Low energy ion identification method using a silicon semiconductor detector telescope

Low energy ion identification method using a silicon semiconductor detector telescope

Nuclear Instruments North-Holland NUCLEAR lNSTRUMENtS 81METHODS IN PHVSICS RESEARCH and Methods in Physics Research A 348 (1994) 192-197 Low energy...

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Nuclear Instruments North-Holland

NUCLEAR lNSTRUMENtS 81METHODS IN PHVSICS RESEARCH

and Methods in Physics Research A 348 (1994) 192-197

Low energy ion identification detector telescope **

method using a silicon semiconductor

Luis de1 Peral, JosC Medina *, Enrique Bronchalo Departamento Received

de Fisica. Uniuersidad de Alcali. Apartado 20, 28871 Alcalri de Henares, Madrid, Spain

11 March 1994

A method for discriminating cosmic ions that can be applied at low energies using AE-E is presented. The method is tested with a simple detector telescope, consisting of surface barrier silicon detectors. The results obtained irradiating the detector with 3zS ions at 795 MeV are presented and then compared with those obtained by applying the Seamster et al. algorithm.

1. Introduction Ion discrimination main problems

in a detector

in the study

of solar

telescope

is one of the

energetic

particles

and

cosmic rays, particularly when we consider a wide range of charges and energies and low abundances. The lost energies, measured by the different detectors, produce a data matrix that can be broken down according to the nature of each ion. The charge and mass spectra for these ions are deduced on the basis of this matrix. The most commonly used method was developed by Seamster, Green and Korteling in 1977 [l] and is based on integrating the Bragg curves using the Bethe-Bloch equation, and assuming the ion mass is twice its charge (M(amu) = 22). The identification parameter PI = ( MZ2/2)‘/3 is obtained with an iterative calculation program for each event (a point on the energy loss matrix). This method gives good results at energies below 10 MeV/nucleon and atomic numbers below 10, but above these values the method is quite imprecise. low energy

2. Identification

method

Our identification method consists of minimizing the difference between the experimental AE value and an estimated AE, value. This estimated value is obtained with an expression that is deduced from a set of data generated by a Monte Carlo simulation with the detector

* Corresponding 49 42, e-mail * * This work has de Ciencia y 0306-CO2-02.

telescope being used. This method has been tested with ions from proton to sulfur at energies below 2.5 MeV/nucleon.

author. Tel. +34 1 885 49 40, fax +34 1 885 [email protected]. been supported by the Comisi6n Interministerial Technologia (CICYT) of Spain, grant ESP88-

2.1. First identification

step

A simulation program is used in the first step to supply a set of data that will be analogous to the expected experimental data, in the same charge and energy range. It is only necessary to simulate the most abundant stable isotope for each element. An expression similar to the nonrelativistic approach of the Bethe-Bloch equation is fitted to these data. The expression is: MZ’Ax

(1)

AE=kE

R

where k (MeV*/amu pm) and s (amu/MeV) are the parameters to be fitted, M (amu) and Z the mass and charge of the generated ions, Ax (pm) the thickness of the tracking detector where the ion loses AE (MeV) and E, (MeV) is the residual energy in the stopping detector. M, Z and Ax are inputs to the simulation program and A E and E, are the outputs. This step gives a pair of parameters, k and s, for each type of simulated ion. 2.2. Second

identification

step

The k and s parameters from expression (1) are charge-dependent, unlike those which are obtained with the Bethe-Bloch equation which only depend on the material detector. The k parameter in the Bethe-Bloch equation is 0.0166 MeV’/amu p,rn for silicon detectors. However, in Eq. (1) this parameter depends on the atomic number of the ionizing particle, since substituting the effective charge with the total nuclear charge provokes the

0168-9002/94/$07.00 0 1993 - Elsevier Science B.V. All rights reserved SSDI 0168-9002(94)00489-T

L. del Peral et al. /Nucl. Instr. and Meth. in Phys. Res. A 348 (1994) 192-197 appearance of this dependence. The true value of A E is obtained by integrating the Bethe-Bloch equation. However, in this work the content of the integral has been considered a constant and was finally multiplied by the thickness of the detector. Therefore there is also a certain dependence on detector thickness in the k(Z) parameter, such that the thicker the detector, the more it will deviate from 0.0166 M e V 2 / a m u Ixm. With this in mind the k dependence on Z is expressed as:

k ( Z ) = 0.0166 + k111 - exp( - k 2 Z ) ] .

(3)

s(Z) = s,/zs2.

The coefficients kl, k2, s I and s 2 are obtained by simply fitting Eqs. (2) and (3) to the parameters obtained in the previous step. Eq. (1) can then be rewritten as: 2zaAx mE

e =

k(Z)---~R

[ . . ER]

ln[s(Z)~-~]

O D1

D2

(2)

The s parameter represents the curvature of expression (1), so the larger the parameter the quicker the logarithm changes, thus generating a greater curvature. In this way the parameter implicitly provokes a logarithmical variation in the integration of the Bethe-Bloch equation, and thus depends on detector thickness. Thus, when the thickness tends to be negligible, the parameter goes to 12.4 a m u / M e V , its value in the Bethe-Bloch equation. The s parameter is expressed as:

(4)

in which it has been assumed that the mass is twice the charge of the ion ( M = 2Z). Eq. (4) makes possible to calculate the estimated value ( A E e) required for the next step.

2.3. Third identification step To obtain the charge and thereby identify the event, the value for Z from expression (4) that minimizes ( E - AEe) 2 is taken. A E is the experimental value, A E e the value deduced from expression (4), and E R is always the experimental value. So as to obtain the acceptance limit for ( A E - A E e ) 2 this third step can be done with the data generated with the simulation program. The maximum value obtained with these data will be the acceptance limit for the experimental data.

3. Experimental procedure This identification method has been applied to a detector telescope composed of four circular surface barrier silicon detectors, placed within an aluminium structure. The pulse amplifying chain was composed of nuclear instrumentation modules (NIM), and a personal computer was used for data acquisition. Fig. 1 shows the detector telescope as well as the telescope used in the simulation

193

D4 / / l f / /

1 em

Fig. 1. Scheme of detector telescope and the Monte Carlo simulation detector telescope.

program. Table 1 gives the characteristics of each detector. The detector system was explained in a previous paper [2]. This telescope can register ions from proton to iron at energies below 50 MeV/nucleon.

3.1. Monte Carlo simulation A Monte Carlo program from the European Space Agency [2] was used for the simulation; it was modified so as to obtain data analogous to the experimental data instead of the global information that the program supplied as its standard output. The modification allows detailed results to be obtained for each simulated event that are similar to the ones obtained experimentally. The program is only useful for telescopes with cylindrical symmetry. The program inputs are: charge and mass of the particle to be simulated; the energy per nucleon range that the particle may have; the inclination angle range that the telescope is able to detect; the energy-range tables for each material (aluminium and silicon) used in the telescope; the number of ions generated; and the coincidence criterion used in the telescope. For our telescope (Fig. 1), we have simulated the most abundant stable natural isotopes from helium to sulfur, in an energy range from 1 to 25 MeV/nucleon, with an inclination angle of between 0 ° and 20°; 2500 events were generated for each ion; and the fourth detector

Table 1 Detector characteristics

Area (cm 2) Thickness (ixm) Resistivity (k['l cm) Alpha resolution fwhm (keV) Dead layer (l~g/cm 2)

D1

D2

D3

D4

3 31 0.4 36.8

4.5 151 1.8 26.6

4.5 1014 12.5 20.8

9 100 1.9 26.1

40.0 Au 40.0 Au 40.1 Au 40.0 Au 40.1A1 40.0A1 40.0A1 40.0A1

L. del Peral et al. /Nucl. Instr. and Meth. in Phys. Res. A 348 (1994) 192-197

194

I

400

I

I

I

I

'

I

I

'

10 2 ~"

350

(a)

''~:" -..... ...

w

I

. -...

.--... . . ,.'~+. ..:~ " ,.;..

300

:.

.+ +

:'. -~:,

1

I

6

8

10

I

I

I

'

12

14

16

I

I

I

(b)

10

10 o

. . . .

0

100

,

200

. . . .

,

300

. . . .

,

400

. . . .

,

. . . .

500

600

ER (MeV) Fig. 2. Energy loss matrix for the Monte Carlo simulation data and the curves obtained with eq. (4).

acted in anticoincidence. The program randomly generates the position and inclination of ion entry and energy. It simulates particle m o v e m e n t in the telescope using the e n e r g y - r a n g e tables, and obtains the result for energy loss for each material.

3.2. Accelerator data The telescope was irradiated in the V I C K S I accelerator ( V a n de Graaf Isochron Cyclotron Kombination fiir Schwere Ionen, H a h n - M e i t n e r - I n s t i t u t , Berlin). A 795 M e V b e a m of 3 2 8 and two targets of 197Auwith thickness of 124 i x g / c m 2 and 1.5 m g / c m 2 were used. The scattered and fragmented ions were detected by the telescope placed 20 cm from the target at angles of 12 ° for the 124 ~ g / c m 2 target and 15 ° and 20 ° for the 1.5 m g / c m 2 target with respect to the b e a m direction. The global results have been presented in a previous paper [3].

2

10

6

12

14

16

Z Fig. 3. Charge spectra for the simulation data, obtained (a) with the Seamster et al. algorithm and (b) with our identification method.

type of simulated ion. The second identification step was applied and the following equations were obtained:

k ( Z ) = 0.0166 + 0.019511 - exp( - 0 . 1 8 Z ) ] ,

(5)

s ( Z ) = 4.17//Z °'71.

(6)

o

o.7

..'+........++........i.................+.................~.................'...-....+....../..................i.................'........~.. ,+,

o.

............................. +................. +.................................... +................. +................. +..................

+-

+ o+ .............................+.................+...................................+.................i.................+...................

............................................................................................ + 0

o 7 ................7

,..,

................................................................................. + ................ +................. +................. ;r"

o.,+.

..............................................

4. Results

The first identification step was applied to the data obtained with the simulation program using the second 151 Ixm detector as the tracking detector and the third 1014 ixm detector as stopping detector (points on Fig. 2). Eq. (1) was used to fit these data and a chi-square below 0.9 was obtained. This gave the k and s parameters for each

4

+................. G................. i

.

+

+

+

+

m

o

+

,! . . i = ,

o

~ 2

:

i 4

+

i 6

,

I Io

P

i

,

, ,

l 12



l

,

I 16

, ,

I 14

+: ,

Z ( M o n t e Carlo inputs) Fig. 4. Standard deviations for the simulation data, obtained with the Seamster et at. algorithm (rq) and with our identification method ( • ).

195

L. del Peral et al. / Nucl. Instr. and Meth. in Phys. Res. A 348 (1994) 192-197

Fig. 2 shows the curves deduced from Eq. (4) using the charge-parameter relations given in the Eqs. (5) and (6). As result of the logarithm in Eq. (4) the curves peak and quickly fall off. These curves do not agree with the data on the left of the peak (Fig. 2), and this occurs when the energy loss (MeV) in the stopping detector is less than five times the atomic number of the ion. Therefore, our method cannot discriminate these events, and as a result, about 10% of the total data generated by Monte Carlo are lost.

These lost data correspond to the ions that lose the greatest part of their energy in the tracking detector. 4.1. Monte Carlo results

As a first test of the method and to compare it with the Seamster et al. method [1], the third identification step was applied to the data (points on Fig. 2) obtained with the simulation program that had given ( A E - AEe) 2 values

10 3 10 2

10

'

0.8

1

1.2

10 2

400

10

200

1

2

0

2.2S

103 10 2

10

0.8 p

1

10 2

4o0

10

2o0

2

t

3He

4He

i

75

120

50

2S

6

8

0

(b)

3

4

5

(a)

4O

10

0

12

14

15

2OO

200 100

160

75

120

100

50

80

50

25

40

150

0

5

200 160

50

4

7U 9Be 11B 6Li 81i7Be lOBe 10B12 B

6He

100

100

0

0

2.25

2OO

150

3

6oo

1.2

d

(a)

600

6

8

12C 13c

14C

is N 160 t4 N 170

1~0

0

10 F Ne

0

12 Na Mg

AI

(b)

14

15

28Si 29Si 30Si

31p 30p

Fig. 5. Charge and mass spectra obtained (a) with the Seamster et al. algorithm and (b) with our identification method.

196

L. del Peral et al. /Nucl. Instr. and Meth. in Phys. Res. A 348 (1994) 192-197

below 0.00035, which was used as an acceptance value to fit the experimental data. The resulting charge spectrum is shown in Fig. 3b together with the spectrum obtained using the Seamster et al. [1] algorithm (Fig. 3a), both for the same data set. In the simulation data, the type of ion that produces the results is known (it was input in the simulation program), so, once the discrimination is done, the results can be compared with the data. To do this, the spectrum obtained with the simulation performed with the same ion is fitted with a Gaussian curve to obtain the standard deviation (o-). This process was carried out with Table 2 Mass and charge resolution Seamster et al.

Our results

1H 2H 3H

0.025 0.028 0.037

0.027 0.025 0.033

3He 4He 6He

0.051 0.024 0.054

0.030 0.019 0.024

6Li 7Li 8Li

0.035 0.034 0.045

0.034 0.030 0.037

7Be 9Be 1oBe

0.039 0.047 0.038

0.037 0.041 0.032

lo B 11B 12B

0.038 0.041 0.079

0.033 0.034 0.034

12C 14C

0.049 0.049 0.061

0.044 0.042 0.053

14N 15N

0.053 0.051

0.050 0.040

160 180

0.065 0.082 0.099

0.035 0.045 0.042

F Ne Na

0.27 0.24 0.22

0.18 0.16 0.12

24Mg 25Mg 26Mg

0.11

0.051 0.045 0.045

13C

170

27A1 28A1

0.16

0.053 0.068

28Si 29Si 30Si

0.076 0.069 0.085

0.050 0.044 0.054

3op 31p

0.049 0.054

0.048 0.046

all the simulated ions between helium and sulfur; the standard deviations are shown in Fig. 4 for both identification methods. In general it can be seen (Fig. 4) that our method produces smaller dispersion than does the Seamster et al. method and the charge resolution is good (Fig. 3b), better than the one obtained with the Seamster et al. method (Fig. 3a), particularly with the charge ions greater than the oxygen ion. For light ions, up to carbon, both methods give fairly similar and acceptable results with dispersion below 2%. The difference between the results (Figs. 3 and 4) are caused by the increase in charge, which is what makes the Seamster et al. method less exact. In fact their method becomes so imprecise, it gives a dispersion value of 0.27 for neon, upon which it is not possible to distinguish between the 2°Ne and 22Ne isotopes. A dispersion value on the order of 0.1 (our method gives 0.11) is needed to do this. The Seamster et al. results worsen with the increase in charge, giving as much as 0.66 for sulfur, which is much worse than 0.17 obtained with our method. 4.2. Accelerator results

It is not necessary to obtain the charge-parameters relations from Eqs. (5) and (6) for the accelerator data, so expressions (4), (5), and (6) are valid for any set of data that are studied with this telescope. The third identification step consists in minimizing ( A E -- AEe) 2 using the experimental data for A E and E R. Applying the third identification step gives the spectra shown in Fig. 5b, while the spectra obtained using the Seamster et al. algorithm are shown in Figs. 5a. As above our method cannot discriminate those events in which the energy (MeV) loss in the stopping detector is less than five times the atomic number of the ion, which means losing 10% of the obtained data. There are not enough ions between fluorine and aluminium to attain good mass discrimination, but very good separation was obtained in charge. However, using our method it was possible to separate the isotopes of magnesium and aluminium, which is not possible with the Seamster et al, method. Table 2 gives the charge and mass resolution deduced from the above spectra (Fig. 5) using a Gaussian adjustment of the spectral peaks. Resolution is generally good for charge and mass, and always better than what can be obtained with the Seamster et al. algorithm, even for those isotopes that have low abundances, like 6He, 8Li, 12B, 14C, laN and from fluorine to phosphorus. It is interesting to note that it is possible to use the same Eqs. (4), (5), and (6), in any amplification system, since they only refer to the configuration of the detector telescope itself.

5. Conclusions With this identification method it is possible to obtain good charge and mass discrimination, even with low abun-

L. del Peral et al. / Nucl. Instr. and Meth. in Phys. Res. A 348 (1994) 192-197

dances isotopes. The method does not depend on the electronic amplification systems used. However, about 10% of the registered events are lost. Compared with the Seamster et al. algorithm, our method has better resolution, although it is more complicated since it requires that parameters be adjusted and a minimization be performed, thus requiring a longer process.

Acknowledgements The authors thank Dr. K. Ziegler and Dr. W. Bohne of the Hahn-Meitner-Institut for their advice and help, and

197

C.F. Warren of the ICE of the Alcalfi University for her linguistic assistance.

References [1] A.G. Seamster, R.E.L. Green and R.G. Korteling, Nucl. Instr. and Meth. 145 (1977) 583. [2] J. Medina, L. del Peral, S. S~inchez, M. Rosa, J. Sequeiros, E. Garcia and D. Meziat, Proc. 22nd Int. Cosmic Ray Conf., vol. 3 (1991) 776. [3] J. Medina, L. del Peral, S. Sfinchez and D. Meziat, Proc. 26th ESLAB Symposium., ESA SP-346 (1992) 321.