M Lalanne

P Demont
email: demont@cict.fr

A Barnabé

AC conductivity and dielectrics properties of CuFe 1-x Cr x O 2 :Mg delafossite

published or not. The documents may come

Introduction

For more than 30 years, delafossite compounds have been studied for their unusual magnetic and electrical properties [1][2][3]. More recently, delafossite compounds have attracted much attention since Kawazoe et al. [4] showed that CuAlO 2 was a good candidate for p-type transparent conducting oxides (TCO). The development of p-type TCO is one of the most crucial technologies for p-n junction-based devices such as transparent solar cells and transparent light emitting diodes. Among various materials, copper metal oxide with the molar ratio Cu/M = 1, i.e. CuMO 2 , with M = {Al, Ga, Cr, …} and with delafossite structure has been known as one of the p-type TCO materials for potential industrial applications. Several CuMO 2 thin films have been reported with different conductivities and transparencies [5][6][7][8][9].

The CuMO 2 structure can be described as a stacking, along the c axis, of edge-shared MO 6 octahedra forming MO 2 layers. These MO 2 layers are connected together with triangular metallic planes of monovalent copper. Each Cu + cation is linearly coordinated with two O 2-anions of upper and lower MO 2 layers as seen in figure 1. The oxygen layers can be stacked in different ways along the c axis, leading to two polytypes of the delafossite structure: the hexagonal 2H (space groupe P6 3 /mmc) and the rhombohedral 3R (space group R-3m) polytypes.

CuFeO 2 delafossite is a well-known p-type semiconductor. At room temperature, the highest electrical conductivity (σ RT = 2 S.cm -1 ) [1,10] among the CuMO 2 delafossite series is obtained with ptype CuFeO 2 delafossite when an off-stoichiometric CuFeO 2+δ phase is formed. This electrical conductivity can also be improved by magnesium doping up to 30 S.cm -1 for CuFe 0.98 Mg 0.02 O 2 [10,[START_REF] Nozaki | Proceedings of the ICT 2007 26th International Conference on Thermoelectrics[END_REF]. In the CuMO 2 compounds, the transport properties are mainly governed by the copper mixed valency Cu I /Cu II [START_REF] Thomas | [END_REF]13]. In CuFeO 2+δ and CuFe 1-x Mg x O 2 , this Cu I /Cu II ratio is respectively controlled by the oxygen non stoichiometry value δ according to (Cu + 1-2δ Cu 2+ 2δ )FeO 2+δ [14], and the Fe-site doping stoichiometry x according to (Cu + 1-x Cu 2+ x ) (Cr 3+ 1-x Mg 2+ x )O 2 . Moreover, CuFeO 2 can be deposited in thin film form by radio-frequency sputtering method at low temperature on conventional glass [15], and then accordingly presents a real interest for industrial applications. CuCrO 2 delafossite is also a p-type semiconductor but with a lower intrinsic electrical conductivity (σ RT = 3.5 10 -5 S.cm -1 ) [9] due to the difficulties in intercalating oxygen into the stoichiometric delafossite structure [16]. However, the electrical conductivity can be also improved up to 220 S.cm -1 with appropriate M-site doping like in CuCr 0.95 Mg 0.05 O 2 thin film [8], by the same way than CuFeO 2 .

As a result, CuFe 1-x Cr x O 2 :Mg solid solution is particularly attractive due to the potential merge of the low temperature deposition process of the p-type CuFeO 2 delafossite and the optimized p-type TCO properties of CuCrO 2 :Mg. Previously, we studied the phase stability and thermal behaviour of the CuFe 1-x Cr x O 2 (0 x 1) solid solution by thermogravimetric analysis (TGA) and high-temperature XRD under an air atmosphere up to 1000°C in order to characterize the oxygen intercalation [16]. For 0 x < 1, two oxidations were observed. A slight oxidation appears between 400 and 500°C, leading oxygen intercalation in the Cu + layers. An off-stoichiometric (Cu + 1-2δ Cu 2+ 2δ )Fe 1-x Cr x O 2+δ delafossite phase is then formed. Above 500°C, a phase transition occurs; the delafossite phase is transformed into spinel and CuO phases. For x = 1, i.e.CuCrO 2 , the delafossite phase is thermally stable in air up to 1000°C.

In this paper, the electrical properties of CuFe 1-x Cr x O 2 :Mg (0 x 1) solid solutions were studied by dielectric spectroscopy in order to observe the effect of the substitution of Fe by Cr on the M-site on the electrical conduction mechanism.

Experimental section

Polycrystalline samples of CuFe 1-x Cr x O 2 (0 x 1) doped with 3 % of Mg were prepared by a conventional solid-state reaction from stoichiometric mixtures of Cu 2 O, Fe 2 O 3 , Cr 2 O 3 and MgO commercial powders. Mg content is fixed to 3 % in order to avoid the precipitation of the secondary phases [17].The obtained mixtures were heated in a nitrogen atmosphere between 900 and 1000°C for 30 h with intermittent grindings. Then, the powders were pressed into pellets and sintered at 1050°C in neutral atmosphere for 10 h. Electrical conductivity measurements were performed by recording the complex impedance Z*(ω) and complex conductivity σ*(ω) using a Novocontrol broadband dielectric spectrometer. The measurements were done in the frequency range from 10 -2 to 10 6 Hz at room temperature and in the temperature range from -100 to 150°C. The real part, σ'(ω), of the complex conductivity was investigated. The ac output voltage was adjusted to 1.5 V. For all the samples considered in this study, the phase lag between the measured impedance and the applied ac voltage was negligible at low frequencies, so that the reported impedance at 0.01 Hz is equivalent to the dc resistance. The dc conductivity σ dc of samples was determined from the independent frequency part of σ'(ω) (low frequency plateau).

The powder samples were enclosed in a Teflon sample holder between two circular stainless steel electrodes (10 mm in diameter). The sintered samples 1.6 mm thick were placed between two circular gold platted electrodes (10 mm in diameter). To reduce contact resistance with the cell electrodes, a thin layer of gold (100 nm) was sputtered onto both sides of the pellets using a BOC Edwards scancoat six SEM sputter coater.

Results and Discussion

DC and AC conductivity

Figure 2 shows the frequency dependence of the real part, σ'(ω) of the complex electrical conductivity, for Mg-doped CuFe 1-x Cr x O 2 powders at room temperature (25°C°). At low frequencies, σ'(ω) is independent of the electric field frequency. Above a characteristic onset angular frequency ωc, the ac conductivity increases with increasing angular frequency and obeys a power law. Then, the angular frequency dependence of the total ac conductivity is well described by the following equation:

] ) ( 1 [ ) 0 ( ) ( ' n c dc n A ω ω σ ω σ ω σ + = + = ( 1
)
where σdc is the independent frequency conductivity or dc conductivity,

dc n c A σ ω - =
is a preexponential factor and n is an exponent dependent on both frequency and temperature in the range 0 <n≤ 1. This behaviour is characteristics of the charge transport in disordered materials and interpreted by Jonscher [18] as universal dynamic response (UDR). However a value of n >1 was reported in ionconducting glasses [19], ionic crystals [20][21] and underlined by Papathanassiou et al [22][23] in a new approach of the universal power law in disordered materials. The experimental σ'(ω) conductivity for CuFe 1-x Cr x O 2 powders were fitted using (1). The best fits of the conductivity spectra at room temperature for 0 ≤ x ≤ 1 are shown as solid lines in figure 2. The dc conductivity σdc, the crossover frequency ωc and the exponent n were obtained by a non-linear fitting procedure and reported in table 1. The variation of the dc conductivity with x is shown in figure 3 Cu + (3d 10 ) with increasing x are responsible of the observed n decrease through a reinforcement of the interaction between Cu + ions.

The ac conductivity is dependent of the stoichiometric parameter x as the dc conductivity and don't obey a scaling with x, i.e., no scaling law is obtained for all the CuFe 1-x Cr x O 2 delafossite when the reduced conductivity σ'(ω)/σdc is plotted against the reduced frequency ω r =a x ω where

1)] = ( )/ ( = x x ω ω [ a x
is a shit factor depending on x, i.e., all the conductivity curves at constant x don't fall onto one master curve. The shape of the frequency dependence of the ac conductivity is then dependent of x as dc conductivity and the onset frequency.

According to the revision of the universal power law dispersion of ac conductivity in disordered solids proposed by Papathanassiou [22], the ratio -LnA/n is reported as a function of x in figure 4. This ratio is near constant because the weak change in the dc conductivity value with the substitution of Fe 3+ by Cr 3+ . Such behaviour, i.e., -LnA/n independent of composition, was observed in ion-conducting glasses [19].

The effect of Cr substitution on the conduction relaxation mechanism of CuFe powder is also investigated by analyzing electrical loss modulus M" as a function of frequency and temperature. Imaginary part of modulus spectra is reported in figure 6 for x=0 to and x=1 and compared with Z" spectra. The M'' spectrum exhibits one main peak as the Z'' spectrum. It is important to note that M" maxima are at higher frequency in respect to Z'' maxima. Let τ Μ be the relaxation times obtained from modulus plot. The relatively large width and asymmetrical nature of the Z" and M'' peaks at room temperature indicate a non-Debye behaviour of the conduction relaxation process. In order to follow the effect of the substitution of Fe 3+ by Cr 3+ on relaxation times, Havriliak-Negami (HN) empirical equation was used to describe the frequency dependence of the shape of the Z" and M'' peaks as follows:

β α ωτ ] ) ( 1 [ * * ' ' ' Z s s s s i R Z i Z Z + = - = (2)
β α ωτ ] ) ( 1 [ ) ( ' ' ' * * 0 M i M M M M i M M + - - = + = ∞ ∞ (3)
where σ 0 is the pre-exponential factor , E σ is the activation energy for dc conductivity. As can be seen, only the data from -30°C to about 150°C can be well linearized in this representation with E σ = 0.43 eV and σ 0 =1905 S.cm -1 .

In the universal dynamic response (UDR) the onset frequency or the crossover frequency ω c from the dc regime at low frequencies to the dispersive regime is also the hopping frequency ω h . The frequency behaviour of ac conductivity as a power law were largely observed in many other low mobility oxides amorphous semiconductors and disordered systems and attributed to the hopping of charge carriers between sites having variable heights and separation distances. To correlate dc and ac conductivities, the temperature dependence of the hopping frequency ω h is compared with the corresponding dc conductivity behaviour in figure 8. As expected the crossover frequency is also thermally activated and ω h obeys an Arrhenius equation:

) exp( 0 T k E B h h h c - = ≡ ω ω ω (5)
with an activation energy value E h = 0.36 eV close to the value of E σ . The value of the corresponding characteristic hopping attempt frequency ω h0 = 10 13 s -1 is close to the lattice phonon frequency like the inverse preexponential factor 1/τ 0Z,M . It is well known that, in most conductive materials, σ dc and ω h satisfy the Barton-Nakajima-Namikawa (BNN) relation [24][START_REF] Nakajima | Conf. on Electrical Insulation and Dielectric Phenomena[END_REF][START_REF] Namikawa | [END_REF], i.e.,

c dc p ω ε ε σ ∆ = 0 (6)
where p is a constant of order 1, ∆ε is the dielectric strength and ε o is the permittivity of free space. σ dc and ω h are thermally activated with nearly the same activation energy. The inset in figure 5 shows the log σ dc versus log ω h for x= 0.5. The solid line is the least-squares straight-line fit and gives a slope of

) T k E exp( B M , aZ M , Z 0 * M , z τ τ = (7)
where E a is the activation energy and τ 0 is the high-temperature limit of the relaxation time. The best fit to (7) gives E aZ =0.35 eV and E aM =0.39 eV which corresponds to the value of dc conduction activation energy E σ . This result indicates that charge carrier has to overcome the same energy barrier while conducting as well as relaxing. The mechanism of electrical conduction is the same as that of dielectric relaxation in CuFe 1-x Cr x O 2 powder. As expected from the observed dc conductivity temperature behaviour, ω c and τ * Z are independent of the temperature below -40°C.

In hopping transport, we can use the relationship between the dc conductivity σ dc and the hopping frequency ω h [22],

h B h c dc T k r e N ω π σ ) 12 ( 2 2 = ( 8
)
where r h is the hopping distance (i.e., the Cu-Cu distance a [16]) and N c is the number density of effective charge carrier. Using (8), N c can be evaluated at room temperature and compared to the number density of Cu sites in CuFe To complete the temperature behaviour of ac conductivity, the temperature dependence of the frequency exponent n for x= 0.835 is shown in the figure 9. The value of n calculated from (1) in figure 10 is decreasing with increasing temperature from -30 to 50°C and is increasing above 80°C.

The temperature dependence of n, at low temperature up to -10°C, is weak compared with the variation above 0°C. This behaviour suggests that relaxation processes and conduction mechanism at low temperature are linked to tunnelling of charge carriers. This result is in agreement with the weak activation energy measured below -40°C using the temperature dependence of dc conductivity; impedance and loss modulus (see figures 8 and9).

According to Dyre et al [START_REF] Mott | Electronic Processes in Non-crystalline Materials[END_REF] presentation of a review on ac hopping conduction, the temperature dependence of the parameter n was explained on the basis of the many body interaction models. At low temperatures the interaction between the neighbouring charge carriers is almost negligible. As the temperature increases, the interaction increases, leading to a decrease in n. The universal power law dependence of ac conductivity on the frequency corresponds to the short range hopping of charge carriers between the sites separated by energy barriers of varied heights. If hopping takes place between a random distribution of localized charge states, then lies between 0.5 and 1 as observed in CuFe 1-x Cr x O 2 delafossite. The lower value of n occurs for multiple hops while the higher value occurs for single hops. Theoretical models have been proposed to correlate the conduction mechanism of ac conductivity with n(T) behaviour. If n increases with temperature, a small polaron is the predominant mechanism, while the correlated barrier hopping (CBH) is characterized by a decrease of n with temperature [START_REF] Dyre | [END_REF]. Benko et al [2] assumed conduction mechanism by hopping of small polarons localized on the Cu sites in Mg-doped CuFeO 2 . Substituting Mg 2+ for Fe 3+ by Mg doping results in the mixed valence Cu + /Cu 2+ and contributes a hole. The calculated carrier mobility is very low and insufficient to measure the Seebeck coefficient in sample powders and to display some precise information about the nature of the involved charge carrier in the conduction of the CuFe 1-x Cr x O 2 delafossite.

According to Papathanassiou [22] the ratio (LnA/n), in disordered solids, is independent of the temperature. The ratio -LnA/n is reported as a function of temperature in the inset of figure 4. The variation of (-LnA/n) in delafossite (x=0.835) is less than 2 orders of magnitude in the investigated temperature range. This behaviour is in agreement with those observed in other experimental data from ionic conducting glasses or disordered semiconductors and compiled by Papathanassiou [22].

From literature, the conduction mechanism in CuCrO 2 [8,[29][30] or CuFeO 2 delafossites at low temperature (T<25°C) is a hopping of holes between the nearest neighbour Cu sites in Cu layers and a crossover from thermal activation behaviour to that of 3D VRH occurs at a very low temperature. As shown in figures 8 and 9, a such VRH behaviour of σ dc in T 0.25 is not observed because σ dc ,τ * Z and ω c are independent of the temperature below -40°C. Hence the charge carrier transport occurs via tunnelling from Cu atom to another at low temperature.

Conclusion

The electrical conductivity and dielectric behaviour of Mg-doped CuFe 1-x Cr x O 2 delafossite powders has been studied by dielectric spectrometry. At room temperature, the conductivity behaviour is frequency and composition dependent and obeys a power law, above the onset frequency ω c . In In delafossite, the ratio LnA/n extracted from the power law dispersion of the ac conductivity was found poorly dependent of composition and temperature. Tables Table 1: Dc conductivityσ dc , characteristic onset frequency ω c and exponent n, using (1), for different CuFe 1-x Cr x O 2 delafossite powders at room temperature.

Figures Captions

  . As expected the conductivity increases weakly with x, only one decade in magnitude, because the progressive substitution of Fe 3+ by Cr 3+ reduces the distance Cu + -Cu + in CuFe 1-x Cr x O 2 . The inset in figure3shows the variation of the power law exponent n with x. The exponent n decreases from 0.92 for CuFeO 2 (x=0) to 0.65 for CuCrO 2 (x=1) and a sharp decrease is observed above x=0.5. This behaviour can be compared with the decrease of particles sizes of CuFe 1-x Cr x O 2 solid solution with increasing x[16]. The substitution of Fe 3+ by Cr 3+ leaded to contraction of unit cell, and reduction of lattice parameter a. The lower value of n above x= 0.5 indicates that the dispersion of ac conductivity with frequency is reduced with the introduction of large amount of Cr at Fe site. This behaviour may be correlated with the change in the distance and barrier height of the sites available for charge carriers for electrical conduction. The decrease of the lattice parameter a in the plane of the Cu atoms and the increased overlap between

  1-x Cr x O 2 powder were also investigated by the complex impedance Z*(ω) and complex dielectric modulus M*(ω) as the function of angular frequency and temperature. Electrical modulus formalism was used in conductive materials to distinguish a frequency domain within the charge transport is long range and above which is localized since it emphasizes bulk properties compared with the interfacial polarization. The frequency dependence of the imaginary part' of Z*(ω), Z'' (ω) is shown in figure5for CuFeO 2 (x=0) to and CuCrO 2 (x=1) and compared with the σ'(ω) behaviour. The relaxation conduction of charge carriers is represented by well-defined loss peaks in Z''(ω) and no such corresponding peak in the imaginary part of the complex dielectric permittivity ε''(ω) occurs. The maximum of the Z" spectrum, occurring in the high frequency range part of the experimental frequency range [10 -2 -10 6 Hz], is associated to the contribution of the bulk property of the material. Let τ Z be the relaxation times obtained from impedance plot. The absence of a ε'' loss peak together with the equivalence ω c signify long range charge carriers diffusion. The conduction relaxation mechanism in CuFe 1-x Cr x O 2

1 , 7 .

 17 figure7. As expected for semiconductor behaviour, σ dc increases with increasing temperature. Figure8

1 .

 1 16 close to unity in good agreement with the BNN relation σ dc ~ωh . It can be conclude that dc and ac conductions are correlated with each other in CuFe 1-x Cr x O 2 delafossite and that they are governed by the same transport mechanism, namely thermally activated nearest neighbour hopping. At the lower temperature range, below -40°C, the dc conductivity is independent of the temperature. The thermally activated behaviour for conduction in the temperature range [-30, 150°C] is confirmed by analyzing the temperature dependence of τ * Z and τ * M . It is clear that the relaxation times predicted by each empirical equations show an activated behaviour, i.e., obey the Arrhenius equation:

CuFe 1 -

 1 x Cr x O 2 delafossite no scaling of ac conductivity has been observed at room temperature at different x. The Cu+-Cu+ distance has a great influence on electrical properties of CuFe 1-x Cr x O 2 delafossite. The dc conductivity σ dc increases with increasing x and decreasing Cu-Cu distance. The behaviour of the exponent n in the power law shows also a decrease when x increases from 0 to 1. The dc and ac conductivities are driven by the same mechanism, as the BNN relation is found to be valid. The same temperature behaviour is observed for the dc conductivity and the onset frequency: the activation energy is the same for both ac and dc conduction, confirming the BNN relation. The dielectric behaviour of CuFe 1-x Cr x O 2 delafossite powders has been analyzed in the framework of complex impedance and complex dielectric modulus. The characteristic relaxation times τ * Z and τ * M extracted from impedance and modulus losses Z''(ω) and M''(ω), using a Havriliak-Negami empirical equation, are decreasing monotonous functions of x in agreement with the x dependence of dc conductivity. The observed dielectric behaviour is characteristic of a conduction relaxation of charge carriers. Above -40°C, the characteristic relaxation times τ * Z is thermally activated and the activation energy is close to the value obtained from dc conductivity for x=0.835. The relaxation conduction and dc conduction are governed by charge carriers hopping from Cu site to another. At low temperature, the charge transport occurs via tunnelling.

Figure 1 :Figure 2 :

 12 Figure 1 : CuMO 2 delafossite structure Figure 2: Angular frequency dependence of the real part σ'of the complex conductivity at room

Figure 3 :

 3 Figure 3: x dependence of: (µ) dc conductivity; (ξ) characteristic relaxation time τ * Z from impedance plot ;(7) characteristic relaxation time τ * M from dielectric modulus plot; (-) reciprocal characteristic onset frequency ω c -1.

Figure 4 :

 4 Figure 4: Composition dependence of the ratio (-LnA/n) in CuFe 1-x Cr x O 2 delafossite at room temperature.

Figure 5 :

 5 Figure 5: Angular frequency dependence of: the real part σ' of the complex conductivity for: (,) x=0;

Figure 6 :

 6 Figure 6: Angular frequency dependence of: the imaginary part Z'' S of the complex impedance for: (-)

Figure 7 :

 7 Figure 7: Angular frequency dependence of the real part σ'of the complex conductivity at different temperatures between -100 and 150°C: ( !) -100°C; (-) -60°C; (7) -20°C; (Χ) 40°C; (Λ) 80°C;

Figure 8 :

 8 Figure 8: Dc conductivity σ dc (Λ) and characteristic onset frequency ω c (-) as function of reciprocal

Figure 9 :

 9 Figure 9: Characteristic onset frequency ω c (-) and characteristic relaxation time τ * Z (ξ) as function of

Figure 10 :

 10 Figure 10: Variation of the exponent n with temperature for x=0.835. The inset shows the temperature

Figure 2 Figure 10 (

 210 Figure 2 (figure2.TIF)

Table 2 :

 2 Number density of Cu sites N Cu , Cu-Cu distance (a-axis lattice parameter), number density of effective charge carrier density N c using (8) and charge carrier mobility µ using(9) for different powders at room temperature.

			σ dc (S.cm -1 )	ω c (s -1 )	n
	CuFeO 2 :Mg		9.3×10 -8		2.3×10 5	0,92
	CuFe 0,835 Cr 0,165 O 2 :Mg	7.2×10 -8		1.8×10 5	0,97
	CuFe 0,667 Cr 0,333 O 2 :Mg	2.3×10 -7		3.5×10 5	0,89
	CuFe 0,5 Cr 0,5 O 2 :Mg		5.6×10 -7		4.8×10 5	0,70
	CuFe 0,333 Cr 0,667 O 2 :Mg	4.0×10 -7		2.8×10 5	0,66
	CuFe 0,165 Cr 0,835 O 2 :Mg	5.1×10 -7		4.0×10 5	0,65
	CuCrO 2 :Mg		1.4×10 -6		8.4×10 5	0,64
	Table 1
		N Cu (m -3 )	a (Å) [15]	N C (m -3 )	µ (m -2 .V -1 .S -1 )
	CuFeO 2 :Mg	2.19×10 28	3,0344	2.19×10 27	2.2×10 -14
	CuFe 0,835 Cr 0,165 O 2 : Mg	2.21×10 28	3,0268	2.21×10 27	1.7×10 -14
	CuFe 0,667 Cr 0,333 O 2 : Mg	2.22×10 28	3,0159	2.22×10 27	3.3×10 -14
	CuFe 0,5 Cr 0,5 O 2 :Mg	2.24×10 28	3,0055	2.24×10 27	4.5×10 -14
	CuFe 0,333 Cr 0,667 O 2 : Mg	2.26×10 28	2,9942	2.26×10 27	2.6×10 -14
	CuFe 0,165 Cr 0,835 O 2 : Mg	2.28×10 28	2,9826	2.28×10 27	3.7×10 -14
	CuCrO 2 :Mg	2.29×10 28	2,9742	2.29×10 28	7.7×10 -14

Table 2

 2


V Colombo

E Ghedini

P Sanibondi
email: paolo.sanibondi@unibo.it

A three-dimensional investigation of the effects of excitation frequency and sheath gas mixing in an atmospheric-pressure inductively-coupled plasma system

Keywords: numbers: 52, 75, Hn Plasma torches -52, 65, -y Plasma simulation -52, 80, Pi Highfrequency and RF discharges

A three-dimensional investigation of the effects of excitation frequency and sheath gas mixing in an atmospheric-pressure inductively coupled plasma system V Colombo, E Ghedini, P Sanibondi

Introduction

Inductively coupled plasma torches are widely used as high-temperature, high-purity sources in numerous applications such as powder spheroidization, synthesis of nano-powders and deposition of protective coatings. The success of a given process depends directly on the plasma temperature and velocity fields in the discharge, which in turn depend on the geometric and operating parameters of the system; for example mass flow rate of different gases, Joule power coupled to the plasma, coil current frequency, gas composition, pressure; thus, characterization of the plasma thermo-fluid-dynamic fields and knowledge of the influence of such parameters on plasma properties is of primary importance [1].

Since relevant progress has recently been made in computer capability which allows for the implementation of more and more sophisticated approaches [2,3,4,5,6], numerical modeling represents a valid and powerful tool to predict the characteristic behavior of plasma sources.

Increasing attention is given to three-dimensional effects in temperature and velocity fields which arise taking into account realistic three-dimensional geometries: e.g. the effects of the real coil shape [3,7,8,9,10], the detailed inlet gas region of the torch [11] and the transverse injection of cold jets [12,13,[START_REF] St | Proceedings of 17th International Symposium on Plasma Chemistry (ISPC 17)[END_REF] have already been studied. Moreover, the effect of changing fluid-dynamic and electromagnetic operating conditions in 3D geometries has been reported in [START_REF] Bernardi | [END_REF].

The scope of this study is to investigate by means of a fully three-dimensional code the influence of different coil current frequencies on thermo-fluid-dynamic fields, the hydrogen mixing in an argon primary gas and the flow patterns and temperature distributions which take place in a reaction chamber with a lateral gas outlet system and two observation windows suitable for diagnostics.

The induction torch chosen for this study is one of the most common commercial models: a Tekna Plasma Systems Inc. model PL- 35.

A previous work by some of the authors [16] has shown that torch configurations with high-frequency and high turn coil density can result in almost axisymmetric plasma discharges inside the torch. Thus, the first goal of this paper is to give deeper insights about the influence of frequency alone on the three-dimensional shape of temperature, velocity and composition fields inside the torch.

This study is in line with the fact that the same torch can be operated with different coil current frequencies, depending on the configuration of the RF generator connected thereto, and that typical values for this parameter in a Tekna PL-35 torch are 3 MHz and 13.56 MHz. We concentrated on these values for coil current frequency since they are commonly used in many systems for both research and production purposes and they are dedicated by law to industrial applications in many countries.

The second goal and third goals of this work arise from the fact that different gas mixtures (inert, oxidant, reducing) can be injected in the torch [17,18] and that in powder processing applications the induction torch is usually used in connection with a reaction chamber in order to obtain conditions for pressure and gas composition suitable for the purpose of treating and processing injected raw materials.

In powder spheroidization, waste treatment and nano-powder production an argonhydrogen mixture is usually used [19,20] since the higher specific heat and the higher thermal conductivity of hydrogen results in a higher plasma enthalpy and in a higher heat flux to the particles. Argon-hydrogen is usually injected as sheath gas and hydrogen has small mole fractions (less than 10%) to preserve the quartz tube from overheating. The second goal is thus to accurately investigate the diffusion of hydrogen from the sheath gas, since powder treatment processes are very sensitive to hydrogen content in the core of the discharge.

The diffusion of gases in induction torches has been studied in many papers with different approaches, including combined diffusion [5] and chemical non-equilibrium [21]. Some works by Tanaka [22,23], Watanabe et al [24,25,26] and other authors [4,[START_REF] Xue | Proc. 17th International Symposium on Plasma Chemistry[END_REF] implemented the second approach, obtaining accurate prediction of species distribution in the torch: as a drawback, in those papers, demixing due to mole fraction and temperature gradients has not been investigated. On the contrary, a combined diffusion approach has been used by Chen [START_REF] Chen | [END_REF], but the effects of demixing have not been discussed in detail, although results for the mass fraction of hydrogen shows that it occurs in the near-wall region.

In this paper we considered diffusion of hydrogen from the secondary gas with a combined diffusion approach in a three-dimensional framework, including investigation of different relevant demixing mechanisms (mole fraction and temperature gradients).

The third goal of this paper is to predict flow patterns inside a non-axisymmetric reaction chamber with a lateral outlet gas system and investigate the influence of advection on temperature distribution in the tail of the plasma discharge. This type of investigation is of interest for nano-powder synthesis applications, where main processes (particle nucleation and growth) take place in the low temperature (over-saturated) zone located in the downstream region of the torch [18,29].

Inductively coulpled plasma torches have been investigated also using thermal nonequilibrium approaches [START_REF] Xue | Proc. 16th International Symposium on Plasma Chemistry[END_REF]25,23]: these studies have shown that for pressure higher that 0.5 bar NLTE conditions exists only in the discharge fringes (near cold gas injection regions and torch walls) where high temperature gradients exist. Moreover, for argonhydrogen mixtures Ye et al [START_REF] Ye | [END_REF] showed that NLTE effects are much less pronounced that in the case of pure argon, as a result of higher electron-heavy particle cross section for hydrogen species than for argon species. Consequently, in this paper, since an atmospheric pressure argon-hydrogen plasma has been considered, a LTE approach has been chosen.

Modeling approach

The following hypothesis are assumed in the present calculations:

(i) Plasma is in local thermodynamic equilibrium (LTE);

(ii) Combined diffusion approach of Murphy is used to model the diffusion in a mixture of two non-reactive gases;

(iii) Turbulent effects are taken in account through RNG kmodel;

(iv) Plasma is optically thin and radiative losses are taken in account considering only the presence of argon in the mixture;

(v) Composition is computed taking in account six species: Ar, Ar + , H 2 , H, H + and electrons;

(vi) Viscous dissipation term in the energy equation is neglected;

(vii) Displacement currents are neglected.

Governing equations

The physical behavior of the plasma has been modeled removing any axisymmetric assumption and a fully 3D model has been implemented in the FLUENT c environment.

The governing equations can be written as

∇ • (ρv) = 0 (1) ∇ • (ρvv) = -∇p + ∇ • τ + ρg + F L (2) ∇ • (ρvh) = -∇ • k ef f c p ∇h + ∇ • i h i J i + k c p ∇Y i + P J -Q r ( 3
)
where ρ is the plasma density, v is the velocity, p is the pressure, τ is the stress tensor, g is the gravitational force, h is the total enthalpy, k ef f is the effective thermal conductivity, c p is the specific heat at constant pressure and Q r is the volumetric radiative loss; Y i and J i are the mass fraction and the diffusion current of the i-th gas. The Lorentz forces F L and Joule dissipation P J can be written as

F L = 1 2 (J × B * ) ( 4
)
P J = 1 2 (J • E * ) ( 5
)
where J is the complex phasor for the current density induced in the plasma, B is the magnetic induction complex phasor, E is the electric field complex phasor. The superscript "*" indicates the complex conjugate. Using the commercial software FLUENT c to solve fluid equations, the Lorentz forces, ohmic heating, radiative loss terms and energy sources due to diffusion must be taken into account by using suitable User-Defined Functions written in C language. Diffusion of gases can be described using the combined approach of Murphy [5,6], assuming local chemical equilibrium. This method allows to treat diffusion of gases containing a large number of species (six species in our case) solving only (N-1) equations, where N is the number of gases in the mixture (N=2 in our simulations), leading to a great reduction in computational time. Moreover, this method can be considered as accurate as a fully multi-component diffusion approach provided that local chemical equilibrium has been reached; as shown by Rini et al [32] for air plasmas, this conditions is verified in ICP torches for pressure greater that 0.3 bar. The FLUENT c software provides modules for the solution of diffusion equations with the following form:

∇ • ρvY i + ∇ • J i = 0 (6)
where diffusion currents J i can be written as

J i = - µ t Sc + ρD Y i ∇Y i -D T i ∇ ln T ( 7
)
where Y i , D Y i and D T i are mass fraction, the mass fraction diffusion coefficient and the temperature diffusion coefficient for the i-th gas, respectively; µ t is the turbulent viscosity and Sc is the Schmidt number taken equal to 0.7.

Using the same symbols introduced by Murphy [6] and taking ∇x i = ∂x i /∂Y i ∇Y i + (∂x i /∂T ) ∇T , the combined diffusion equations given by Murphy for a binary mixture composed by the gases i and j can be solved in the FLUENT c environment setting

D Y i = n 2 ρ 2 m i m j D x ij ∂x i ∂Y i ( 8
)
D T i = D T ij + n 2 ρ m i m j D x ij T ∂x i ∂T (9)
where D x ij and D T ij are the combined diffusion coefficients due to mole fraction gradients and due to temperature gradients, respectively. It should be noted that temperature diffusion coefficient D T i includes some of the effects of diffusion due to mole fraction gradients (the second term in equation 9) and those of diffusion due to temperature gradients (D T ij ). Diffusion due to pressure gradients and electric fields have been reasonably neglected.

Turbulent effects in the downstream region of the discharge have been included in the flow calculations using the RNG kmodel:

∇ • (ρkv) = ∇ • (α k µ ef f ∇k) + G k + G b -ρ (10) ∇ • (ρ v) = ∇ • (α µ ef f ∇ ) + C 1 k (G k + C 3 G b ) -C 2 ρ 2 k -R (11)
where G k and G b represents the generation of turbulence kinetic energy due to the mean velocity gradients and buoyancy, respectively; the quantities α k and α are the inverse effective Prandtl numbers for k and , respectively; C 1 , C 2 and C 3 are constants with values 1.42, 1.68 and 0.09, respectively. The turbulent viscosity, the inverse effective Prandtl numbers, the turbulent thermal conductivity, the turbulent diffusion coefficients and the source term R are computed from the RNG theory as described in [START_REF]FLUENT 6.3 User's Guide 2006[END_REF].

Turbulent wall function has been chosen according to mesh size near the chamber and torch walls: since in this region the grid is sufficiently fine (cell characteristic length less than 0.2 mm), the viscosity-affected near-wall sub-layer could be fully resolved and the transition to turbulent regions could be modeled using an enhanced wall treatment, which include the traditional two-layer zonal model [START_REF]FLUENT 6.3 User's Guide 2006[END_REF].

The electromagnetic field generated by the current flowing in the coil (J coil ) and by the induced currents in the plasma (J ) can be described by means of Maxwells equations written in their vector potential formulation:

∇ 2 A -iωµ 0 σA + µ 0 J coil = 0 ( 12
)
where µ 0 is the magnetic permeability of the free space (4π10 -7 H/m), σ is the plasma electrical conductivity, and ω = 2πf , f being the frequency of the electromagnetic field. The electric field complex phasor E and the magnetic field complex phasor B are obtained from the vector potential complex phasor A with the following expressions:

E = -iωA, B = ∇ × A.
In this work, we have used the simplified Ohm's law J = σE.

Computational domain and boundary conditions

The domain considered in the calculations includes a PL-35 torch and a nonaxysimmetric reaction chamber with two observation windows (OW1 and OW2) and a lateral gas outlet tube. A schematic of the computational domain is reported in figure 1. The origin of z-axis is located at the top of the torch. Gas is supplied to the torch through three inlets: carrier gas from the axially movable probe tip, primary gas from the inlet between the probe and the quartz tube and sheath gas from the inlet between the quartz and ceramic tubes; mass flow rates are 2.5 slpm of Ar, 15 slpm of Ar and 60 slpm of Ar + 4.5 slpm of H 2 for carrier gas, central gas and sheath gas, respectively. A no-slip boundary condition is assumed on internal walls.

In order to reduce the total number of cells in the computation grid, the inlet regions of the primary and secondary gas (8 separate injection points for the tangential injection of the primary gas and 18 points for the axial injection of the secondary gas) have been idealized with two annular inlets with uniform gas injection, since it has been shown that results are only slightly sensible to this simplification [11].

The equation of energy has been solved including in the domain the solid regions inside the quartz and ceramic tubes, whereas the EM field has been computed using the extended field approach [START_REF] Bernardi | [END_REF], thus solving the EM equations in a cylindrical domain around the torch (150 mm diameter, 113 mm height) with vanishing vector potential on its surface. A fixed temperature (300 K) has been imposed at the internal walls of the chamber and at the external walls of the torch. The torch and the reaction chamber operate at atmospheric pressure.

Plasma properties

Plasma thermodynamic and transport properties have been computed using 4th order Chapman-Enskog method, including Ar, Ar + , H 2 , H, H + and electrons in the computation of composition [35]. Combined diffusion coefficients have been computed following Murphy [6]. In order to carry out the computation of equilibrium composition, data for partition function calculations have been obtained from JANAF tables [START_REF] Chase | JANAF Thermochemical Tables 3rd[END_REF] and NIST database [START_REF] Ralchenko | NIST Atomic Spectra Database (version 3.1.5)[END_REF]. Each iteration, plasma properties have been updated on the basis of the local temperature and local mass fraction of hydrogen in the mixture.

Radiation losses have been taken in account using data reported by Beulens et al [START_REF] Beulens | [END_REF] for atmospheric pressure plasmas. Radiation losses due to the presence of hydrogen have been neglected because, to the knowledge of the authors, no reliable radiation power data are available for argon-hydrogen mixtures and radiative emission due to hydrogen is substantially lower than that of argon [39]; moreover, in these simulations, hydrogen contribution to radiation can be reasonably neglected owing to small mass fraction of this gas (maximum Y H = 0.0045).

Results and discussion

Computations have been carried out for a plasma source operating at 3 MHz (case C1) and for the same system with coil current frequency set to 13.56 MHz (case C2). In both cases, the current intensity has been adjusted to make the total Joule power dissipated in the plasma discharge equal to 15 kW: in case C1 the current is 210 A whereas in case C2, as a result of the higher frequency, its value must be set at 117 A.

Three-dimensional effects on temperature and velocity fields inside the torch

In figure 2 the temperature field on two orthogonal planes passing through the axis of the torch for case C1 and C2 is reported. The maximum temperature for case C1 (11713 K) is located approximately at the same axial position of the probe tip (z = 60 mm), whereas for case C2 the maximum temperature (11606 K) is reached at z = 49 mm; in both cases, owing to the shielding effect of the induced currents, the maximum temperature is located at an off-axis position (r = 9 mm and r = 10 mm for case C1 and C2, respectively). As shown in the x-y cross sections reported in figures 2-c and 2-f, at the torch outlet the distribution of temperature is strongly deviated in the positive y-direction for the case at 3 MHz, whereas it is almost axisymmetric for the case with 13.56 MHz. As can be seen from temperature distributions reported on the cross sections at 58 mm and 85 mm, the non-axisymmentry for the case C1 is lower in the mid-coil region of the torch than at the outlet, whereas for case C2 it is more pronounced at z = 58 mm.

Logarithmic contours of Joule dissipation and Lorentz forces for case C1 and C2 are reported in figures 3 and 4, respectively; according to previous works on simulation of ICP torches with various frequencies imposed to the coil current [START_REF] Bernardi | [END_REF]40,41], the Joule dissipation inside the torch for case C1 is concentrated in a larger region than for case C2, as a result of a bigger skin depth. A similar distribution is obtained for Lorentz forces (figures 3-c, 3-d, 4-c and 4-d), because both Joule dissipation and Lorentz forces arise in the regions characterized by higher plasma conductivity.

Temperature and Joule power distributions along the x and y axis for case C1 and C2 at z = 85 mm are reported in figure 5. A non-axisymmetry is present for the temperature distribution along the y-axis for the case at 3 MHz (C1), whereas for the case C2 the temperature profiles along x-axis and y-axis are similar and almost axisymmetric. For the case at 3 MHz the Joule power has a peak at r = 0.01 m and high values (order of magnitude = 10 8 W/m 3 ) are present also inside the hot region of the discharge, whereas for the case at 13.56 MHz the peaks are located at r = 0.013 m but with a strong decrease of Joule power in the central portion of the torch and negligible values for r < 0.005 m. A strong non-axisymmetry in Joule power distribution is present for both cases along the y-axis; for case C2 it is located at radial coordinate greater than 0.01 m, whereas for the case at 3 MHz the non-axisymmetry is pronounced also inside the discharge.

Since non-axisymmetries in temperature and Joule distributions are mainly located along the y-axis direction, in figure 6 a detail of the Lorentz force field along y-axis at different z-axis position for case C1 and C2 are reported: the higher value of the skin depth in case C1 leads to a larger region with high values (order of magnitude = 10 4 N/m 3 ) of Lorentz forces (0.005 < r < 0.015 m for case C1, 0.009 < r < 0.015 for case C2).

Since Joule power distribution, Lorentz forces and temperature field are coupled by means of the electrical conductivity field, it is difficult to state whether the non-axisymmetric distribution of the temperature field is the effect or the cause for other non-axisymmetries. However, the only source of non-axisymmetry in the torch is the helicoidal shape of the induction coil; a previous work by some of the authors [7] has shown that non-axisymmetric temperature distribution inside the inductively coupled plasma torch results a consequence of the unbalanced Lorentz forces due to the first and the last coil turns, which pull the discharge in opposite y-directions leading to a 'torque' on the discharge. In this work, lower maximum absolute values of Lorentz forces have been obtained for the case with higher coil current frequency. As a consequence, it can be argued that a lower torque is applied to the discharge and that fluid-dynamic inertia prevails over Lorentz forces resulting in an almost axisymmetric discharge.

In figure 7 a detailed view of velocity magnitude field inside the torch is reported for both case C1 and C2. The velocity magnitude field for case C1 is strongly deviated towards the positive y-direction as a result of the non-axisymmetric viscosity and density fields, which in turn depend on mass fraction and temperature fields. On the contrary, the velocity magnitude field is almost axisymmetric for the case C2. In figure 8 different components of the plasma velocity inside the torch are shown: in case C1 the nonaxisymmetric Joule power dissipation, Lorentz forces and temperature fields induce an increase in the y-component of the plasma velocity below the probe tip, whereas the y-component of the velocity for case C2 and the x-component for both cases are almost axisymmetric.

Temperature and velocity fields in the reaction chamber

Figure 9 reports the temperature fields in the reaction chamber on two orthogonal planes passing through the axis of the torch, for case C1 and C2. Temperature in the downstream region of the torch for case C1 is generally lower than for case C2; in fact, the iso-surfaces at 2640 K extend up to 110 mm and 188 mm below the torch exit for the first and second case, respectively. This can be attributed to the lower power dissipated through radiation inside the torch: the larger region at high temperature in case C1 leads to a higher radiative dissipation (7.2 kW) with respect to case C2 (5.4 kW) and to a lower enthalpy flux entering the reaction chamber (6.9 kW for case C1 and 8.2 kW for case C2).

In the region below the torch outlet, for both case C1 and C2, the temperature field is markedly non-axisymmetric. Since in the chamber there is no heating power, a non-axisymmetric temperature distribution can be determined by advection and conduction only: as far as in both cases conduction losses are determined by the same chamber geometry, different directions of the plasma tail temperature distribution can be attributed mainly to different recirculation flow patterns in the chamber.

In figure 10 different flow patterns in the reaction chamber are reported for C1 and C2. In case C1 the flow exiting the torch is deviated towards both the observation window OW1 and the outlet tube of the chamber, as can be seen from the pathlines released from the plasma gas inlet shown in figures 10-a and 10-b; the temperature isosurfaces in the reaction chamber for case C1 (figure 9-a and 9-b) are similarly deviated. In case C2 both the flow pattern and the temperature iso-surfaces are deviated in the direction of observation windows OW1 and OW2 (figures 9-c, 9-d, 10-a and 10-b).

In the reaction chamber the energy transport by conduction is enhanced by turbulent diffusion. A direct correlation exist between turbulent thermal conductivity and turbulent viscosity. In figure 11 the turbulent viscosity ratio fields in the reaction chamber for case C1 and C2 are reported. This parameter is defined as the ratio between turbulent and molecular viscosities and can be considered as an index of turbulence intensity. Below the torch outlet the turbulent viscosity ratio reaches high values (greater than 50) as a consequence of recirculation flows, for both case C1 and C2.

Mass fraction fields and demixing effects

Three-dimensional effects in the temperature field lead to non-axisymmetric mass fraction fields as shown in figure 12 and 13 for case C1 and C2, respectively. Hydrogen mass fraction profile along y-axis at z = 95 mm is reported in figure 14.

As can be seen from these pictures, for both case C1 and C2 a strong accumulation of hydrogen can be evidenced near the torch wall (figure 12-e); however, for case C1 the region with higher mass fraction of hydrogen (Y H > 0.003) is larger for negative yaxis positions than for positive ones (figures 12-c and 14); in case C2 the accumulation is even stronger than in case C1 (see figure 14) but the region with higher values of mass fraction is more axisymmetric (figure 13-e); on the contrary, in case C2 a nonaxysimmetric distribution has been obtained for the region with lower values of the hydrogen mass fraction (Y H < 0.003), as can be seen in figures 13-c, 13-e and 14. In the reaction chamber three-dimensional composition fields arise near the top wall and in the observation window OW2 (figures 12-a, 12-b, 13-a and 13-b).

Hydrogen injected from the secondary gas inlet moves towards the central region of the torch according to three mechanisms: diffusion due to mass fraction gradients, turbulent diffusion and thermal diffusion. The latter, as shown in figure 15, generally entails the diffusion of argon towards lower temperature regions; however, on the contrary, for a temperature range between 2000 K and 5000 K, the temperature diffusion coefficient for argon D T i is negative, as a result of hydrogen dissociation, and the argon is pushed towards higher temperature regions. In this range of temperature, it is known that negative values of the temperature derivative of the argon mole fraction exist for argon-hydrogen mixtures [42], leading to negative values of the temperature diffusion coefficient for argon (see equation 9). In figure 16 different contribution to temperature diffusion coefficient have been reported for the temperature range 300 K -12000 K: thermal diffusion contribution due to temperature gradients (D T ij ) is always positive whereas the one due to mole fraction gradients (the second term in equation 9) is generally null with exception of dissociation and ionization temperature ranges where it assumes negative and positive values, respectively. Temperature diffusion coefficient is responsible for the effect of demixing.

As can be seen in figures 12-a, 12-b, 13-a and 12-b, at the outlet of the quartz tube, hydrogen diffuses towards the central region of the plasma discharge mainly as a result of mass fraction and temperature gradients, since turbulence in this region is negligible (see figure 11); since there are strong temperature gradients near the internal wall of the torch, thermal diffusion acts mainly as an obstacle to the diffusion of hydrogen towards the central region.

Negative values of argon temperature diffusion coefficient around 3300 K and positive values for lower temperature result in an accumulation of hydrogen in the temperature region where the coefficient is null (T = 2000 K). In fact, hydrogen mass fraction has its maximum value (Y H = 0.0045) in the fringes of the discharge and this is greater than the mass fraction of hydrogen in the inlet sheath gas (Y H at inlet = 0.00374).

In figure 14 hydrogen mass fraction and argon temperature diffusion coefficient along the y-axis at z = 85 mm have been reported: peaks in hydrogen mass fraction are strongly correlated with negative peaks in argon temperature diffusion coefficients and they are located where temperature is about 2000 K, i.e. the just below the dissociation temperature range.

As can be seen in figure 15, for temperature higher than 4500 K the argon temperature diffusion coefficient is positive. The point of transition between negative and positive values is a dispersion point for hydrogen: in presence of a temperature gradient, hydrogen at temperature lower than the transition temperature is pushed towards lower temperature zones whereas hydrogen at temperature higher than the transition temperature is pushed towards higher temperature ones; this results in a hydrogen dispersion towards lower or higher temperatures. This is clear from figure 14 where mass fraction of hydrogen has been plotted: for case C1 a local minima which correspond to dispersion points are found at y = -0.011 m and y = 0.013 m whereas for case C2 they are located at y = -0.015 m and y = 0.012 m.

Similar results have been obtained also by Chen for a different ICP torch configuration [START_REF] Chen | [END_REF] and the accumulation of hydrogen in the cold boundary layer of a thermal spray torch was simulated by Ghorui et al [43] using a two-temperature combined diffusion approach. These results are in agreement also with previous investigations by Murphy [42] in which a peak of hydrogen mass fraction has been predicted in the low-temperature fringes of a free burning arc.

In the reaction chamber, hydrogen diffusion is dominated by turbulence: the viscosity ratio reaches values of the order of 50 where the gas expands in the reaction chamber, as shown in figure 11, and the hydrogen is almost completely mixed (figures 12-a, 12-b, 13-a and 13-b). In the fringes of the plasma plume in the reaction chamber, where temperature is below the dissociation range, thermal diffusion pushes hydrogen (almost completely in its molecular form) towards higher temperature regions.

In figure 17 the mass fraction of hydrogen is reported for a fictitious case where thermal diffusion due to temperature gradients has been neglected. The temperature coefficient used has been plotted in figure 16 for Y H = 0.002. For both cases C1 and C2, the mass fraction in the chamber is almost constant, as a result of null temperature diffusion coefficient below the dissociation temperature range. In the torch, the accumulation of hydrogen in the fringes of the discharge is enhanced, since the positive contribution to the temperature coefficient due to temperature gradients has been neglected. Thus, according to previous investigations by Murphy on free-burning arcs [42], the accumulation of hydrogen in the fringes of the discharge can be attributed mainly to diffusion due to mole fraction gradients.

Conclusions

A fully three-dimensional model of a commercial ICP torch with laboratory scale reaction chamber has been developed using a commercial CFD software (FLUENT c ). Numerical results, which completely characterize the electromagnetic and thermo-fluiddynamic behavior of the system, are presented for an atmospheric pressure argonhydrogen mixture using the RNG k-turbulence model and the combined diffusion approach of Murphy. Two different cases have been considered with different coil current frequency (3 MHz and 13.56 MHz), the other operating conditions being fixed (mass ow rates, total Joule power dissipated, inlet gas composition).

This approach has allowed a deeper insight in the three-dimensional effects of the coil current frequency: non-axisimmetrical velocity, temperature, Joule dissipation and Lorentz force fields have been found for current frequency equal to 3 MHz, whereas for the case at higher frequency the discharge in the torch is almost axisymmetric. At higher frequency, the lower absolute value of Lorentz forces and the smaller volume of the discharge where they are applied, induces a lower unbalance between the force exerted on the discharge by the first and the last coil turn; thus, it is argued that fluiddynamic inertia prevails over the torque applied to the discharge by the coil and the resulting temperature field is more axisymmetric.

Moreover, the distribution of hydrogen mass fraction inside the torch and inside the reaction chamber has been accurately predicted, in agreement with previous works which accounted for demixing effects in thermal plasmas. Different diffusion mechanisms have been investigated, considering the effects on mass fraction field of thermal diffusion due to mole fraction gradients and temperature gradients. Finally, the temperature field in the reaction chamber has been simulated: its threedimensional shape has been correlated to different types of recirculation flow arising when a non-axisymmetric reaction chamber, which include a lateral outlet tube, is used.

Accurate modeling of devices characterized by inherently non-axisymmetric geometries such as inductively coupled plasma torches, requires the implementation of three-dimensional codes to analyze the magnitude of non-axisymmetric effects on plasma properties arising under different operating conditions. This is true in particular for the modeling of powder treatment processes such as powder spheroidization and nano-particles production, since the behavior of injected raw materials and of nucleated aerosols in the reaction chamber depends strongly on temperature and velocity fields.

Figure 1 .

 1 Figure 1. Detail of the PL-35 torch geometry and reaction chamber geometry (dimensions in mm).

Figure 2 .

 2 Figure 2. Detail of the temperature field (K) inside the torch: case C1 -plane y-z (a), plane x-z (b) and x-y sections with positive x-axis oriented to the top at z = 58 mm, z = 85 mm and z = 112 mm (c); case C2 -plane y-z (d), plane x-z (e) and x-y sections with positive x-axis oriented to the top at z = 58 mm, z = 85 mm and z = 112 mm (f).

Figure 3 .

 3 Figure 3. Case C1 -Detail of the Joule power (W/m 3 ) inside the torch: plane y-z (a) and plane x-z (b); detail of the Lorentz force magnitude (N/m 3 ) inside the torch: plane y-z (c) and plane x-z (d).

Figure 4 .

 4 Figure 4. Case C2 -Detail of the Joule power (W/m 3 ) inside the torch: plane y-z (a) and plane x-z (b); detail of the Lorentz force magnitude (N/m 3 ) inside the torch: plane y-z (c) and plane x-z (d).

Figure 5 .Figure 6 .

 56 Figure 5. Temperature (left) and Joule power (right) for cases C1 and C2 along the x-axis and the y-axis at z = 85 mm.

Figure 7 .

 7 Figure 7. Detail of the field of the magnitude of the velocity (m/s) inside the torch: case C1 -plane y-z (a) and plane x-z (b); case C2 -plane y-z (c) and plane x-z (d).

Figure 8 .

 8 Figure 8. Velocity field components (m/s): y-component on the y-z plane for cases C1 (a) and C2 (b); x-component on the x-z plane for cases C1 (c) and C2 (d).

Figure 9 .

 9 Figure 9. Temperature field (K) in the reaction chamber: case C1 -plane y-z (a) and plane x-z (b); case C2 -plane y-z (c), plane x-z (d).

Figure 10 .

 10 Figure 10. Pathlines released from plasma gas inlet: case C1 -y-z view (a), x-z view (b); case C2 -y-z view (c), x-z view (d).

Figure 11 .

 11 Figure 11. Turbulent viscosity ratio: case C1 -plane y-z (a) and plane x-z (b); case C2 -plane y-z (c) and plane x-z (d).

Figure 12 .

 12 Figure 12. Case C1 -Mass fraction of hydrogen: plane y-z (a) and plane x-z (b); detail of the mass fraction of hydrogen inside the torch: plane y-z (c), plane x-z (d) and x-y sections with positive x-axis oriented to the top at z = 58 mm, z = 85 mm and z = 112 mm (e).

Figure 13 .

 13 Figure 13. Case C2 -Mass fraction of hydrogen: plane y-z (a) and plane x-z (b); detail of the mass fraction of hydrogen inside the torch: plane y-z (c), plane x-z (d) and x-y sections with positive x-axis oriented to the top at z = 58 mm, z = 85 mm and z = 112 mm (e).

Figure 14 .

 14 Figure 14. Hydrogen mass fraction and argon temperature diffusion coefficient along y-axis at z = 95 mm: case C1 --, case C2 ----.

Figure 15 .

 15 Figure 15. Argon temperature diffusion coefficients (D T Ar ) as a function of temperature for argon-hydrogen mixtures, for constant mass fractions of hydrogen.

Figure 16 .

 16 Figure 16. Different contributions to argon temperature diffusion coefficient (D T Ar ) as a function of temperature for argon-hydrogen mixtures, for constant mass fraction of hydrogen (Y H = 0.002).

Figure 17 .

 17 Figure 17. Mass fraction of hydrogen on plane y-z neglecting thermal diffusion due to temperature gradients: case C1 -chamber view (a) and torch view (b); case C2chamber view (c) and torch view (d).


Laurent Ferraris

Marie-José Butel

Julio Aires
email: julio.aires@univ-paris5.fr

Antimicrobial susceptibility and resistance determinants of Clostridium butyricum isolates from preterm infants

Keywords:

This study reports the antibiotic susceptibility and genetic resistance determinants of 39 Clostridium butyricum strains isolated from the faeces of preterm infants as well as one reference strain. Results showed that all the strains were susceptible to cefoxitin, imipenem, vancomycin, tigecycline, metronidazole, chloramphenicol and linezolid.

Resistance was observed to clindamycin (100%), penicillin G, amoxicillin and piperacillin (15%), tetracycline (7.5%) and erythromycin (5%). Investigation of the genetic basis of the observed resistance phenotypes showed that resistance to penicillin was due to lactamase activity and that resistance to tetracycline involved tet(O) or tet(O/32/O) homologue genes. Clindamycin and erythromycin resistance may involve another genetic determinant, different from those commonly described for clostridia.

A c c e p t e d M a n u s c r i p t

Introduction

Preterm infants have delayed bacterial colonisation compared with full-term infants, leading to microbiota imbalance with overgrowth of potentially pathogenic bacteria. This dysbiosis is a risk factor for the onset of gastrointestinal diseases in this target population [START_REF] Morowitz | Redefining the role of intestinal microbes in the pathogenesis of necrotizing enterocolitis[END_REF]. For instance, compared with term infants, premature infants at risk of necrotizing enterocolitis (NEC) have a paucity of bacterial species and/or delayed onset of bacterial gut colonisation [START_REF] Wang | 16S rRNA genebased analysis of fecal microbiota from preterm infants with and without necrotizing enterocolitis[END_REF].

Clostridia are among the anaerobes that are part of the indigenous intestinal microbiota of humans. These commensal spore-forming Gram-positive rods belong to the species isolated from the normal neonatal gut bacterial community of full-term [START_REF] Eae | Bifidobacterium, Bacteroides, and Clostridium spp. in fecal samples from breast-fed and bottle-fed infants with and without iron supplement[END_REF] and preterm infants [START_REF] Blakey | Development of gut colonisation in pre-term neonates[END_REF][START_REF] Rotimi | The development of bacterial flora of premature neonates[END_REF]. In preterm infant gut microbiota, occurrences of clostridia, in particular Clostridium butyricum, have been described [START_REF] Blakey | Development of gut colonisation in pre-term neonates[END_REF][START_REF] Rotimi | The development of bacterial flora of premature neonates[END_REF]. Clostridial colonisation has been linked to a higher risk of NEC [START_REF] Kosloske | Fulminant necrotising enterocolitis associated with clostridia[END_REF], a devastating gastrointestinal disease with high morbidity and mortality, and several investigations have supported the role of clostridial species in NEC pathogenesis [START_REF] Kosloske | Fulminant necrotising enterocolitis associated with clostridia[END_REF][START_REF] Cashore | Clostridia colonization and clostridia toxin in neonatal necrotizing enterocolitis[END_REF][START_REF] Sturm | Neonatal necrotizing enterocolitis associated with penicillin-resistant, toxigenic Clostridium butyricum[END_REF][START_REF] Alfa | An outbreak of necrotizing enterocolitis associated with a novel Clostridium species in a neonatal intensive care unit[END_REF][START_REF] Obladen | Necrotizing enterocolitis-150 years of fruitless search for the cause[END_REF], although other bacterial species have also been implicated [START_REF] Morowitz | Redefining the role of intestinal microbes in the pathogenesis of necrotizing enterocolitis[END_REF][START_REF] Waligora-Dupriet | Evidence for clostridial implication in necrotizing enterocolitis through bacterial fermentation in a gnotobiotic quail model[END_REF]. Indeed, high production of metabolites through colonic bacterial fermentation is thought to be responsible for the onset of digestive lesions, i.e. gas cysts, haemorrhagic lesions and necrosis, as shown in animal models of NEC [START_REF] Waligora-Dupriet | Evidence for clostridial implication in necrotizing enterocolitis through bacterial fermentation in a gnotobiotic quail model[END_REF][START_REF] Bousseboua | Experimental cecitis in gnotobiotic quails monoassociated with Clostridium butyricum strains isolated from patients with neonatal necrotizing enterocolitis and from healthy newborns[END_REF][START_REF] Butel | Clostridial pathogenicity in experimental necrotising enterocolitis in gnotobiotic quails and protective role of bifidobacteria[END_REF]. Despite the similarities of NEC to clostridial infection, only a few studies have employed anaerobic culture techniques for isolation, identification and characterisation of clostridial strains routinely. Little information is therefore available on this species. In particular, data on its susceptibility to antibiotics are very scarce and relate to few strains, although perinatal antibiotic treatment is very frequent in preterm infants. The aim of this study was to perform and report the first

Material and methods

Isolates and strain identification

Among 102 premature infants screened from four different French hospitals, 39 C. butyricum strains were isolated (from 2004 to 2009). Among the 39 strains, 3 were isolated from three different neonates with NEC from the different hospitals.

Strain isolation was as performed as follows. Faecal samples were crushed in brainhearth infusion broth using an Ultra-Turrax T25 (Fisher-Bioblock, Illkirch, France) and diluted in peptone water and then 10 -2 , 10 -4 and 10 -6 dilutions were spread using a WASP apparatus (AES Chemunex, Bruz, France) on clostridia sulphite-polymyxin-milk selective medium and incubated for 48 h at 37 C in an anaerobic chamber (AES Chemunex) under anaerobic gas phase (H 2 :CO 2 :N 2 , 10:10:80, v/v/v). Colonies suspected as being clostridia on the basis of cellular morphology and Gram staining were identified using Rapid ID 32A strips (bioMérieux, Marcy l'Etoile, France). Identification was confirmed by partial sequencing of the 16S rRNA gene, which was amplified by polymerase chain reaction (PCR) using primers LPW58 (5'-AGGCCCGGGAACGTATTCAC-3') and LPW81 (5'-TGGCGAACGGGTGAGTAA-3'). Reference strain C. butyricum ATCC 19398 was included in the study. Liquid cultures were performed in TGYH broth (tryptone 30 g/L, glucose 5 g/L, yeast extract 20 g/L and hemin 5 mg/L) for 24 h at 37 C in an anaerobic chamber (AES Chemunex).

A c c e p t e d M a n u s c r i p t 5

Minimal inhibitory concentration (MIC) determination

MICs for penicillin G, amoxicillin, cefoxitin, piperacillin, imipenem, vancomycin, tetracycline, tigecycline, erythromycin, clindamycin, ofloxacin, metronidazole, chloramphenicol and linezolid were determined using the agar dilution method on Brucella agar medium supplemented with 0.5% sheep blood. An inoculum was prepared for each strain by suspending cells from a plate in TGYH broth to achieve a turbidity equivalent to that of a 0.5 McFarland standard (3  10 5 cells/mL) and the inoculum was delivered by a Steers replicator onto agar plates. Resistant and susceptible strains were characterised following Clinical and Laboratory Standards Institute (CLSI) breakpoints [START_REF]Methods for antimicrobial susceptibility testing of anaerobic bacteria; approved standard[END_REF].

PCR amplifications

Purified genomic DNA of all 40 strains (39 clinical strains and 1 reference strain) was used as a template for PCR amplification of the protection ribosomal genes tet(M), tet(W), tet(O) and tet(Q), the efflux pump genes tet(K) and tet(L), and the C. butyricum chromosomal efflux pump tet(P) (GenBank accession no. EDT76835.1), rRNA methylases genes erm(B), erm(Q) and erm(F), and lmrB (accession number no. EDT76011) (Table 1).

The PCR mixture was composed of 1 M of each primer, 5% dimethyl sulphoxide (DMSO), each deoxynucleotide triphosphate (dNTP) at a concentration of 250 M in 1 PCR buffer and 1.25 U of recombinant DNA polymerase (Invitrogen, Illkirch, France) in a final volume of 25 L. The PCR programme was 4 min at 95 C, followed by 30 cycles of 30 s at 94 C, 30 s at 50 C and 90 s at 72 C, and a 5 min final extension at 72 C. When PCR products where obtained for tet, erm or lmrB genes they were sequenced to confirm their identity (Genome Express SA, Meylan, France). Sequences were analysed using the

tet(P) and lmrB reverse transcription polymerase chain reaction (RT-PCR)

After 16 h of growth in TGYH broth, 0.5 mL of bacterial culture was mixed with 1 mL of RNAprotect (QIAGEN, Courtaboeuf, France). Total RNA was isolated using an RNeasy Mini Kit (QIAGEN). Following extraction, DNA contamination was removed by RNase-free DNase (QIAGEN) digestion for 30 min at 37 C. Total RNA concentration and purity were determined using a NanoDrop ® ND-1000 spectrophotometer (Thermo Fisher Scientific, Villebon-sur-Yvette, France) and total RNA was stored at -80 C. RT-PCR was performed using a SuperScript ® III RT Kit (Invitrogen) with 1 g of total RNA. The primer pairs TetP-ShrtF/TetP-ShrtR and LmrB-ShrtF/LmrB-ShrtR (Table 1) were used for cDNA amplification. The C. butyricum housekeeping gene recA (accession no. EDT76977) was used as a reference, and cDNA amplification was performed using primers RecA-F/RecA-R (Table 1). One microlitre of the resulting cDNA was amplified with tet(P) and lmrB primers (Table 1).

Nucleotide sequence accession numbers

Nucleotide sequences of the potential tet(O/32/O) gene homologue and tet(O) genes were deposited in the GenBank database under the accession nos. GQ240299, GQ240297 and GQ240298, respectively.

A c c e p t e d M a n u s c r i p t 7

Results and discussion

Susceptibility levels

Non-perfringens Clostridium spp. have been reported to be susceptible to penicillins, imipenem and metronidazole, whereas resistance occurred to cefoxitin and clindamycin [START_REF] Mory | Survey of anaerobic susceptibility patterns: a French multicentre study[END_REF][START_REF] Hecht | Anaerobes: antibiotic resistance, clinical significance, and the role of susceptibility testing[END_REF]. With regard to C. butyricum, no comparative data were available because its susceptibility levels were included among the Clostridium spp. group. In this study, out of the 40 C. butyricum strains tested, all were susceptible to vancomycin (MICs ≤ 4 mg/L), imipenem (MICs ≤ 2 mg/L), tigecycline (MICs ≤ 4 mg/L), linezolid (MICs < 4 mg/L), metronidazole (MICs ≤ 4 mg/L) and cefoxitin (MICs < 32 mg/L) (Table 2); strains were susceptible (MICs ≤ 1 mg/L) or intermediate (1 mg/L < MICs < 4 mg/L) to ofloxacin (Table 2). Although chloramphenicol resistance has been reported for C. butyricum reference strains [START_REF] Sebald | Genetic basis for antibiotic resistance in anaerobes[END_REF], in this study all the strains were susceptible (MICs ≤ 8 mg/L). Antibiotic resistance was observed to penicillin G (MICs > 8 mg/L), amoxicillin (MICs > 8 mg/L) and piperacillin (MICs > 16 mg/L) for six strains, to tetracycline for three strains (MICs > 8 mg/L), to clindamycin for all strains (MICs  8 mg/L) and to erythromycin for two strains (MICs = 256 mg/L) (Table 2).

-Lactam resistance

Most clostridia are susceptible to -lactam agents. However, some species, such as Clostridium difficile, are less susceptible [START_REF] Mory | Survey of anaerobic susceptibility patterns: a French multicentre study[END_REF]. -Lactamase production has been reported in only three species, namely C. butyricum, Clostridium clostridioforme and Clostridium ramosum [START_REF] Nord | Resistance to -lactam antibiotics in anaerobic bacteria[END_REF], with no data on its incidence owing to the low number of strains tested. In this study, resistance to penicillin G (MICs > 8 mg/L), amoxicillin (MICs > 8 mg/L) and piperacillin (MICs > 16 mg/L) was observed for six strains (15%). Based on the nitrocefin A c c e p t e d M a n u s c r i p t 8 assay, all of the penicillin-resistant strains showed -lactamase activity. In addition, the lactamases were inhibited by clavulanic acid, which has been reported to be a particularity of C. butyricum [START_REF] Magot | Some properties of the Clostridium butyricum group -lactamase[END_REF].

Tetracycline resistance

In this study, three C. butyricum strains showed resistance to tetracycline (MICs > 8 mg/L). One of the mechanisms involved in tetracycline resistance among anaerobic bacteria is ribosomal protection. Among clostridia, tet(M) was the most frequently identified tetracycline resistance gene for C. difficile [START_REF] Spigaglia | New variants of the tet(M) gene in Clostridium difficile clinical isolates harbouring Tn916-like elements[END_REF][START_REF] Schmidt | Antimicrobial phenotypes and molecular basis in clinical strains of Clostridium difficile[END_REF] and C. perfringens [START_REF] Lyras | Genetic organization and distribution of tetracycline resistance determinants in Clostridium perfringens[END_REF]; the tet(O) [START_REF] Schmidt | Antimicrobial phenotypes and molecular basis in clinical strains of Clostridium difficile[END_REF] and tet(W) [START_REF] Spigaglia | Tetracycline resistance gene tet(W) in the pathogenic bacterium Clostridium difficile[END_REF] genes were less frequently reported. In this study, the genomic DNA of all strains was used as a template for PCR amplification of the tet(M), tet(W), tet(O) and tet(Q) genes. Using the degenerated primers tet1 and tet2, PCR results showed that the tet(M), tet(W) and tet(Q) genes were absent in all of the isolates tested.

Of the three tetracycline-resistant strains (strains 2, 22 and 33), only strain 22 showed amplification of the expected 1250-bp PCR product. The same 1250-bp PCR product was amplified for two non-resistant strains (strains 51 and 52). The nucleotide sequence of the 1250-bp fragment of strain 22 shared 71% identity with the mosaic tet(O/32/O) gene (accession no. AJ295238) from Clostridiaceae bacterium K10. Meanwhile, the nucleotide sequences of the same fragment for strains 51 and 52 showed 99% identity with tet(O) genes from Enterococcus faecalis (accession no. AY660532) and Campylobacter jejuni (accession no. M18896). To amplify the full-length genes of strains 22, 51 and 52, the primer combination OFF2/OFR3 was used (Table 1). This approach allowed the amplification of a 2000-bp PCR product with only the OFF2/OFR3 primers for strains 51 and 52 but not for strain 22. After sequencing, the 2000-bp PCR product nucleotide sequences from strains 51 and 52 shared 99% identity with the already mentioned tet(O)

A c c e p t e d M a n u s c r i p t 9 genes. Attempts to amplify the full-length gene for strain 22 using multiple primer combinations were unsuccessful (data not shown).

To investigate the tetracycline resistance mechanism of strains 2 and 33, all strains were screened for the tet(P), tet(K) and tet(L) tetracycline efflux pumps genes. Indeed, such genes have been identified in C. difficile [START_REF] Roberts | Characterization of the genetic basis of antibiotic resistance in Clostridium difficile[END_REF] and C. perfringens [START_REF] Soge | A conjugative macrolide resistance gene, mef(A), in environmental Clostridium perfringens carrying multiple macrolide and/or tetracycline resistance genes[END_REF]. PCR screening showed that tet(K) and tet(L) were absent from all the strains tested. The tet(P) gene (accession no. EDT76835.1), which was found to be present on the C. butyricum 5521 sequenced genome (accession no. NZ ABDT00000000), was identified for all strains except strains 22, 51 and 52. RT-PCR experiments confirmed tet(P) expression for tetracycline-resistant strains 2 and 33. However, tet(P) expression was also observed for all susceptible strains. The fact that tet(P) may be tightly regulated at the transcriptional or translational levels may explain these observations [START_REF] Johanesen | Transcriptional analysis of the tet(P) operon from Clostridium perfringens[END_REF].

Erythromycin and clindamycin resistance

Macrolide-lincosamide-streptogramin B (MLS B ) resistance in clostridia is mostly encoded by rRNA methyltransferase erm genes. In C. difficile and C. perfringens it involves the erm(B), erm(Q) or erm(F) genes [START_REF] Schmidt | Antimicrobial phenotypes and molecular basis in clinical strains of Clostridium difficile[END_REF][START_REF] Soge | A conjugative macrolide resistance gene, mef(A), in environmental Clostridium perfringens carrying multiple macrolide and/or tetracycline resistance genes[END_REF]. With regard to C. butyricum, one clinical isolate was reported to carry erm(B) and erm(F) genes [START_REF] Chung | Host range of the ermF rRNA methylase gene in bacteria of human and animal origin[END_REF]. In this study, all strains showed MICs  8 mg/L to clindamycin and two were resistant to erythromycin (MICs of 256 mg/L). PCR amplification for erm genes showed the absence of erm(B), erm(Q) and erm(F) as an explanation for the observed resistance (data not shown). Such observations have been reported for other erm-negative clostridia with erythromycin and clindamycin resistance [START_REF] Spigaglia | Comparative analysis of Clostridium difficile clinical isolates belonging to different genetic lineages and time periods[END_REF]. These results suggest the presence of an alternative resistance mechanism(s).

Interestingly, an lmrB efflux gene homologue (accession number no. EDT76011) was

Conclusion

This study provides recent information on the status of C. butyricum antimicrobial susceptibility and shows that this human gut commensal bacterium is susceptible to common anti-anaerobe antimicrobial agents. The prevalence of this species in preterm neonates may be not linked to a high degree of resistance to antimicrobial agents. This

  antimicrobial susceptibility patterns and genetic resistance determinants of C. butyricum isolated from preterm infant faeces.

  A c c e p t e d M a n u s c r i p t 6 BLAST Align program available from the National Center for Biotechnology Information (NCBI).

  present on the C. butyricum 5521 sequenced genome (accession no. NZ ABDT00000000). Although efflux pumps may participate in clindamycin resistance in anaerobic bacteria [29], it was not reported for clostridia. In this study, PCR amplification of the chromosomal C. butyricum efflux gene homologue lmrB was positive for 70% of the strains. RT-PCR experiments showed that 75% of the lmrB-positive strains showed gene expression. This suggests the involvement of other mechanism(s) in the observed resistance.

  study provides new data on the genetic antibiotic resistance determinants of C. butyricum and reports for the first time the acquired resistance to tetracycline by ribosomal protection genes tet(O) and a potential mosaic tet(O/32/O) homologue.

1 1

 11 Kim HJ, Kim Y, Lee MS, Lee HS. Gene lmrB of Corynebacterium glutamicum confers efflux-mediated resistance to lincomycin. Mol Cells 2001;12:112-6. A c c e p t e d M a n u s c r i p tTable Primers used for PCR and RT-PCR experiments Genes Primers Primer sequences (5'3') tet(W), tet(M), tet(Q) chain reaction; RT-PCR, reverse transcription PCR.

A c c e p t e d M a n u s c r i p t 1

 1

Table 2

 2 Susceptibility of Clostridium butyricum isolates to antimicrobials agentsAntimicrobial agent No. of strains at an MIC (mg/L) of: MIC, minimal inhibitory concentration; MIC 50/90 , MICs for 50% and 90% of the organisms, respectively.

	MIC (mg/L)

Funding

None.

Competing interests

None declared.

Ethical approval

Not required.