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P.M. Dinh, E. Suraud

Time-Dependent Density Functional Theory in metal clusters. P.M. Dinh, E. Suraud. Laboratoire de Physique Théorique (Toulouse). P.G. Reinhard, F. Fehrer. Institut für Theoretische Physik (Erlangen). Outline. Nuclei vs. metal clusters DFT in metal clusters A cluster@substrate model

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P.M. Dinh, E. Suraud

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  1. Time-Dependent Density Functional Theory in metal clusters P.M. Dinh, E. Suraud Laboratoire de Physique Théorique (Toulouse) P.G. Reinhard, F. Fehrer Institut für Theoretische Physik (Erlangen)

  2. Outline • Nuclei vs. metal clusters • DFT in metal clusters • A cluster@substrate model • Deposition of Na cluster on Ar surface • Conclusion and perspectives

  3. quantum mean field Nuclei vs. Metal clusters Nuclei Metal clusters N < 300 nucleons 3 < N < 105-7 atoms R~r0N 1/3 R~rsN 1/3 relevant length scale dense systems with strong Pauli

  4. Free nucleons Nucleons IN nucleus Nucleus Free atom Atom INcluster Cluster Nuclei vs. Metal clusters Interactions Short range (nuclear) + long range (Coulomb) interactions ... 82 50 28 20 8 2 MEAN FIELD Long range (Coulomb) interactions ... 138 92 40 20 8 2

  5. 100 fs 1000 fm/c 10 fs 100 fm/c 10 fm/c 1 fs Nuclei vs. Metal clusters Time scales Alkalines (Li, Na, K, Rb, Cs) Nuclei

  6. DFT in metal clusters Degrees of freedom ? Valence electrons Ions = core electrons + atom

  7. DFT in metal clusters How to solve the problem? « Exactly » Ab initio methods of quantum chemistry Wave packets in molecular physics But very small systems « Adiabatically» Born-Oppenheimer approximation = Electrons bound to ground state surface But very weak excitations « Effectively » Density Functional Theory (effective mean field ) Level 1 : Electrons only (1984…)  Shells, plasmon,… Level 2 : Electrons + ions (1994 …) Complete non-adiabatic treatment of electrons and ions 3 groups : Dresden, Kyoto-Seattle, Erlangen-Toulouse Semi-classical versions (Grenoble, Erlangen-Toulouse)

  8. DFT in metal clusters start from HF procedure (local) for Coulomb system, Hohenberg-Kohn (1964) GS energy = functional of r

  9. ??? homogeneous electron gaz DFT in metal clusters Local Density Approx. Perdew, Wang (1992)

  10. in LDA MD-TDDFT(LDA) DFT in metal clusters dynamics ? TDDFT  Adiab. LDA or TDLDA non-adiab. dynamics (≠Born-Oppenheimer) IONS ?

  11. TDDFT in metal clusters I = 5x1011 W/cm2 FWHM = 125 fs w = 2.3 eV delay = 50 fs Na9+ under laser irradiation

  12. exp. ab initio TDLDA Yabana,Bertsch (1997) TDLDA Berkus, Reinhard,Suraud(2002) TDDFT in metal clusters Optical response Carbon chains Na9+ Calvayrac, Reinhard, Suraud (1998)

  13. A cluster@substrate model Experiments... easier with embedded or deposited clusters Need to model interaction with environment Na cluster + Ar substrate 2 others classical d.o.f. • RAr core • DAr dynamically polarizable electron cloud DAr RAr  gaussians, width from a(w)

  14. ab initio Coulomb final fine-tuning dipole-dipole A cluster@substrate model Coupling to valence electrons and ions

  15. Na @Ar383 a vacancy surface Deposition of Na cluster on Ar surface atom Na and Na+@Ar384 minimum in matrix !

  16. Deposition of Na cluster on Ar surface atom Na@Ar384 Ekin0 = 4.7 meV mechanical wave in matrix

  17. Na finally inside Ar matrix ! an Ar atom ejected from first layer Deposition of Na cluster on Ar surface atom Na@Ar384 Ekin0 = 4.7 meV NO ! contradiction with previous BO calculations ? ≈ Na@Ar383 complex cross-over between BO surfaces

  18. Deposition of Na cluster on Ar surface cluster Na6@Ar87 Ekin0 = 2.2 meV soft material • systematics on • Ekin0 • size of Na cluster • size of Ar cluster • deformation • transfer of kin. E • wave celerity • ...

  19. Conclusion • MD-TDLDA: powerful tool for metal clusters • in agreement with experiments • Interaction with polarizable Ar substrate • quite cumbersome • high computing-time • very soft material Perspectives • Other materials ... • In progress: • Ne, Kr substrates • In the future: • hard substrates (MgO, NaCl) • water environment CNRS post-doc sept/oct 2006

  20. lessexpensive DFT in metal clusters Self-Interaction Correction

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