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Experimental confirmation of thermal plasma CVD of diamond with liquid feedstock injection model
Diamond and Related Materials 9 (2000) 13–21 www.elsevier.com/locate/diamond
Experimental confirmation of thermal plasma CVD of diamond with liquid feedstock injection model M. Asmann, D. Kolman, J. Heberlein, E. Pfender * High Temperature Laboratory, University of Minnesota, Minneapolis, MN, USA Received 30 April 1999; accepted 6 September 1999
Abstract A three-dimensional model of diamond chemical vapor deposition in a thermal plasma system has been compared with experimental results to confirm the validity of the model in simulating reactor flow patterns and deposit characteristics. Model and experimental cases were tested with the same boundary and operating conditions. Several sets of operating conditions were analyzed to confirm the validity of the model. Trends in the diamond chemical vapor deposition system based on the effects of droplet size, injection probe to substrate offset, the addition of an inert carrier gas, and the differences associated with the use of liquid or gaseous precursor feedstock were investigated. To test the validity of flow patterns predicted by the model, a laser strobe video system was used to map droplet trajectories in the reactor. Experimental results were found to support the calculated droplet trajectories and flowlines in the reactor. Deposition characteristics such as the mass deposition rate and the area of deposit were examined in the model and experimental cases. General trends, with respect to deposition characteristics, produced by altering the operating conditions in the experiment, and respectively the boundary conditions in the model were found to be similar. Differences between model and experimental results are probably due to the use of an overly simplified surface chemistry model, which does not take into account graphite deposition. In addition, modeling of radial droplet injection does not take into account non-radial perturbations. © 2000 Elsevier Science S.A. All rights reserved. Keywords: Diamond CVD; Experimental confirmation; Liquid precursor; Modeling; Thermal plasma
1. Introduction Diamond chemical vapor deposition (CVD) experiments usually rely on gaseous hydrocarbon precursors, typically methane. Several studies, however, have been conducted utilizing evaporated liquid precursors such as diethyl ether [1], methanol [2–4] and dimethyl carbonate [5]. Researchers at the High Temperature Laboratory of the University of Minnesota have utilized a unique direct liquid precursor injection system to perform diamond CVD. The system allows for the direct injection of (oxygenated) hydrocarbon liquid precursors into the thermal plasma jet for activation. Diamond CVD experiments have been conducted with numerous liquids, including acetone [6–11], ethanol [6–10,12], toluene [10] and n-heptane [10] with success. While these experiments seem to suggest that higher growth rates are possible utilizing the direct liquid injection method * Corresponding author. Fax: +1 612 624 1398. E-mail address: [email protected] ( E. Pfender)
rather than using a gaseous hydrocarbon feedstock such as methane, the results have been inconsistent. In order to understand more fully the processes that control the liquid phase precursor deposition process, a theoretical analysis including droplet evaporation, vapor dissociation, activation and active radial deposition at the substrate has been undertaken. Details of this model have been given elsewhere [13–15]. The model has given insight into the processes, which enable growth in the liquid phase precursor diamond CVD system, including verification of increased mass transport when compared with deposition utilizing gaseous hydrocarbon precursors. In terms of the precursor feeding mechanism, the primary difference between gaseous and liquid precursor injection is that in the latter case highly concentrated precursor packets (droplets) can be fed directly to the reactor activation region, while in the former case a more disperse feeding mechanism is active. Feeding of highly concentrated packets of precursor to the thermal plasma jet tip leads to very high local dissociation and concentrations of activated species. In turn, these high
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M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
concentrations of activated species induce high mass transport rates to the substrate. The result is a localized increase in growth rate, when compared with the more dispersed gaseous hydrocarbon precursor feeding mechanism. The objective of the experiments discussed in this paper has been to confirm experimentally the validity of the thermal plasma CVD model used to simulate the liquid precursor diamond CVD system. Verification of the model will be based on reactor flow patterns and deposit characteristics in each case. The general model verification will be based on an evaluation of the model and experimental results for a given set of investigations which will test various aspects of the model, in particular its ability to predict trends in the diamond CVD system when altering operating conditions. It is also the goal of this study to determine shortcomings of the model, with the final objective of furthering our understanding of diamond CVD utilizing liquid precursors.
2. Experiment apparatus and conditions All experiments were carried out using a dual-liquid side injection thermal plasma reactor as shown in Fig. 1. This system consists of a single d.c. plasma torch, watercooled reaction chamber with ports for two side injection probes and a water-cooled substrate holder. The injection probes consist of an inner tube, which carries the precursor, and an outer tube, which carries the atomizing gas. The atomizing gas comes into contact with the precursor only at the tip of the probe. The inner precursor-carrying tube and outer atomizing gas tube can also be exchanged to enable exact control of the average droplet size and atomizing gas velocity. The precursor injection probe is water cooled by another set of surrounding tubes. Furthermore, the position of the probe can be changed with respect to the substrate. The torch to substrate distance, however, was kept constant throughout all cases at 25 mm. During deposition the
Fig. 1. Dual liquid side-injection thermal plasma reactor.
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M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21 Table 1 System operating conditions
Ar torch (slm) H torch (slm) 2 Ar probe (slm/probe) H probe (slm/probe) 2 CH COCH (ml min−1 — probe) 3 3 CH (slm/probe) 4 Torch–substrate distance (m) Probe–substrate distance (m) Ratio of SMDs
STAND
BIG
3MM
ARG
CH4/CH4.II
24 0.6 0 10 0.8 – 0.025 0.002 1.0
24 0.6 0 10 0.8 – .025 0.002 2.0
24 0.6 0 10 0.8 – 0.025 0.0035 1.0
24 0.6 3 10 0.8 – 0.025 0.002 0.8
24 0.6 0 10 – 0.8/0.5 0.025 0.002 1.0
chamber is at 1 atm, with exhaust gases vented from the cooling chamber located below the reaction chamber. The torch is typically run at 300 A and 34 V using a constant current d.c. power supply. Deposition time for all cases was 30 min. Since the nucleation stage is not modeled, it is necessary to run the system long enough to eliminate the effects of the nucleation stage, so the deposition characteristics of interest are mainly determined by the parameters in the growth stage of the process. Since a full film can be formed in this system in less than 4 min, a 30 min run was deemed sufficient to eliminate the effects of the nucleation stage. Substrates consisting of 3.75 cm diameter, 2 mm thick Mo disks are bolted onto the copper substrate holder. Silver print is applied to the surfaces between the substrate and copper holder to decrease thermal resistance. Using a set of uniformly spaced thermocouples along the substrate radius, the substrate temperature profile has been measured as T(r)=880−15.333r°C, where r is the radial distance from the center of the substrate in mm. The substrate temperature was found to be relatively independent of the case conditions tested in this investigation. This linear substrate temperature profile therefore was applied as a boundary condition in the model. In Table 1 the system operating conditions for the various cases are shown. Torch and probe gas precursor flowrates are shown, as well as the respective probe to substrate distance and Saunters mean diameter (SMD) ratio. The SMD ratio is ratio of the mean droplet diameter of the case of interest to the STAND case. The STAND case is the base liquid case against which the role of the parameters of interest, which have been changed in the other cases, are compared. The BIG case allows for a comparison based on increasing the droplet size, while the 3MM case focuses on a change in the probe to substrate distance. The ARG case is investigated to determine the effect of adding an inert, heavy, carrier gas to the precursor, while the CH4 case allows for a comparison based on changing the composition and phase of the precursor used. Conditions for a second gaseous precursor case, CH4.II, are given for later
highlighting of the differences between the model and experiment. Several diagnostic techniques have been used to characterize the thermal plasma system. A laser strobe video system (LSVS ) has been used to map droplet trajectories in the system. The LSVS consists of a pulsed nitrogen laser (337 nm) which is facing one of the injection probes. Then a CCD camera outfitted with a monochromatic filter is used to observe and record droplet trajectories. Voltage fluctuations in the torch are measured using an HP 54540A oscilloscope, with voltage trace data recorded using Labview software. Cooling water heat transfer was also measured using inline thermocouples to obtain the cooling water temperature in and out of the torch, and a rotameter was used to obtain volumetric flowrates. Deposit characterization is performed using a JEOL 840II scanning electron microscope.
3. Model review The model is steady-state, three-dimensional with spatially fully resolved deposition and has the geometry shown in Fig. 1. The experimental set-up and model geometry are equivalent for all cases. The process parameters for the various cases in the model are also the same as in the experiment, and are given in Table 1. The flow is chemically reacting, viscous and compressible, and species diffusion is fully incorporated. The flow is assumed to be in thermal equilibrium. The finite difference method SIMPLER is used to solve for the gas dynamics, energy, and chemical species equations. A predictor–corrector type of Lagrangian scheme is used to trace droplet temperature, trajectory and sizes. The overall model includes submodels of the vaporization, gas phase and surface chemical kinetics rates. Radiation and charged species effects are neglected. The input data for the model are discussed in the following. Total enthalpy flow is assumed and mass flow rates are given by the operating conditions for the various cases. Peak temperature and maximum velocity at the torch nozzle exit are specified based on studies of similar systems. The atomizing probes gas flowrate and
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Fig. 2. (a) Laser strobe video images of droplet and injection probe; (b) calculated droplet trajectories, with initial radii indicated; (c) calculated reactor streamlines in injection plane.
precursor flowrates are specified as well, based on the values given in Table 1. Reactor wall temperature is assumed to be close to room temperature and the
substrate temperature profile measured for the experimental cases, as discussed above, is used. Finally, the reactor exit pressure is assumed to be atmospheric.
M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
Model outputs include flow pattern, reactor enthalpy (temperature) profiles and chemical species mass fraction fields. Substrate heat flux and chemical species deposition rates are given as well. No differentation between graphite deposition and diamond deposition is made in the model. Further description of the model and results are given elsewhere [13–15].
4. Reactor gas phase and liquid flow pattern comparison Fig. 2 shows a plot of the model-predicted gas-phase streamline flow patterns, droplet trajectories, and a single snapshot using the LSVS of droplet trajectories in the reactor system for the various cases being investigated. Focusing first on the difference between the ARG and STAND cases, we see that the flow in the injection plane recirculation region has been reversed for the former case when compared with the latter. The recirculation region is present in all cases, and is due to the high momentum plasma gas impacting on the substrate, flowing across it, and changing course at the reactor wall, then returning across the top of the reactor to be either entrained into the plasma flow, or recirculated again. In the ARG case, the direction of flow in the recirculation zone, however, has been reversed owing to the high momentum flow of Ar issuing from the precursor injection probe. Outside the injection plane, the recirculation zone flow returns to its standard direction as in other cases. Also notable from the calculated streamline flow patterns of gas in the dual liquid side-injection reactor is that penetration of the flow issuing from the precursor injection probe for the ARG case is much higher than for any of the other cases. For all other cases, the main plasma flow diverts the precursor together with the atomizing gas to the recirculation zone, away from the substrate. Therefore, the only case where gas flow from the injection probe directly reaches the plasma jet tip, is in the ARG case. These data also imply that the exposure of the precursor present in the gas flow of the ARG case to the plasma jet is much higher than in any of the other cases. The precursor in the ARG gas is therefore activated, where activation is the process by which those species which participate in the diamond growth process are produced, at a much higher rate than for any of the other cases. Also shown in Fig. 2 are the calculated droplet trajectories, which can be compared with the laser strobe video images of the droplet trajectories for the various cases. The trajectories are shown for droplets of various starting sizes. The droplet size distribution has been taken from an experimental study of droplet diameter [16 ]. The initial droplet diameter in microns is shown at the end of the trajectory for the given droplet size, where the end of the trajectory is the point at which the droplet has completely evaporated.
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The model and experimental data show good agreement with respect to droplet trajectories. The STAND case in the model shows trajectories at about 60° from the substrate surface, where the laser strobe video images shows trajectories with large variation, with an average at approximately the same angle. The experimental and model ARG case droplet trajectories agree almost perfectly. Flow in both cases is nearly parallel to the substrate surface, enabled by the addition of the carrier gas Ar, which imparts significant momentum to the droplets. As shown for the modeled droplet trajectories in the BIG case, the droplet size is increased when compared with the STAND case. This increase is also shown in the laser strobe video images for the BIG case. Flow in the BIG case, however, does seem to be at a higher angle than that shown in the calculations. For the 3MM case the model indicates a much lower angle of trajectory than the experimental results. The discrepancies between the calculated and measured droplet trajectories in the 3MM and BIG case may be due to neglecting the energy required to break up the droplets in the model. The model assumes a given droplet distribution, and droplet momentum is calculated based on the interaction between the atomizing gas and the droplets, as well as the droplet interaction with the opposing flow of plasma gases. However, in reality much of the energy carried by the atomizing gas is used up in breaking apart the droplet. Therefore the atomizing gas velocity is reduced after the droplets have formed. The forward momentum of the droplets in the experiment is thereby lowered, resulting in a higher angle trajectory.
5. Mass deposition rate comparison The experimental mass deposition rates for the various cases tested are shown in Fig. 3. One surprising difference is between the mass deposition rates of the CH4 and CH4.II cases. The former is run using 800 sccm of methane, and the latter with only 500 sccm, with all other operating conditions remaining the same. It is found that the CH4.II case has a significantly higher mass deposition rate than the CH4 case. The CH4 case has been run initially to maintain the same carbon feedrate as in the other cases, but later experiments showed that the mass deposition rate actually increases with decreasing methane input rates. A possible explanation for this observation is based on system optimization related to either the surface or the gas phase mechanisms, which enable diamond growth. For instance, graphite deposition may have been enhanced in the CH4 case, and because of the high concentration of atomic hydrogen higher carbon etching rates may have been realized. The normalized mass deposition rates for the model and experiment are shown in Fig. 4. For both cases the
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M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
Fig. 3. Experimental average mass deposition rates.
Fig. 4. Normalized experimental and model mass deposition rates.
ARG case has the highest mass deposition rate. If we replace the experimental CH4 case results with those of the CH4.II case for the purpose of comparison with the model, we see that the relative trends in the model and experiment hold. Since graphite formation and etching are not considered in the surface kinetics, the CH4.II case better corresponds to the simulation and will be used in further comparisons. In the model, liquid injection occurs in a single plane, as there are no perturbations included in a perfectly radial fashion. In reality, however, the liquid droplets are dispersed over a solid angle. The error associated with the single plane injection pattern is indicated by the order of magnitude change in results that altering the offset angle will have on the model mass deposition rate. Note that the methane cases are not affected by this perfect symmetry artefact.
Shown in Table 2 are the percent changes in mass deposition rate that offsetting the injection plane by the given offset angle will produce. Model cases have been run to compare with the STAND and ARG cases. It is evident that by increasing the offset angle the mass Table 2 Effect of changing the droplet injection offset angle from a perfectly radial direction on mass deposition rate (model ) Case
Offset angle (°)
Change in mass deposition rate (%)
STAND STAND10 STAND20 ARG ARG10 ARG20
0 10 20 0 10 20
– −13.2 −24.5 – −44.3 −63.9
M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
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Fig. 5. Normalized experimental and model area of deposit.
deposition rate is significantly reduced. In the STAND case droplets are evaporated in the recirculation zone, and the active species are carried to the substrate predominantly by the main plasma gas. In the ARG case they are evaporated directly above the substrate and do not go through the recirculation process; therefore a change in the offset angle translates into much less precursor feeding to the activation zone, and hence increasing the offset angle has a relatively large effect on mass deposition rate. This explains why increasing the offset angle for the ARG case has a much stronger effect than in the STAND case. A comparison of absolute mass deposition rates between the model and experimental results has not been performed for three reasons. First, as shown above, the effect of liquid feedstock dispersion angle on the mass deposition rate is significant, making a comparison of absolute mass deposition rates meaningless unless the model included consideration of three-dimensional droplet dispersion. Second, the surface submodel does not take into account the difference between diamond and graphite deposition. By not differentiating between the graphite and diamond forms of carbon deposition, carbon etch rates can also not be properly accounted for. Finally, investigations show temporal voltage and cooling rate fluctuations in the experiment leading to large standard deviations in the mass deposition rate results, and making comparisons troublesome. While a comparison of absolute mass deposition rates in the model and experiments was not undertaken, we can state that the absolute mass deposition rate in the model is higher than in the experiment for all cases.
6. Area of deposition comparison The normalized area of deposit for the model and experiment are shown in Fig. 5. This comparison should give some verification of the calculated active species distribution over the substrate, and the associated transport of these species. The experimental area of deposit is based on measurements of the crystal size as a function of radial position in the injection plane ( IP) and plane perpendicular to the injection plane (PIP) using scanning electron microscopy (SEM ) images as shown in Fig. 6. For the model, the area of deposit is based on the axial location where growth rate is less than some critical value. The normalized area comparison between the model and experiment agrees only moderately well. Assuming some error associated with the way the area of deposit has been defined in both cases, the difference between the model and experimental results is not significant except for the ARG case. Note in particular that the model deposition profile, not shown, is highly irregular and translating it into an equivalent area is not a very well-defined procedure. Since graphite deposition typically occurs at the outer radius of the substrate, where the substrate temperature is lower, and since hydrogen etching rates are maximized at approximately 500°C [17], the hydrogen etching of graphite would remove all or most of the graphite deposited in the experiment at the outer radius of the substrate. No such removal mechanism exists in the surface submodel, and for this reason, the ARG case in the model results in high carbon deposition rates over the whole substrate, unlike any of the other cases.
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Fig. 6. Sample SEM of crystalline deposits used to obtain average crystal size as a function of radial position (value underneath image refers to width of image in microns).
7. Summary and conclusion Calculated model streamlines, mirroring flow patterns in the reactor, and droplet trajectories agree with droplet trajectories measured experimentally using an LSVS. Small differences in the droplet trajectory angle between the model and experiment can be attributed to the assumption of a given droplet size distribution in the model, and the disregard for energy required to obtain droplet break-up in the model. However, the general flow pattern trends and droplet trajectories for the model are the same as in the experiment for the various cases tested, indicating a strong verification of the model flow pattern results. A comparison of the deposit results, based on the mass deposition rate and area of deposit, for the model and experiment also shows significant agreement for the cases investigated. Mass deposition trends are correctly predicted by the model, except for the CH4 case, where growth was overestimated because of the absence of
graphite etching in the model. The area of deposit results showed negligible variation with respect to the changes in operating conditions in the model and experiment. Correct prediction by the model of deposit characteristics is a strong verification for the overall model, including the reaction mechanism in the gas phase and at the surface, flow patterns and transport mechanisms. A comparison of the model and the experiment based on the normalized mass deposition rate results shows trend agreement for all cases except the CH4 case. Overall agreement of model and experimental results with respect to reactor flow patterns, and trends in mass deposition rates and area of deposit have been shown. However, to verify fully the validity of the model, several in situ diagnostics are required. Enthalpy probe studies of the jet to determine temperature and velocity profiles would provide further verification of the model reactor flow patterns and temperature profiles. Near nozzle temperature measurements utilizing a spectroscopic technique, several of which may be applicable, would
M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
be useful in determining the validity of assumptions. Furthermore, emission spectroscopy to determine species concentration utilizing actinometry could also provide strong verification of the model. Finally, seeding of the gas stream to determine reactor flow patterns would be a simple mans of determining reactor flow patterns. In the course of this investigation, several shortcomings of the model have been determined. To enhance further the capabilities of the model, allowing for threedimensional dispersion of the droplets would solve several of the encountered problems. A more accurate determination of the upstream boundary conditions, i.e. the torch exit temperature and velocity distributions, should be performed for the conditions under consideration. Finally, enhancement of the surface model to include graphite formation, and associated etch rates, would significantly improve the accuracy of the model.
Acknowledgements This research was supported by the US Department of Energy under Grant No. FG02-85ER-13433. We would also like to thank the Minnesota Computer Institute, which provided computer time on the IBM SP supercomputer.
References [1] Y. Hirose, Y. Terasawa, Jpn. J. Appl. Phys. 25 (1986) L519–L521. [2] T. Humphreys, J. Posthill, D. Malta, R. Thomas, R. Rudder, G.
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Hudson, R. Markunas, Mater. Res. Soc. Proc. 416 (1996) 133–138. [3] J. Posthill, D. Malta, T. Humphreys, G. Hudson, R. Thomas, R. Rudder, R. Markunas, Mater. Res. Soc. Proc. 416 (1996) 45–49. [4] R. Rudder, G. Hudson, J. Posthill, R. Thomas, R. Hendry, D. Malta, R. Markunas, T. Humphreys, R. Nemanich, Appl. Phys. Lett. 60 (1992) 329–331. [5] C.F. Chen, S.-H. Chen, T.-M. Hong, S.-H. Wu, Diamond Relat. Mater. 2 (1993) 732–736. [6 ] Q.Y. Han, T. Or, Z. Lu, J. Heberlein, E. Pfender, Proceedings of the 2nd International Symposium on Diamond Materials 91 (8) (1991) 115–122. [7] J. Heberlein, E. Pfender, Mater. Sci. Forum 140–142 (1993) 477–496. [8] T. Or, Q.Y. Han, Z. Lu, J. Heberlein, E. Pfender, Proceedings of the 10th International Symposium on Plasma Chemistry, Bochum, Germany 3.1-16 (1991) 1–6. [9] E. Pfender, Q.Y. Han, T. Or, Z. Lu, J. Heberlein, Diamond Relat. Mater. 1 (1992) 127–133. [10] Q. Zhuang, P. Schwendinger, C. Hammerstrand, J. Heberlein, E. Pfender, R. Young, Proceedings of the 12th International Symposium on Plasma Chemistry, Minneapolis, USA (1995) 2303–2308. [11] Q. Zhuang, Q.Y. Han, J. Heberlein, Transport Phenomena in Materials Processing and Manufacturing HDT-280 (1994) 113–119. [12] M. Asmann, C.F.M. Borges, J. Heberlein, E. Pfender, Proceedings of the 13th International Symposium on Plasma Chemistry, Beijing, China Vol. 13 (1997) 1206–1211. [13] D. Kolman, J. Heberlein, E. Pfender, Proceedings of the 13th International Symposium on Plasma Chemistry, Beijing, China Vol. 13 (1997) 320–325. [14] D. Kolman, J. Heberlein, E. Pfender, Plasma Chem. Plasma Process. 18 (1998) 73–98. [15] D. Kolman, J. Heberlein, E. Pfender, Diamond Relat. Mater. 7 (1998) 794–801. [16 ] C. Hammerstrand, An analysis of droplet sizing and evaporation rates applied to liquid hydrocarbon sprays in a high temperature gaseous environment, Internal Report, High Temperature Laboratory, University of Minnesota, Minneapolis, MN, 1993. [17] W. Hsu, D.M. Tung, E.A. Fuchs, K.F. McCarty, Appl. Phys. Lett. 55 (1989) 2739–2741.
Experimental confirmation of thermal plasma CVD of diamond with liquid feedstock injection model M. Asmann, D. Kolman, J. Heberlein, E. Pfender * High Temperature Laboratory, University of Minnesota, Minneapolis, MN, USA Received 30 April 1999; accepted 6 September 1999
Abstract A three-dimensional model of diamond chemical vapor deposition in a thermal plasma system has been compared with experimental results to confirm the validity of the model in simulating reactor flow patterns and deposit characteristics. Model and experimental cases were tested with the same boundary and operating conditions. Several sets of operating conditions were analyzed to confirm the validity of the model. Trends in the diamond chemical vapor deposition system based on the effects of droplet size, injection probe to substrate offset, the addition of an inert carrier gas, and the differences associated with the use of liquid or gaseous precursor feedstock were investigated. To test the validity of flow patterns predicted by the model, a laser strobe video system was used to map droplet trajectories in the reactor. Experimental results were found to support the calculated droplet trajectories and flowlines in the reactor. Deposition characteristics such as the mass deposition rate and the area of deposit were examined in the model and experimental cases. General trends, with respect to deposition characteristics, produced by altering the operating conditions in the experiment, and respectively the boundary conditions in the model were found to be similar. Differences between model and experimental results are probably due to the use of an overly simplified surface chemistry model, which does not take into account graphite deposition. In addition, modeling of radial droplet injection does not take into account non-radial perturbations. © 2000 Elsevier Science S.A. All rights reserved. Keywords: Diamond CVD; Experimental confirmation; Liquid precursor; Modeling; Thermal plasma
1. Introduction Diamond chemical vapor deposition (CVD) experiments usually rely on gaseous hydrocarbon precursors, typically methane. Several studies, however, have been conducted utilizing evaporated liquid precursors such as diethyl ether [1], methanol [2–4] and dimethyl carbonate [5]. Researchers at the High Temperature Laboratory of the University of Minnesota have utilized a unique direct liquid precursor injection system to perform diamond CVD. The system allows for the direct injection of (oxygenated) hydrocarbon liquid precursors into the thermal plasma jet for activation. Diamond CVD experiments have been conducted with numerous liquids, including acetone [6–11], ethanol [6–10,12], toluene [10] and n-heptane [10] with success. While these experiments seem to suggest that higher growth rates are possible utilizing the direct liquid injection method * Corresponding author. Fax: +1 612 624 1398. E-mail address: [email protected] ( E. Pfender)
rather than using a gaseous hydrocarbon feedstock such as methane, the results have been inconsistent. In order to understand more fully the processes that control the liquid phase precursor deposition process, a theoretical analysis including droplet evaporation, vapor dissociation, activation and active radial deposition at the substrate has been undertaken. Details of this model have been given elsewhere [13–15]. The model has given insight into the processes, which enable growth in the liquid phase precursor diamond CVD system, including verification of increased mass transport when compared with deposition utilizing gaseous hydrocarbon precursors. In terms of the precursor feeding mechanism, the primary difference between gaseous and liquid precursor injection is that in the latter case highly concentrated precursor packets (droplets) can be fed directly to the reactor activation region, while in the former case a more disperse feeding mechanism is active. Feeding of highly concentrated packets of precursor to the thermal plasma jet tip leads to very high local dissociation and concentrations of activated species. In turn, these high
0925-9635/00/$ - see front matter © 2000 Elsevier Science S.A. All rights reserved. PII: S0 9 25 - 9 63 5 ( 9 9 ) 00 1 8 9- 2
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M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21
concentrations of activated species induce high mass transport rates to the substrate. The result is a localized increase in growth rate, when compared with the more dispersed gaseous hydrocarbon precursor feeding mechanism. The objective of the experiments discussed in this paper has been to confirm experimentally the validity of the thermal plasma CVD model used to simulate the liquid precursor diamond CVD system. Verification of the model will be based on reactor flow patterns and deposit characteristics in each case. The general model verification will be based on an evaluation of the model and experimental results for a given set of investigations which will test various aspects of the model, in particular its ability to predict trends in the diamond CVD system when altering operating conditions. It is also the goal of this study to determine shortcomings of the model, with the final objective of furthering our understanding of diamond CVD utilizing liquid precursors.
2. Experiment apparatus and conditions All experiments were carried out using a dual-liquid side injection thermal plasma reactor as shown in Fig. 1. This system consists of a single d.c. plasma torch, watercooled reaction chamber with ports for two side injection probes and a water-cooled substrate holder. The injection probes consist of an inner tube, which carries the precursor, and an outer tube, which carries the atomizing gas. The atomizing gas comes into contact with the precursor only at the tip of the probe. The inner precursor-carrying tube and outer atomizing gas tube can also be exchanged to enable exact control of the average droplet size and atomizing gas velocity. The precursor injection probe is water cooled by another set of surrounding tubes. Furthermore, the position of the probe can be changed with respect to the substrate. The torch to substrate distance, however, was kept constant throughout all cases at 25 mm. During deposition the
Fig. 1. Dual liquid side-injection thermal plasma reactor.
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M. Asmann et al. / Diamond and Related Materials 9 (2000) 13–21 Table 1 System operating conditions
Ar torch (slm) H torch (slm) 2 Ar probe (slm/probe) H probe (slm/probe) 2 CH COCH (ml min−1 — probe) 3 3 CH (slm/probe) 4 Torch–substrate distance (m) Probe–substrate distance (m) Ratio of SMDs
STAND
BIG
3MM
ARG
CH4/CH4.II
24 0.6 0 10 0.8 – 0.025 0.002 1.0
24 0.6 0 10 0.8 – .025 0.002 2.0
24 0.6 0 10 0.8 – 0.025 0.0035 1.0
24 0.6 3 10 0.8 – 0.025 0.002 0.8
24 0.6 0 10 – 0.8/0.5 0.025 0.002 1.0
chamber is at 1 atm, with exhaust gases vented from the cooling chamber located below the reaction chamber. The torch is typically run at 300 A and 34 V using a constant current d.c. power supply. Deposition time for all cases was 30 min. Since the nucleation stage is not modeled, it is necessary to run the system long enough to eliminate the effects of the nucleation stage, so the deposition characteristics of interest are mainly determined by the parameters in the growth stage of the process. Since a full film can be formed in this system in less than 4 min, a 30 min run was deemed sufficient to eliminate the effects of the nucleation stage. Substrates consisting of 3.75 cm diameter, 2 mm thick Mo disks are bolted onto the copper substrate holder. Silver print is applied to the surfaces between the substrate and copper holder to decrease thermal resistance. Using a set of uniformly spaced thermocouples along the substrate radius, the substrate temperature profile has been measured as T(r)=880−15.333r°C, where r is the radial distance from the center of the substrate in mm. The substrate temperature was found to be relatively independent of the case conditions tested in this investigation. This linear substrate temperature profile therefore was applied as a boundary condition in the model. In Table 1 the system operating conditions for the various cases are shown. Torch and probe gas precursor flowrates are shown, as well as the respective probe to substrate distance and Saunters mean diameter (SMD) ratio. The SMD ratio is ratio of the mean droplet diameter of the case of interest to the STAND case. The STAND case is the base liquid case against which the role of the parameters of interest, which have been changed in the other cases, are compared. The BIG case allows for a comparison based on increasing the droplet size, while the 3MM case focuses on a change in the probe to substrate distance. The ARG case is investigated to determine the effect of adding an inert, heavy, carrier gas to the precursor, while the CH4 case allows for a comparison based on changing the composition and phase of the precursor used. Conditions for a second gaseous precursor case, CH4.II, are given for later
highlighting of the differences between the model and experiment. Several diagnostic techniques have been used to characterize the thermal plasma system. A laser strobe video system (LSVS ) has been used to map droplet trajectories in the system. The LSVS consists of a pulsed nitrogen laser (337 nm) which is facing one of the injection probes. Then a CCD camera outfitted with a monochromatic filter is used to observe and record droplet trajectories. Voltage fluctuations in the torch are measured using an HP 54540A oscilloscope, with voltage trace data recorded using Labview software. Cooling water heat transfer was also measured using inline thermocouples to obtain the cooling water temperature in and out of the torch, and a rotameter was used to obtain volumetric flowrates. Deposit characterization is performed using a JEOL 840II scanning electron microscope.
3. Model review The model is steady-state, three-dimensional with spatially fully resolved deposition and has the geometry shown in Fig. 1. The experimental set-up and model geometry are equivalent for all cases. The process parameters for the various cases in the model are also the same as in the experiment, and are given in Table 1. The flow is chemically reacting, viscous and compressible, and species diffusion is fully incorporated. The flow is assumed to be in thermal equilibrium. The finite difference method SIMPLER is used to solve for the gas dynamics, energy, and chemical species equations. A predictor–corrector type of Lagrangian scheme is used to trace droplet temperature, trajectory and sizes. The overall model includes submodels of the vaporization, gas phase and surface chemical kinetics rates. Radiation and charged species effects are neglected. The input data for the model are discussed in the following. Total enthalpy flow is assumed and mass flow rates are given by the operating conditions for the various cases. Peak temperature and maximum velocity at the torch nozzle exit are specified based on studies of similar systems. The atomizing probes gas flowrate and
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Fig. 2. (a) Laser strobe video images of droplet and injection probe; (b) calculated droplet trajectories, with initial radii indicated; (c) calculated reactor streamlines in injection plane.
precursor flowrates are specified as well, based on the values given in Table 1. Reactor wall temperature is assumed to be close to room temperature and the
substrate temperature profile measured for the experimental cases, as discussed above, is used. Finally, the reactor exit pressure is assumed to be atmospheric.
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Model outputs include flow pattern, reactor enthalpy (temperature) profiles and chemical species mass fraction fields. Substrate heat flux and chemical species deposition rates are given as well. No differentation between graphite deposition and diamond deposition is made in the model. Further description of the model and results are given elsewhere [13–15].
4. Reactor gas phase and liquid flow pattern comparison Fig. 2 shows a plot of the model-predicted gas-phase streamline flow patterns, droplet trajectories, and a single snapshot using the LSVS of droplet trajectories in the reactor system for the various cases being investigated. Focusing first on the difference between the ARG and STAND cases, we see that the flow in the injection plane recirculation region has been reversed for the former case when compared with the latter. The recirculation region is present in all cases, and is due to the high momentum plasma gas impacting on the substrate, flowing across it, and changing course at the reactor wall, then returning across the top of the reactor to be either entrained into the plasma flow, or recirculated again. In the ARG case, the direction of flow in the recirculation zone, however, has been reversed owing to the high momentum flow of Ar issuing from the precursor injection probe. Outside the injection plane, the recirculation zone flow returns to its standard direction as in other cases. Also notable from the calculated streamline flow patterns of gas in the dual liquid side-injection reactor is that penetration of the flow issuing from the precursor injection probe for the ARG case is much higher than for any of the other cases. For all other cases, the main plasma flow diverts the precursor together with the atomizing gas to the recirculation zone, away from the substrate. Therefore, the only case where gas flow from the injection probe directly reaches the plasma jet tip, is in the ARG case. These data also imply that the exposure of the precursor present in the gas flow of the ARG case to the plasma jet is much higher than in any of the other cases. The precursor in the ARG gas is therefore activated, where activation is the process by which those species which participate in the diamond growth process are produced, at a much higher rate than for any of the other cases. Also shown in Fig. 2 are the calculated droplet trajectories, which can be compared with the laser strobe video images of the droplet trajectories for the various cases. The trajectories are shown for droplets of various starting sizes. The droplet size distribution has been taken from an experimental study of droplet diameter [16 ]. The initial droplet diameter in microns is shown at the end of the trajectory for the given droplet size, where the end of the trajectory is the point at which the droplet has completely evaporated.
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The model and experimental data show good agreement with respect to droplet trajectories. The STAND case in the model shows trajectories at about 60° from the substrate surface, where the laser strobe video images shows trajectories with large variation, with an average at approximately the same angle. The experimental and model ARG case droplet trajectories agree almost perfectly. Flow in both cases is nearly parallel to the substrate surface, enabled by the addition of the carrier gas Ar, which imparts significant momentum to the droplets. As shown for the modeled droplet trajectories in the BIG case, the droplet size is increased when compared with the STAND case. This increase is also shown in the laser strobe video images for the BIG case. Flow in the BIG case, however, does seem to be at a higher angle than that shown in the calculations. For the 3MM case the model indicates a much lower angle of trajectory than the experimental results. The discrepancies between the calculated and measured droplet trajectories in the 3MM and BIG case may be due to neglecting the energy required to break up the droplets in the model. The model assumes a given droplet distribution, and droplet momentum is calculated based on the interaction between the atomizing gas and the droplets, as well as the droplet interaction with the opposing flow of plasma gases. However, in reality much of the energy carried by the atomizing gas is used up in breaking apart the droplet. Therefore the atomizing gas velocity is reduced after the droplets have formed. The forward momentum of the droplets in the experiment is thereby lowered, resulting in a higher angle trajectory.
5. Mass deposition rate comparison The experimental mass deposition rates for the various cases tested are shown in Fig. 3. One surprising difference is between the mass deposition rates of the CH4 and CH4.II cases. The former is run using 800 sccm of methane, and the latter with only 500 sccm, with all other operating conditions remaining the same. It is found that the CH4.II case has a significantly higher mass deposition rate than the CH4 case. The CH4 case has been run initially to maintain the same carbon feedrate as in the other cases, but later experiments showed that the mass deposition rate actually increases with decreasing methane input rates. A possible explanation for this observation is based on system optimization related to either the surface or the gas phase mechanisms, which enable diamond growth. For instance, graphite deposition may have been enhanced in the CH4 case, and because of the high concentration of atomic hydrogen higher carbon etching rates may have been realized. The normalized mass deposition rates for the model and experiment are shown in Fig. 4. For both cases the
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Fig. 3. Experimental average mass deposition rates.
Fig. 4. Normalized experimental and model mass deposition rates.
ARG case has the highest mass deposition rate. If we replace the experimental CH4 case results with those of the CH4.II case for the purpose of comparison with the model, we see that the relative trends in the model and experiment hold. Since graphite formation and etching are not considered in the surface kinetics, the CH4.II case better corresponds to the simulation and will be used in further comparisons. In the model, liquid injection occurs in a single plane, as there are no perturbations included in a perfectly radial fashion. In reality, however, the liquid droplets are dispersed over a solid angle. The error associated with the single plane injection pattern is indicated by the order of magnitude change in results that altering the offset angle will have on the model mass deposition rate. Note that the methane cases are not affected by this perfect symmetry artefact.
Shown in Table 2 are the percent changes in mass deposition rate that offsetting the injection plane by the given offset angle will produce. Model cases have been run to compare with the STAND and ARG cases. It is evident that by increasing the offset angle the mass Table 2 Effect of changing the droplet injection offset angle from a perfectly radial direction on mass deposition rate (model ) Case
Offset angle (°)
Change in mass deposition rate (%)
STAND STAND10 STAND20 ARG ARG10 ARG20
0 10 20 0 10 20
– −13.2 −24.5 – −44.3 −63.9
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Fig. 5. Normalized experimental and model area of deposit.
deposition rate is significantly reduced. In the STAND case droplets are evaporated in the recirculation zone, and the active species are carried to the substrate predominantly by the main plasma gas. In the ARG case they are evaporated directly above the substrate and do not go through the recirculation process; therefore a change in the offset angle translates into much less precursor feeding to the activation zone, and hence increasing the offset angle has a relatively large effect on mass deposition rate. This explains why increasing the offset angle for the ARG case has a much stronger effect than in the STAND case. A comparison of absolute mass deposition rates between the model and experimental results has not been performed for three reasons. First, as shown above, the effect of liquid feedstock dispersion angle on the mass deposition rate is significant, making a comparison of absolute mass deposition rates meaningless unless the model included consideration of three-dimensional droplet dispersion. Second, the surface submodel does not take into account the difference between diamond and graphite deposition. By not differentiating between the graphite and diamond forms of carbon deposition, carbon etch rates can also not be properly accounted for. Finally, investigations show temporal voltage and cooling rate fluctuations in the experiment leading to large standard deviations in the mass deposition rate results, and making comparisons troublesome. While a comparison of absolute mass deposition rates in the model and experiments was not undertaken, we can state that the absolute mass deposition rate in the model is higher than in the experiment for all cases.
6. Area of deposition comparison The normalized area of deposit for the model and experiment are shown in Fig. 5. This comparison should give some verification of the calculated active species distribution over the substrate, and the associated transport of these species. The experimental area of deposit is based on measurements of the crystal size as a function of radial position in the injection plane ( IP) and plane perpendicular to the injection plane (PIP) using scanning electron microscopy (SEM ) images as shown in Fig. 6. For the model, the area of deposit is based on the axial location where growth rate is less than some critical value. The normalized area comparison between the model and experiment agrees only moderately well. Assuming some error associated with the way the area of deposit has been defined in both cases, the difference between the model and experimental results is not significant except for the ARG case. Note in particular that the model deposition profile, not shown, is highly irregular and translating it into an equivalent area is not a very well-defined procedure. Since graphite deposition typically occurs at the outer radius of the substrate, where the substrate temperature is lower, and since hydrogen etching rates are maximized at approximately 500°C [17], the hydrogen etching of graphite would remove all or most of the graphite deposited in the experiment at the outer radius of the substrate. No such removal mechanism exists in the surface submodel, and for this reason, the ARG case in the model results in high carbon deposition rates over the whole substrate, unlike any of the other cases.
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Fig. 6. Sample SEM of crystalline deposits used to obtain average crystal size as a function of radial position (value underneath image refers to width of image in microns).
7. Summary and conclusion Calculated model streamlines, mirroring flow patterns in the reactor, and droplet trajectories agree with droplet trajectories measured experimentally using an LSVS. Small differences in the droplet trajectory angle between the model and experiment can be attributed to the assumption of a given droplet size distribution in the model, and the disregard for energy required to obtain droplet break-up in the model. However, the general flow pattern trends and droplet trajectories for the model are the same as in the experiment for the various cases tested, indicating a strong verification of the model flow pattern results. A comparison of the deposit results, based on the mass deposition rate and area of deposit, for the model and experiment also shows significant agreement for the cases investigated. Mass deposition trends are correctly predicted by the model, except for the CH4 case, where growth was overestimated because of the absence of
graphite etching in the model. The area of deposit results showed negligible variation with respect to the changes in operating conditions in the model and experiment. Correct prediction by the model of deposit characteristics is a strong verification for the overall model, including the reaction mechanism in the gas phase and at the surface, flow patterns and transport mechanisms. A comparison of the model and the experiment based on the normalized mass deposition rate results shows trend agreement for all cases except the CH4 case. Overall agreement of model and experimental results with respect to reactor flow patterns, and trends in mass deposition rates and area of deposit have been shown. However, to verify fully the validity of the model, several in situ diagnostics are required. Enthalpy probe studies of the jet to determine temperature and velocity profiles would provide further verification of the model reactor flow patterns and temperature profiles. Near nozzle temperature measurements utilizing a spectroscopic technique, several of which may be applicable, would
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be useful in determining the validity of assumptions. Furthermore, emission spectroscopy to determine species concentration utilizing actinometry could also provide strong verification of the model. Finally, seeding of the gas stream to determine reactor flow patterns would be a simple mans of determining reactor flow patterns. In the course of this investigation, several shortcomings of the model have been determined. To enhance further the capabilities of the model, allowing for threedimensional dispersion of the droplets would solve several of the encountered problems. A more accurate determination of the upstream boundary conditions, i.e. the torch exit temperature and velocity distributions, should be performed for the conditions under consideration. Finally, enhancement of the surface model to include graphite formation, and associated etch rates, would significantly improve the accuracy of the model.
Acknowledgements This research was supported by the US Department of Energy under Grant No. FG02-85ER-13433. We would also like to thank the Minnesota Computer Institute, which provided computer time on the IBM SP supercomputer.
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