ULTRASONIC AND MEGASONIC PARTICLE REMOVAL. Ahmed A. Busnaina, Ph.D. and. Glenn W. Gale

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1 ULTRASONIC AND MEGASONIC PARTICLE REMOVAL by Ahmed A. Busnaina, Ph.D. and Glenn W. Gale ABSTRACT Particulate surface contamination is one of the major causes of low yields in the semiconductor and other affected industries. The theory of low frequency (ultrasonic) and high frequency (megasonic) cleaning will be presented. Ultrasonic cleaning (less than 100 khz) is relevant to cleaning of optics and precision parts. Megasonic cleaning (0.8 to 1.2 MHz) is used in semiconductor manufacturing. Experimental results for both types of cleaning, using semiconductor wafers, will be presented. Effects of varying operational parameters such as sonication time, and solution chemistry are shown. Effects of different particle composition and size challenges upon removal efficiency are also shown and discussed in terms of theory. Results indicate a strong dependence upon particle size and composition. Removal is also shown to be higher in SC1 than in water. Emphasis will be placed upon cleaning of semiconductor (Si) wafers, but concepts can be applied to cleaning of other parts as well. 1. INTRODUCTION Particulate contamination is a major cause of yield loss in a number of industries. Precision optical surfaces need to be as free of contaminant particles as possible. Aerospace and aircraft guidance parts, surgical parts, and electronic parts also require extreme cleanliness. Semiconductor manufacturing places perhaps the most stringent demands upon its cleaning processes (wafer cleaning). Particles introduced by chemical reactions during processing, or deposited via human or automated wafer handling, can subsequently shield lithographic reproduction, cause oxidation-induced stacking faults, and lead to both short and open circuits. Film and ionic contamination must also be controlled in the manufacture of state-of-the-art integrated circuits. Particulate control is governed, to a first approximation, by the one-tenth rule, which specifies the need to control particles to one tenth the minimum circuit linewidth. Figure 1.1 shows the decrease in characteristic linewidth with semiconductor generation and year, and the maximum contaminant particle size allowable under the one-tenth rule. Precision Cleaning 95 Proceedings 347

2 Figure 1.1 Decrease in linewidth with technology generation, and corresponding maximum allowable particle size based on the one-tenth rule. Cleaning at typical ultrasonic frequencies ( khz, used for less critical parts in other industries) became somewhat discredited in semiconductor manufacturing, since associated cavitation implosion can cause surface damage. However, it was later found by engineers at RCA that sonic cleaning in the 0.8 to 0.9 MHz range (termed megasonic cleaning), was effective at removing surface contaminants without inflicting damage [l-2]. The investigators concluded that at megasonic frequencies there was insufficient time between wave passages for the formation and implosion of cavities to occur. The specifics of ultrasonic and megasonic cleaning will be presented here, beginning with a theoretical and literature review. Some particle removal data will also be presented. 2. THEORETICAL REVIEW 348 Precision Cleaning 95 Proceedings

3 2.1 Ultrasonics - General Theory Ultrasonic cleaning tanks typically have bottoms which vibrate at a known frequency. The flexing is generated by piezoelectric transducers. A piezoelectric substance will become electrically polarized when mechanically stressed, and will mechanically deform when electrically polarized. Alternating positive and negative polarization results in alternating thickness of the material at the same frequency. This produces a sound wave that propagates through the tank. A sound wave is a pressure wave traveling with a particular velocity, c, which is dependent upon the medium. Pressure is a function of position and time, governed by the well known wave equation in which p=p(x,y,z,t) is the dynamic pressure. solution is a sinusoidal plane wave, given by For one dimensional motion the most common where p 0. is the pressure amplitude, ƒ the frequency, the wavelength equal to c/ƒ, and the phase shift. If we define the angular wave number as and as the angular frequency, equation (2.2) can be expressed as The same form applies for fluid particle velocity at a point, u(x,t), in terms of the velocity amplitude u O. There is, however, attenuation of the wave or loss of energy as it travels through the medium. Causes of attenuation are scattering, diffraction, and absorption [3]. Scattering occurs only when the fluid contains a significant number of particles which reflect the sound beam. Attenuation near the transducer is caused mainly by absorption. The primary type of absorption results from interaction with the fluid medium and can be subdivided into viscous losses, heat conduction losses, and losses associated with molecular energy exchange [4]. In most liquids, including water, absorption is due mainly to the bulk viscosity. It is characterized by a lag or relaxation time associated with viscous damping of the pressure waves. The absorption results in work being done on the fluid during each pressure variation cycle, resulting in an increase in temperature and heat energy of the medium and a decrease in acoustic energy of the wave. Absorption is governed by the absorption coefficient a, which is a property of the medium. Accounting for absorption, any wave function (such as pressure or velocity), must be multiplied Precision Cleaning 95 Proceedings 349

4 Values of ultrasonic power are typically presented in terms of intensity I, which is power per unit area. For a wave propagating in one direction from a source, the intensity is given by [3] where p is the density of the medium. The units of intensity are W/m. Sound speed is a strong function of temperature, decreasing as the latter increases in most liquids [3]. In water, however, it increases with temperature up to 73 C, after which it decreases. At room temperature the speed of sound in water is about 1500 m/s. Strictly speaking, the term ultrasonics refers to any frequency above what is audible to humans (approximately 18 khz and higher). The term megasonics is used in industry to refer to ultrasonics at frequencies near 1 MHz. 2.2 Cavitation One of the primary sources of cleaning effects, particularly at low frequencies. is cavitation. Cavitation is the formation and collapse of bubbles of either gas or vapor in a liquid subjected to pressure changes. If the liquid pressure drops below a certain value, known as the cavitation threshold, cavitation will occur. In ultrasonics, this threshold corresponds to a minimum pressure amplitude required to induce cavitation. Cavitation can be stable or transient. Stable cavitation entails only small oscillations about an equilibrium bubble radius, while transient cavitation is characterized by large bubble size variations (over just a few acoustic cycles) and eventual bubble collapse which can frequently be quite violent [5]. The formation of cavities in liquids is somewhat analogous to tensile failure in solids. When the tensile strength of a liquid is exceeded, cavities form. Actual values of these strengths are much lower than theoretical values. In water, for example, the theoretical tensile strength is approximately 1000 bar, whereas in practice it is only about 1 bar. As with solids, this is a result of imperfections in the material; in liquids these imperfections are gas pockets found in solid contaminants or other immersed solid surfaces [6]. These gas pockets serve as nuclei for cavitation. When a high enough amplitude is reached the nucleus becomes unstable and rapidly grows into a mostly vapor-filled bubble which is a transient cavity (whereas stable cavities are primarily gas-filled). The cavitation threshold, defined as the minimum pressure amplitude to induce cavitation, has been studied for water as a function of various liquid properties [5]. Cavitation threshold has been found to decrease with increasing liquid/gas surface tension (which stabilizes nuclei), increase with increasing hydrostatic pressure (under most conditions), decrease with increasing temperature (dropping to zero near the boiling point) and decrease with increasing number of solid contaminants. In the sonic cleaning of silicon wafers, the two important aspects of cavitation are its effect on particle removal and its infliction of surface damage. It is useful, then, to know at what frequencies and acoustic intensities cavitation will occur in a cleaning bath. The existence of cavitation at low frequencies, up to 100 khz, is well known. Shwartzman. 350 Precision Cleaning 95 Proceedings

5 et. al. [l], concluded from their pioneering work in megasonic cleaning that in the 850 to 900 khz range there is insufficient time between pulses to allow the formation of cavitation bubbles. The intensity was 5-10 W/cm 2 in their experiments. Studies have confirmed that the cavitation threshold pressure increases considerably with increasing frequency [7]. Some of the most comprehensive experimental work in this area was performed by Esche [8]. He studied cavitation over a range of frequencies and determined cavitation threshold pressure amplitudes for both aerated and degassed water. At 40 khz, a typical ultrasonic cleaning frequency, the threshold according to Esche s curves is on the order of one atmosphere. At 850 khz, a typical megasonic cleaning frequency, his data indicate a threshold in excess of 100 atmospheres. In contrast, other data [9] indicate a threshold of around 10 atmospheres at this frequency. The reason for the discrepancies is that the threshold is extremely sensitive to experimental conditions. Furthermore, there are no standard criteria for determining whether or not cavitation exists. Different investigators employ different criteria and have varying limits as to the smallest scale on which cavitation can be detected. In fact, sound frequency does not affect cavitation threshold so much as it affects the maximum radius to which cavities can grow [9]. In some cases, then, bubbles may exist but be undetectably small. Cavitation erosion of surfaces is a physical phenomenon. While low gas content increases the cavitation threshold pressure, it will also increase cavitation damage since those cavities that do form collapse more violently in the absence of cushioning gas [l0]. Determination of the exact mechanism of damage has been an area of considerable study. Extremely high velocities and temperatures are associated with cavity implosion. Experiments by Naude and Ellis [11] using high speed photography have shown, however, that erosion is caused by high speed jets from bubble implosion at a surface, rather than from extreme pressures and temperatures resulting from cavity collapse. Furthermore, their calculations indicated that a cavity oscillating as it grew would create higher jet speeds than would a jet which grew monotonically with time. Busnaina and Kashkoush [12] observed cavitation damage to silicon wafers subjected to 40 khz ultrasonic cleaning. Lifting of metal lines less than 1.0 µm wide, caused by vibrating bubbles penetrating beneath the lines, was also observed. The investigators were able to eliminate such damage by using a frequency sweep and maintaining a high gas content in the water (to lessen the impact of cavitation implosion). 2.3 Acoustic Streaming In spite of the sinusoidal nature of sound waves, the particle velocities they induce are not strictly sinusoidal. Rayleigh and other researchers noted the motion of dust particles in a tube of air in the presence of sound. Patterns of circulation that were not time dependent were observed. When the Navier-Stokes equations governing the flow are solved, there is indeed a time independent component of velocity which exists in addition to the oscillating component. This occurs because of small drifts in the position of a fluid particle during each acoustic cycle, caused by attenuation of the wave in a viscous medium [13]. The sum of these small drifts is acoustic streaming, the patterns of which are complex and geometry dependent. Streaming can be classified as occurring inside or outside of the acoustic boundary layer. Outside the boundary layer streaming is characterized by a larger scale (larger than the acoustic Precision Cleaning 95 Proceedings 351

6 wavelength). Inside the boundary layer (Schlichting streaming) the scale of the streaming vortices is much smaller than the acoustic wavelength. An extensive review of the equations of acoustic streaming is given by Nyborg [14, 15]. Figure is an image taken by the present authors, at the Microcontamination Research Laboratory at Clarkson University. It shows streaming from a 360 khz transducer at 100 W in a water tank. Prior to the experiment, air was pumped into the water. An argon ion laser was used to generate a vertical sheet of light, which illuminated bubbles in the water to reveal the streaming pattern. A video camera at a shutter speed of l/1000 seconds, and a frame grabber were used to capture the image. The acoustic boundary layer thickness is given by [13]. Velocity gradients are very large in the boundary layer. Steady viscous stresses are exerted on the boundaries where this type of circulation occurs, and these stresses may contribute significantly to removal of surface layers [15]. Rate processes can also be accelerated by this convective motion. Also of interest is acoustic microstreaming, which occurs near bubbles of gas, or any compressible substance, in the irradiated liquid [14, 16]. In this powerful type of streaming, the bubbles scatter sound waves and generate remarkably swift currents in localized regions. These also contribute to sonic cleaning. The currents are most pronounced near bubbles undergoing volume resonance, and located along solid boundaries [16]. Microstreaming has been observed to pass abruptly through several stable regimes as amplitude is varied. Experiments by Elder in water, revealed that several modes of vibration of bubbles on a solid boundary. As the bubble surface velocity increased past 11 cm/sec, the bubble surface vibrated in a stable mode and microstreaming was observed near the top of the bubble. When the surface velocity reached 31 cm/sec, a new surface mode suddenly appeared and the streaming reversed its direction. Some time after a 60 cm/sec surface velocity was exceeded, this stable surface mode was transformed into a chaotic surface agitation, and the bubble was surrounded by a large vortex ring. After this point, no change was observed when driving amplitude was increased further. A very thin boundary layer region was observed near the bubble surface. Similar streaming patterns and regimes were generated for liquids of different viscosities. For an air bubble in water at 10 khz a tremendous velocity gradient of 1.5 x 10 5 cm/sec per cm was calculated [16]. Acoustic streaming, both inside and outside the boundary layer, clearly provides sonochemical enhancement to cleaning processes. Transport is aided significantly by the strong currents and small boundary layer thicknesses resulting from streaming. The acoustic boundary layer thickness decreases with frequency, dropping from about 2.82 µm at 40 khz to about 0.59 pm at 900 khz. 3. CLEANING EXPERIMENTS All experiments were performed in the class 10 cleanroom of the Microcontamination Research Laboratory at Clarkson University [17]. Particle removal efficiency was measured at several frequencies between 40 and 862 khz. The 862 khz experiments were performed using a commercially available megasonic cleaning system (maximum power input 150 W), while 352 Precision Cleaning 95 Proceedings

7 Fig Acoustic streaming from a 360 khz transducer at 100 W. [Transducer courtesy of Branson Ultrasonics]. Precision Cleaning 95 Proceedings 353

8 commercial ultrasonic tanks and generators (40, 65, 80, and 100 khz) were used in the remaining experiments. Silicon wafers used were 125 mm p-type (100), of Q-cm resistivity. The wafers were cleaned prior to deposition using an SC1 (1 NH 4 OH : 1 H 2 O 2 : 5 H 2 O) bath and scanned by a PMS laser surface scanner (with 0.1 µm resolution) to establish a background particle count. This number of particles of unknown origin was subtracted from the total number of particles on the wafer before and after sonic cleaning. Particles used were PSL spheres, SiO 2 (silica) spheres, and nonspherical Si 3 N 4 (silicon nitride) particles. Mean diameters of 0.3, 0.4, 0.5,0.6,0.7, and 1.0 µm were employed. These particles, originally in a concentrated high purity aqueous solution, were mixed with isopropanol (IPA) to form a dilute solution, eliminating the problem of particle agglomeration. The resulting suspension was atomized using a nebulizer with 0.1 µm filtered air, and deposited onto the wafers. Approximately 150 to 300 particles were deposited on each wafer, resulting in relatively low pre-cleaning particle counts ( particles/cm 2 ). Wafers were then loaded into a 25-wafer PFA teflon cassette, which was inserted vertically into the tank. After the required immersion time, the cassette of wafers was removed from the tank. Wafers were rinsed in DI water and dried, They were then scanned once more to obtain the post-clean particle count and particle size distribution. Thus a removal efficiency could be computed as follows: in which N before is the number of particles deposited on the wafer surface prior to sonic cleaning, and N after is the number of particles remaining on the surface after cleaning. For any particular operating condition, ten experiments were run, ten removal efficiency values were measured, and their average was calculated. The experimental matrix included the effects of frequency, irradiation time, liquid temperature, particle diameter and composition, power output, and solution chemistry. This paper will focus on the effects of particle composition and solution chemistry on megasonic particle removal. 4. RESULTS 4.1 Effect of Particle Composition Figures 4.1.1, and show the removal efficiencies in DI water of PSL, SiO 2 and Si 3 N 4 particles, respectively [17]. Data were taken at 862 khz, using a power of 150 W to the transducers. The results show that in nearly all cases the removal efficiency increased with increasing particle size. Additionally, while removal efficiencies for silica and PSL were comparable, the removal efficiency of silicon nitride particles was clearly lower. The removal efficiencies of PSL, SiO 2 and Si 3 N 4 in SC 1 solution are shown in figures 4.1.4, and 4.1.6, respectively [17]. Again efficiency increased with increasing particle size. Furthermore, efficiency was again lowest for silicon nitride particles, while removal efficiencies 354 Precision Cleaning 95 Proceedings

9 Fig Removal efficiency as a function of irradiation time for PSL spheres in DI water at 862 khz and 150 W. Fig Removal efficiency as a function of irradiation time for SiO 2 spheres in DI water at 862 khz and 150 W. Precision Cleaning 95 Proceedings 355

10 Fig Removal efficiency as a function of irradiation time for Si 3 N 4 particles in DI water at 862 khz and 150 W. Irradiation Time (min) Fig Removal efficiency as a function of irradiation time for PSL spheres in SC1 solution at 862 khz and 150 W. 356 Precision Cleaning 95 Proceedings

11 Fig Removal efficiency as a function of irradiation time for SiO 2 particles in SC1 solution at 862 khz and 150 W. Fig Removal efficiency as a function of irradiation time for Si 3 N 4 particles in SC1 solution at 862 khz and 150 W. Precision Cleaning 95 Proceedings 357

12 between silica and PSL particles were comparable. The reasons behind these effects of particle composition will be discussed in the next section. 4.2 Effect of Solution Chemistry The data in figures through indicate that for all particle types, SC1 solution was more effective for removing particles. The mechanism of particle removal by SC1 will be discussed in the next section. 5. DISCUSSION 5.1 Forces on Particles and the Effect of Composition The dominant particle adhesion mechanism in liquid media is the long range Van der Waals force, which results from dipole attractions. the magnitude of the van der Waals force for a sphere adhering to a flat substrate is given by (51.1) where r is the sphere radius, z is the distance of separation between sphere and substrate (typically taken to be 4 Angstroms) and A is the Hamaker constant. The Hamaker constant is a property of the materials involved, and has energy units. If two substances have Hamaker constants A,, and A 22, the Hamaker constant between them is given by If the two substances are immersed in a medium (material 3), then the Hamaker constant for the system is typically defined by (5.1.3) Visser [18] compared microscopic (Hamaker) theory with macroscopic (Lifshitz-van der Waals) theory and developed a medium-dependent correction factor, c, such that (5.1.4) 358 Precision Cleaning 95 Proceedings

13 For water, c is about 1.5 to 1.6. Hamaker constants and associated adhesion forces have been calculated for various particles adhering to silicon in water [19]. In any case, the relationship between van der Waals force and particle diameter means that the adhesion force will decrease linearly with decreasing particle size. In most particle removal techniques using forces such as centrifugal and/or hydrodynamic drag, however, removal forces are proportional to the second or third power of particle radius and therefore decrease at a higher rate. Thus particles of smaller sizes are more difficult to remove. Differences in removal efficiency can be attributed in large part to different Hamaker constants between materials. The Hamaker constant is slightly higher for SiO 2 than for PSL. While we would thus expect a slightly lower removal efficiency for silica compared with PSL, the efficiencies are in fact comparable. Though the discrepancy is small, it could be due to electrical double layer effects (to be discussed later) or deformation of the PSL spheres which has been shown to increase adhesion [19]. The removal efficiency of Si 3 N 4, however, is significantly lower. This is attributable in part to the nonspherical nature of the silicon nitride particles. Their shape leads to greater numbers of contact points with the substrate, increasing the adhesion force. Electrokinetics are also a factor. Solid surfaces in liquid media form a layer of charge through adsorption of ions or dissociation of surface groups. This layer of charged species moves with the particle, and attracts a layer of oppositely charged ions in the surrounding liquid. The two layers are collectively called the electrical double layer, and the boundary between them is the shear plane. The electrical potential at the shear plane is defined as the zeta potential. The zeta potential is important because it determines whether a particle will be attracted or repelled by another charged surface in the fluid if their electrical double layers overlap. Zeta potential is a strong function of both the ph and the ionic strength of the solution. The effect of zeta potential on deposition of particles onto silicon wafers has been studied [20] using various ph and ionic strength solutions. As ph increases zeta potential decreases, typically changing from positive to negative somewhere between low and high ph values. The point at which the zeta potential is exactly zero is referred to as the isoelectric point or point of zero charge (pzc). The pzc of different solids depend uppon the H + and OH - ion concentrations in the solution, and therefore occur at different ph values. The curves for zeta potential as a function of ph will depend on the water used as well as the batch of particles and the way in which it was prepared. Measurements by the current authors at Clarkson University (using electrophoresis) on the particles used for this study indicate pzc values (in terms of ph) of about 3.4 for SiO 2 and about 4.4 for Si 3 N 4, while PSL was negatively charged throughout the ph range. All particles exhibited negative zeta potentials at both the ph of water and the ph of SC1 (approximately ph 11), and in both cases silica particles were the most negative (-60 mv for water and -85 mv for SCl), PSL particles were less negative (-45 mv for water and -65 mv for SCl) and silicon nitride were the least negative (-25 mv for water and -30 mv for SCl). Since an oxidized silicon wafer surface is also negatively charged, this means that the electrical double layer repulsion between particle and wafer was largest for the silica particles and smallest for the silicon nitride. This is a likely explanation for why silica particles were relatively easy to remove and silicon nitride particles were relatively difficult. 4.6 Effect of Solution Chemistry Precision Cleaning 95 Proceedings 359

14 The results indicate that removal is enhanced by the use of SCl, which is expected since SC1 is well known to be an efficient particle removal chemistry. The ammonium hydroxide acts as a small-scale etchant for the silicon dioxide layer which is formed chemically by the hydrogen peroxide. Particles are undercut by this small-scale etching. The high ph of the solution also supplies a favorable electrokinetic environment for particle repulsion from the wafer surface, as discussed above. This repulsion works to minimize redeposition. Ultrasound enhances the effects of SC1 by increasing chemical reaction rates at the wafer surface [21]. 5. Conclusion Silicon wafer cleaning is already a critical technology in semiconductor manufacturing, and is becoming increasingly so as circuits decrease in size. Though very promising, sonic cleaning processes have not traditionally been well understood. This paper has attempted to elucidate some of the fundamentals of sonic removal of particles from surfaces through theory and experiment. Still, there is additional work to be done. Current research in sonic cleaning to further optimize operational parameters. Additionally, microroughening of Si wafer surfaces due to the small-scale etching behavior of SC1 solutions is an area of current concern, due to its deleterious effects on subsequently deposited films. Research to maximize cleaning while minimizing roughening is ongoing. REFERENCES 1. Schwartzman, S., Mayer, A., and Kern, W., RCA Review, Vol. 46, 81, March (1985). 2. Mayer, A., and Schwartzman, S., J. Electronic Materials, Vol. 8, 855 (1979). 3. Blitz, J., Ultrasonics: Methods and Applications, Van Nostrand Reinhold, New York (197 1). 4. Kinsler, L. E., and Frey, A. R., Fundamentals of Acoustics, Wiley, New York (1962). 5. Atchley, A., and Crum, L., in Ultrasound, Its Chemical, Physical, and Biological Effects, ed. by K. S. Suslick, VCH Publishers, New York (1988). 6. Crum, L., Nature, Vol. 278, 8 March, 148 (1979). 7. Meyer, E., J. Acoust. Soc. Am., Vol. 29, 4 (1957). 8. Esche, R., Acustica, Vol. 2, AB 208 (1952). 9. Strasberg, M., J. Acoust. Soc. Am., Vol. 29, 4 (1957). 10. Flynn, H. G., in Physical Acoustics, Vol. 1, Part 1, ed. by W. P. Mason, Academic Press, New York (1966). 360 Precision Cleaning 95 Proceedings