Materials Chemistry and Physics 121 (2010) 267–273

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Materials Chemistry and Physics

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Crystallite growth kinetics of highly pure nanocrystalline tin dioxide: The effectof palladium doping

R.G. Pavelkoa,∗, A.A. Vasilieva, F. Gispert-Guiradob, N. Barrabesc, J. Llorcad, E. Llobeta, V.G. Sevastyanove

a University Rovira i Virgili, Department of Electronic, Electrical & Automatic Control Engineering (DEEEA), Av. Paisos Catalans, 26, 43007 Tarragona, Tarragona, Spainb University Rovira i Virgili, Scientific Resources Service, Tarragona, Spainc University Rovira i Virgili, Chemical Engineering Department (DEQ) Tarragona, Spaind Institute of Energy Technology, Universitat Politècnica de Catalunya, Barcelona, Spaine N.S. Kurnakov Institute of General and Inorganic Chemistry RAS, Moscow, Russia

a r t i c l e i n f o

Article history:Received 12 August 2009Received in revised form 14 January 2010Accepted 16 January 2010

Keywords:Tin oxide

a b s t r a c t

TXRD study together with BET, HRTEM and TEM techniques were performed to investigate the effect of Pddoping on crystallite growth kinetics of highly pure nanocrystalline SnO2 during isothermal annealingat 873, 973 and 1073 K. Apparent activation energy for crystallite growth of blank as well as surfaceand bulk doped SnO2 was estimated applying grain growth model with size-dependent impediment.Low activation energy for blank material (∼23 kJ mol−1) suggests that Sn self-diffusion on the reducedcrystallite’s surface is the most probable mechanism contributing to the growth process. Together withvery low crystallite growth rate blank material demonstrates the highest agglomeration degree after

Palladium dopingCrystal growthIsothermal annealingN

annealing. Doping with Pd does not result in drag effect on crystallite boundary mobility. In contrary,it results in remarkable increase of crystallite growth rate together with an increase in the activation

k dop

1

om(tbmmpafatbTctwbp

0d

anocrystalline materials energy. In the case of bul

. Introduction

Tin dioxide is a material with wide application. Outstandingptical, electronic and catalytic properties make SnO2 a promisingaterial for optoelectronic applications, heterogeneous catalysis

including photocatalysis) and gas sensors [1]. It is well knownhat physical and chemical properties (and therefore catalyticehaviour) of dispersed materials strongly depend on size andorphology of constituent particles. The most crucial change inaterial properties is observed for nanoclusters of 1–4 nm, where

ercentage of surface atoms varies from 30% up to 75% of totaltom number in cluster [2]. However, apart from the promisingeatures of highly dispersed materials – e.g. high catalytic activitynd enhanced selectivity [2], high sensitivity to gas ambient [3],unable electrooptical properties [4,5] – there is one chief draw-ack which can discard easily the above mentioned advantages.his is poor thermal stability. Crystallites or grains (the smallestoherently diffracting domains) with the size of several nanome-

ers predominantly consist of coordinatively unsaturated atoms,hich make them non-equilibrium structures with high crystallite

oundary energy [6], depressed surface stress [7] and low meltingoint [8].

∗ Corresponding author. Tel.: +34 977 55 87 64; fax: +34 977 55 96 05.E-mail address: roman.pavelko@gmail.com (R.G. Pavelko).

254-0584/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.matchemphys.2010.01.034

ed SnO2 the phenomenon of crystallite coalescence was observed.© 2010 Elsevier B.V. All rights reserved.

Several methods allow us to evaluate thermal stability of thenanodispersed materials, among them – in situ X-ray diffraction,which provides a reliable characterization of the growth pro-cesses during powder annealing [9]. On the basis of the diffractionline broadening analysis, which comprises reflection fitting in thewhole range of the diffraction pattern, one calculates mean crys-tallite size as a function of time and temperature of the annealing.The crystallite growth kinetics can be estimated from the crystallitesize evolution applying various models.

Early considerations of isothermal crystallite growth kinet-ics assumed asymptotic power-law dependency of the crystallitesize change on annealing time (generalized parabolic grain growthmodel):

Dn − Dn0 = kt, (1)

where D0 is the initial crystallite size at annealing time t = 0, D isthe crystallite size at time t /= 0, k is the rate constant, which isa function of the activation energy of isothermal growth, n is thecrystallite size exponent and t is the annealing time. The empiricparameter n depends on diffusion mechanism: in the case of n = 3

volume diffusion mechanism is believed to be predominant, whenn = 4 surface diffusion governs crystallite growth [6]. However, fornanomaterials n varies with temperature and usually equals to val-ues exceeding 10 which can hardly be explained by the model sinceit ignores pinning effects of second phase, impurities or pores.

2 istry and Physics 121 (2010) 267–273

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D

wwbe

T

wv

nmmmk

Ssdseduooh[mgHtg

2

2

(fnwdu(ct6atuwtPtTa

2

(

68 R.G. Pavelko et al. / Materials Chem

Later, the model was modified by including a drag term, whichook into account the solute drag effect and limiting crystalliteize [10]. Finally, Michels et al. [11] demonstrated that retarda-ion effect caused by pores or impurities with low mobility shouldepend on crystallite size (grain growth model with size-dependent

mpediment):

(t) =√

D2lim − (D2

lim − D20) exp

(−2At

D2lim

)(2)

here Dlim is the limiting crystallite size and A is the rate constant,hich is the product of specific interface energy and crystallite

oundary mobility, and is a function of the diffusion activationnergy [10]:

A ∝ exp(−Q

RT

)(3)

here T is the temperature, R is the gas constant and Q is the acti-ation energy.

Taking into account that the majority of the applications ofanodispersed materials assumes the employment of porous andulti-component dispersed systems (e.g. catalysts, gas sensitiveaterials) the model with size-dependent impediment should be theost appropriate to describe and analyze the crystallite growth

inetics of nanomaterials.Recently, we reported the synthesis of highly pure and dispersed

nO2 for gas sensor applications starting from metalorganic precur-ors [12,13]. By means of in situ thermal XRD analysis (TXRD), weemonstrated that low amounts of Cl, S and Pd admixtures changeignificantly the crystallite growth kinetics (estimated using gen-ralized parabolic model) increasing integral crystallite growth rateuring isothermal annealing at 973 K [14]. This article is our contin-ation to the investigation in this field. Here we report our resultsn TXRD study of thermal stability of the system containing nan-dispersed pure SnO2 and noble metal, namely palladium, whichas been widely used as gas sensing material for almost five decades15]. On the basis of the kinetic model with size-dependent impedi-ent we compare apparent activation energies for the crystallite

rowth of blank, surface and bulk Pd-doped SnO2. In addition,RTEM, TEM and BET analysis were employed to better understand

he role and contribution of noble metal additives in the isothermalrowth of SnO2 crystallites.

. Experimental

.1. Materials

For the synthesis of the materials the following chemicals were used: tin powderP/N 265632, Sigma–Aldrich), glacial acetic acid (P/N 45731, Sigma–Aldrich), wateror trace analysis (Trace SELECTTM Ultra, P/N 14211, Sigma–Aldrich) and ammo-ia hydroxide, 27% (P/N 09861, Sigma–Aldrich). Synthesis of tin acetate complexas performed from tin powder and glacial acetic acid according to the protocolescribed elsewhere [16]. The water free acetic solution of tin acetate complex wassed for the synthesis of dispersed SnO2. Cooled solution of ammonia hydroxide12.5%) was added dropwise under continuous stirring to the cooled solution of theomplex. The transparent mixture was heated up to 333 K to induce the forma-ion of the colloid. The solid phase was separated by continuous centrifugation at000 rpm, washed three times with hot deionized water and then dried at 363, 423nd 573 K. To introduce Pd admixture we added water solution of Pd(NH3)4(NO3)2

o tin acetate prior to ammonia addition. Surface deposition of Pd was carried outsing conventional impregnation of blank SnO2 (synthesized from tin acetate asell) with water solution of Pd(NH3)4(NO3)2 followed by drying and then calcina-

ion at 573 K to ensure complex decomposition. Blank tin dioxide, bulk and surfaced-doped SnO2 are denoted as “SnO2 blank”, “SnO2-Pd” and “SnO2 dep Pd”, respec-ively. All samples before TXRD experiment underwent calcination at 573 K for 10 h.he catalyst content was determined by laser spark mass spectrometry on EMAL-2

pparatus.

.2. Characterization methods

TXRD measurements were performed using Siemens D5000 diffractometerBragg–Brentano parafocusing geometry and vertical �–� goniometer) equipped

Fig. 1. Typical XRD pattern (a) of SnO2-Pd after 30 h at 1073 K, the pattern fit (b),and difference between the experimental data and the fit (c).

with an Anton-Paar HTK10 platinum ribbon heating stage. Ni-filtered Cu K� radia-tion (30 mA, 40 kV) and a Braun position sensitive detector (PSD) were used. Sampleswere mixed with a few drops of absolute ethanol and deposited onto the plat-inum heater as a thin flat and even layer. The angular 2� diffraction range wasbetween 20◦ and 96◦ , constant step size of approximately 0.02◦ and 0.4 s step−1 (e.g.∼25 min pattern−1). The first pattern was recorded at room temperature (303 K), thesecond one – immediately after the preset temperature (873, 973 or 1073 K) wasreached with a heating rate of 10 K min−1. The third and followings patterns wereobtained at constant temperature with 30 min delay between each other. Overall 31patterns were collected during isothermal heat treatment. The overall time of TXRDexperiment amounted to 31 h, while time of isothermal annealing to ∼30 h. Staticair atmosphere was used throughout the analysis.

The X-ray diffractograms were analyzed using TOPAS 3.1 program [17]. Apseudo-Voigth function was used to fit the diffraction pattern. The instrumentalcontribution to the peak width was obtained from a sample of LaB6 from the NIST(SRM 676b). The LaB6 pattern was analyzed with the same software by fitting apseudo-Voigth function. The calculated parameters for LaB6 were maintained con-stant for SnO2 samples. It was assumed for all samples that only crystallite sizeaffects the XRD peak broadening and no effects of microstrains were observed inthe XRD line width. For each pattern we fitted following parameters: the zero shift,a 2◦ Chebyshev polynomial as a background, cell parameters for SnO2 (Cassiterite,P42/mnm, a = b = 4.73820 Å, c = 3.18710 Å), and the integral breadth for Pt that camefrom the heater. Fig. 1 shows a typical fitted pattern (taken at 1073 K after 30 h ofisothermal annealing).

Crystallite size was calculated from the integral breadth, ˇi , according to theScherrer’s equation [18]:

ˇi = �

D cos �(4)

where � is the wavelength, D is the crystallite size and � is the Bragg angle. In ourcase, all reflections of SnO2 contributed to the crystallite size calculation in such away that the obtained value represents the mean for the whole sample, assumingthat crystallites are ideal spheres. The software TOPAS 3.1 was used in the so-called“launch mode”, which permits the fitting of a number of diffractograms in a sequen-tial way. In our case, 31 diffractograms were analyzed sequentially. The calculatedcrystallite size is in good agreement with the values obtained for the same samplesat room temperature using D8 Bruker diffractometer.

High-resolution transmission electron microscopy (HRTEM) was carried outonly for initial materials (after calcination at 573 K) at 200 kV with a JEOL JEM 2100instrument equipped with a LaB6 source. The point-to-point resolution of the micro-scope was 0.20 nm. Samples were deposited on holey-carbon-coated Cu grids fromalcohol suspensions. For each sample, at least 100 particles were used for particlesize distribution calculation. All samples before and after thermal treatment werestudied by means of conventional transmission electron microscopy (TEM) on JeolJEM 1011 at 100 kV accelerating voltage.

BET surface area was calculated from N2 adsorption–desorption isotherms forinitial samples (before annealing) and the ones after annealing at 973 K for 30 h. Thephysisorption was performed on Micromeritics ASAP 2000 surface analyzer at 77 K.Before analysis, all the samples were degassed in vacuum at 393 K for 6 h.

R.G. Pavelko et al. / Materials Chemistry and Physics 121 (2010) 267–273 269

Fig. 2. HRTEM and FT images of SnO2 blank (a) and SnO2-Pd (b) after calcination at 573 K.

at 57

3

dmeoov1fi

t(atl5

TA

Fig. 3. HRTEM and FT images of SnO2 dep Pd after calcination

. Results

Using laser spark mass spectrometry, the content of the intro-uced elements together with other impurities in the synthesizedaterials was estimated (Table 1). The instrumental error was

qual to 20% for light elements (e.g. Cl and S) and 10% for the restf the elements. As one can see the main background impurities,bserved in all samples, are P, Al and Si (probably from the glassessel). Bulk doped and surface doped samples contain 0.02 and.2 wt% Pd, respectively. The change of the background impuritiesrom sample to sample does not exceed the amount of intentionallyntroduced admixtures.

All initial materials calcinated at 573K exhibit similar par-icle size and morphology as deduced from HRTEM images

Figs. 2 and 3). Particles generally range from 2 to 10 nm in sizend consist of poorly faceted crystallites. Fig. 2 shows HRTEM pic-ure as well as the Fourier transform (FT) image obtained from theattice-fringe image for the blank and bulk doped SnO2 calcinated at73 K. Electron diffraction spots at 3.35 Å correspond to the (1 1 0)

able 1dmixture and impurity content in the synthesized materials.

Element SnO2 blank (wt%) SnO2-Pd (wt%) SnO2 dep Pd (wt%)

Cl 0.01 0.01 0.01S 0.01 0.01 0.01Pd 0.00 0.02 1.2Na 0.01 0.01 0.02P 0.02 0.01 0.03Si 0.05 0.06 0.05Al 0.02 0.02 0.02

3 K. Areas 1 and 2 correspond to SnO2 and PdO (respectively).

crystallographic planes of several SnO2 crystallites. In the case ofbulk doped SnO2 no evidence was found for the Pd incorporationinto the SnO2 structure, probably because of very small amount ofthe admixture. Spots at 3.35 Å in the corresponding FT image areascribed to the (1 1 0) planes of SnO2. Images of surface doped mate-rial are shown in Fig. 3. Area labeled “1” demonstrates the latticefringes at 3.35 Å which corresponds to SnO2 (1 1 0). Area labeled “2”shows spots at 3.05 Å, which are ascribed to (1 0 0) planes of PdO,in which particles are well dispersed over SnO2 and measure about2–3 nm.

Figs. 4–6 show TEM pictures of the initial materials and the onesafter heat treatment at 973 K for 30 h (denoted as “after HT”). Atlower magnification it is clear that prior to the annealing all materi-als consist of evenly shaped particles. Both catalyst doped materialsseem to be less agglomerated in comparison with blank SnO2. Themorphology of all materials changes notably after annealing. Inthe case of blank and surface doped tin dioxide in addition to anincrease in particle size, higher agglomeration is noticeable. Amongall materials the most drastic morphology change was observedfor SnO2-Pd, which suggests that the abnormal crystallite growthtook place during the annealing. Surface doped material did notdemonstrate abrupt crystallite growth. However, the particles areremarkably bigger than that of blank SnO2.

Results of crystallite size calculations together with agglom-erate size (calculated from BET surface area) and agglomeration

degree of the materials before and after annealing at 973 K for30 h are shown in Table 2. Instrumental error for XRD and BETtechniques estimated as a standard deviation for three iterativemeasurements was ca. 5%. The degree of agglomeration was foundas a ratio between XRD and BET surface area which equals to an

270 R.G. Pavelko et al. / Materials Chemistry and Physics 121 (2010) 267–273

Fig. 4. TEM images of SnO2 blank before (a) and after heat treatment at 973 K for 30 h (b).

and a

attBaPea

Fig. 5. TEM images of SnO2-Pd before (a)

verage quantity of crystallites closely packed together [9]. Prioro the annealing, materials have high surface area and the par-icles available for the gas adsorption consist of 2–4 crystallites.efore annealing crystallite sizes of bulk and surface doped SnO2

re roughly 1.5 times bigger than that of blank SnO2. Due to this factd-doped materials are less agglomerated and the highest agglom-ration degree is observed for blank SnO2. After heat treatment thegglomerate size increases significantly for all materials. However,

Fig. 6. TEM images of SnO2 dep Pd before (a) and

fter heat treatment at 973 K for 30 h (b).

due to the small crystallite size, blank material again demonstratesthe highest agglomeration: ∼9 crystallites per particle. Surfacedoped SnO2 after annealing shows the best result regarding bothagglomerate and crystallite size.

Fig. 7 represents time and temperature evolution of mean crys-tallite size of blank SnO2. Two kinetics models were used to fitthe experimental data: generalized parabolic grain growth model,Eq. (1) (lines marked with “1”) and grain growth model with size-

after heat treatment at 973 K for 30 h (b).

R.G. Pavelko et al. / Materials Chemistry and Physics 121 (2010) 267–273 271

Table 2Crystallite and agglomeratea sizes before and after heat treatment (HT) at 973 K for 30 h.

Material XRD crystallite sizebefore HT (nm)

BET agglomeratesize before HT (nm)

XRD crystallite sizeafter HT (nm)

BET agglomeratesize after HT (nm)

Average number ofcrystallites peragglomerate before HT

Average number ofcrystallites peragglomerate after HT

SnO blank 1.5(1) 5.8(2) 2.9(1) 27(1) 3.9(2) 9.3(4)25(1) 2.6(2) 1.9(1)12(1) 3.2(2) 1.7(1)

e of the particles and SnO2 bulk density as 6.95 g cm−3.

dtrfbereu

taran1nv

matuo[aclaw

Fed

Table 3Fitting parameters of the model with size-dependent impediment according withEq. (2), and drag parameter b.

Material Temperature (K) D0 (nm) Dlim (nm) A (nm2 s−1) b (s−1)

SnO2 blank 873 2.14(3) 2.65(2) 0.52(7) 0.07(1)973 2.27(3) 2.93(2) 0.68(7) 0.08(1)

1073 2.54(4) 3.22(2) 0.76(9) 0.07(1)

SnO2-Pd 873 5.92(15) 10.23(7) 7.2(5) 0.07(1)973 7.51(19) 12.8(9) 11.1(8) 0.07(1)

1073 9.72(25) 16.0(9) 24(2) 0.09(1)

2

SnO2-Pd 2.3(1) 5.9(2) 13(1)SnO2 dep Pd 2.5(1) 8.1(3) 7.2(1)

a Agglomerate size was calculated from BET surface area assuming spherical shap

ependent impediment, Eq. (2) (lines marked with “2”). To comparehe fit results we used the residual sum of square (�2), known aseliable parameter to estimate the goodness-of-fit. In spite of theact that generalized parabolic model fits experimental data slightlyetter (e.g. at 973 K �2 equals to 0.5 × 10−3 and 2.0 × 10−3 for gen-ralized parabolic model and model with size-dependent impediment,espectively), the difference between two fittings is lower thanxperimental error and from this standpoint both models can besed for the analysis.

Fitting with generalized parabolic law results in very high crys-allite growth exponent (n) for blank material: 20.0 at 873 K, 17.3t 973 K and 18.4 at 1073 K, which is consistent with the valueseported in literature for nc-SnO2 powder compacted under uni-xial pressure of 0.5 and 1 GPa [19]. For SnO2-Pd and SnO2 dep Pdvaries from 8.6 to 11.6 and from 10.6 to 12.7 between 873 and

073 K, respectively. However, conclusion about growth mecha-ism as well as reliable apparent activation energy for such bigalues of n could not be derived within this model [10].

Table 3 lists the results of the fits with size-dependent impedi-ent model (according to Eq. (2)) and drag parameter b calculated

s ratio: A/D2lim. All obtained parameters are shown together with

heir errors, calculated as a standard deviation. The obtained val-es of b for all materials remain roughly constant and of the samerder of magnitude reported in the literature for metal systems10]. It is worthwhile to note that D0 makes up 45–60% of the over-ll crystallite growth, estimated as a difference between Dlim and

rystallite size before annealing (Table 2). This means that rapidow-temperature growth occurred for all materials between 573nd 873 K when the system was reaching the specified temperatureith the rate of 10 K min−1. Thus, measured kinetics reflects only

ig. 7. Time evolution of mean crystallite size of blank SnO2 at 873, 973 and 1073 K:xperimental data, fits with generalized parabolic model (1), and fits with size-ependent impediment model (2).

SnO2 dep Pd 873 4.27(7) 6.29(5) 2.0(2) 0.05(1)973 4.69(9) 7.10(5) 3.3(3) 0.07(1)

1073 5.96(11) 8.70(4) 6.4(5) 0.08(1)

“slow” processes for crystallites which have already undergone acertain size change (45–60%) at lower temperature.

Fig. 8 represents Arrhenius plots for the materials in question.The apparent activation energy of the crystallite growth calculatedfrom the slope of the linear fits is very low, especially for blankmaterial: 23(2) kJ mol−1. Palladium doping results in significantincrease of the activation energy, which amounts roughly to similarvalues for bulk and surface doped SnO2: 58(10) and 53(6) kJ mol−1,respectively. Unfortunately data on activation energy for nc-SnO2crystallite growth are scarce in the literature. Shek et al. [19,20],using a model based on the structural relaxation of the interfacecomponent, found an apparent activation energy of blank SnO2in the range 32–44 kJ mol−1, which is close to the values reported

here. Much more data are available in the literature for TiO2 crys-tallite growth in which activation energy values vary from 5 to230 kJ mol−1 [21].

Fig. 8. Arrhenius plot of ln(TA) vs 1000/T, where A is the growth rate constant (Eq.(2)) and T is the temperature (in K).

272 R.G. Pavelko et al. / Materials Chemistry

Table 4Integral growth rate, crystallite size exponent and apparent activation energy ofcrystallite growth.

Material Integral growth rate (nm h−1) Eact (kJ mol−1)

873 K 973 K 1073 K

SnO2 blank 0.022(1) 0.025(1) 0.026(2) 23 (2)

4

aw2Fbta(aia(tdccTPfo

ctictstsmd

ttmgievoc[L–dti[ooiS

ical Review B 42 (1990) 11914–11925.

SnO2-Pd 0.16(1) 0.20(1) 0.20(3) 58 (10)SnO2 dep Pd 0.077(1) 0.092(1) 0.10(1) 53 (6)

. Discussion

It is generally believed that material densification duringnnealing occurs through consolidation and crystallite growthithin individual agglomerates [6], which were found to consist of

–4 crystallites for our materials before heat treatment (Table 2).rom the comparison of agglomerate size and XRD crystallite sizeefore and after annealing at 973 K we can clearly distinguishhree different cases of the densification: when crystallite size afternnealing does not reach the agglomerate size before annealingi), which was observed for SnO2 blank; when crystallite size afternnealing is comparable with the agglomerate size before anneal-ng (ii), observed for SnO2 dep Pd; and finally when crystallite sizefter annealing is bigger than the agglomerate size before annealingiii), observed for SnO2-Pd. First two cases correspond apparentlyo the normal crystallite growth. The last one suggests that bulkoped material underwent abnormal crystallite growth or coales-ence – preferential fast growth of a few crystallites which leads toonsuming of the surrounding crystallites and agglomerates (seeEM images, Fig. 5). The fact that fast growth is induced by smalld quantity is in line with the results of Bonnet et al. [22], who alsoound that small addition of second phase (0.01 mol% of copperxide) drastically increases sintering of microcrystalline SnO2.

The nature of coalescence phenomenon is still unclear, espe-ially for nanomaterials. Existing models explain it as a result ofhe uneven distribution of the pinning admixtures, which resultsn remarkable difference in the mobility of free and solute draggedrystallite boundaries [23]. However, from our data it can be seenhat blank material has the smallest crystallite growth rate and iteems that doping with Pd (both surface and bulk cases) in con-rary notably promotes crystallite growth (Table 4). This is alsoupported by the fact that drag parameter b is fairly similar for allaterials (Table 3), which indicates that introduced Pd admixtures

o not take part in the crystallite boundary retardation.Majority of the theories explain crystallite growth as a result of

hermally induced diffusion of mobile species in the crystalline lat-ice [6]. In general, both oxygen and tin ions should be considered as

obile species contributing to the growth process. Activation ener-ies for oxygen self-diffusion in single-crystalline SnO2 are highern comparison with our results for blank SnO2. For example, Kampt al. [24] reported values ca. 100 kJ mol−1. On the other hand, acti-ation energy for self-diffusion of metal species, namely diffusionf interstitial ions, is known to be lower than that of oxygen in thease of TiO2 [25] (including nonstoichiometric TiO2−x [26]) and ZnO27] (data on tin self-diffusion in SnO2 are scarce in the literature).ow activation energy obtained for crystallite growth of blank SnO223(2) kJ mol−1 – corresponds best to activation energy of self-

iffusion in the metallic tin: 24.7 kJ mol−1 [28]. Considering thatin dioxide is known as highly nonstoichiometric oxide which read-ly loses surface oxygen upon temperature or low oxygen pressure1,29], it is possible that growth of the highly defective crystallites

ccurs through diffusion of tin atoms, rather than through oxygennes. Thus, we assume that tin self-diffusion on the Sn-rich surfaces the most probable process to explain low activation energy fornO2 crystallite growth during annealing.

and Physics 121 (2010) 267–273

Apart from low activation energy blank material demonstratesvery low integral rate of crystallite growth (defined as (D0 − Dlim)/t,see Table 4). In spite of this, its agglomeration degree after anneal-ing (at 973 K for 30 h) is the highest among all the materialsand amounts up to ∼9 crystallites per particle (Table 2). In con-trary, surface doped SnO2 has the lowest agglomeration, indicatingthat surface doping effectively prevents crystallites from adhesivecontact. PdO formation probably creates electrostatic repulsionbetween crystallites, while blank surfaces bind to each otherbecause of van der Waals interaction between partially reducedboundaries [6].

Table 4 summarizes activation energy values and integral ratesof crystallite growth. Bulk and surface doping of tin dioxide resultsin remarkable increase of activation energy and crystallite growthrate. Generally, activation energy for self-diffusion is considered tobe the sum of the defect formation energy and the energy requiredto move the defect (migration energy barrier) [27]. Simultaneousrise of activation energy and growth rate for doped materials sug-gests that migration energy barrier is notably lower for SnO2–PdOsystem (resulting in high growth rate) and energy required fordefect formation is much higher than that for blank SnO2 (whichexplains increase of activation energy). The latter can be explainedif we take into account that activation energy was estimated formaterials with different crystallite size D0 (as a result of differentgrowth rates during reaching of the preset temperature, see Table 3)and therefore with different structural order. So, in the case of SnO2-Pd, in which 6–10 nm crystallites have the most ordered crystallinestructure, energy for defect formation is expected to be higher thanfor other materials.

5. Conclusion

Blank material demonstrates very low apparent activationenergy for crystallite growth which allowed us to assume thatcrystallite growth occurs through self-diffusion of Sn ions on thepartially reduced surface rather than through oxygen diffusion. Thepartially reduced surface can be also a reason for the fact that blankmaterial tends to agglomerate more than surface doped one. Ingeneral, doping with Pd does not result in the solute drag effect.In contrary, it notably changes crystallite growth kinetics increas-ing both values of activation energy and growth rate. It seemsreasonable from the obtained results that low migration barriertogether with high defect formation energy is responsible for sucha behaviour. The most pronounced effect in the form of coalescenceis observed for Pd bulk doped material.

Acknowledgments

R.G.P. gratefully acknowledges a PhD scholarship from URV. Thiswork was partially supported by Presidium of Russian Academy ofScience (project 20П1) and Federal Agency for Science and Inno-vations of Russian Federation.

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oman G. Pavelko, graduated from People’s Friendship University of RussiaMoscow) in 2003, obtained his PhD in Chemistry in 2007 at the Institute of General

and Physics 121 (2010) 267–273 273

and Inorganic Chemistry (Russian Academy of Science, Moscow). At present he is aPhD student at University Rovira i Virgili (Tarragona, Spain) in the Electronic Engi-neering Department. His research interests concern synthesis of dispersed materials,material science, experimental and theoretical study of surface processes related tosemiconductor metal oxides.

Alexey A. Vasiliev graduated from Moscow Institute of Physics and Technology in1980, obtained his PhD in 1986 for the “Study of the kinetics of low-temperaturereactions of atomic fluorine by ESR method”. Gained his Dr. of Science degree (habil-itation) in solid state microelectronics in 2004 for the investigation of “Physical andchemical principles of design of gas sensors based on metal oxide semiconductorsand MIS structures with solid electrolyte layer”. Recently he is working in Sensorgroup of the University Rovira i Virgili (Tarragona, Spain) and at Russian researchcenter Kurchatov Institute (visiting position). Research interests are related withthe study of the kinetics and mechanisms of heterogeneous processes related withchemical sensing, kinetics and mechanisms of electrochemical processes in liquidand solid electrolytes.

Noelia Barrabes received MS from Chemical Engineering Department in Rovira iVirgili University in 2006. She is currently finishing her PhD degree in chemicalengineering, working in catalysis, at the Rovira i Virgili University.

Eduard Llobet, graduated in telecommunication engineering from the UniversitatPolitècnica de Catalunya (UPC) (Barcelona, Spain) in 1991, and received his PhD in1997 from the same university. He is currently an associate professor in the Elec-tronic Engineering Department at the Universitat Rovira i Virgili (Tarragona, Spain).His main areas of interest are in the design of semiconductor and carbon nanotubebased gas sensors and in the application of intelligent systems to complex odoranalysis.

Vladimir G. Sevastyanov was graduated from Mendeleyev University of Chem-

of Physical Chemistry of Sensor Materials in the N.S. Kurnakov Institute of Gen-eral and Inorganic Chemistry (Moscow, Russia). His research activity is related tosynthesis and investigation of volatile coordination compounds of wide range of ele-ments (including actinides), ultra pure chemical compounds, dispersed oxides andcarbides.