Cooling dynamics of glass-embedded metal nanoparticles

Transcription

1 Cooling dynamics of glass-embedded metal nanoparticles Vincent Juvé, Paolo Maioli, Aurélien Crut, Francesco Banfi,, Damiano Nardi, Claudio Giannetti, Stefano Dal Conte, Natalia Del Fatti and Fabrice Vallée FemtoNanoOptics group, LASIM, Université Lyon -CNRS, 43 Bd du Novembre, 696 Villeurbanne, France Dipartimento di Matematica e Fisica, Università Cattolica, I-5 Brescia, Italy

2 Outline Introduction - Fundamental and technological motivations - Time-resolved pump-probe spectroscopy Results ) Room temperature experiments - Complete analysis of thermal signals - Interface resistance vs acoustic mismatch ) Low temperature experiments - Interface resistance vs temperature Conclusions and prospects

3 Motivations Technology: nanometric components Example: heat dissipation in processors Fundamental physics: heat transfer at the nanoscale Increased role of interface thermal resistance Medium (T) Medium (T ) ΔT J = R Kapitza 45 nm transistor (Intel) Fast heat dissipation is crucial to avoid processor damage. - Variations with. interface composition?. temperature? - Modeling. Acoustic/diffuse mismatch models. Molecular dynamics

4 Nano-thermics with metal nanoparticles: state of the art Previous studies: Metal nanoparticles - Selective heating / monitoring of cooling dynamics - Nanometric size large interface effects - Parameters: size, composition, surface, environment, Size effects Hu & Hartland J. Phys. Chem. B Plech et al. Europhys. Lett. 3 Nature of interfaces - solvant Wilson et al. PRB Ge et al. J. Phys. Chem. B 4 - ligands Wang et al. Science 7 - core-shell structures Hu et al. Chem. Phys. Lett. 3 Ge et al. Nano Letters 5 Rashidi-Huyeh et al. PRB 8 Structural changes Melting Plech et al. PRB 4 Solvent vaporization Merabia et al. PRE 9 Not/less investigated: - Solid environment - Complete description of cooling dynamics - Precise extraction of thermal parameters - Low-temperature measurements

5 /Tx-3Δ TNano-thermics with metal nanoparticles: time-resolved studies fs laser pump pulse Experimental approach I S T x I S ΔT/T probe pulse sample Pump pulse: Delayed Probe pulse: Signal reflects changes of nanoparticle volume or temperature 3 AuAg in glass (9 nm diameter) ) electron heating lattice heating: electron-lattice energy transfer time τ e-ph ) coherent vibrations 3) nanoparticle thermal cooling ( )Pump-probe delay (ps) 3 3

6 Time-resolved signals vs temperature changes Optical response of a metal nanoparticle Absorption of a nanoparticle (ε = ε + i ε ) in a matrix (ε m ): σ abs 8πVε = λ 3/ m ε ( λ) [ ε ( λ) + ε ] + ε ( λ) (Mie theory for a sphere, dipolar approximation) m Glass-embedded Ag nanoparticles (D = 3 nm) Surface Plasmon Resonance (SPR) Wavelength (nm) Predictions: - Probe near SPR: signal not proportional to nanoparticle temperature (influence of external medium) - Probe away from SPR (infrared): signal proportional to nanoparticle temperature

7 Experiments: effect of probe wavelength ΔT/T (normalisé) Blue probe (445 nm) IR probe (89 nm). 5 5 t (ps) Ag, R=. nm, Embedded in glass (expected conductivity <.4 W.m -.K - ) Infrared probe Glass conductivity (interpolation):. W.m -.K - : OK Blue probe Glass conductivity (interpolation):. W.m -.K - : UNREALISTIC All further experiments performed with infrared probe.

8 Modeling Equations Tm ( t) t = 3G R c m ( T ( t) T ( R, t) ) m g interface (conductance G) R c g T g ( r, t) t = Λ g r r ( rt ( r, t) ) g heat diffusion in glass (thermal conductivity Λ g ) Result κ=λ g /c g Δ T m ( t) = kr g ΔT π + du u [ u ( + Rg) krg] exp( κu t / R ) 3 + ( u krgu) - ΔT = ΔT m () -k=3c p /c g g=g/λ g Plech et al. PRB 4

9 Interpolation of experimental data ΔΤ/Τ (normalisé) First attempt (Interface resistance) Second attempt (Diffusion in matrix) Ag nanoparticles (R=3 nm) t (ps) V. Juvé et al., PRB 9 Optimal fit (both processes) G = 94 MW.m -.K - Λ g =. W.m -.K - Conclusions: - Separation of interface/diffusion contributions - Inclusion of both effects necessary for all investigated samples (4-6 nm diameters).

10 Interface resistance vs acoustic mismatch Experimental results Acoustic mismatch model Based on continuum acoustics, no scattering /G (GW - m K) Ag/glass Au/glass AuAg/glass (m) Z m = ρ m v lm Transmission coefficient : Thermal conductance: α = ( Z (g) Z g = ρ g v lg 4 Z m m Z + Z g g ) G 4 c v m mα Z m /Z g V. Juvé et al., PRB 9 c:specific heat; v: sound speed Swartz & Pohl, Rev. Mod. Phys. 989 Conclusion: good correlation between interface resistance and acoustic mismatch.

11 Low-temperature experiments (Breschia) -5 ΔT/T ( -6 ) t (ps) 7K 3K K 5K - Sample: Ag/glass, R=4.5 nm - Optical setup inserted in a cryostat Cavity-damped laser with 54 khz repetition rate

12 Results Analysis: use of tabulated c silver (T) Deduced interface resistance c (J.kg -.K - ) T (K) Meads et al., JACS 94 Conductance G (MW.m -.K - ) T (K) Conclusions - G(T) c silver (T) ( 4% decrease from 3K to 7K) - Agreement with simple models (Acoustic/Diffuse Mismatch Models) (for instance, AMM predicts G ¼ c m v m α)

13 Conclusions Conclusion Probe wavelength matters! (time-resolved signals reflect T m only for probing away from resonance). Conclusion : - Both interface resistance and heat diffusion in matrix contribute to cooling dynamics in our experiments. - Interface resistance can be extracted from analysis with a complete model. Conclusion 3: Interface resistance varies as: - Acoustic mismatch at interface (room temperature) - /c m (low temperature) Qualitative agreement with Acoustic Mismatch Model G cvα

14 Prospects Larger range of impedance mismatch Goal: More quantitative study of the dependence of G vs impedance mismatch /G (GW - m K) Z m /Z g Correlation thermics/vibrations Goal: Compare breathing mode damping and cooling dynamics (involves all vibration modes) Single particle experiments - Tool: Spatial Modulation Spectroscopy Arbouet PRL 4 - Avoids averaging issues - Possible correlation with electron microscopy - Sensitivity to particle-substrate coupling?

15 Acknowledgements FemtoNanoOptics (LASIM, Lyon) V. Juvé A. Lombardi D. Mongin P. Maioli N. Del Fatti F. Vallée Università Cattolica Brescia Low-temperature Experiments F. Banfi D. Nardi C. Giannetti S. Dal Conte LPMCN (Lyon) Modeling S. Merabia L. Joly LPCML (Lyon) Samples A. Mermet E. Duval Nagoya university Samples S. Omi FemtoNanoOptics group (June ) Funding Opthermal project