- Email: [email protected]
Experimental measurement of in-depth secondary defects distribution produced by helium implantation in silicon
NIM B Beam Interactions with Materials & Atoms
Nuclear Instruments and Methods in Physics Research B 253 (2006) 90–93 www.elsevier.com/locate/nimb
Experimental measurement of in-depth secondary defects distribution produced by helium implantation in silicon S. Daliento a, L. Mele a
a,*
, P. Spirito a, L. Gialanella b, B.N. Limata b, M. Romano
b
Dipartimento di Ingegneria Elettronica e delle Telecomunicazioni, University of Napoli ‘‘Federico II’’ Via Claudio 21, 80125 Napoli, Italy b Dipartimento Scienze Fisiche e INFN Sezione di Napoli Via Cinthia, 80100 Napoli, Italy Available online 13 November 2006
Abstract The effect of lifetime engineering processes on the electrical behaviour of electronic devices is related to the stable defects concentration that establishes in the semiconductor material. The modelling of such processes is complicate because the mechanisms leading from primary defects (the ones directly created by the process) to secondary ones (arising from the interactions between primary defects themselves and between primary defects and other impurities present in the material) depend, in an unpredictable way, on the microscopic structure of each particular material. In this paper we present an experimental study showing the distribution of secondary defects created by an helium implantation process. The defects are characterised in terms of energy levels, effectiveness, and concentration. A comparison with the distribution predicted by the TRIM code is also given. 2006 Elsevier B.V. All rights reserved.
1. Introduction Helium and proton implantation are very attractive techniques for the optimisation of the switching behaviour of power bipolar devices. This is because the damage of the silicon lattice, induced by implantation at the depth of the ion range, produces a local decrease of the minority carriers recombination lifetime, so that, by varying the energy and the fluence of the ion beam it is possible, in principle, to design a recombination profile optimised for a given application. The value of the lifetime at a given position along the semiconductor layer depends on the stable defects structure, created by the ion beam, and on their concentrations. Defects generation is a complex phenomenon. Ions impact on the silicon lattice causes the displacement of silicon atoms from their stable position, the defects thus created are the so called vacancies and are referred to as primary defects. These defects are highly mobile, also at room temperature, and unstable; they tend to combine
*
Corresponding author. Tel.: +39 81 7683134; fax: +39 081 593448. E-mail address: [email protected] (L. Mele).
0168-583X/$ - see front matter 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.nimb.2006.10.021
with other impurity and/or with other primary defects thus creating a large variety of secondary defects [1]. The widely accepted tool used to evaluate the primary defects distribution is the Monte Carlo simulation code TRIM [2], however, the relation between primary and secondary defects is not completely understood. The major difficult arises from the strong spatial dependence of the defects distribution created by the ion implantation. In this case, in fact, usual techniques used to identify the species of defects in silicon fail because they are unable to give any information about the spatial distribution of such defects. As a consequence it is usual to attribute to the secondary defect distribution the same shape predicted by TRIM for the primary ones. In this paper we use an all electrical measurement technique based on a special test device [3], having the unique feature to detect the in-depth minority carriers recombination lifetime profile. As the temperature dependence of the recombination lifetime is directly related to the energy levels in the silicon bandgap created by each particular defect specie, we are able, by measuring the lifetime profile in a wide temperature range (from 190 K to 390 K), to reconstruct the temperature dependence of the lifetime at each
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93
point along the semiconductor layer and hence to relate it to the particular defects present in that points. This analysis allows a direct comparison with the density of primary defects simulated by TRIM. The results obtained with this procedure could be compared with that gained by other techniques based on DLTS [4] measurements. However we have to emphasize that what we do is to interpret (by means of the SRH model) the temperature dependence of the recombination lifetime in terms of energy levels of recombination centers, while DLTS based methods directly detects the presence of trap centers. This fact implies that less effective recombination centers, actually present in the material, could be not detected by our technique.
2. Test device operation The measurement technique used in this work has been already used to characterise a large variety of materials and processes [5–8], details on its operation can be found in [9]. In the following we briefly recall the measurement principle with reference to the cross section schematic of the test device shown in Fig. 1. The samples used in this work have been fabricated on lightly doped n-type epitaxial layers grown on a heavily doped n-type substrate. As can be seen the device is basically constituted by a lateral diode, formed by the surface p+ and n+ regions, and by a third electrode made on the bottom of the n-type substrate. Direct biasing of the surface diode cause minority carrier (holes) injection into the epilayer, while positive biasing of the substrate pushes them toward the surface of the device. The width Xc of the region in which minority carriers are confined depends
91
on the magnitude of the bottom voltage and on the injection level imposed by the diode voltage according with the formula [9] Xc ¼ 2
wð1 þ P ON Þ ; V S =V t þ 2ð1 þ P ON Þ
ð1Þ
where w is the epilayer thickness, Vt is the thermal voltage, VS is the voltage applied to the substrate and PON is the normalised injection level. When a small signal voltage, dVS, is superimposed to the dc bias, VS, the confine identified by Xc moves of a quantity dXc giving rise to a modulation of the minority carriers region. From a physical point of view this modulation corresponds to holes generation-recombination around the confine Xc as a consequence an ac component in the surface diode current appears. Such a component is directly related to the hole lifetime value around Xc so that, for each Xc, it is possible to obtain sðX c Þ ¼
X 1 c ; d id 1 Dn 2 þ P ON dX c is
ð2Þ
where Dn is the electron diffusivity, id and is are the ac components of the lateral diode current and of the substrate current respectively. It is important to note that, differently from other profiling techniques, like CV, that are based on the control of the depletion layer related to a reverse biased junction, the magnitude of the substrate voltage needed to move Xc along the entire layer does not depend on the epilayer doping nor on the epilayer thickness but only on the injection level so that few volts (instead of hundred of volts) are sufficient to scan the whole epilayer. 3. Sample preparation and experimental results
Fig. 1. Cross section schematic of the three terminal test structure used for the resistivity profiling.
As said above test devices have been fabricated on n-type silicon epitaxial layers. Epitaxial doping was 2 · 1014 atm/cm3 and epitaxial thickness was about 60 lm. Ion implantation have been performed at the Dynamitron Tandem Laboratory of the Ruhr University (Bochum) with an energy beam of 5.8 MeV and a fluence of 1 · 1011 ions/cm2. Lifetime profiles have been measured in the temperature range 190–390 K. The results are shown in Fig. 2. Also interesting is the fact that the same test device permits the measurement of the resistivity profile [10] this feature is important both because highlights the effect of ion implantation also on the apparent doping of the device and because the doping of the device directly affects the reliability of the lifetime measurement [11]. Fig. 3 shows the effective doping profiles (evaluated from the resistivity profiles) of the sample implanted with 1 · 1011 ions/cm2; these profiles have been used to correct the epilayer doping during the lifetime measurements shown in Fig. 2.
92
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93 1E-04
Lifetime (s)
1E-05
390 K 335 K 295 K 220 K 190 K
1E-06
1E-07
1E-08
10
20
30
40
50
Depth (μm)
Fig. 2. Lifetime profiles of 1 · 1011 cm2 helium implanted test device measured at different temperatures.
Effective doping (cm-3 )
1E+15
carriers vth) extracted from the curves of Fig. 2 by fixing the abscissa at x = 30 lm. These data have been analysed by using a multitrap SRH model [12] and it has been found that the experimental behaviour is well described by the interaction of two recombination centers whose energy levels are Ec–0.17 eV and Ec–0.23 eV; the contribute of each of the above energy levels is shown in the figure. As it was expected the figure shows that the lifetime is constant at low temperatures and starts to increase at the temperature where the Fermi level crosses the energy level of the recombination center present in the material. However, as shown in the figure, a single trap process does not describe the whole set of the experimental points because the value of the constant part and the knee of the curve are correlate [12]. It is important to note that at low temperatures, when the normalised lifetime becomes constant, the constant value is given by s T 1=2 /
1E+14 390 K 335 K 295 K 220 K 190 K
1E+13
1E+12 10
20
30
40
50
Depth (μm)
Fig. 3. Resistivity profiles of 1 · 1011 cm2 helium implanted test device evaluated at different temperatures.
4. Analysis and comments The knowledge of the lifetime profile at various temperatures permits to extract the temperature dependence of the lifetime at each point along the semiconductor layer. An example of such an analysis is shown in Fig. 4 where circles indicate the values of the lifetime (normalised to the temperature dependence T1/2 of the thermal velocity of the
ð3Þ
where r is the capture cross section of the recombination center and Nt is its concentration. Hence, from plots like that of Fig. 4 it is also possible to obtain, for each center, the product rNt that represents the effectiveness of the center. Moreover, if the capture cross section is known, it is possible to calculate the absolute number of defects Nt. The analysis described above with reference to Fig. 4 has been repeated at various point along the epitaxial layer thus obtaining the identification of the centers present along the entire epitaxial layer and their concentration. Fig. 5 shows the distribution of the most relevant recombination centers that have been identified. As can be seen three energy levels, with different weight along the layer, are reported. In particular, at the ion stopping range Ec–0.23 eV and Ec–0.17 eV appears to be dominant, while toward the silicon surface, a center located at Ec–0.45 eV seems more important (note that at the depth of 30 lm the center Ec–0.45 eV is not revealed because its effect on the lifetime is negligible with respect to the others, this fact does not mind that it is not present at all).
1
1E-04
Fit Ec-0.23 eV Ec-0.17 eV Experimental
Normalized σ N *N
1/2 1/2 τ x T (sK )
1 ; rN t
1E-05
1E-06 0
2
4
6
8
-1
1000/T (K )
Fig. 4. Normalised plot of recombination lifetime as a function of 1000/T at the depth of 30 lm for the 1 · 1011 cm2 helium implanted test device.
Ec-0.45 Ec-0.23 eV Ec-0.17 0.1
0.01
0.001 20
25
30
35
40
Depth (μm)
Fig. 5. In-depth product rNt of the most relevant centers normalised at the maximum of the concentration of center Ec–0.23 eV.
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93
By using the above values we obtain the absolute number of defects reported in Fig. 7, compared with the TRIM vacancy distribution. The figure shows that the A center is much less concentrate than the divacancy, but, thank to its capture cross section, its effectiveness as recombination center is almost equivalent (see Fig. 5).
1
Normalized σ N*N
93
Ec-0.23 eV TRIM
0.1
5. Conclusions 0.01 20
25
30
35
40
Depth (μm)
Fig. 6. Comparison between the normalised distribution of the center Ec– 0.23 eV and normalised vacancy distribution evaluated by TRIM.
The distribution of the center with energy level Ec– 0.23 eV, is compared in Fig. 6 with the primary defects distribution evaluated by TRIM. The figure clearly shows that the width of the heavily damaged region is wider than that provided by TRIM. As a final point, we note that the method we have used permits to interpret the temperature behaviour of the lifetime in terms of energy levels of the recombination centers, however, in principle, it does not permit an unambiguous identification of the physical defects responsible for that behaviour. However, the comparison with DLTS results allows us to propose a possible identification of the defects we found. In particular the energy levels Ec–0.17 eV, Ec–0.23 eV and Ec–0.42 eV have been elsewhere [13] attributed to the oxygen-vacancy complex (A-center) and to the double and single negatively charged level of the divacancy respectively. In particular, values reported in [13] for the capture cross sections of the first two are Ec –0:23 eV;
r ¼ 2 1015 cm2 ;
Ec –0:17 eV;
r ¼ 2 1014 cm2 :
1E+18
N/cm 3
1E+17
Ec-0.23 Ec-0.17 Total centres concentration TRIM-Vac
1E+16 1E+15 1E+14 1E+13 10
15
20
25
30
35
40
Depth (μm) Fig. 7. Comparison between the primary defects concentration evaluated by TRIM and secondary defects distribution extracted by our measurement technique.
In this paper an experimental study of the effects of helium implantation on the defect distribution in silicon materials has been reported. The study takes advantage of a measurement technique that gives the in-depth recombination lifetime profile along a semiconductor layer. The results we have obtained show that the distribution of the secondary defects resulting from helium implantation are slightly different from that predicted by TRIM. The temperature dependence of the lifetime has been explained in terms of energy levels of the recombination centers and the relative weight of each of them has been given as a function of the position along the material. Also the in depth absolute concentration of the defects has been given. This last result should help to understand the mechanisms underlying the interactions between primary defects in implanted materials. References [1] J.Vobecky, P. Hazdra, J. Voves, F. Spurny, J. Homola, in: Proc. of ISPSD Davos, 31 May–2 June 1994. [2] www.srim.org. [3] P. Spirito, G. Coccorullo, IEEE Trans. Electron Dev. ED-32 (9) (1985). [4] Dieter K. Schroder, Semiconductor Material and Device Characterization, John Wiley and Sons, New York, 1990. [5] S. Daliento, A. Sanseverino, P. Spirito, P.M. Sarro, L. Zeni, IEEE Electron Dev. Lett. 17 (3) (1996) 148. [6] S. Daliento, A. Sanseverino, P. Spirito, L. Zeni, IEEE Trans. Power Electron. 14 (1) (1999) 117. [7] S. Daliento, A. Sanseverino, P. Spirito, G. Busatto, J. Wiss, Proc. of 12th Int. Symp. on Power Semiconductor Devices and ICs, 22–25 May 2000, p. 283. [8] P. Spirito, S. Daliento, A. Sanseverino, L. Gialanella, M. Romano, B.N. Limata, R. Carta, L. Bellemo, IEEE Electron Dev. Lett. 25 (9) (2004) 602. [9] S. Daliento, A. Sanseverino, P. Spirito, IEEE Trans. Electron Dev. 46 (8) (1999) 1808. [10] S. Daliento, L. Mele, P. Spirito, B.N. Limata, Mater. Sci. Eng. B 124– 125 (2005) 310. [11] S. Daliento, L. Mele, P. Spirito, L. Gialanella, M. Romano, B.N. Limata, R. Carta, L. Bellemo, in: Proc. of ISPSD Naples, 4–8 June 2006. [12] P. Spirito, A. Sanseverino, Solid-State Electron. 37 (7) (1994) 1429. [13] B.G. Svensson, B. Mohadjeri, A. Hallen, J.H. Svensson, J.W. Corbett, Phys. Rev. B 43 (3) (1991).
Nuclear Instruments and Methods in Physics Research B 253 (2006) 90–93 www.elsevier.com/locate/nimb
Experimental measurement of in-depth secondary defects distribution produced by helium implantation in silicon S. Daliento a, L. Mele a
a,*
, P. Spirito a, L. Gialanella b, B.N. Limata b, M. Romano
b
Dipartimento di Ingegneria Elettronica e delle Telecomunicazioni, University of Napoli ‘‘Federico II’’ Via Claudio 21, 80125 Napoli, Italy b Dipartimento Scienze Fisiche e INFN Sezione di Napoli Via Cinthia, 80100 Napoli, Italy Available online 13 November 2006
Abstract The effect of lifetime engineering processes on the electrical behaviour of electronic devices is related to the stable defects concentration that establishes in the semiconductor material. The modelling of such processes is complicate because the mechanisms leading from primary defects (the ones directly created by the process) to secondary ones (arising from the interactions between primary defects themselves and between primary defects and other impurities present in the material) depend, in an unpredictable way, on the microscopic structure of each particular material. In this paper we present an experimental study showing the distribution of secondary defects created by an helium implantation process. The defects are characterised in terms of energy levels, effectiveness, and concentration. A comparison with the distribution predicted by the TRIM code is also given. 2006 Elsevier B.V. All rights reserved.
1. Introduction Helium and proton implantation are very attractive techniques for the optimisation of the switching behaviour of power bipolar devices. This is because the damage of the silicon lattice, induced by implantation at the depth of the ion range, produces a local decrease of the minority carriers recombination lifetime, so that, by varying the energy and the fluence of the ion beam it is possible, in principle, to design a recombination profile optimised for a given application. The value of the lifetime at a given position along the semiconductor layer depends on the stable defects structure, created by the ion beam, and on their concentrations. Defects generation is a complex phenomenon. Ions impact on the silicon lattice causes the displacement of silicon atoms from their stable position, the defects thus created are the so called vacancies and are referred to as primary defects. These defects are highly mobile, also at room temperature, and unstable; they tend to combine
*
Corresponding author. Tel.: +39 81 7683134; fax: +39 081 593448. E-mail address: [email protected] (L. Mele).
0168-583X/$ - see front matter 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.nimb.2006.10.021
with other impurity and/or with other primary defects thus creating a large variety of secondary defects [1]. The widely accepted tool used to evaluate the primary defects distribution is the Monte Carlo simulation code TRIM [2], however, the relation between primary and secondary defects is not completely understood. The major difficult arises from the strong spatial dependence of the defects distribution created by the ion implantation. In this case, in fact, usual techniques used to identify the species of defects in silicon fail because they are unable to give any information about the spatial distribution of such defects. As a consequence it is usual to attribute to the secondary defect distribution the same shape predicted by TRIM for the primary ones. In this paper we use an all electrical measurement technique based on a special test device [3], having the unique feature to detect the in-depth minority carriers recombination lifetime profile. As the temperature dependence of the recombination lifetime is directly related to the energy levels in the silicon bandgap created by each particular defect specie, we are able, by measuring the lifetime profile in a wide temperature range (from 190 K to 390 K), to reconstruct the temperature dependence of the lifetime at each
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93
point along the semiconductor layer and hence to relate it to the particular defects present in that points. This analysis allows a direct comparison with the density of primary defects simulated by TRIM. The results obtained with this procedure could be compared with that gained by other techniques based on DLTS [4] measurements. However we have to emphasize that what we do is to interpret (by means of the SRH model) the temperature dependence of the recombination lifetime in terms of energy levels of recombination centers, while DLTS based methods directly detects the presence of trap centers. This fact implies that less effective recombination centers, actually present in the material, could be not detected by our technique.
2. Test device operation The measurement technique used in this work has been already used to characterise a large variety of materials and processes [5–8], details on its operation can be found in [9]. In the following we briefly recall the measurement principle with reference to the cross section schematic of the test device shown in Fig. 1. The samples used in this work have been fabricated on lightly doped n-type epitaxial layers grown on a heavily doped n-type substrate. As can be seen the device is basically constituted by a lateral diode, formed by the surface p+ and n+ regions, and by a third electrode made on the bottom of the n-type substrate. Direct biasing of the surface diode cause minority carrier (holes) injection into the epilayer, while positive biasing of the substrate pushes them toward the surface of the device. The width Xc of the region in which minority carriers are confined depends
91
on the magnitude of the bottom voltage and on the injection level imposed by the diode voltage according with the formula [9] Xc ¼ 2
wð1 þ P ON Þ ; V S =V t þ 2ð1 þ P ON Þ
ð1Þ
where w is the epilayer thickness, Vt is the thermal voltage, VS is the voltage applied to the substrate and PON is the normalised injection level. When a small signal voltage, dVS, is superimposed to the dc bias, VS, the confine identified by Xc moves of a quantity dXc giving rise to a modulation of the minority carriers region. From a physical point of view this modulation corresponds to holes generation-recombination around the confine Xc as a consequence an ac component in the surface diode current appears. Such a component is directly related to the hole lifetime value around Xc so that, for each Xc, it is possible to obtain sðX c Þ ¼
X 1 c ; d id 1 Dn 2 þ P ON dX c is
ð2Þ
where Dn is the electron diffusivity, id and is are the ac components of the lateral diode current and of the substrate current respectively. It is important to note that, differently from other profiling techniques, like CV, that are based on the control of the depletion layer related to a reverse biased junction, the magnitude of the substrate voltage needed to move Xc along the entire layer does not depend on the epilayer doping nor on the epilayer thickness but only on the injection level so that few volts (instead of hundred of volts) are sufficient to scan the whole epilayer. 3. Sample preparation and experimental results
Fig. 1. Cross section schematic of the three terminal test structure used for the resistivity profiling.
As said above test devices have been fabricated on n-type silicon epitaxial layers. Epitaxial doping was 2 · 1014 atm/cm3 and epitaxial thickness was about 60 lm. Ion implantation have been performed at the Dynamitron Tandem Laboratory of the Ruhr University (Bochum) with an energy beam of 5.8 MeV and a fluence of 1 · 1011 ions/cm2. Lifetime profiles have been measured in the temperature range 190–390 K. The results are shown in Fig. 2. Also interesting is the fact that the same test device permits the measurement of the resistivity profile [10] this feature is important both because highlights the effect of ion implantation also on the apparent doping of the device and because the doping of the device directly affects the reliability of the lifetime measurement [11]. Fig. 3 shows the effective doping profiles (evaluated from the resistivity profiles) of the sample implanted with 1 · 1011 ions/cm2; these profiles have been used to correct the epilayer doping during the lifetime measurements shown in Fig. 2.
92
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93 1E-04
Lifetime (s)
1E-05
390 K 335 K 295 K 220 K 190 K
1E-06
1E-07
1E-08
10
20
30
40
50
Depth (μm)
Fig. 2. Lifetime profiles of 1 · 1011 cm2 helium implanted test device measured at different temperatures.
Effective doping (cm-3 )
1E+15
carriers vth) extracted from the curves of Fig. 2 by fixing the abscissa at x = 30 lm. These data have been analysed by using a multitrap SRH model [12] and it has been found that the experimental behaviour is well described by the interaction of two recombination centers whose energy levels are Ec–0.17 eV and Ec–0.23 eV; the contribute of each of the above energy levels is shown in the figure. As it was expected the figure shows that the lifetime is constant at low temperatures and starts to increase at the temperature where the Fermi level crosses the energy level of the recombination center present in the material. However, as shown in the figure, a single trap process does not describe the whole set of the experimental points because the value of the constant part and the knee of the curve are correlate [12]. It is important to note that at low temperatures, when the normalised lifetime becomes constant, the constant value is given by s T 1=2 /
1E+14 390 K 335 K 295 K 220 K 190 K
1E+13
1E+12 10
20
30
40
50
Depth (μm)
Fig. 3. Resistivity profiles of 1 · 1011 cm2 helium implanted test device evaluated at different temperatures.
4. Analysis and comments The knowledge of the lifetime profile at various temperatures permits to extract the temperature dependence of the lifetime at each point along the semiconductor layer. An example of such an analysis is shown in Fig. 4 where circles indicate the values of the lifetime (normalised to the temperature dependence T1/2 of the thermal velocity of the
ð3Þ
where r is the capture cross section of the recombination center and Nt is its concentration. Hence, from plots like that of Fig. 4 it is also possible to obtain, for each center, the product rNt that represents the effectiveness of the center. Moreover, if the capture cross section is known, it is possible to calculate the absolute number of defects Nt. The analysis described above with reference to Fig. 4 has been repeated at various point along the epitaxial layer thus obtaining the identification of the centers present along the entire epitaxial layer and their concentration. Fig. 5 shows the distribution of the most relevant recombination centers that have been identified. As can be seen three energy levels, with different weight along the layer, are reported. In particular, at the ion stopping range Ec–0.23 eV and Ec–0.17 eV appears to be dominant, while toward the silicon surface, a center located at Ec–0.45 eV seems more important (note that at the depth of 30 lm the center Ec–0.45 eV is not revealed because its effect on the lifetime is negligible with respect to the others, this fact does not mind that it is not present at all).
1
1E-04
Fit Ec-0.23 eV Ec-0.17 eV Experimental
Normalized σ N *N
1/2 1/2 τ x T (sK )
1 ; rN t
1E-05
1E-06 0
2
4
6
8
-1
1000/T (K )
Fig. 4. Normalised plot of recombination lifetime as a function of 1000/T at the depth of 30 lm for the 1 · 1011 cm2 helium implanted test device.
Ec-0.45 Ec-0.23 eV Ec-0.17 0.1
0.01
0.001 20
25
30
35
40
Depth (μm)
Fig. 5. In-depth product rNt of the most relevant centers normalised at the maximum of the concentration of center Ec–0.23 eV.
S. Daliento et al. / Nucl. Instr. and Meth. in Phys. Res. B 253 (2006) 90–93
By using the above values we obtain the absolute number of defects reported in Fig. 7, compared with the TRIM vacancy distribution. The figure shows that the A center is much less concentrate than the divacancy, but, thank to its capture cross section, its effectiveness as recombination center is almost equivalent (see Fig. 5).
1
Normalized σ N*N
93
Ec-0.23 eV TRIM
0.1
5. Conclusions 0.01 20
25
30
35
40
Depth (μm)
Fig. 6. Comparison between the normalised distribution of the center Ec– 0.23 eV and normalised vacancy distribution evaluated by TRIM.
The distribution of the center with energy level Ec– 0.23 eV, is compared in Fig. 6 with the primary defects distribution evaluated by TRIM. The figure clearly shows that the width of the heavily damaged region is wider than that provided by TRIM. As a final point, we note that the method we have used permits to interpret the temperature behaviour of the lifetime in terms of energy levels of the recombination centers, however, in principle, it does not permit an unambiguous identification of the physical defects responsible for that behaviour. However, the comparison with DLTS results allows us to propose a possible identification of the defects we found. In particular the energy levels Ec–0.17 eV, Ec–0.23 eV and Ec–0.42 eV have been elsewhere [13] attributed to the oxygen-vacancy complex (A-center) and to the double and single negatively charged level of the divacancy respectively. In particular, values reported in [13] for the capture cross sections of the first two are Ec –0:23 eV;
r ¼ 2 1015 cm2 ;
Ec –0:17 eV;
r ¼ 2 1014 cm2 :
1E+18
N/cm 3
1E+17
Ec-0.23 Ec-0.17 Total centres concentration TRIM-Vac
1E+16 1E+15 1E+14 1E+13 10
15
20
25
30
35
40
Depth (μm) Fig. 7. Comparison between the primary defects concentration evaluated by TRIM and secondary defects distribution extracted by our measurement technique.
In this paper an experimental study of the effects of helium implantation on the defect distribution in silicon materials has been reported. The study takes advantage of a measurement technique that gives the in-depth recombination lifetime profile along a semiconductor layer. The results we have obtained show that the distribution of the secondary defects resulting from helium implantation are slightly different from that predicted by TRIM. The temperature dependence of the lifetime has been explained in terms of energy levels of the recombination centers and the relative weight of each of them has been given as a function of the position along the material. Also the in depth absolute concentration of the defects has been given. This last result should help to understand the mechanisms underlying the interactions between primary defects in implanted materials. References [1] J.Vobecky, P. Hazdra, J. Voves, F. Spurny, J. Homola, in: Proc. of ISPSD Davos, 31 May–2 June 1994. [2] www.srim.org. [3] P. Spirito, G. Coccorullo, IEEE Trans. Electron Dev. ED-32 (9) (1985). [4] Dieter K. Schroder, Semiconductor Material and Device Characterization, John Wiley and Sons, New York, 1990. [5] S. Daliento, A. Sanseverino, P. Spirito, P.M. Sarro, L. Zeni, IEEE Electron Dev. Lett. 17 (3) (1996) 148. [6] S. Daliento, A. Sanseverino, P. Spirito, L. Zeni, IEEE Trans. Power Electron. 14 (1) (1999) 117. [7] S. Daliento, A. Sanseverino, P. Spirito, G. Busatto, J. Wiss, Proc. of 12th Int. Symp. on Power Semiconductor Devices and ICs, 22–25 May 2000, p. 283. [8] P. Spirito, S. Daliento, A. Sanseverino, L. Gialanella, M. Romano, B.N. Limata, R. Carta, L. Bellemo, IEEE Electron Dev. Lett. 25 (9) (2004) 602. [9] S. Daliento, A. Sanseverino, P. Spirito, IEEE Trans. Electron Dev. 46 (8) (1999) 1808. [10] S. Daliento, L. Mele, P. Spirito, B.N. Limata, Mater. Sci. Eng. B 124– 125 (2005) 310. [11] S. Daliento, L. Mele, P. Spirito, L. Gialanella, M. Romano, B.N. Limata, R. Carta, L. Bellemo, in: Proc. of ISPSD Naples, 4–8 June 2006. [12] P. Spirito, A. Sanseverino, Solid-State Electron. 37 (7) (1994) 1429. [13] B.G. Svensson, B. Mohadjeri, A. Hallen, J.H. Svensson, J.W. Corbett, Phys. Rev. B 43 (3) (1991).