Effects of Pressure, Temperature, and Particles Size on O2 Diffusion

Apr 14, 2013 - The O2 diffusion process in silica nanoparticles is experimentally studied in samples of average radius of primary particles ranging fr...
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Effects of Pressure, Temperature, and Particles Size on O2 Diffusion Dynamics in Silica Nanoparticles G. Iovino,* S. Agnello, F. M. Gelardi, and R. Boscaino Dipartimento di Fisica, Università di Palermo,Via Archirafi 36, I-90123 Palermo, Italy ABSTRACT: The O2 diffusion process in silica nanoparticles is experimentally studied in samples of average radius of primary particles ranging from 3.5 to 20 nm and specific surface ranging from 50 to 380 (m2/g). The investigation is done in the temperature range from 98 to 177 °C at O2 pressure ranging from 0.2 to 66 bar by measuring the interstitial O2 concentration by Raman and photoluminescence techniques. The kinetics of diffusion can be described by the Fick’s equation with an effective diffusion coefficient depending on the temperature, O2 pressure, and particles size. In particular, the dependence of the diffusion coefficient on the pressure and nanoparticles size is more pronounced at lower temperatures and is connected to morphological and physical factors.

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INTRODUCTION Research for nanotechnology involves amorphous SiO2, or silica, due to its wide band gap, high dielectric constant, and chemical resistance, which are very useful features for optical and electronics devices.1−6 Silica has been also a reference material for many years for the study of the basic properties of amorphous systems due to its simple composition and easiness of manufacturing, and the extension to the nanosized system constitutes a topic of actual interest for nanomaterial science.1,2,7 Recently, the technological interest has also extended toward composite materials employing silica as a component for electronics as well as optics devices on nanometer scale.5,6 The relevant properties of silica are related also to its structural features and to the presence of impurities or interstitial molecules that could affect the material performances. In this respect, the clarification of the role of these elements is fundamental for the material final use. In particular, the potentialities of small molecules to diffuse through silica layers or nanostructures under working conditions can lead to molecules trapping and reaction with the resulting modification and compromission of the system.8−16 Furthermore, the presence of interstitial molecules could compromise the material features in the presence of ionizing radiation in the environment during its use due to, for example, the activation of chemical reactions able to deteriorate the device itself.17,18 Among these small molecules, the oxygen is of particular relevance due to its presence in atmosphere as well as in many biological systems toward which some probe nanoparticles are targeted.8,19,20 The presence of interstitial O2 molecules in silica has been revealed both directly and indirectly by many experimental works on bulk systems aiming to clarify the effects of this molecule on the point defects generation and on the oxide growth in microelectronic devices.8,10,21−23 In this © 2013 American Chemical Society

context, the diffusion of oxygen in silica has been investigated mainly in a temperature range above 500 °C to enable experimental detection in laboratory time scales, despite the interest in the investigation at lower and, in particular, at room temperature, too. These studies have also shown that interstitial molecular oxygen can be detected through its near-infrared emission band and its diffusion kinetics can be followed.24,25 In particular, it has been suggested that the diffusion process could occur without exchange with the network oxygen at low temperature, whereas a more complex dynamics arises above 900 °C. At variance, few studies have been carried out on nanoscale systems but for essentially indirect ones based on the diffusion through the silica layer on top of silicon in metal− oxide−semiconductor devices and the detection of oxide grown on silicon nanoparticles.8,14,20 Recently, a direct investigation of O2 diffusion in nanoparticles systems has been reported and it has been found that the small size reduces the time required for the oxygen to move through the overall volume of the system, thus allowing a direct measurement of O2 diffusion by near-infrared photoluminescence detection.16,26 However, a full study has not been reported, the results being limited to oxygen release from nanoparticles in air atmosphere without investigation of the loading effects. In this work, we focus on the experimental investigation of the O2 diffusion in commercial silica nanoparticles with radius from 20 nm down to 3.5 nm in the range of temperature up to 177 °C. Aiming to study the dependence of the diffusion coefficient on particles size and on the concentration of diffusing molecules, the investigation has been carried out in Received: December 21, 2012 Revised: April 10, 2013 Published: April 14, 2013 9456

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The overall time between sample insertion in the pipe and starting of oxygen exposure was typically about 5 min. After treatment time was elapsed, the sample was cooled inside the pipe in about 1 min. In order to get information about the diffusion process kinetics, the oxygen content inside the sample was measured after thermal treatments of increasing duration until O2 equilibrium concentration value was reached. Moreover, in order to study the dependence of the diffusion coefficient on temperature and loading pressure thermal treatments at different temperatures and loading pressures were done in the range from 98 to 177 °C and from 0.2 bar up to 66 bar. For comparison, data relative to outgassing experiments in air are reported in the following. The experimental procedures relative to these experiments are reported in ref 16. To characterize the diffusion process, the O2 diffusion coefficients were determined by fitting the experimental time dependence of volume average concentration of interstitial O2 with the solution of the Fick’s diffusion equation.22,31 Such equation was resolved in spherical geometry supposing a uniform initial concentration of O2 embedded in the nanoparticles and that the oxygen concentration on the nanoparticles inner surface reaches instantaneously its equilibrium value. Furthermore, the approximation was used that nanoparticles are identical spheres of radius equal to the average radius reported by the producer. Under these conditions, the volume average value of interstitial O2 concentration can be put in the following form:31

the pressure interval up to 66 bar. The study in a wide pressure range enables the investigation of the possible dependence of the diffusion coefficient on the high interstitial O2 concentration when the approximation that the flux of diffusing molecules is proportional to the gradient of its concentration could not be valid. Furthermore, the investigation of different nanoparticles aims to study the dependence on the size and on the surface morphology in order to understand the role of these physical parameters on the diffusion process.

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EXPERIMENTAL PROCEDURES The diffusion process is investigated in this study using hydrophilic silica nanoparticles of commercial origin known as Aerosil fumed silica, produced by hydrolysis of silicon tetrachloride. The used nanoparticles are characterized by a purity larger than 99.8% by weight, and by typical average radius and specific surface as summarized in Table 1.27,28 In Table 1. Commercial Name, Nickname, and Morphological Features of the Investigated Materials27,28 commercial name Aereosil Aereosil Aereosil Aereosil

380 300 150 OX50

specific surface

average radius

nickname

(m2/g)

(nm)

AE380 AE300 AE150 AEOX50

380 300 150 50

3.5 3.5 7 20

order to handle each material, which initially is a powder of spherical nanoparticles, it was pressed at about 0.3 GPa by a mechanical press to obtain tablets. The diffusion experiments were carried out on tablets of volume 4 × 4 × 2 mm3 produced by powders of given specific surface and average radius of primary nanoparticles. To study the diffusion kinetics, the tablets were thermally treated in O2 atmosphere and the volume average concentration of the interstitial O2 inside the nanoparticles was measured after each thermal treatment by a spectroscopic technique. In particular, the concentration of interstitial oxygen molecules was estimated from the amplitude of the associated photoluminescence (PL) band peaked at 1272 nm, under excitation at 1064 nm.26,29,30 Measurements were performed by an FT-Raman spectrometer (RAMII Bruker) equipped with a Nd:YAG laser source (1064 nm emission wavelength) at 500 mW beam power selecting a spectral resolution of 15 cm−1. The recorded spectra show both the Raman bands of the silica intrinsic vibrational modes and the PL band of interstitial O2, permitting a direct estimation of the volume average concentration of O2 inside the sample by bands amplitude comparison, as already explained in previous papers.26,29,30 Because of the simultaneous presence of photoluminescence and Raman bands in the recorded spectra, in this work we will refer to them as Raman/PL spectra. The diffusion process was investigated by means of experiments defined of loading. In these latter, after a thermal treatment at 300 °C for 5 min in air to remove native oxygen16 the sample was put in a stainless steel blind pipe. This pipe was preliminarily heated at the experiment temperature by placing it in a furnace and after insertion of the sample the pipe was evacuated by a vacuum pump and then filled with O2 gas. The temperature of the furnace was stabilized within 1 °C, the vacuum pressure inside the emptied pipe was about 0.1 mbar, and the oxygen was introduced just after vacuum was reached.

C(t ) − C i 6 =1− 2 Cf − C i π

∞

∑ n=1

1 −π 2n2Dt / r 2 e n2

(1)

where Ci, Cf, and C(t) are the initial, final, and at time t O2 volume average concentrations, respectively, D is the diffusion coefficient, and r is the radius of the nanoparticles. Since the relative change in the concentration was used, see left side of eq 1, the diffusion coefficient values determined by the used fitting procedure are not affected by possible errors in the estimation of the absolute values of interstitial O2 concentration.

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RESULTS Figure 1 shows the acquired Raman/PL spectra for the AE150 sample thermally treated in O2 at 6 bar and 113 °C for different times. The initial spectrum, labeled 0 min, is relative to the sample annealed at 300 °C in air to remove native oxygen.16 The bands below 1200 cm−1 are relative to vibrational Raman active modes of the silica network32,33 whereas the one at 1538 cm−1 Raman shift, corresponding to 1272 nm absolute wavelength (7862 cm−1 absolute wavenumber), is the photoluminescence band of interstitial O2 molecules excited by the laser source of the Raman spectrometer.17,26,29,30 The Raman bands of silica network are not modified by thermal treatments whereas the PL band of interstitial O2 molecules increases its amplitude with no change in shape on increasing the thermal treatment time in O2 atmosphere. The volume average value of interstitial concentration of O2 was estimated from the Raman/ PL spectra taking into account the quantum yield obtained from the PL lifetime of O2 when trapped in silica nanoparticles,26 and its time dependence is shown in the inset of Figure 1. This time evolution shows that the concentration of interstitial O2 increases until an equilibrium value between the trapped O2 molecules and the surrounding gas is reached. Moreover, as shown in Figure 2, the concentration of the 9457

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Figure 1. Raman/PL spectra of the AE150 sample annealed at 300 °C in air for 5 min (0 min) then thermally treated in O2 atmosphere at 113 °C and 6 bar for increasing time. The spectra are scaled to have equal amplitude of the silica Raman band at ∼440 cm−1. The inset shows the time evolution of the volume average concentration of interstitial O2 estimated by the amplitude of its PL band in Raman/PL spectra.26,29,30

Figure 3. Time evolution of the relative variation of the volume average concentration of interstitial O2 ((C(t) − Ci)/(Cf − Ci) where Ci, Cf, and C(t) are the experimental volume average concentrations of interstitial O2 before the treatment, at the equilibrium state and at time t, respectively) (a) in the AE300, AE150, and AEOX50 samples at 127 °C and 66 bar O2 pressure and (b,c) in the AE380, AE300, and AE150 samples at 98 °C and at 6 and 66 bar O2 pressure, respectively. The first point for the lowest x-axis value refers to untreated sample.

were observed in all the investigated conditions. In general, the diffusion kinetics as a function of the time depends on the morphology and size of the nanoparticles. By supposing the nanoparticles are spherical in shape, one can see from the eq 1 that the size dependence can be eliminated by plotting the diffusion kinetics as a function of t/r2. Kinetics plotted in such a way are shown in Figures 4 and 5. Figure 4 shows the time dependence of the relative variation of the O2 volume average concentration at a given temperature for different loading pressures, and hence for different concentrations of interstitial O2, for each of the samples AE300, AE150, and AEOX50. The data labeled “in air” are relative to outgassing experiments reported in ref 16 and are shown for comparison. By comparing the data relative to the same temperature and sample but at different external O2 pressure (about 0.2 bar in the case of the outgassing experiments), a dependence of the kinetics on the loading pressure can be noticed. In particular, the kinetics is faster at higher loading pressure. This behavior was observed in all the investigated samples but not at all the investigated temperatures because the dependence on the pressure decreases on increasing the temperature till to vanish. It is worth noting that this phenomenon is independent of the physical quantity

Figure 2. Time evolution of the volume average concentration of interstitial O2 in the AE150 sample thermally treated at 98 °C for various external O2 pressures. Data relative to outgassing experiments, labeled in air, are reported from ref 16. The first point for the lowest xaxis value refers to untreated sample.

diffusing molecules increases on increasing the O2 pressure in the thermal treatment atmosphere. In particular, the equilibrium value of the interstitial O2 concentration varies more than 1 order of magnitude when the concentration in the atmosphere is changed from about 0.2 bar (in air) to 66 bar. A similar behavior was observed in all the other samples at all the temperatures investigated in this work. Figure 3 shows the time dependence of the relative variation of the O2 volume average concentration for the investigated materials in various thermodynamical conditions. In the panel a, it can be seen that the kinetics of the AE150 and AE300 samples is faster than that of the AEOX50 whereas no difference among the sample AE380, AE300, and AE150 is detectable within the experimental errors (panel b and c). These findings, shown for few thermodynamical conditions, 9458

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Figure 5. Time evolution of the relative O2 content (C(t) − Ci)/(Cf − Ci) for the sample AE300, AE150, and AEOX50 at 6 bar loading pressure at the temperatures between 98 and 143 °C. Ci ,Cf, C(t) are the experimental volume average concentrations of interstitial O2 before the treatments, at the equilibrium state, and at time t, respectively. The x-axis r values are the average radius of the nanoparticles (see Table 1), the time t is the duration of each thermal treatment. The lines are the best fit curves obtained by fitting the experimental data with eq 1. The first point for the lowest x-axis value refers to untreated sample.

Figure 4. Time evolution of the relative O2 content (C(t) − Ci)/(Cf − Ci) for the sample AE300, AE150, and AEOX50 for various O2 loading pressures. For comparison, data relative to outgassing experiments, labeled in air, are reported from ref 16. Ci, Cf, and C(t) are the experimental volume average concentrations of interstitial O2 before the treatments, at the equilibrium state, and at time t, respectively. The x-axis r values are the average radius of the nanoparticles (see Table 1) and the time t is the duration of each thermal treatment. The lines are the best fit curves obtained by fitting the experimental data with eq 1. The first point for the lowest x-axis value refers to untreated sample.

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DISCUSSION Diffusion of oxygen in bulk silica in the temperature range investigated in this work cannot be studied in laboratory time due to the low value of the diffusion coefficient. By contrast, the diffusion in a nanometer scale due to the short distance that the diffusing molecules have to cross inside the sample can be investigated at low temperature in experimentally accessible time. The data reported in this work are relative to the temperature range below 180 °C not explored in bulk silica but relevant for nanometer silica. Oxygen diffusion in silica at low temperature on nanometer systems was studied in a preceding work by detecting the outdiffusion of embedded molecules and showing the applicability of Fick’s theory in the low concentration range of embedded molecules.16 The kinetics as a function of time (see Figure 3) are faster for smaller nanoparticles when the radius is reduced from 20 to 7 nm and independent of the size when the radius is further reduced. In general, the kinetics plotted as a function of the time depend on the diffusion coefficient as well as on the shape and size of the nanoparticles. In order to get information about the diffusion coefficient, the contribution to the diffusion kinetics related to the last two factors has to be eliminated by

relative to the x-axis, either t or t/r2, because only the kinetics relative to the same sample type are compared. Figure 5 shows the time dependence of the relative variation of the O2 volume average concentration at 6 bar loading pressure in the temperature range from 98 to 143 °C, obtained by carrying out loading experiments on different samples at the same temperature. It is worth to note, in general, that doing diffusion experiments at the same temperature on different samples is not always possible because the time evolution of the diffusion kinetics relative to the various sample types is very different. In particular, at low temperature the diffusion kinetics in bigger nanoparticles takes long time to be investigated in laboratory time, whereas at high temperature the diffusion kinetics in smaller nanoparticles is too fast to be investigated. By comparing the diffusion kinetics as a function of t/r2 relative to the same temperature but different samples, it can be noticed that the diffusion kinetics of the AE300 sample are slower than ones of the AE150 and AEOX50 and that the kinetics relative to AE150 sample are the fastest. This result evidences that the diffusion process is affected by physical characteristics of the nanoparticles apart from their nominal size. 9459

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doing some hypothesis about the morphology of the materials. As a first approximation, the materials were supposed to be constituted by identical nanoparticles whose radius is equal to the average radius of the primary nanoparticles. Under this hypothesis, the contribution to the diffusion kinetics related to the size is removed by plotting them as a function of t/r2. Kinetics in such a form are plotted in Figures 4 and 5. Independently from the x-axis physical quantity, a dependence of the kinetics on the external pressure of O2 is found. This phenomenon is evident by comparing the diffusion kinetics at the same temperature for the same sample but at different O2 external pressures, as shown in Figure 4 (for comparison, the diffusion kinetics relative to outgassing experiments in which the external pressure of oxygen was about 0.2 bar are also reported16). In particular, the kinetics are faster at higher pressure. We stress the fact that as the comparison is done among diffusion kinetics relative to the same sample type, this finding is independent of the way to plot the diffusion kinetics, either as a function of t or t/r2. Being the external pressure related to the concentration of the interstitial O2 (see Figure 2), the dependence of the kinetics on the external pressure could be related to the dependence of the diffusion coefficient on the concentration. This finding does not agree with the Fick’s theory of the diffusion according to which the diffusion kinetics should be independent of the concentration of diffusing molecules. Nevertheless, as a first approximation, the experimental data reported in Figure 4 were fitted with eq 1 obtained from Fick’s theory in order to analyze them quantitatively. By comparing the experimental data and the best fit curves shown in Figure 4, it can be seen that the diffusion kinetics can be described by eq 1 assuming an effective diffusion coefficient depending on external pressure and temperature. The dependence of the effective diffusion coefficient on the external pressure takes into account the average dependence of the true diffusion coefficient on the concentration of the diffusing O2 molecules. The diffusion coefficients determined by this approximation are collected in Table 2 and plotted in Figure 6 in an Arrhenius plot. From these values it is evident a dependence of the effective diffusion coefficient on O2 external pressure. In particular, it increases on increasing the external pressure. Moreover the

Figure 6. Arrhenius plot of the effective diffusion coefficients collected in Table 2. The effective diffusion coefficients relative to outgassing experiments (labeled in air) are plotted for comparison.16

observed effect is less detectable at higher temperatures due to the increase of the diffusion coefficient with the temperature and the fulfilling of the condition (π2Dt)/(r2) > 1 (see eq 1), where D is the effective diffusion coefficient, r is the average radius of the nanoparticles, and t is the shortest time experimentally investigable (5 min). Indeed, under this condition only the last part of the diffusion kinetics can be investigated with a lack of information preventing the possibility to distinguish among the kinetics. By inspection, a dependence of the values reported in Table 2 on the nanoparticles size can be noticed. In order to evidence this dependence, the effective diffusion coefficients are plotted in Figure 7 grouped by loading pressure. From this Arrhenius plot, it can be seen that at low temperature the effective diffusion coefficient is minimum in the AE300 sample and maximum in the AE150. The dependence on the nanoparticles size could be related to many factors whose origin is both physical and morphological. As well as for the dependence of the effective diffusion coefficient on the pressure, the dependence on the particles size disappears at high temperature. This effect could be related to the experimental impossibility to distinguish among diffusion kinetics within the experimental errors when they are too fast and only the last part of the kinetics can be measured. To interpret these results it is useful to consider the structure of the nanoparticles. This latter can be described by the core− shell model according to which the topology of the outer part of the nanoparticles, the surface shell, is different with respect to the inner part, the core region. In particular, the shell is more

Table 2. Diffusion Coefficients in nm2/min Worked out by Fitting the Experimental Data Obtained for Thermal Treatments of the Samples AE300, AE150, and AEOX50 at the Investigated Temperatures and Pressures with Equation 1a temperature (°C)

sample

98 98 113 113 127 127 127 143 143 157 177

AE300 AE150 AE300 AE150 AE300 AE150 AEOX50 AE150 AEOX50 AEOX50 AEOX50

6 bar 0.025 0.14 0.12 0.21 0.18 0.8 0.4 1.0 1.0 2.4 4.7

± ± ± ± ± ± ± ± ± ± ±

0.008 0.03 0.05 0.05 0.1 0.3 0.1 0.4 0.2 0.5 1.2

66 bar 0.10 0.4 0.14 0.60 >0.35 0.65 0.8 1.2 1.9 3.5 6

± ± ± ±

0.03 0.1 0.04 0.15

± ± ± ± ± ±

0.15 0.2 0.4 0.4 1.1 2

A part of relative data and best fit curves are shown in Figures 4 and 5. a

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presence of aggregates whose size is about equal to the primary nanoparticles in the AE150. Finally, the equality of the effective diffusion coefficient between the AE300 and AE380 samples having the same radius and different specific surface suggests that the dependence of the diffusion coefficient on the specific surface is negligible and that the assumption that the concentration on the nanoparticles surface instantaneously reaches its equilibrium value is good.

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CONCLUSION The reported results here show that the diffusion kinetics in nanoparticles is affected by the temperature, gas pressure, and nanoparticles size. Diffusion kinetics are faster at higher temperature, higher pressure, and in smaller nanoparticles. Furthermore, the dependence on the nanoparticles size is negligible for nanoparticles with radius less than 7 nm whereas the dependence on the pressure decreases on increasing the temperature. The Fick’s diffusion equation in a sphere with radius equal to the average radius of the primary nanoparticles describes the diffusion kinetics by introducing an effective diffusion coefficient depending on temperature, pressure, and nanoparticles size. For particles of radius lower than 7 nm, an alternative interpretation is also possible that assumes the presence of aggregates that dominate the kinetics and assimilate the small nanoparticles to one of 7 nm radius.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +39 091 23891787. Fax: +39 091 6162461.

Figure 7. Arrhenius plot of the effective diffusion coefficients collected in Table 2.

Notes

The authors declare no competing financial interest.

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34−36

stressed than the core and has a thickness of about 1 nm. The diffusion of oxygen in silica film with a stressed structure and nanometer thickness was found to be faster than that in the bulk silica so the effective diffusion coefficient should increase on increasing the specific surface or equivalently reducing the nanoparticles size, as recently observed.16,37 However, other effects related to the morphological features of the investigated materials could have opposite effects on the dependence of the effective diffusion coefficient on the nanoparticles size. For instance, the presence of aggregates of primary nanoparticles constitutes a departure from spherical geometry leading to an underestimation of the diffusion coefficient if the diffusion kinetics are described by using the spherical approximation. In this context, it is worth to observe that the tendency to aggregate is larger in the smaller nanoparticles so this phenomenon could compensate the expected increase in the diffusion coefficient related to the larger specific surface16,37 and explain the overall decrease found in the present work as reported in Figure 7. The way to describe the diffusion coefficient reported up to now is not the only possible way. The kinetics reported in the panels b and c of Figure 3 show that the kinetics as a function of the time is independent of the nanoparticles size for radius less than 7 nm. According to that, the diffusion kinetics for these materials can be described by using the diffusion coefficient found out in the case of the sample AE150 and substituting the average radius in the eq 1 with the radius of the AE150. This procedure could be physically meaningful under the hypothesis that the major contribution to the effective diffusion coefficient in the AE300 and AE380 is related to the

ACKNOWLEDGMENTS The authors would like to thank the people of the LAMP group (http://www.fisica.unipa.it/amorphous/) for useful discussions, and technical assistance by G. Napoli and G. Tricomi. Partial financial support by the FAE-PO FESR SICILIA 2007/2013 4.1.1.1. project is acknowledged

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