EDXRF measurements on gold diffusion-doped Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy

ARTICLE IN PRESS Physica B 403 (2008) 3320– 3325

Contents lists available at ScienceDirect

Physica B journal homepage: www.elsevier.com/locate/physb

EDXRF measurements on gold diffusion-doped Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy C. Terzioglu  Department of Physics, Faculty of Arts and Sciences, Abant Izzet Baysal University, 14280 Bolu, Turkey

a r t i c l e in f o

a b s t r a c t

Article history: Received 31 January 2008 Received in revised form 17 April 2008 Accepted 21 April 2008

Gold (Au) diffusion in superconducting Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy was investigated over the temperature range 500–800 1C by the energy dispersive X-ray fluorescence (EDXRF) technique. It is found that the Au diffusion coefficient decreases as the diffusion-annealing temperature decreases. The temperature dependences of Au diffusion coefficient in grains and over grain boundaries are described by the relations D1 ¼ 6.7  105exp(1.19 eV/kBT) and D2 ¼ 9.7  104exp(1.09 eV/kBT), respectively. The diffusion doping of Bi-2223 by Au causes a significant increase of the lattice parameter c by about 0.19%. For the Au-diffused samples, dc electrical resistivity and transport critical current density measurements indicated the critical transition temperature increased from 100 to 104 K and the critical current density increased from 40 to 125 A cm2, in comparison with those of undoped samples. From scanning electron microscope (SEM) and X-ray diffraction (XRD) measurements it is observed that Au doping of the sample also improved the surface morphology and increased the ratio of the high-Tc phase to the low-Tc phase. The possible reasons for the observed improvement in microstructure and superconducting properties of the samples due to Au diffusion are also discussed. & 2008 Elsevier B.V. All rights reserved.

PACS: 74.72.h 74.25.Sv 74.62.c 66.30.Jc 61.10.Nz Keywords: Au diffusion Diffusion coefficient Activation energy Transition temperature

1. Introduction Partial cation substitution and diffusion are important approaches to elucidate the high-temperature superconducting mechanism and to determine the possibilities of improving the superconducting properties of the materials. Two techniques of impurity doping of superconductors are generally used for substitution of matrix cations by impurity atoms: (1) addition of impurity in the mixed powders before the sintering process and (2) diffusion doping of the pure superconductors by impurity atoms. Doping of superconductors during the sintering is accompanied by precipitation of a solid solution of impurities in the superconductors and formation of new phases. The diffusion technique of impurity opens new possibilities of preparation of superconductors with improved properties. Data on the diffusion parameters and the mechanism of impurity migration are useful to control the crystalline structure and the properties of superconductors [1]. Therefore, the diffusion parameters of gold (Au) may be useful for understanding the doping mechanism and changes of the microstructure and superconducting properties of Bi(Pb)SrCaCuO under doping.

 Corresponding author. Tel.: +90 3747 2541000; fax: +90 374 2534642.

E-mail address: [email protected] 0921-4526/$ - see front matter & 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.physb.2008.04.027

Jin et al. [2] found that the addition of Au degraded the superconducting properties of Bi(Pb)SrCaCuO. In contrast to this, it was observed that Au addition does not affect the transition temperature and the lattice parameters of Bi(Pb)SrCaCuO [3]. The common point of both Refs. [2,3] is that addition doping of Au to Bi(Pb)–Sr–Ca–Cu–O was carried out in the mixed powders before pressing and sintering of pellets. Dzhafarov et al. [4] studied the effect of Au diffusion on critical temperature and critical current density in Bi(Pb)–Sr–Ca–Cu–O system and found that Au diffusion promotes formation of the high-Tc (Bi-2223) phase and increases Jc significantly. To our knowledge, no detailed work has been published on the diffusion coefficient of Au in Bi(Pb)–Sr–Ca–Cu–O bulk samples except our recent work on calculation of diffusion coefficient via lattice parameter c in Au-diffused samples of Bi-2223 [5,6]. In these works, diffusion coefficient of Au was determined using the successive removal of thin layers and measurement of the sample’s resistivity and lattice parameter c at room temperature. In recent works [7,8], the effect of Au doping and diffusionannealing time on mechanical properties (hardness, yield strength, Young’s modulus, and fracture toughness) of Bi-2223 was studied. The investigation indicated that Au doping and diffusion-annealing time increased Vickers hardness, Young’s modulus, yield strength, and fracture toughness. In this work, we have reported the influence of Au diffusion on the properties of Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy samples, in order to

ARTICLE IN PRESS C. Terzioglu / Physica B 403 (2008) 3320–3325

3321

Surface morphologies of the Au-diffused and pure samples were studied by using a Philips XL30 SFEG SEM. SEM micrographs were taken from fracture surfaces of the bulk samples. Lattice parameters of the Au-doped and pure samples were analysed by means of a Rigaku D/Max-IIIC XRD with a CuKa target giving a monochromatic beam with 1.54 A˚. The spectra were collected from 2y ¼ 4–601 with a scan speed of 31 min1 and a step increment of 0.021 at room temperature. Phase purity and the lattice parameters were determined from these XRD patterns. The accuracy in determining the lattice parameter c was70.001 A˚. The mean values of lattice parameter c of Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy samples are determined from the high-angle (0 0 l) peaks of the XRD measurements. The EDXRF technique was used for determination of the concentration of Au atoms in the diffusion region of Bi1.8Pb0.35 Sr1.9Ca2.1Cu3Oy samples [9]. For the excitation of Au atoms, an annular Am-241 radioactive source (50 mCi) emitting 59.54 keV photons was used. An ultra LEGe detector was used for intensity measurements of Au La peaks at 9.7 keV. Determination of the Au concentration distribution was performed by the sequential removal of thin layer from the sample and measuring the EDXRF intensity. We used etching method (in HCl+H2O solution) to remove thin layers from the Au-diffused surface of the samples. The diffusion coefficient of Au in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy was estimated by differentiation of the measured distribution curve of the residual EDXRF intensity with respect to the thickness of the sample [10].

determine the diffusion parameters of Au and gain insight on changes in the crystalline structure and superconducting properties of the samples.

2. Experimental details The undoped Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy samples were prepared using a conventional solid-state reaction method from high-purity starting powders of Bi2O3, PbO, SrCO3, CaO, and CuO. After the milling, the mixed powders were calcined in air at 700, 750, and 800 1C for 24 h. At each calcination temperature, the sample was cooled to room temperature and ground. The calcined powder was ground and pressed into pellets of 10  4  2 mm3 at 300 MPa. The pellets were sintered in air at 830 1C for 48 h and then cooled down to room temperature. Doping of Au in Bi-2223 was carried out by means of diffusion from an evaporated Au film on the pellets. The Au evaporation (thickness of about 50 mm) on one face of the samples was carried out using an AUTO 306 Vacuum Coater (EDWARDS). Then, the Au-layered superconducting samples were annealed at 830 1C for 10 h. At the end of this run, Au diffusion was realized through the samples. For comparison, an undoped sample was also annealed under the same conditions. In addition to this, the diffusion annealing process was investigated to calculate the diffusion coefficient of Au. For this reason, virgin bulk samples were coated with an Au layer and diffusion annealing was carried out at 800, 750, 700, 600, and 500 1C for 10 h. Typical dimensions of the samples for transport, X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive X-ray fluorescence (EDXRF) measurements were 2  4  10 mm3. Electrical resistivity was measured as a function of temperature between 60 and 130 K by the standard dc four-probe method using a closed-cycle cryostat. The critical temperature Tc was determined from the zero of resistivity. The accuracy of the sample temperature measurements was 70.1 K The critical current density was determined by measuring the current–voltage plots at the onset of voltage (about 3 mV). Both voltage and current contacts were made with silver paint.

3. Results and discussion The samples of Bi-2223 pellets will be hereafter denoted as G0 (undoped sample annealed at 830 1C for 10 h), and G1 (Au-diffused sample annealed at 830 1C for 10 h). Powder XRD patterns from the surface of G0 and G1 powder samples are shown in Fig. 1. Some of the Miller indices are indicated in the figure. We used the linear least square method to calculate lattice parameters of the samples. The lattice parameters determined

(1119)H

(220)H

(1212)H

(00 12)H

(00 10)H

(115)H (115)L

(008)L

G1

100

0

0

10

20

(115)L (00 12)H (119)H (0014)H

Ca2Pb04

(002)L

200

(008)L

300

(00 10)H (115)H

Intensity (a.u.)

400

(008)H

(002)H

500

(119)H (200)H (00 14)H (1111)H

600

30 2 (deg.)

G0

40

50

60

Fig. 1. XRD patterns for the G0 and G1 samples. The peaks indexed (h k l)L and (h k l)H represent the Bi-2212 and Bi-2223 phases, respectively.

ARTICLE IN PRESS 3322

C. Terzioglu / Physica B 403 (2008) 3320–3325

from the (0 0 l) peaks of the XRD data are given in Table 1. Diffusion doping of Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy by Au is seen to increase the lattice parameter c by 0.19% if we compare the c of G0 and G1 samples. The increase in the c-parameter indicated that cations of the system (Bi+3, Sr+2, Ca+2) may partly be substituted by Au ions (0.85 A˚). Substitution at the Cu site is less likely because we have observed that Tc of the samples has increased. The increase in the intensities of the peaks for the G1 sample may testify for enhanced grain growth and better orientation of grains with Au diffusion, causing the critical current density to increase, as will be confirmed in critical current density measurements in the present work. The variation of the lattice parameter c with removed surface depth of G1 sample is shown in Fig. 2. The lattice parameter c for G0 and G1 was estimated to be 36.960 and 37.030 A˚, respectively, from XRD patterns. The value of lattice parameter c for G0 sample corresponds approximately to the value of lattice parameter of G1 at 20 mm depth. The decrease of lattice parameter c with increasing depth can be interpreted as a transformation from intragrain diffusion to intergrain diffusion behaviour. Surface morphology of Au-doped Bi(Pb)–Sr–Ca–Cu–O was studied by SEM in order to determine the grain sizes and possible precipitation at the grain boundaries. Fig. 3 represents the surface micrographs for the G0 and the G1 samples. The grain size of the G1 sample is relatively larger than that of the G0 sample as shown in Fig. 3, although we have not carried out conclusive quantitative analysis. The surface of the G1 sample is also smoother and denser. These results indicate that the surface morphology of the sample is relatively improved by Au doping. G0 has non-uniform surface appearance with smaller grains. SEM pictures show better connectivity in Au-coated samples after heat treatment at 830 1C for 10 h. The undoped (G0) sample consists of flake-type grains as shown in Fig. 3a and the composition of flake-type grains is

Table 1 Critical temperature Tc, transport critical current density Jc, lattice parameter c, and room temperature resistivity of the samples

Fig. 3. SEM micrographs of the (a) G0 and (b) G1 samples.

Samples Tcoffset (K) Lattice parameter c (A˚) Jtrans (A cm2) r at 300 K (mO cm) c G0 G1

10070.2 10470.2

36.960 37.030

40 125

8.50 7.10

37.05

c-lattice parameter

37

36.95

36.9

36.85

36.8

0

20

40

60 X (m)

80

100

Fig. 2. Variation of the lattice parameter with removed surface depth of G1 sample.

approximately equal to that of the Bi-2212 phase [10,11]. It was observed that the grains in the G0 sample are oriented randomly and poorly connected. In the sample G1, the flake-like grains are less dominant compared to the sample G0, while the concentration of the needle-like grains grew gradually for the G1 sample. The needle-like grains are more common in the high-Tc phase compared to the low-Tc phase [11–13]. These results are in agreement with our XRD examinations and indicate that the surface morphology of the sample is relatively improved by Au doping. From the above results, in agreement with our XRD results, it is inferred that doped Au has a positive effect of decomposing the structure of the low-Tc phase, enhancing the high-Tc phase formation, and improving the connections between the grains. Electrical resistivity was measured using the standard fourprobe dc technique, in the temperature range between 60 and 130 K. Room temperature resistivities were calculated from room temperature I–V curves (Table 1). Au doping is found to decrease the room temperature resistivity, which can be explained by noting that Au film on the sample forms a metallic connection; this resistive short circuit connects the grains and lowers the room temperature resistivity. The temperature dependence of normalized resistivity for G0 and G1 samples is shown in Fig. 4. The temperature dependence of the resistivities of the samples shows metallic behaviour (for TX110 K) with the zero-resistivity transition temperatures of 100 and 104 K, respectively. This result is consistent with the finding of Dzhafarov et al. [4]. The 4 K

ARTICLE IN PRESS C. Terzioglu / Physica B 403 (2008) 3320–3325

3323

1.2

1

0.0025

0.8

0.6

0.0015 0.001

0.4

0.0005

0.2 G0 G1 0 90

Zero field 100 mT 200 mT 300 mT 500 mT

0.002 P (.cm)

Normalized resistivity at 130 K

0.003

95

100

105

110 T (K)

115

120

125

0 60

130

Fig. 4. Temperature dependence of normalized resistivity for G0 and G1 samples.

80

90 100 110 Temperature (K)

120

130

80

110 90 100 Temperature (K)

120

130

0.003 0.0025

Zero field 100 mT 200 mT 300 mT 500 mT

0.002 P (.cm)

increase in Tc of G1 sample compared to that of G0 is reproducible using different batches of the G1 samples. The increased Tc accompanied by a sharp transition might be caused by an improved homogeneity of the hole concentration. The broadening of the transition width shows that G0 sample has lower percentage of the Bi-2223 phase compared to that of Au-diffused samples. The reduction of the broadening in rT curve may be due to the modifying effect of the Au diffusion on the grain boundaries. Sharper transitions are accompanied by higher critical temperature and higher critical current density values in the present work. As can be seen from Fig. 4, the transition curves from the normal state to the superconducting state have double step behaviour (more pronounced in G0), which indicates weak links and dominancy of the Bi-2212 phase. It is also possible that resistive nature of the grain boundaries is modified by accumulation of Au atoms at the grain boundaries. But this conjecture requires elucidation by transmission electron microscopy study, which is within our plans. Although wetting of the grain boundaries by a very thin layer of Au is unlikely, preferential accumulation of Au ions at the grain boundaries may reduce the resistive behaviour. We have also carried out magnetoresistivity measurements for G0 and G1 samples at 0, 0.1, 0.2, 0.3, and 0.5 T and displayed the results in Fig. 5. The figures indicate that the critical temperature of the sample is lowered when an external magnetic field is applied. Specifically, with increasing dc magnetic field up to 0.5 T, Tcoffset decreases from 100 to 67 K for the G0 and 104 to 72 K for the G1 sample. We observed that the broadening of the resistivity transition width increases with increasing external dc magnetic field. The transport critical current density of the G0 and the G1 Bi(Pb)–Sr–Ca–Cu–O samples measured in liquid nitrogen are 40 and 125 A cm2, respectively. It should be noted that the transport critical current density of the Au-doped sample is about three times larger than that of undoped Bi(Pb)–Sr–Ca–Cu–O. A similar increase of Jc was observed in Au-doped Bi(Pb)–Sr–Ca–Cu–O [4] and YBaCuO superconductors [14]. The increase of Jc in Bi(Pb)–Sr–Ca–Cu–O by Au diffusion may be caused by the increase of grain sizes and their co-orientations. This can be due to an improved coupling between Au-diffused superconducting grains, and an increased number of flux-pinning centres due to the presence of Au in the intergrain regions. This similar improving effect of Au-diffusion in Jc is revealed for the critical transition temperature in the present work. The increased value of

70

0.0015 0.001 0.0005 0 60

70

Fig. 5. Temperature dependence of resistivity at different magnetic fields for (a) G0 and (b) G1 samples.

Jc in the G1 sample compared to the G0 in our investigations can be interpreted as a result of Au diffusion in intergrain boundaries. This in turn causes an increase of intergrain contact surface or decreases intergrain resistivity. There are several methods to estimate the diffusion parameter in polycrystalline high-Tc superconductors. The most common four methods are: successive removal of thin layers and (1) the measurement of the sample’s resistivity, (2) the measurements of lattice parameters from XRD patterns, (3) the radio tracer, and (4) the EDXRF method. In this study, we used EDXRF technique to determine the diffusion coefficient of Au in Bi(Pb)–Sr–Ca–Cu–O system. Fig. 6 exhibits the typical concentration profile of Au over thickness of the sample, exposed to Au diffusion at 800 1C for 10 h. The solid curves 1 and 2 illustrate the calculated concentration profiles of the impurity diffusion from a constant source into a semi-infinitive solid as [10] pffiffiffiffiffiffi Nðx; tÞ ¼ N 0 ½1  erfðx=2 Dt Þ (1) where erf[x/2(Dt)1/2] represents the error function with argument y ¼ x/2(Dt)1/2: Z y 2 erfðyÞ ¼ pffiffiffi expðy2 Þ (2) p 0

ARTICLE IN PRESS 3324

C. Terzioglu / Physica B 403 (2008) 3320–3325

1.1

10-7

1.0

D2

0.8

D1 = 3.49x10-9 cm2s-1

10-8

0.7

D (cm2 s-1)

N/N0 (Relative Units)

0.9

0.6 0.5 0.4

D1

10-9

0.3 D2 = 2.80x10-8 cm2s-1

0.2 0.1 0.0

10-10 0

10

20

30

40

50 60 x (m)

70

80

90

100 110

0.9

0.95

1

1.05

1.1

1000/T

Fig. 6. Concentration profile of Au over the thickness of the sample, exposed to Au diffusion at 800 1C for 10 h.

1.15

1.2

1.25

1.3

(K-1)

Fig. 7. Temperature dependence of the diffusion coefficients of Au in the nearsurface and inner region of Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy.

related with migration into grains and over grain boundaries, pores, and other defects, respectively. This relatively low value of the activation energy (1.19 eV) of Au in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy may testify that the migration of Au primarily proceeds through defects of polycrystalline sample (pore surfaces, grain boundaries, etc.) as in the case for Au diffusion in YBaCuO ceramics [14].

Table 2 Values of Au diffusion coefficients for each temperature Diffusion-annealing temperature (1C)

D1 (cm2 s1)

D2 (cm2 s1)

500 600 700 750 800

8.00  1011 3.76  1010 1.39  109 2.28  109 3.49  109

4.95  1010 2.59  109 9.35  109 1.78  108 2.80  108

4. Conclusions

Here, N0 ¼ N(0, t) is the constant concentration on the surface of the sample, N(x, t) the impurity concentration at the distance x from the surface, D the diffusion coefficient, and t the diffusion annealing time. The experimental data for 800 1C in Fig. 6 can be described by two concentration regions: (1) curve 1 for the near-surface region (x ¼ 0–35 mm) and (2) curve 2 for the inner region (x435 mm) of the sample. The diffusion coefficients in these regions are calculated as D1 ¼ 3.49  109 cm2 s1 (slow diffusion) and D2 ¼ 2.80  108 cm2 s1 (fast diffusion). Similar two-region concentration profiles of Au diffusion in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy were also observed at 500, 600, 700, and 750 1C. The same fitting method was used for the samples that are diffusion annealed at these three temperatures and the values of Au diffusion coefficients for each temperature are calculated and listed in Table 2. Diffusion coefficient at 500 1C is found to be two orders of magnitude lower than at 800 1C for both of the regions. The mean values of the diffusion coefficients of Au in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy as a function of temperature for two regions are given in Fig. 7. The results of these studies showed that the Au diffusion coefficients, D1 and D2, in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy system in the temperature range 500–800 1C increase in accordance with the Arrhenius relation D1 ¼ 6:7  105 expfð1:19  0:10Þ eV=kB Tg

(3)

D2 ¼ 9:7  104 expfð1:09  0:10Þ eV=kB Tg

(4)

It is well known that impurity diffusion in polycrystalline samples of high-Tc superconductors take place simultaneously over the grain boundaries and into the grains [10,14,15]. Therefore, the slow Au diffusion (D1) and fast Au diffusion (D2) may be

Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy samples were prepared through solid-state reaction method. In the temperature range of 500–800 1C, diffusion of Au in Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy sample takes place with two diffusion coefficient, D1 and D2, which are attributed to the relatively slow migration in the grains and the fast migration over the grain boundaries, respectively. The corresponding activation energies were 1.19 and 1.09 eV. The lattice parameter c of the Au diffusion-doped sample (G1) is found to increase by about 0.19%. The diffusion doping of Bi1.8Pb0.35Sr1.9Ca2.1Cu3Oy by Au increased the critical current density from 40 to 125 A cm2 and the critical transition temperature by about 4 K compared to the pure sample. In addition, Au doping improved the surface morphology.

Acknowledgement This work is supported by the Scientific and Technological Council of Turkey (Project no: 104T325). References [1] T.D. Dzhafarov, Phys. Stat. Sol. (a) 158 (1996) 335. [2] S. Jin, R.C. Sherwood, T.H. Tiefel, G.W. Kammlott, Appl. Phys. Lett. 52 (1998) 1628. [3] H.K. Liu, S.X. Dou, K.H. Song, C.C. Sorrell, Supercond. Sci. Technol. 3 (1990) 210. [4] T.D. Dzhafarov, M. Altunbas-, A. Varilci, T. Ku¨c- u¨ko¨merog˘lu, S. Nezir, Solid State Commun. 99 (11) (1996) 839. [5] O. Ozturk, T. Ku¨c- u¨ko¨merog˘lu, C. Terzioglu, J. Phys.: Condens. Matter 19 (2007) 346205. [6] C. Terzioglu, O. Ozturk, I. Belenli, J. Alloys Compd., in press. [7] M. Yilmazlar, O. Ozturk, O. Gorur, I. Belenli, C. Terzioglu, Supercond. Sci. Technol. 20 (2007) 365. [8] M. Nursoy, M. Yilmazlar, C. Terzioglu, I. Belenli, J. Alloys Compd. 459 (2008) 399.

ARTICLE IN PRESS C. Terzioglu / Physica B 403 (2008) 3320–3325

[9] E.P. Bertin, Principles and Practice of X-ray Spectrometric Analysis, Plenum Press, New York, 1975. [10] G.B. Abdullaev, T.D. Dzhafarov, Atomic Diffusion in Semiconductor Structures, Harwood, New York, 1987. [11] S.M. Khalil, J. Phys. Chem. Solids 62 (2001) 457. [12] Y.C. Chen, K.K. Chong, T.H. Meen, Jpn. J. Appl. Phys. 30 (1991) L33.

3325

[13] K.H. Yoon, Y.B. Lee, J. Mater. Sci. 26 (1991) 5101. [14] T.D. Dzhafarov, M. Altunbas, A. Varilci, T. Ku¨cu¨ko¨merog˘lu, Mater. Lett. 25 (1995) 81. [15] T.D. Dzhafarov, M. Altunbas, A. Varilci, U. C - evik, A.I˙. Kopya, Mater. Lett. 26 (1996) 305.