Normalized Time
4. Removal of particles on surfaces via laser induced bubble nucleation: Steam Laser
Cleaning
The forces exerted by the laser induced explosive evaporation can be used to remove particle contamination from surfaces. In this process called Steam Laser Cleaning (SLC) a liquid is condensed onto the surface to be cleaned and irradiated by a laser pulse. Clearly the experiments on laser induced bubble nucleation in bulk liquids described so far provide an important basis for the understanding of the SLC process. However, it should be pointed out that the bubble behavior described above is characteristic for bulk liquid rather than thin liquid films. Studies on film boiling still have to be carried out in future experiments.
4.1. Efficiency measurements
4.1.1. Dependence on the number of applied laser pulses
Clearly, with view to applications, the most interesting question in a surface cleaning process is its efficiency. More precisely, one is interested in the minimum particle size that can be removed, the percentage of particles of different size that can be removed, and in the process parameters necessary for particle removal.
As described in Section 2 we have used spherical colloidal particles made of PS and SiO2 as model contaminants in our cleaning studies. For these particles we have determined cleaning efficiencies for a wide range of particle sizes. While varying the process parameters regarding the applied Nd: YAG laser (number of pulses, laser fluence) we have up to now not varied the liquid film properties. The film thickness was kept at a constant value in between 200 nm and 400 nm as determined by reflectometry. We also did not vary the composition of the liquid; a mixture of water (90%)
Fig. 22. Computed maximum temperatures in water on a silicon surface as function of the heat transfer coefficient (HTC) xH2O for different starting temperatures T0. As laser fluence we used the experimentally determined threshold fluence for bubble nucleation.
Fig.23. Computed maximum temperatures in IPA on silicon as function of the heat transfer coefficient xIPA for different starting temperatures T0. As laser fluence we used the threshold laser fluence.
and IPA (10%) was evaporated in all experiments.
When preparing samples with a high density of particle contaminants (average distance about 10 mm) of course one must make sure that they do not influence each other during the cleaning process. Fig. 24 shows the removal efficiency for 800 nm silica spheres as a function of laser fluence for 1, 2, 10, 20 cleaning steps. At a laser fluence of 115 mJ/cm2 the first probability P that a particle is removed by an individual laser pulse should only depend on the applied laser fluence F and not on the previous pulses.
Hence when a sequence of n pulses is applied, the fraction of remaining
An analysis of the data presented in Fig. 24 indeed confirms this prediction experimentally, as demonstrated in Fig. 25, where we have plotted data for
(
1-I I0)
versus the number of applied laser pulses for a laser fluence of 115 mJ/cm2 per pulse (I0 denotes the initial scattering intensity.) According to the argument given earlier the quantity I I0 is equivalent to the fraction of remaining particles. Hence(
1-I I0)
is the fraction of removed particles, which we denote in the following as "cleaning efficiency". Using Eq. (19) one expects that(
1-I I0)
should vary as(
1-(
1-P)
n)
. The full line in Fig.25 represents this quantity with P taken to be 0.05, as derived from the datum point for the first pulse. The agreement between the data and this line is quite satisfactory. Therefore the removal process for our samples appears to be well controlled and statistically independent for different particles, making quantitative studies feasible.
Fig. 24. Cleaning efficiency for 800 nm silica spheres as a function of laser fluence for 1, 2, 10, 20 cleaning steps.
4.1.2. Dependence on the laser fluence and variation of particle size Results of the energy dependence of particle removal by the steam laser cleaning process for PS spheres with diameters of 800 nm, 500 nm, and 60 nm are plotted in Fig. 26. With regard to a better illustration of the cleaning behavior the results for 20 cleaning steps are plotted, which is justified by the statistically independent cleaning behavior.
For all sizes we obtain a similar behavior of the efficiency as a function of laser fluence: a steep increase in the cleaning efficiency at of F = 110 mJ/cm2. This absolute value of the threshold fluence was determined as described in Section 2. A comparison of the laser fluence needed for cleaning to the one necessary for melting the optical penetration depth of the silicon substrate resulted in a value of 0.35, which corresponds to above quoted threshold fluence.
Fig. 25. Comparison of the experimental data from Fig. 24 obtained at a laser fluence of 115 mJ/cm2 and of the theoretical value provided the particles are detached statistically independent.
The same cleaning threshold was found for PS spheres with diameters of 235 nm and 300 nm. These results are not shown in the graph for the sake of clarity. At fluences above 170 mJ/cm2 more than 90% of the particles were removed after 20 cleaning steps (steam pulse plus laser pulse). For comparison the threshold where a (bare) Si surface would start to melt at the laser parameters used here is 270 mJ/cm2.
In order to study the influence of the particle material on the cleaning efficiency we used silica spheres with diameters of 800 nm and 500 nm and polydisperse alumina particles with a mean diameter of 300 nm. Once again we obtain the same threshold as for PS spheres (Fig. 27) and the same dependence of the cleaning efficiency on the laser fluence. Thus the cleaning threshold is independent of both particle size and material for the investigated particles. Experiments using slightly different laser parameters (l = 583 nm, FWHM = 2.5 ns and 7 ns as well as l = 532 nm and FWHM = 2.5 ns) revealed again the same cleaning threshold as reported above (Mosbacher, 2000).
Fig. 26. Experimentally determined cleaning efficiencies as a function of applied laser fluence for various PS spheres. The cleaning threshold is size independent and the cleaning efficiency exhibits a steep increase above the onset of cleaning.
Fig. 27. Experimentally determined cleaning efficiencies as a function of applied laser fluence for particles of different geometry, material and size. A material- and size independent threshold and a steep increase of the cleaning efficiency was monitored.
4.2. Discussion and concluding remarks
Whereas the majority of publications on "laser cleaning" deal with DLC, only few focus on the quantitative determination of removal efficiencies in SLC and the investigation of the basic processes. Before discussing our results described in the previous sections, we will highlight three of these SLC studies in order to provide the necessary background.
In a recent theoretical study (Lu, 1999) have developed a first approximate scenario for the SLC process. The most important prediction of this treatment is size dependent cleaning threshold fluence for the removal of particles from surfaces when using ethanol and acetone as liquids in the process. Experimental results reported by (She, 1999) seem to indicate that the predictions by Lu et al. are valid. Removing Al2O3 - particles from NiP surfaces and using a "micron thick" water film, She, Kim and Grigoropoulos found that "the minimum laser fluence for removal of micron-sized or larger contaminants was lower by a factor of about 2 than the fluence necessary for complete removal of 0.3 mm particles".
The second theoretical description of SLC by Wu, Sacher and Meunier, 2000 also predicts a particle size dependent cleaning threshold. As in the Lu model, the authors compute the pressure of a shock wave created by the nucleating bubbles and deduce from this pressure the cleaning force exerted on the contaminant particles. Interestingly the authors report some experimental values. They found that for SiO2 and Al2O3 particles with a mean diameter of 100 nm the particle removal threshold is identical and very close to the threshold of bubble nucleation.
Our findings of a universal cleaning threshold in SLC are in serious contradiction to the predictions of size dependent thresholds. The universality actually refers to two aspects. First we noted an independence of the applied particle materials PS, SiO2 and Al2O3 that was also reported by Wu et al. Even more surprising, however, is the size independence, especially if one brings to mind the large differences in the adhesion forces of the particles used in our experiments. The difference in adhesion between the smallest particles with 60 nm in diameter and the largest ones with a diameter of 800 nm should vary by one order of magnitude, since the adhesion force is proportional to the particle radius (Johnson, 1971; Heim, 1999).
Although the investigations presented here are the first systematic quantitative studies of cleaning thresholds in SLC, many open questions still have to be answered prior to a full understanding of the processes underlying particle removal in SLC. Most of these refer to the dependence of the cleaning threshold and maybe its uniformity on process parameters such as liquid film thickness, liquid composition or laser wavelength. For instance one possible explanation for the different findings of the Grigoropoulos group may be their film thickness of a few micron compared to our 200-400 nm thick films.
The importance of controlling the liquid film properties and understanding its influence on the SLC process becomes even more obvious taking into account that the mechanism considered to be responsible for particle removal - the explosive liquid evaporation - should depend critically on the liquid film properties. As already mentioned above Wu et al. point out a close agreement of the particle removal threshold and the bubble nucleation threshold in their experiments. Indeed such an agreement provides one possible explanation for the universality of the cleaning threshold for particles completely embedded in the liquid film (Mosbacher, 2000). Should SLC be solely governed by an explosion of the liquid film, the process consequently will be determined by parameters of the film rather than particle properties.
Although this is a possible and plausible interpretation of our results, still a lot of research has to be carried out in the field of laser induced bubble nucleation and explosive film evaporation in order to unequivocally clarify the relevant SLC processes. The experiments reported in the first part of this paper were also motivated by this requirement. Improving techniques such as Scattered Light Probes (SLP) and developing powerful tools like Surface Plasmon Probe (SPP) we have been able to elucidate crucial details of laser induced bubble nucleation on surfaces. These include the recording of the pressure waves and detecting the associated pressure amplitudes in the MPa regime. From the experiments we were also able to deduce the gas bubbles growth velocities, which were found to be in the range of a few m/s.
Probably the most important results, however, are related to the measurement of the laser threshold fluences necessary for bubble nucleation and especially the related superheating temperatures of the liquids.
Superheating of the liquid can occur in SLC due to the deposition of the laser energy during a very short time interval of a few ns. Since the pressure amplitudes in SLC depend very strongly on the liquid temperature, the
liquid superheating may be the key parameter of the process. One major finding of our experiments in this field is the strong dependence of the extent of superheating on the surface roughness. On thin metal films only small amounts of superheating in the order of 10-30 K have been measured.
In contrast on smooth silicon wafers we measured superheating of about 150 K! Moreover, from these superheating temperatures it was possible to show that the heat does not flow freely from the substrate to the liquid, but is inhibited by the solid-liquid heat resistance described in the case of a silicon-water interface by a heat transfer coefficient of 3 ·107 W/m2K.
These two results - high superheating temperatures on smooth silicon wafers and the existence of a finite temperature jump between substrate and liquid - severely question the predictions of the existing SLC models (Lu, 1999; Wu, 2000). Both models strongly rely on several assumptions whose validity must be challenged against the experimental findings. In reference (Lu, 1999), e.g., the bubble growth velocities are computed using the oversimplified formula (14) and our results on bubble growth and superheating (Yavas, 1997 a) obtained on rough metal films are transferred to the silicon-liquid system, which is clearly invalid. Additionally both groups obtain the temperature of the liquid layer by a numerical computation assuming a perfect heat flow from the substrate into the liquid. This is invalid as well, which can be illustrated by the results of numerical computations we carried out on our own. Inserting not only the correct heat transfer coefficient but also temperature dependent material properties for the liquid and the substrate, our calculations based on the 1D heat equation (Bischof, 1996; Dobler, 2002) show temperature differences of liquid and substrate of about 100 K!
Besides the above comments some even more fundamental questions remain. Both models rely on the assumption that shock or pressure waves produced by the growing bubbles/ growing vapor layer exert the removal force on the particles. However, the details of this scenario are still open .
Is it really a vapor layer, as suggested by Wu, which is responsible for the removal force? Or are a few gas bubbles enough, as it is incorporated in the Lu model? Where are these gas bubbles nucleated - all over the bare silicon surface as Lu suggests? In this case as well as in the assumption of a vapor layer - why is it possible to perform “steam" cleaning just by adsorbing a small amount of liquid at the particle-surface interstice via capillary condensation (Fourrier, 2001; Mosbacher, 2002 a)? Here the above approaches to explain the cleaning mechanism fail. And - related to the last
comment - what is the influence of the film parameters, especially the film
Even the experimental results pose questions: The threshold for bubble nucleation by a single Nd: YAG-pulse measured for the silicon/bulk water system is about 80 mJ/cm2. When compared to the universal cleaning industry. Considering the unsolved questions raised above one might doubt that there is any hope of developing SLC to be a reliable tool in the near future.
We do not agree and believe, that SLC is extremely promising for the process parameters we used. The existence of the universal cleaning threshold at a laser fluence a factor of three below the melting threshold of bare silicon shows, that it is possible to choose one fixed laser fluence well below the substrate melting fluence to remove particles of a broad size range. Moreover, this is also a considerable advantage in terms of possible applications over DLC, where the threshold is size and material dependent, the removal efficiencies are lower and particles smaller than 100 nm could not be removed (Zapka, 1991; Mosbacher, 1998, 2002 a, b). Thus SLC allows particle removal at lower and therefore safer laser fluences, which is essential for avoiding surface modifications.
In the field of liquid parameters still a lot of systematic research has to be carried out, however, our results with removal efficiencies of 90% for particles 60 nm in diameter show that efficient cleaning is already possible.
Thus the basic prerequisite for a real world application of SLC is fulfilled:
the process works and suitable process parameters are known. Nevertheless it is not clear whether these parameters are the optimum ones. This optimization will be triggered by the growing knowledge on the fundamentals of SLC and will, together with the investigation of different
substrate materials, provide the field of future research on this exciting topic.
Acknowledgements
This review is result of our scientific collaboration between the University of Konstanz, Germany and Data Storage Institute, Singapore. We thank Dr.
Nikita Arnold (Johannes-Kepler-University, Linz, Austria), Dr. Bernd-Uwe Runge, Johannes Graf and Florian Lang (all University of Konstanz) for constructive discussions of the findings of our experiments. Financial support by EU TMR project "Laser Cleaning" (no ERBFMRXCT98 0188) and the Konstanz Center for Modern Optics is gratefully acknowledged.
Wacker Siltronic supplied the industrial silicon wafers.
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