Pitted surfaces are observed %1000 K [12], whereas a ‘‘nanostructured,’’ low-density ‘‘f ‘‘coral’’ surface morphology is observed between approx 1000 and 2000 K [13–16], while micron-sized holes, or p observed to form above about 2000 K [17,18] The nanostr ‘‘fuzz’’ has recently been observed in the divertor regions of mak device operating with a helium plasma as well [19 surface features could lead to changes in heat transf (deuterium/tritium) retention [20], increased rates of through both sputtering and dust formation [21 •  Plasma-material interactions (PMI) in nuclear fusion devices: Cause the surface reconstruction of plasma-facing materials (PFMs, W) to roughness or even more complex nanostructures (mounds, fuzz, bubbles, pores and blisters) & ion (D/T/He) retention and sputtering of PFMs & degradation of structural materials ITER – PFMS (Be, W) D+, T+, He+, n 150 000 000 oC Fig Schematic illustration of the synergistic plasma surface interaction processes that dictate material evolution and performance in the magnetic fusio environment, as reproduced from [9] B.D Wirth et al., J Nucl Mater 463 (2015) 30 Please cite this article in press as: B.D Wirth et al., J Nucl Mater (2014), http://dx.doi.org/10.1016/j.jnucmat.2014.11.072 •  Surface morphology of W under ion irradiation •  Loop punching and bubble rupture causing surface roughening: mounds, fuzz, bubbles, pores and blisters •  What is the influence of surface roughness on ion retention and sputtering of materials under energetic ion irradiation? ~ t Fuzz S Kajita et al., Nucl Fusion 49 (2009) 095005 He-W Loop punching & bubble rupture O El-Atwani et al, Nucl Fusion 54 (2014) 083013 F Sefta et al, Nucl Fusion 53 (2013) 073015 •  How does surface roughness enhance ion retention and reduce ion sputtering? W D Nishijima et al J Nucl Mater 415 (2011) S96 Roughness W fuzz Ar RNRA He Surface roughness: polishing process C González et al., Nucl Fusion 55 (2015) 113009 Around one order of magnitude below the expected sputtering yields I Tanyeli et al., Sci Rep (2015) 9779 Monte Carlo simulation of primary radiation damage •  Primary radiation damage: Ballistic phase, in the range of ~ nm and the timescale of ~ sub-ps; two types of collision – binary & cascade/spike collision •  Until now radiation damage simulation codes (like SRIM) have been limited in ability to describe 3D geometry, computational efficiency, or both Advantages: MC v.s MD BCA Binary collision •  Simple and high efficiency; •  Arbitrary 1D/3D structures; •  Accounting of electronic energy loss and multiple- and plural-scattering; Cascade/spike collision •  No limitations in nanostructure sizes, ion energies, or availability of empirical interatomic potentials •  IM3D: Primary radiation damage under ion irradiation IM3D: A 3D Parallel MC Code for Efficient Simulation of Primary Radiation Damage (0, 0, 0) y x Ions z = zin z z = zsub Standard SRIM database Substrate Constructive Solid(x , y , z ) Geometry (CSG) t0 (0, 0, 0) x y t0 t0 Ions z = zin z + Fast database indexing technique (xb1, yb1, zb1) z = zsub dpa MPI parallel (xb0, yb0, zb0) nm Substrate 50 keV Si ! GaAs (xt0, yt0, zt0) Finite Element Triangular Mesh (FETM) Arbitrarily complex 3D structures C & MPI Efficiency ~ at least orders higher Y.G Li et al., Sci Rep (2015) 18130 As accurate as SRIM More efficient and universal http://theory.issp.ac.cn/IM3D, MIT •  IM3D: Arbitrarily complex targets based on CSG/FETM methods 500nm H -> W MeV He -> Ni (a) 10 keV He ions, Si (b) dpa 200 Fe z (nm) 400 600 Cu 800 CSG -dpa He ion 100 nm Bulk - Spatial correlation 1000 (a) FETM - ion (c) 100 CSG - dpa (b) Ga ions FETM - Vs NV - N 200 z (nm) 300 He ion 400 500 600 700 He ions, 100 keV Total 50 keV, x 100 nm 100 keV, x 3.2 150 keV, x 200 keV, x Ga -> W NiP 130 nm FETM - dpa W •  Random rough surface model •  FETM - Gaussian distribution f ( Z ) ∝ exp ( − Z 2σ ) , Z ∈[ −3σ , 3σ ] •  Square mesh – a (50 nm) 100 eV D -> W Influence of surface roughness on ion retention & sputtering of materials •  Two Key factors: Smooth surface – Incident angle Roughness 3σ & Incident angle θ Rough surface – Incident angle 10 •  The ion radiation albedo effect •  Both primary ion backscattering (1retention) and sputtering yields decrease with increasing roughness, and increase with more oblique irradiation angles •  It is mainly dominated by the direct, lineof-sight deposition of a fraction of emitted atoms onto neighboring asperities W Nishijima et al., J Nucl Mater 415 (2011) S96 W Rough peaks 11 •  Ion retention and sputtering of W with roughness surface •  Primary ion retention rate: R2 = − η (α ) + R20 ⋅ η (α ) ⋅ Ps Backsca+ering Nano-geometric /Shadingeffect effect •  Sputtering yield: Y = A (α ) ⋅Y0 (α ) ⋅ (1− Ps ) Nano-geometric/Shadingeffect 12 Summary •  A new, sophisticated 3D Monte Carlo code (IM3D) and a random rough surface model have been developed •  Both primary ion backscattering and sputtering yields decrease with increasing roughness, which is mainly dominated by the direct, line-of-sight deposition of a fraction of emitted atoms onto neighboring asperities •  Backscattering and sputtering increase with more oblique irradiation angles •  A simple analytical model is proposed to relate rough-surface and smoothsurface results •  There could be an additional positive feedback mechanism to promote the dendritic growth of surface asperities besides the loop-punching and bubble rupture mechanisms Ions Outgoing atoms Atom re-deposition 13 Acknowledgements •  Institute of Solid State Physics, CAS, China Cuan-guo Zhang, Liang Hu, Zhe Zhao, Gu-yue Pan, Pan-fei Tang •  Massachusetts Institute of Technology, USA Ju Li, Michal P Short, Yang Yang •  University of Sciences and Technology of China, China Ze-jun Ding, Shi-feng Mao Thanks for your attention! 14 •  Comparison of IM3D and SRIM 106 Serial: 2-3 orders higher 70 FC KP 103 102 40 30 20 Parallel: ~ 80% 10 101 100 Order-N scaling IM3D scaling 50 Slow Fast 104 105,2 MeV,Au->ZrO2/Si 60 Speepup CPU Time (s) 105 Li et al., Sci Rep (2015) 18130 SRIM Iradina 16 24 32 40 48 56 64 IM3D Processors So9ware SRIM http://www.srim.org IM3D http://theory.issp.ac.cn/IM3D Scattering angles MAGIC approximation Fast database indexing Geometries 1D bulk or multi-layers Arbitrarily 3D geometries Computational Efficiency Serial, low 2-3 orders faster for serial version, MPI parallel (> 80%) Defect distributions 1D depth-distributions > 700 citations per year 3D space-distributions, spatial correlation More efficient and general 15 •  Validation and Verification of IM3D •  IM3D vs SRIM for bulk Borschel et al., Nucl Inst Meth Phys Res B 269 (2011) 2133 Stoller et al., Nucl Inst Meth Phys Res B 310 (2013) 75 •  Ion depth-distributions under ion implantation with different energies •  V depth-distribution predicted by full-cascade and Kinchin-Pease models FC : KP ~ 16 Z L ∝a W Zp Profile element α Z=0 Zv ΔZ 17 •  Nano-energetic and nano-geometric effects Ren et al., Phys Rev B 86 (2012) 104114 Ar ion ~ 50 % Modified NRT model: ⎞ ⎛ 2Sb ⎞ N D ( R ) Ed ( ∞ ) N d ( R ) ⎛ 1 −R t ⎡ ⎤⎦ = ⋅ = 1+ exp ⋅ 1− 1+ R t ⋅ e ( ) 0 ⎣ ⎜⎝ ⎜⎝ 3R 4R h − ⎟⎠ ND Ed ( R ) N d 4R h − ⎟⎠ c Nano-energetic effect ~ 20 nm Nano-geometric effect Volume Vanithakumari et al., Phys Lett A 372 (2008) 6930; Ouyang et al., Nanotech 19 (2008) 045709 18 et al sputtering induced the bending of W nanowire •  IonCui beam 213112-2 Appl Phys W bending W fuzz Cui et al., Appl Phys Lett 102 (2013) 213112 (a) 10 * 10 * 10 nm3 (b) FETM (c) Ga ions 2402 NV - NI 2400 100 nm W -110 -111.5 19 Y Ueda et al J Nucl Mater 442 (2013) S267; S Kajita et al., Nucl Fusion 49 (2009) 095005 20
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