Introduction

Random laser is a stimulated emission source without any precise external cavities.^1–3 Random laser consists of randomly shaped nano-or micropowders, and various luminescent materials such as semiconductor powders (ZnO,⁴ GaAs,^5,6 and ZnSe⁷), solid-state laser materials, and organic molecules.^8,9

In simple language, multiple scattering is the core reason behind the random lasing. Hence, this requires the randomness of the medium which lacks any long order. In the random medium with strong scattering strength, recurrent light scattering event arises. After multiple scattering the light returns to the previous scatterer. The interference of the return light is constructive only at certain frequencies. Therefore, the requirement for constructive interference of backscattered light selects the resonant frequencies. At or above the threshold lasing excitation power density (Pth), which is the minimum power density at which the lasing occurs, this multiple scattering leads to the increase in the population of the excited state so that the population inversion takes place, and consequently the stimulated emission occurs.

Because of its simplicity and low cost, the random laser is an attractive candidate for use in various light-emitting devices.³ However, in contrast to the case of the conventional lasers, the control of lasing emission wavelength in case of random lasers remains a challenge due to their simplicity. Some strategies for the control of the random lasing wavelength were proposed, e.g., controlling the Mie resonance by changing the sizes of scatterers,¹⁰ and modifying the gain curve by adding a light absorber.¹¹ Note that these reports describe the control of the characteristics of organic-dye random lasers with incoherent feedback.^1,10,11

In this experiment, we demonstrate the control of random lasing characteristics of semiconductor nanopowders (ZnO) with coherent feedback by the inclusion of dielectric nanopowder scatterers of Al2O3.

5.1 OBJECTIVE

In this experiment we demonstrate that the random lasing wavelength of ZnO/Al2O3 nanopowders can be controlled by varying the weight fraction of Al2O3 to ZnO (ƒw) in the sample. Specifically, we induce a blueshift in the lasing wavelength of the sample with increase in ƒw. We also show that the random lasing characteristics, like lasing wavelength and threshold excitation power density (Pth), can be well explained by a theoretical model based on the photon-transport mean free path( 𝑙𝑚𝑓).

5.3 EXPERIMENTAL

The size of ZnO and Al2O3 were 230 and 300 nm respectively. These nanopowders were mechanically mixed, and a thin film of the mixture was formed on a silicon substrate. The thickness of the samples was ~1 mm. The weight fraction of Al2O₃ to ZnO (ƒ_w) of the mixture samples was

32

varied from 0 to 100. Random lasing experiments were performed using a frequency-tripled light pulse of 355 nm from a Nd:YAG laser with a pulse duration of 5 ns. The excitation area was ~0.17 mm². All measurements were performed at room temperature.

5.4 RESULTS

5.4.1 Blueshift of lasing wavelength

As shown in Fig. 5.1, the wavelength of the lasing emission clearly depends on weight fraction of Al2O3 to ZnO (ƒw). With increasing ƒw, the lasing wavelength shifts toward a shorter wavelength side.

Also, as the lasing occurs simultaneously at wider range of wavelengths, we calculate the mean lasing wavelength (λ_{𝑚𝑒𝑎𝑛}) for each sample separately and the maximum shift of λ_{𝑚𝑒𝑎𝑛} observed in this study is ~4.0 nm. The sharp spike-like peaks appearing in the emission spectra fluctuate from pulse to pulse and this fluctuation is a typical feature of random lasers.¹²

0.08 0.09 0.10 0.11 0.12

160 180 200 220 240 260 280 300

P th (kW/cm2 )

l_mf (m)

Photoexcitation emission spectra of ZnO/Al2O3 nanopowders with various values of the weight fraction fw.

Excitation power density is 1450 kW/cm2.

Fig.5.1

33

In Fig. 5.3, the mean lasing wavelength (λ_{𝑚𝑒𝑎𝑛}) is plotted as a function of ƒw (solid squares, left axis).

λ_{𝑚𝑒𝑎𝑛} decreases with increasing ƒw. This result clearly shows that the random lasing wavelength can be controlled by changing ƒw.

To confirm the dependence of the scattering strength on weight fraction of Al2O3 to ZnO (ƒw), the photon-transport mean free path length ( 𝑙_𝑚𝑓), which is the average distance a wave travels before its direction of propagation is randomized, is calculated. The 𝑙_𝑚𝑓 gives the measure of scattering in the medium; higher its value, lower is the scattering strength. The mathematical model to calculate 𝑙_𝑚𝑓 is outlined below based on the literature.^13–15

𝑙_𝑚𝑓≅ _π𝑊^λ (𝑛_𝑒𝑓𝑓) (5.1)

Where, 𝜆 is the wavelength of scattered light and W represents full width at half maximum of the coherent backscattering peaks.¹³ (𝑛𝑒𝑓𝑓) is calculated as below.¹⁵

(𝑛𝑒𝑓𝑓) ≅ [1 − (𝑛𝑒𝑓𝑓)] [1 − 0. (𝑛𝑒𝑓𝑓)] (5.2) (𝑛_𝑒𝑓𝑓) = (3C₂ C₁) (3C₂− C₁ ) (5.3) 𝐶_𝑛 = ∫₀^{π 2}𝑟(θ, 𝑛_𝑒𝑓𝑓)sin 𝜃cos^𝑛θ𝑑𝜃, (5.4)

Where, 𝑟(θ, 𝑛_𝑒𝑓𝑓) is the Fresnel reflection coefficient averaged over the polarization of the boundary at given at a given incident angle θ.^16,17 𝑟(θ, 𝑛_𝑒𝑓𝑓) depends on the effective refractive index (𝑛𝑒𝑓𝑓) and is calculated using Maxwell-Garnett theory¹⁸ as below.

. (a)–(d) Histograms of the number of spike-like lasing peaks vs. lasing wavelength for various values of fw. 0

20 40 (a)f

w = 0 (only ZnO)

0 20 40 (b)f

w = 0.2

Number of lasing peaks

0 10 20 30 (c)f

w = 2

378 380 382 384 386 388 390 392

0 10

20 f

w = 20

Wavelength (nm)

(d)

Fig. 5.2

34 𝑛𝑒𝑓𝑓= [^{(1−𝑓)𝑛}_{1−𝑓+∑ 𝑓}^{𝑚2+∑ 𝑓𝑖β𝑖𝑛𝑖2}

𝑖β_𝑖 ]^{1 2} (5.5)

𝑓 = ∑ 𝑓𝑖 𝑖=2

𝑖=1

(5.6)

β_𝑖 = 3𝑛_𝑚² (𝑛_𝑖² 𝑛_𝑚²) (5.7)

𝑓1= 𝑓 (1 𝑓𝑤𝑑 ) (5.8) 𝑓2= 𝑓𝑑 (1 𝑓𝑤𝑑 ) (5.9)

Where, 𝑖 = 1 for ZnO; 𝑖 = 2 for Al2O3

𝑛𝑖: Refractive index of the 𝑖th inclusion 𝑓𝑖: Volume fraction of the 𝑖th inclusion

𝑛𝑚: Refractive index of the surrounding medium, which is air in this case 𝑑: Ratio of mass density of Al2O3 to ZnO

Also, in our case, the following is true.

𝑛1= .3 𝑛2= 1.76 𝑛𝑚= 1 𝑓 = 0.6 𝑑 = 0.71 W = 0.2 rad¹⁵

In Fig. 5.3, the inverse of the calculated photon-transport mean free path length (𝑙_𝑚𝑓) is plotted as a function of the weight fraction (ƒw). The value of 1/𝑙_𝑚𝑓 decreases, i.e., the scattering strength decreases as ƒw increases.

5.4.2 Blueshift analysis

One possible reason for the dependence of lasing wavelength on weight fraction of Al2O3 to ZnO (ƒw) is the modification in the extent of self absorption by ZnO nanopowders as a result of the addition of Al2O3. In the lasing process, a certain amount of the scattered light can be re-absorbed if the emission and absorption occurs in a pronounced manner in the case of the short wavelengths, longer light path length, or in other words, greater light-scattering strength may lead to redshift of the laser emission. The inset of Fig. 5.3 shows the absorbance spectrum of ZnO nanopowders. It can be easily understood from this spectrum that the optical absorbance is higher in the shorter wavelength region.

35

In the literature,¹⁹ the peak shift of photoluminescence spectra of dye molecules by modifying the self-absorption strength with the addition of scatterers in the luminescent medium was reported.

Therefore, one can expect that the self-absorption effect can lead to a peak shift in the photoluminescence spectra even though excitation power is below the lasing threshold (< ~160 kW/cm²). Figure 5.4 shows the peak wavelength of the emission spectra under no lasing excitation as a function of fw. Examples of these emission spectra are shown in the inset of Fig. 5.4. The blueshift with increasing fw can be clearly observed. However, the shift of ~1.9 nm is smaller than that of the lasing wavelength, which is ~4.0 nm [Fig. 5.2]. Although this difference is not fully understood at present, the larger shift corresponding to the laser wavelength may be because coherent light has a longer path length, and therefore, it is absorbed to a greater extent than spontaneous light.

380 385 390 395 400 405 410 0.0

0.2 0.4 0.6

Absorbance

Wavelength (nm)

Mean of the peak lasing wavelength as a function of the weight fraction of ƒw. The solid curve is the inverse of the calculated photon-transport mean free path ( 𝑙𝑚𝑓) (right axis) vs. ƒw. Inset shows the absorbance spectrum of ZnO nanopowders.

Fig. 5.3

36

5.4.3 Relationship of lasing parameters

Finally, the dependence of the lasing threshold power density (Pth) on weight fraction of Al2O3 to ZnO (ƒw) is examined. In Fig. 5.5(a), the lasing emission intensity lasing is plotted against the excitation power density for different ƒw. The lasing threshold excitation power density (Pth ) is found to depend on ƒw. This dependence of Pth on ƒw is considered to be related to the change in photon-transport mean free path length ( 𝑙_𝑚𝑓). With increasing ƒw, the effective refractive index of ZnO/Al2O3 decreases, and as a result, 𝑙_𝑚𝑓 changes (increases). In Fig. 5.5(b), Pth is plotted as a function of the calculated 𝑙_𝑚𝑓 for ƒw ranging from 0 to 100. Pth increases with increase in 𝑙_𝑚𝑓.The dependence of lasing threshold power density (Pth) on photon-transport mean free path length (𝑙𝑚𝑓) was reported in the literature.^20,21

In the literature,²⁰ the dependence of lasing threshold power Pth on 𝑙𝑚𝑓 was explained by a simple equation, _𝑡ℎ= 𝐴√𝑙𝑚𝑓, where A is a constant. Here, in the experiment, the best fit, which is represented by the solid line, is obtained with A=800. This good fit suggests that the reason for the variation in Pth with ƒw [Fig. 5.5(a)] is mainly the change in 𝑙𝑚𝑓.

0.1 1 10

383 384 385 386 387 388

380 390 400 410

f _w= 0 (only ZnO)

Peak wavelength (nm)

Weight fraction, f

w f_w = 20

Intensity (arb. units)

Wavelength (nm) f_w = 0 (only ZnO)

Peak wavelength in ZnO/Al2O3 emission spectra as a function of fw when the excitation power is substantially below the lasing threshold power (100kW/cm²). The inset shows examples of the emission spectra for fw=0 and 20.

Fig. 5.4

37

5.5 CONCLUSION

In conclusion, this experiment demonstrates that the change in the lasing wavelength of ZnO/

Al2O3 nanopowder random laser can be achieved by varying weight fraction of Al2O3 to ZnO (ƒw), in the sample. This change was found to be due to the modification in the extent of self-absorbing by ZnO resulting from the addition of Al2O3 scatterers. The controllability of lasing wavelength makes random lasers attractive for potential applications in identifications makers, displays, etc.

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7. T. Takahashi, T. Nakamura, and S. Adachi, Opt. Lett. 34, 3923 (2009).

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9. A. Tulek, R. C. Polson, and Z. V. Vardeny, Nat. Phys. 6, 303 (2010).

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11. R. G. S. El-Dardry and A. Lagendijk, Appl. Phys. Lett. 98, 161106 (2011).

12. K. L. van der Molen, A. P. Mosk, and A. Lagendijk, Phys. Rev. A 74, 053808 (2006).

Fig. 5.5 (a) Integrated lasing intensity of ZnO/Al2O3

nanopowders as a function of excitation power density for various ƒw.

(b) Threshold power density Pth as a function of 𝑙_𝑚𝑓(solid squares). The solid line represents the best-fit result given by the equation _𝑡ℎ= 𝐴√𝑙𝑚𝑓,

0.08 0.09 0.10 0.11 0.12

160 180 200 220 240 260 280 300

(b)

Pth (kW/cm2 )

l_mf (m)

100 200 300 400 500 600 700

0 5 10 15 20

100 20 4 0.2 0 (ZnO)

Ilasing (arb. units)

Excitation power density (kW/cm²) (a)

f_w

38

13. M. B. van der Mark, M. P. van Albada, and A. Lagendijk, Phys. Rev. B 37, 3575 (1988).

14. J. G. Rivas, A. Lagendijk, R. W. Tjerkstra, D. Vanmaekelbergh, and J. J. Kelly, Appl. Phys. Lett. 80, 4498 (2002).

15. D. A. Zimnyakov, A. B. Pravdin, L. V. Kuznetsova, V. I. Kochubey, V. V. Tuchin, R. K. Wang, and O. V. Ushakova, J. Opt. Soc. Am. A 24, 711 (2007).

16. M. Born and E. Wolf, Principles of Optics, 7th ed. (Cambridge University Press, Cambridge, England, 1999).

17. J. X. Zhu, D. J. Pine, and D. A. Weitz, Phys. Rev. A 44, 3948 (1991).

18. C. F. Bohren and D. R. Huffman, Absorption and Scattering of Light by Small Particles (Wiley, New York, 1998).

19. S. A. Ahmed, Z.-W. Zang, K. M. Yoo, M. A. Ali, and R. R. Alfano, Appl. Opt. 33, 2746 (1994).

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21. J. Kitur, M. Bahoura, and M. A. Noginov, J. Opt. 12, 024009 (2010).

39

6 Investigation of photoluminescence decay characteristics in metal/porous-silicon system.

6.1 INTRODUCTION

The luminescence decay characteristics, in various materials are known to be strongly modified by metal nanostructures. This is caused by the electromagnetic interactions between the host materials and metal particles via excitation of the surface plasmons in the nanostructures. This type of modifications has been observed in a wide variety of materials, such as semiconductor nanocrystals and organic molecules.

The primary purpose of this research is to investigate the modification of photoluminescence decay characteristics due to thin Au nanoparticle deposition on porous silicon (PSi), which is a typical nanocrystalline Si assembly. The motivation for the present research is that there are only few works on the PL decay characteristics of nanocrystalline Si modified by metal nanostructures.

This is because the nanocrystalline Si usually shows a complex decay process due to the broad distribution of radiative and non-radiative decay rates caused by the phonon-assisted recombination processes and also fluctuation of Si nanoparticle size and morphology.

6.2 OBJECTIVE

In present work, we investigate the modification of photoluminescence decay characteristics of Si nanocrystals due to very thin metal films. First, the decay curves were analyzed by taking the distribution of the decay rates into consideration. Second, we examined the emission wavelength dependence of the decay rates.

6.3 EXPERIMENTAL

Thin porous Si (PSi) layer of ~75 nm thickness was formed by the conventional anodic etching on the Si substrate and then, gold thin layers were deposited on this PSi by Vacuum Evaporation Deposition Technique. The mass thicknesses of gold is 1.0, 2.5, 5.0 nm. A schematic diagram for sample is shown in the Fig. 6.1.

6.4 Results

To analyze the decay curves, we used two decay functions. One is lognormal distribution function, equation (6.1). Another one is the stretched exponential function, equation (6.2), which is usually used for the fitting of decay curve of porous silicon. We try to fit the decay curves of porous silicon

Fig. 6.1 Sample for Au/PSi

Au

PSi

40

samples with both of these functions and found that both of the equations result in the best fit, as shown in the Fig. 6.2(a) and (b). This is because, the values of the reduced Kai square, which represents the goodness of fit, is close to unity in both cases..

However, as shown in the Fig. 6.3, only the lognormal distribution function results in the perfect fit for Au/porous-silicon ( Au/PSi sample).

𝛾𝑚𝑓= 0.0 1 μS⁻¹ 𝛾 = 0.093 μS⁻¹ 𝛾𝑠𝑡= 0.071 μS⁻¹

𝛽 = 0.7

(a) Stretched exponential decay function (only PSi sample)

Fig. 6.2

(b) Decay function with lognormal

distribution of decay rates (only PSi sample)

0 50 100 150

1 10 100 1000

(b)

 = 660 nm

²_R=0.73 Experiment Fitting

PL intensity (counts)

Time (sec)

∅(𝛾) = ∅(𝛾)

∞ 0

−1

−ln²(𝛾 𝛾_𝑚𝑓) 𝑤²

Decay function with lognormal distribution of decay rates 𝐼(𝑡) = 𝐼(0) ∫ ∅(𝛾)₀^∞ [−𝛾_𝑚𝑓𝑡]𝑑𝛾

𝑤 = sinh⁻¹( 𝛾 𝛾_𝑚𝑓) (6.1)

Stretched exponential decay function 𝐼(𝑡) = 𝐼(0) [−(𝛾𝑠𝑡𝑡)^𝛽] (6.2)

𝛾𝑚𝑓: Most frequent decay rate 𝛾: Width of ∅

𝛾𝑠𝑡: Decay rate of stretched decay 𝛽: Stretching factor

2

R

0 50 100 150

1 10 100 1000 (a)

 = 660 nm

²_R=0.72 Experiment Fitting

PL intensity (counts)

Time (sec)

41

We compare the decay curves for porous silicon/Au (Au/PSi) sample with that of only porous silicon sample. Figure 6.4(a) shows the comparison. We can see that the decay time becomes faster by the deposition of gold. From the decay fitting with the lognormal distribution function, we can obtain the distribution of decay rates. Figure 6.4(b) shows this distribution for the sample with and without gold. The distribution becomes wider by the deposition of Au.

The mean value of decay rate was calculated by the width and peak of distribution. These values are mean decay rates calculated for the sample with and without gold. The mean value of decay rate increases by a factor of about 10.

Figure. 6.5(a), shows that the decay rates for both the sample with gold layer and without gold layer depend on the emission wavelength. Moreover, Fig. 6.5(b), which is the plot of normalized decay rates for various gold layer thickness, demonstrate that the decay rates show the wavelength

] ) 2 / ( sinh 4 / 3

exp[

¹ _mf ²

mf

mean

  

 

^



𝛾𝑚𝑒𝑎𝑛= 0.78 μS⁻¹

𝛾_{𝑚𝑒𝑎𝑛}= 0.08 μS⁻¹

(a) Decay curves (b) Decay rate distributions

Fig. 6.4

0 20 40 60 80 100

1 10 100

1000 ²_R=1.07 Experiment (b) Fitting

PL intensity (counts)

Time (s)

 = 660 nm

𝛾 𝑡= 0. 9 μS⁻¹ 𝛽 = 0.63

𝛾𝑚𝑓= 0.19 μS⁻¹ 𝛾 = 0.71 μS⁻¹

(b) Stretched exponential decay function for Au/PSi sample

Fig. 6.3

(b) Decay function with lognormal distribution of decay rates for Au/PSi samples

0 50 100 150

1 10 100

1000 (a)

with Au

 = 660 nm

PL intensity (counts)

Time (s)

without Au

0.0 0.2 0.4 0.6 0.8 1.0

0.0 0.2 0.4 0.6 0.8 1.0

(b)

without Au

Distribution, () (normalized)

Decay rate,  (s^-1)

with Au

0 20 40 60 80 100

1 10 100 1000 (a)

 = 660 nm

Experiment Fitting

²_R=168

PL intensity (counts)

Time (sec)

ドキュメント内 Properties of metal/porous Si composite materials (ページ 31-42)