Copper nanoprecipitates in steel studied by atom probe tomography and ab initio based Monte Carlo simulation<br />O. Dmitr...
Overview<br /><ul><li>Motivation: Electromobility
Fe-3%Si-1% (2%) Cu model system
Fe-3%Si-Cu engineeringalloy
Simulations (DFT + kMC, model system)
Conclusionsandchallenges</li></ul>Raabe: Adv. Mater. 14 (2002), Roters et al. Acta Mater.58 (2010)<br />
2<br />Motivation<br />Avoiduseof permanent magnetsanduseinsteadelectricalmagnets in synchronouselectricalengines<br />Hig...
3<br />Electrical steels for electrical cars<br />
4<br />Electrical steels<br />Standard soft magnetic steel: based on <br />Fe3 wt. % Si  <br />ferriticphase, coarse gra...
5<br />{Jäniche et al., Werkstoffkunde Stahl}<br />0,1 µm<br />0,2 µm<br />0,3 µm<br />20 nm<br />Nano-precipitates in sof...
Overview<br /><ul><li>Motivation: Electromobility
Fe-3%Si-1% (2%) Cu model system
Fe-3%Si-Cu engineeringalloy
Simulations (DFT + kMC, model system)
Conclusionsandchallenges</li></ul>www.mpie.de<br />
7<br />Precipitation hardened materials<br />Precipitation hardened electrical steels: <br />nucleation of copper precipit...
 water quenching
age hardening at 400-450°C for 10 min - 100 h</li></ul>www.mpie.de<br />
8<br />Precipitation hardened electrical steels<br />Atom probe tomography<br />10 min        120 min                 6000...
9<br />58Ni+2<br />56Fe+2<br />48Ti+2<br />55Mn+2<br />200 nm<br />60Ni+2<br />54Fe+2<br />initiated evaporation<br />by<b...
10<br />APT results: 3D atomic maps (Laser mode at 60K, 0.4 nJ)<br />Cu 1 wt.% <br />120 min<br />Fe; Cu<br />nm<br />nm<...
11<br />APT results: 3D atomic maps (Laser mode at 60K, 0.4 nJ)<br />Cu 1 wt.% <br />Cu 2 wt.% <br />6000 min<br />120 m...
12<br />APT results: quantification<br />Cu 1 wt.% <br />Cu 2 wt.% <br />6000 min<br />120 min<br />6000 min<br />120 mi...
13<br />APT results: Proximity histogram<br />bigger cluster<br />Cu 2 wt.%; 450°C/6000 min<br />smaller cluster<br />20 n...
Overview<br /><ul><li>Motivation: Electromobility
Fe-3%Si-1% (2%) Cu model system
Fe-3%Si-Cu engineeringalloy
Simulations (DFT + kMC, model system)
Conclusionsandchallenges</li></ul>www.mpie.de<br />
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MRS Dec 2010 Steel With Copper Precipitates Dierk Raabe

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Copper nanoprecipitates in steel studied by atom probe tomography and ab initio based Monte Carlo simulation
Authors: O. Dmitrieva, P.-P. Choi, T. Hickel, N. Tillack,
D. Ponge, J. Neugebauer, D. Raabe
MRS Fall Meeting 2010

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MRS Dec 2010 Steel With Copper Precipitates Dierk Raabe

  1. 1. Copper nanoprecipitates in steel studied by atom probe tomography and ab initio based Monte Carlo simulation<br />O. Dmitrieva, P.-P. Choi, T. Hickel, N. Tillack, <br />D. Ponge, J. Neugebauer, D. Raabe<br />Düsseldorf, Germany<br />WWW.MPIE.DE<br />d.raabe@mpie.de<br />Thanksto: DFG<br />MRS Fall Conference 30. November 2010 Dierk Raabe<br />
  2. 2. Overview<br /><ul><li>Motivation: Electromobility
  3. 3. Fe-3%Si-1% (2%) Cu model system
  4. 4. Fe-3%Si-Cu engineeringalloy
  5. 5. Simulations (DFT + kMC, model system)
  6. 6. Conclusionsandchallenges</li></ul>Raabe: Adv. Mater. 14 (2002), Roters et al. Acta Mater.58 (2010)<br />
  7. 7. 2<br />Motivation<br />Avoiduseof permanent magnetsanduseinsteadelectricalmagnets in synchronouselectricalengines<br />High strength soft magneticsteels in carenginesreduce CO2emission<br />www.mpie.de<br />
  8. 8. 3<br />Electrical steels for electrical cars<br />
  9. 9. 4<br />Electrical steels<br />Standard soft magnetic steel: based on <br />Fe3 wt. % Si  <br />ferriticphase, coarse grains <br />soft-magnetic properties<br />Improvement of the mechanical strength! <br />precipitation hardening: 1-2 wt. % Cu, aging at 450°C <br />
  10. 10. 5<br />{Jäniche et al., Werkstoffkunde Stahl}<br />0,1 µm<br />0,2 µm<br />0,3 µm<br />20 nm<br />Nano-precipitates in soft magnetic Fe-3%Si steels<br />magnetic loss (W/kg)<br />15 nm<br />size Cu precipitates (nm)<br />{JP 2004 339603}<br />nanoparticlestoosmallfor Bloch-wall interaction but <br />effectiveasdislocationobstacles<br />mechanicallyvery strong soft magnetsformotors<br />Fe-Si steelwithCu nano-precipitates<br />
  11. 11. Overview<br /><ul><li>Motivation: Electromobility
  12. 12. Fe-3%Si-1% (2%) Cu model system
  13. 13. Fe-3%Si-Cu engineeringalloy
  14. 14. Simulations (DFT + kMC, model system)
  15. 15. Conclusionsandchallenges</li></ul>www.mpie.de<br />
  16. 16. 7<br />Precipitation hardened materials<br />Precipitation hardened electrical steels: <br />nucleation of copper precipitates in iron-silicon matrix<br />Fe<br />Si 3 wt. %<br />Cu 1 wt. % <br />Fe<br />Si 3 wt. %<br />Cu 2 wt.%<br />I.<br />II.<br />Cu<br />Cu<br />Cu<br />Fe-3wt% Si<br /><ul><li> solute annealing 950°C-1150°C for 1h
  17. 17. water quenching
  18. 18. age hardening at 400-450°C for 10 min - 100 h</li></ul>www.mpie.de<br />
  19. 19. 8<br />Precipitation hardened electrical steels<br />Atom probe tomography<br />10 min 120 min 6000 min <br />Time, min<br />www.mpie.de<br />
  20. 20. 9<br />58Ni+2<br />56Fe+2<br />48Ti+2<br />55Mn+2<br />200 nm<br />60Ni+2<br />54Fe+2<br />initiated evaporation<br />by<br />or<br />24 26 28 <br />time of flight  mass / charge state<br /> Time of flight <br />spatial resolution <br />layer-by-layer<br />100 nm<br />– <br />high <br />voltage<br /> 10 kV<br />+<br />3D Atom Probe Tomography<br />LEAP (Local Electrode Atom Probe) 3000X HR <br />3-dimensional <br />reconstructed <br />model of specimen<br />(about 100 Millions of atoms)<br />
  21. 21. 10<br />APT results: 3D atomic maps (Laser mode at 60K, 0.4 nJ)<br />Cu 1 wt.% <br />120 min<br />Fe; Cu<br />nm<br />nm<br />Iso-concentration surfaces at Cu 11 at.%<br />www.mpie.de<br />
  22. 22. 11<br />APT results: 3D atomic maps (Laser mode at 60K, 0.4 nJ)<br />Cu 1 wt.% <br />Cu 2 wt.% <br />6000 min<br />120 min<br />6000 min<br />120 min<br />20 nm<br />20 nm<br />20 nm<br />20 nm<br />450°C aging<br />Iso-concentration surfaces at Cu 11 at.%<br />Fe-Si-Cu, LEAP 3000X HR<br />www.mpie.de<br />
  23. 23. 12<br />APT results: quantification<br />Cu 1 wt.% <br />Cu 2 wt.% <br />6000 min<br />120 min<br />6000 min<br />120 min<br />3.2 nm ± 0.8 nm<br />5.0 nm ± 0.8 nm<br />4.3 nm ± 0.8 nm<br />6.5 nm ± 1.4 nm<br />Cluster:<br />Fe 71 at%<br />Cu 24 at%<br />Si 5 at%<br />Cluster:<br />Fe 62.9 at%<br />Cu 32.1 at%<br />Si 5.0 at%<br />Cluster:<br />Fe 60.7 at%<br />Cu 35.2 at%<br />Si 4.1 at%<br />Cluster:<br />Fe 51.8 at%<br />Cu 44.6 at%<br />Si 3.6 at%<br />Matrix (without clusters):<br />Cu 0.2 at% Cu 0.1 at% Cu 0.2 at% Cu 0.1 at%<br />“Enrichment factor”: <br />content in cluster<br />content in alloy<br />Fe 0.68<br />Cu 40.1<br />Si 0.75<br />Fe 0.65<br />Cu 44.0<br />Si 0.68<br />Fe 0.77<br />Cu 17<br />Si 0.78<br />Fe 0.56<br />Cu 31.9<br />Si 0.58<br />clusters number density, m-3<br />6.110230.910236.41023 0.61023<br />volume fraction of clusters<br /> 2%  2%  5%  3-5%<br />www.mpie.de<br />
  24. 24. 13<br />APT results: Proximity histogram<br />bigger cluster<br />Cu 2 wt.%; 450°C/6000 min<br />smaller cluster<br />20 nm<br />Cluster size<br />5 nm<br />8 nm<br />nm<br />matrix<br />cluster center<br /><ul><li> kinetic reasons? </li></ul> (different stages of particle growth)<br /><ul><li> slow diffusion; misfit ?</li></ul>residual Fe-content<br />diffuse interface<br />www.mpie.de<br />
  25. 25. Overview<br /><ul><li>Motivation: Electromobility
  26. 26. Fe-3%Si-1% (2%) Cu model system
  27. 27. Fe-3%Si-Cu engineeringalloy
  28. 28. Simulations (DFT + kMC, model system)
  29. 29. Conclusionsandchallenges</li></ul>www.mpie.de<br />
  30. 30. 15<br />APT results<br />Overall content in the analysis volume:<br />Fe 92.1 at.%<br />Cu 1.49 at.%<br />Al 0.56 at.%<br />Si 5.83 at. %<br />www.mpie.de<br />
  31. 31. O. Dmitrieva<br />16<br />3D-concentration profiles<br />Fe Si 17924-1FB<br />3wt%Si, 2wt%Cu<br />Iso-concentration-Surfaces at Cu 6 at.%<br />www.mpie.de<br />
  32. 32. 17<br />Cluster analysis<br />(cluster analysis: <br />Nmin=100,<br />dmax=0.7 nm)<br />d = 5.0 ± 1.0 nm<br />(density corrected:<br />d = 6.0 ± 1.4 nm)<br />www.mpie.de<br />
  33. 33. Overview<br /><ul><li>Motivation: Electromobility
  34. 34. Fe-3%Si- 1% (2%) Cu model system
  35. 35. Fe-3%Si-Cu engineeringalloy
  36. 36. Simulations (DFT + kMC, model system)
  37. 37. Conclusionsandchallenges</li></ul>www.mpie.de<br />
  38. 38. Modeling: ab-initio, DFT / GGA, binding energies<br />Fe-Si steelwithCu nano-precipitates<br />
  39. 39. Modeling: ab-initio, DFT / GGA, binding energies<br />Fe-Si steelwithCu nano-precipitates<br />
  40. 40. Modeling: ab-initio, DFT / GGA, binding energies<br />Fe-Si steelwithCu nano-precipitates<br />
  41. 41. Modeling: ab-initio, DFT / GGA, binding energies<br />Fe-Si steelwithCu nano-precipitates<br />
  42. 42. 23<br />Ab-initio, bindingenergies: Cu-Cu in Fematrix<br />Fe-Si steelwithCu nano-precipitates<br />
  43. 43. 24<br />Ab-initio, bindingenergies: Si-Si in Fematrix<br />Fe-Si steelwithCu nano-precipitates<br />
  44. 44. 25<br />Ab-initio, bindingenergies<br />For neighbor interaction energy take difference (in eV)‏<br /> (repulsive) = 0.390<br /> (attractive) = -0.124<br /> (attractive) = -0.245<br />Fe-Si steelwithCu nano-precipitates<br />
  45. 45. 26<br />Ab-initio, usebindingenergies in kinetic Monte Carlo model<br />www.mpie.de<br />
  46. 46. Overview<br /><ul><li>Motivation: Electromobility
  47. 47. Fe-3%Si-1% (2%) Cu model system
  48. 48. Fe-3%Si-Cu engineeringalloy
  49. 49. Simulations (DFT + kMC, model system)
  50. 50. Conclusionsandchallenges</li></ul>www.mpie.de<br />
  51. 51. 28<br />Conclusionsandchallenges<br /><ul><li>Soft magnetic steels for electromobility
  52. 52. Increase mechanical strength without loosing good soft magnetic properties
  53. 53. Use nanoprecipitates with size below Bloch wall thickness
  54. 54. APT suited to provide statistics and composition of nanoparticles
  55. 55. Ab-initio thermodynamics in system Fe-Si-Cu
  56. 56. Kinetics: QM – kMC
  57. 57. Coupling DFT/kMC with atomic-scale experiments</li></ul>www.mpie.de<br />
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