Fluence dependent concentration of low-energy Ga implanted in Si

Nuclear Instruments and Methods in Physics Research B80/81 (1993) 110-114 North-Holland

HMB

Beam Interactions with Materials S Atoms

Fluence dependent concentration of low-energy Ga implanted in Si H. Gnaser, J . Steltmann and H . Oechsner

Fachbereich Physik, Universität Kaiserslautern, W-6750 Kaiserslautern, Germany

Using an ion beam produced in a liquid-metal ion sourct . 7 keV Ga was implanted it . silicon with fluentes ranging from 2 x 10 1' to 1 x 1017 cm -2. These implantation profiles were analyzed quantitatively by secondary-ion mass spectrometry. The derived Ga concentrations were compared with a theoretical retention model which assumes a Gaussian implant distribution and accounts for the concurrent specir-n erosion by sputtering . Furthermore, dynamic computer simulations employing the binary collision approximation were carried out to model the implantation process . All three data sets yield a linear increase of the Ga concentration with fluence to about I x 1016 cm -2 and . beyond r, fluente of 3 x 10 16 em -2 , a saturation value. In this regime the experimentally determined Ga peak concentration is Ictwer by a factor of 3 than the corresponding values obtained from the model and the simulations . This observation indicates that Ga segregates to the surface for very high fiuences .

1. Introduction liquid-metal ion sources (LIv:IS) are now widely used, e.g ., in focused ion beam lithography [1], device micromachining [2], scanning ion .microscopy [3] and s--condary-ion mass spectrometry (SIMS) [4] . Because of their very high brightness (> 10' A/cm 2 sr) and small virtual source size (- 100 fl) [5] extremely high current densities can be achieved employing suitable electrostatic focusing columns . Exposure of a specimen to a beam from a LMIS will, of course, result in an implantation of the source material . This modification of the near-surface region of the sample can be of concern in some applications like in SIMS where an alteration of the composition might change the ionization efficiency of secondary ions [6]. Therefore, knowledge of the stationary metal concentration introduced in a specimen will often be aseful or even mandatory. In fact, attempts were trade to employ the known concentration of the ion implanted species as an internal reference standard in a specific SIMS quantification scheme [7] . However, experiments to determine the stationary, high fluence concentration due to metal ion implantation have rarely been carried out for the low keV energy regime [8,9], which is typical for SIMS and scanning ion microscopy. The present work aimed at studying the fluence dependent evolution of the implanted Ga concentration in silicon. To this end, the specimens were exposed to a focused beam from a LMIS with fiuences ranging from 2 x 10 13 to 1 x 10 17 Ga ions/cm2 and were subsequently analyzed by means of SIMS. The experimental results were compared with a simple

model of ion retention in the presence of ample erosion by sputtering. Further comparison was made with the output of dynamical computer simulations which employ the binary collision approximation (BCA). 2. Experimental Ion implantation was carried out using a Ga-LMIS built in-house [10,11] . The emitter is of the conventional VW-,^~edle type . The focusing column consists of two electrostatic lenses, beam alignment and deflection plates. Typically, small areas of 50 wm x 50 wm were implanted and several such areas (up to nine) were situated on any single specimen. Beam currents were accurately determined by means of a Faraday cup. It is estimated that implantation fiuences could be established with a precision of about 15% . SINIS analyses of the implanted samples were performed in a Cameca IMS-4f ion microscope [12] using a 3 keV 0 2' primary ion beam and monitoring positive secondary ions. While the raster size was chosen slightly larger than the implanted area, the an lyzed area (usually 33 wm in diameter) was located within the latter. Conversion of the measured signals into concentrations was done using relative sensitivity factors derived from a standard . Depth scales were established by means of surface profilometry of sputtered craters . Single crystal wafers of silicon were used as specimens. Native oxides were removed by a brief HF-etch prior to insertion of the sample in :o the implantation chamber.

0168-583X/93/$06.00 © 1993 - Elsevier Science Publishers B .V. All rights reserved

H. G- e, et al. / Fluente den. adent concentrunon of l-

3 . Computer simulation Ion implantath-n and the gradual increase of the near-surface Ga concentration was simulated using the PC version T-DYN [13] of the binary collision Monte Carlo code TRIDYN [14] . Both codes are based on the (static) TRIM program [15,16] but allow for a dynamic rearrangement of the local composition of the target ; thus, effects in high fluence ion implantation, ion beam mixing, and preferential sputtering caused by atomic collision processes can be studied . The basic features [141 and several applications [17,18] of those codes have been described in the literature. In brief, elastic binary collision between incident projectiles and cascade atoms are calculated employing the Kr-.^. interaction potential [19] . A planar surface potential is used . Surface binding energies E,(Si) = E,(Ga) = 2 eV and bulk binding energies E,,(Si) = E,,(Ga) = 0 .1 eV were chosen; by the latter amount the energy of a recoil atom hit in a collision is reduced . The choice of these values will he discussed in section 5 together with the respective output data . 4. Model calculations The retention of implanted species in the presence of sputter erosion can be modeled by means of a continuity equation [6,20,21] considering the competition between ion implantation and sputtering which, finally, leads to an equilibrium state (i .e. the number of implanted and respotcred projectiles per unr time :., equal) . It is frequently assumed that the implantation probability function f(z'), where z' is the depth coordinate will" respect to the instantaneous surface, is Gaussian in shape : 1

( z ,-Rn )

.,,

where R v and AR P are the projected range and its straggling, respectively . This choice leads to a time dependent distribution function for the implanted species [6] : a11 z' - .Q + t~Y/ n, n(z',t) = -`Ierfl '' ( z'-

-crf'

RP

VAR_(2)

where a is the accommodation coefficient, it, is the target's atom density, Y, is the sputtering yield of the target, ¢ is the flux density (ions/cm 2 s) and erf is the error function . From eq. (2) the saturation profile (t --) and the momentary and stationary surface con-

Fir 1 . Evaiuation of the Ga depth distribution as a function of fluente (time) acct -ding to eq . (2) for I keV Ga implanted in Si (Ys. =2.1 atom " /ion, R -95 Â, ARP =37 A, a=1, 0 = 2 .3 x 10' ° ion, cm -2 s -1 and ns, = 5 x 10 22 cm -3 ) . centrations can he seduced . The latter can be approximated for R P/V2 .1 R , >_ 1 .4, by n(0,-) =an,IY,, i .e . the steady state surface concentration of .mplanted species is inversely proportionai to the sputtering yield of the target. Ii is noted, however, that the above derivaiiens are valid only for equal partial sputtering yields of target ana projectile species (no preferential sputtering takes place) . An evaluation of the distribution function (eq. (2)) is shown in fig. 1 cor the implantation of 7 keV Ga in Si, using the following parameters [22,23]: Ys, = 2 .1 z.toms/ .on, R .=05 A, A R =37 A, A = 2.3 x 10 14 ions/cm2 s and it s , = 5 .0 x 10g2 em - '. These and similar data wilt be compared in the following section with the experimental results and the output from computer simulations . 5. Results and discussion SIMS depth profiles of various 7 keV Ga implants in silicon are depicted in fig. 2 . In all cases a good agreement between the experimentally observed depth of the peak position and the theoretical value [23] of the projected range (R p - 95 A) is found. While at the surface due to impurity induced variations of elemental ionization probabilities, evaluation of the Ga concentration is difficult, it can easily be determined for the respective maxima . These values will therefore be compared with data of the theoretical model (see below) . It is noted that due to the sensitivity of the technique very low concentrations can be monitored. In fact, a background level of - 2 x 10 17 cm - ' is deduced from fig . 2 . The output from the T-DYN computer simulations is shown in fig. 3a for 7 keV Ga implantation in silic,, t . lb. BASIC INTERACTIONS (h)

N. Gnaser et al. / Ffuence dependent concentration of (ow-energy Ga

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depth profiles of 7 ke%' Ga implants in silicon with fluences of (a) 3.2X10 15, (b) 1.6X10 15, (c) 5.3X 10 14, (d) IA X10 14 and (e) 5.3X 10 1; cm -2 . Fig. 2. SIMS

Fig . 3 depicts the evolution of the implarted Ga distribution with increasing accumulaied fluence whi, fig. 3b plots the partial sputtering yields of Ga and Si as a function of implantation fluence . Steady state values of the yields are reached for a fluence of about 5 x 10 16 CM -2. The corresponding concentration profile (uppermost curve in fig . 3a) exhibits a comparatively flat portion extending from the surface to a depth of - 90 A P .towed by gradual decrease in the Ga concentration over a depth interval of similar thickness. This value corresponds to R P as deduced from the low

fluence profiles in fig. 3a and is also in good agreement with the SIMS data . As mentioned in section 4 the outcome of the simulations is somewhat sensitive to the input parameters used. In particular, the partial yields (and therefore also the stationary surface concentrations) depend 1 "n the surface binding energies . The values chosen here (ES(Si) = E5 (Ga) = 2 eV, E h = 0.1 eV) result in Ys ; = 2 .1 atoms/ion (cf. fig . 3), which is comparable with the value employed in the model calculations (see fig. 1) and agrees with the result from a recent molecular dynamics calculation (22]. Note also that Yo ,. = I for steady state conditions. Fig. 4 depicts the Ga concentration in the maximum of the distribution as a function of implantation fluence as derived from the theoretical model (eq. (2)), the SIMS analysis (fig . 2) and the T-DYN computer simulations (fig. 3) . The comparison of the three data sets exemplifies that the peak concentration increases linearly with fluence up to roughly 1 x 10 16 Ga ions/cm 2 and reaches saturation at about 3 x 10 16 Cm-2 . Quantitatively, however, there are distinct differences between the data: the results of the model and of the simulations are in excellent agreement, the Ga concentrations determined by SIMS are consistently lower over the whole fluence range . While at low fluences the discrepancy is roughly 50%, the difference at saturation amounts to a factor of 3. Recent investigations of similar specimens by means of Auger electron spectroscopy indicate thai Ga segregation to the surface might occur . Such a Ga enrichment in the topmost surface layer would be difficult to detect by SIMS due to the general impurity-induc,:d enhancement of SIMS signals of the surface ; it might, however, reduce the Ga peak concentration (which is plotted in fig. 4) and this causes the differences between the

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results of (a) the Ga concentration distribution for different fluences and of (b) the fluence dependence of the partial sputtering yields Ysi and Yoa .

H. Gnaser et al. / Fluence dependent concentration of low-energy Ga

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, , , ~_uui 1 , , ,,,i,, 10" 10 , 166 Fluence (cmz) Fig 4 . Concentration of Ga in the peak of the depth distribution vs the implantation fluence for 7 keV Ga in Si . Comparison is made between the theoretical retention model (eq . (2)), the SiMS data (fig. 2) and the computer simulations (fig . 3). 10- `' L

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SIMS data and the two other methods seen in fig. 4 . Although still tentative such an argument could explain the stronger deviations at high fluences where segregation effects are probably most pronounced. It is also in agreement with the occasional observation [7,24] of the surface precipitation of gallium from high fluence implanted silicon.

Acknowledgements We thank J .P. Biersack fer, providing a copy of the T-DYN computer code and for his helpful comments thereon .

References 6. Conclusions Low-energy Ga implantation in silicon was performed using a liquid-metal ion source. Implanted specimens were analyzed by SIMS and the fluence dependence of the near-surface Ga concentration derived thereby is in good agreement with computer simulations and a simple model of ion retention in the presence of sputtering . The latter may therefore be used to estimate the fluence dependent surface concentration in ion implantation also for other projectile/target combinations . It is expected, however, that the applicability will break down if extensive atom relocation processes (e.g ., diffusion or recoil/cascade mixing) are operative during ion implantation . At saturation fluences the SIMS data yield Ga concentrations which are lower by a factor of 3 than the theoretical model indicative of some Ga segregation to the surface .

[1) S . Matsui, Y . Kojima, Y . Ochiai and T. Honda, J. Vac. Sci. Technol. B9 (1991) 2622. [2) K . Nikawa, J . Vac. Sci. Technol . B9 (1991) 2566. [3) R . Levi-Setti, J.M . Chabala and Y .L . Wang, Ultramicroscopy 24 (1988) 97. [4) J.M . Chabala, 12 . Levi-Setti and Y.L. Wang, J . Vac. Sci. Technol . B6 (1988) 910. [5] R.L. Kubena, J.W. Ward, F.P. Stratton, R .J . Joyce, and G.M . Atkinson, J . Vac . Sci . Technol . B9 (1991) 3079 . [6) A. Benninghoven, F.G. Rüdenauer and H.W. Werner, Secondary Ion Mass Spectrometry (Wiley, New York, 1987). [7) H . Gnaser, F.G . Rüdenauer, H. Studnicka and P . Pollinger, Proc . 29th Field Emission Symp., eds. H .D. Andren and H . Norden (Almgvist, Stockholm, 1982) p. 401 . [8) H . Gnaser and F.G . Rüdenauer, unpublished results (1982). [9] V.J. Moore and P.D. Prewett, Vacuum 34 (1984) 189. [10) F . Werner, H. Gnaser, J. Scholtes and H . Oechsner, J . Vac. Sci. Technol. A9 (1991) 2678 . lb . BASIC INTERACTIONS (b)

1,14

H. Gnaser et al. / Fluence dependent concentration of low-energy Ga

[11] J. Steltmann, diploma thesis, Universität Kaiserslautern (1991). [121 H.N. Migeon, C. Le Pipec and J.J. Le Goux, in Secondary Ior, ir:x
[181 W. Baretzky, W . Möller and E. Taglauer, Nucl . Instr. and Meth. B18 (1987) 496. [191 W.D . Wilson, L .G. Haggmark and J.P. Biersack, Phys. Rev. B15 (1977) 2458. [201 G . Carter, J .S. Colligon and J .H. Leek, Proc . Phys. Soc . 79 (14.62) 2°.9 . [211 F . Schulz and K. Wittmaack, Radiat. Eff. 29 (1976) 31. [221 G . Betz and F .G. Rüdenauer, Appl . Surf. Sci. 51 (1991) 103 . [23) M . Behar et al., Radiat. Eff. Lett . 85 (1984) 117. [24] T. Ishitani, A. Shimase and H. Tamura, Appl . Phys . Lett. 39 (1981) 627.