Physics and Chemistry of the Earth 36 (2011) 1700–1707
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Colloid diffusion coefficients in compacted and consolidated clay barriers: Compaction density and colloid size effects Ursula Alonso a,⇑, Tiziana Missana a, Miguel Garcia-Gutierrez a, Alessandro Patelli b, Nairoby Albarran a, Valentino Rigato c a b c
CIEMAT, Environmental Department, Madrid 28040, Spain CIVEN, Nano Fabrication Facility, Venezia – Marguera 30175, Italy LNL-INFN, Materials & Detector Laboratory, Legnaro – Padova I-35020, Italy
a r t i c l e
i n f o
Article history: Available online 17 October 2011 Keywords: Diffusion Colloids Consolidated clay Compacted bentonite RBS
a b s t r a c t An experimental methodology applying the nuclear ion beam technique Rutherford Backscattering Spectrometry (RBS) is used to measure colloid diffusion profiles within three different types of clay: consolidated Opalinus clay (Switzerland), Callovo-Oxfordian clay (France) and FEBEX bentonite (Spain) compacted at different densities. The RBS technique is widely applied in materials science and it was selected because it allows the measurement of concentration profiles at short range distances (lm). The effects of colloid size, clay type and clay density were analyzed with negatively charged Au colloids of 2, 20 and 40 nm. Apparent diffusion coefficients (Da) for gold colloids could be measured and Da values ranged from (1018 to 1019 m2/s). The larger diffusion coefficient was measured for 2 nm colloids in the Opalinus clay with Da(Au 2 nm) = (2.1 ± 0.5) 1018 m2/s. The accessible porosity for colloids is even lower than that measured for anions, since not only anion exclusion but also size exclusion hinders diffusion. For example, 40 nm colloids did not accede at all to bentonite compacted at higher densities. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Compacted bentonite and consolidated clays are suitable barrier materials to isolate the high level radioactive waste in deep geological repositories (DGRs) (Lee and Tank, 1985). For performance assessment (PA) of DGRs, all processes that can affect radionuclide transport rates within these barriers have to be examined. In particular, the colloid-mediated radionuclide transport is of concern because colloids present high sorption for many solutes, and they are considered potential contaminant carriers (Kersting et al., 1999; Kretzschmar et al., 1999; Ryan and Elimelech, 1996). Colloid contribution to radionuclide transport in PA calculations is not explicitly accounted for, because PA calculations only take into account assessed model/parameters, and very little experimental data is available. Colloidal particles expected in a repository scenario could be of different nature: radionuclides themselves precipitated in colloidal form (diameters <2 nm), like for example the actinides (Geckeis and Rabung, 2008); iron and other mineral oxides can be formed upon waste or canister degradation, with diameters from 50 nm to 1 lm (Kaminski et al., 2005); colloids can be also generated from
⇑ Corresponding author. E-mail address:
[email protected] (U. Alonso). 1474-7065/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.pce.2011.10.017
cement materials, with size range from 1 nm to 1 lm (Wieland et al., 2004), or from the engineered clay barriers, with diameters around 100–300 nm (Alonso et al., 2006; Missana et al., 2003; Plaschke et al., 2001); inorganic or organic colloids (1–10 nm) are naturally present in clay formations (Courdouan et al., 2007a,b; Degueldre et al., 1997) or can be generated under certain geochemical conditions (Claret et al., 2003). Not all these colloids are expected to behave in the same way, because they present very different characteristics concerning particle sizes (from 1 nm to 1 lm) and surface charge, amongst others, which may significantly condition their transport behavior. Colloids are considered relevant for radionuclide transport when the geochemical conditions guarantee colloid stability, the bond of radionuclides to colloids is irreversible and when colloids are mobile (Miller et al., 1994). Transport in clays is a diffusiondriven process and, for colloids, it is controlled by the size of the colloids and the relation of colloid size to the medium pore size distribution, the pore space geometry and connectivity. In addition, clays generally present negatively charged surfaces due to substitution of structural ions with less charged ones and therefore, negatively charged colloids (as the majority of mineral under alkaline conditions) may be affected by electrostatic forces, resulting in a smaller volume of pore water available for transport, an effect similar to that observed for anionic exclusion (García-Gutiérrez et al., 2004; Molera et al., 2003; Van Loon et al., 2007).
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Theoretical works predict compacted and consolidated clays to be efficient filters for colloids, (Kurosawa and Ueta, 2001; Voegelin and Kretzschmar, 2002) but scarce experimental data exist. To our knowledge, very few experimental works on colloid diffusion within clays are reported. Reszat and Hendry (2009) studied the transport of dissolved organic carbon (DOC) and polymer colloids of 1.5–6 nm within a non-fractured, clay-rich glacial till from Canada composed by 39% sand, 26% silt, and with a 35% clay content dominated by smectite and measured effective diffusion coefficients around 1010 to 1011 m2/s for colloids smaller than 2 nm, but argued that bigger colloids could not diffuse within the till. Within compacted bentonite, diffusion of organic colloids from 1 to 10 nm was studied, at different compaction densities, by through – diffusion experiments (Wold and Eriksen, 2007, 2003). It was found organic colloid diffusion was not hindered by anion exclusion or by filtering effects, and the measured apparent diffusivities were in the range of 1012 m2/s, independent of the ionic strength or the clay compaction density. Under similar experimental conditions, inorganic colloids, like Au colloids, where filtered within the bentonite (Holmboe and Wold, 2008). Kurosawa and Ueta (2001) and Kurosawa et al. (2006) studied the diffusion of Au colloids within compacted bentonite mixed with sand compacted from 0.8 to 1.8 g/cm3 and found the colloids of 15 nm to be filtered by compacted bentonite at densities higher than 0.8 g/cm3, but the conclusions were based on pore size estimations and not on experimental profile measurements within the solid (Kurosawa et al., 2006; Kurosawa and Ueta, 2001). Within consolidated clays, no experimental work on colloid diffusion has been reported so far; available studies are model calculations, based on clay pore size distribution and available paths, predicting that only colloids smaller than 10 nm may diffuse within these media (Voegelin and Kretzschmar, 2002). In the above-mentioned studies, the colloid diffusion coefficients were never obtained from the direct measurement of profiles in the solid. In fact, it is generally difficult to measure micro-scale diffusion lengths by conventional diffusion experiments. In the present study, a methodology applying the nuclear ion beam technique Rutherford Backscattering Spectrometry (RBS) is selected to measure micro-scale colloid diffusion profiles within clay. Gold colloids of 2, 40 and 100 nm were selected as diffusants, to analyze the dependence on colloid size. Former studies showed that RBS technique is suitable to measure colloid diffusion profiles within granite, but this measurement presented additional difficulties compared to those of solutes (Alonso et al., 2007; Patelli et al., 2006). Starting from these former studies, in the present work the methodology to measure colloid diffusion within clays had to be adapted. The RBS methodology was previously applied within Opalinus clay from the Mont Terri Test site (Switzerland) to measure solute (Sr, Re, Eu and U) diffusion coefficients and it was demonstrated to be suitable to measure diffusants with atomic number Z > 56, provided the diffusion lengths were short enough not to produce signal overlapping from elements naturally present in the clay (Alonso et al., 2009). The selection of Au colloids is therefore appropriate for this study for their atomic weight, stability and their well defined geometry and availability in different sizes. First of all, in-diffusion experiments with the smallest colloids (2 nm) were carried out in the Opalinus under experimental conditions similar to those used to measure that of solutes (Alonso et al., 2009). After demonstrating that the measurement of colloid in consolidated clays is possible the effects of the colloid size on diffusion were analyzed within the consolidated Callovo-Oxfordian clay from Bure site, France (Gaucher et al., 2004).
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The effects of the compaction density was analyzed using compacted FEBEX bentonite (Huertas et al., 2000), at 1.2, 1.4 and 1.65 g/cm3. Diffusion coefficients obtained for the different clays and conditions are discussed.
2. Experimental set-up 2.1. Materials The three clays considered in this study are the consolidated Opalinus and Callovo-Oxfordian clays and the FEBEX bentonite. The Opalinus clay formation is being investigated in the Mont Terri underground laboratory. Opalinus clay is mainly composed by illite (23 ± 2 wt.%), mixed smectite–illite layers (11 ± 2%), quartz (14 ± 4%, calcite (13 ± 8%) and kaolinite (22 ± 2%), chlorite (10 ± 2%), pyrite (1.1 ± 0.5%), siderite (3 ± 1.8%), albite (1 ± 1%), k-feldspar (1 ± 1.6%) and organic carbon (0.8 ± 0.5%) (Thury, 2002; Thury and Bossart, 1999). Millimeter-sized tablets of 1.5 cm in diameter and a few millimeters thick were cut from a cylindrical Opalinus sample extracted from a clay block used for large-scale diffusion studies at laboratory scale (Garcia-Gutierrez et al., 2008; García-Gutiérrez et al., 2006a). Diffusion profiles were measured parallel to the bedding plane of the clay. The average dry density of these clay samples is 2.3 g/cm3 (García-Gutiérrez et al., 2006a). The Callovo-Oxfordian clay from the Bure underground laboratory (France) is mainly composed by a clay fraction (30–65%), with mixed smectite–illite layers (30–35%), illite (10–20 wt.%), quartz (20–35%) a calcite fraction (20–30%) and kaolinite (0–5%), chlorite (0–5%), pyrite (0–2%) and organic carbon (0.2–0.9 wt.%) (Gaucher et al., 2004). Millimeter-sized tablets of 1.5 cm in diameter and a few millimeters thick were cut from a cylindrical sample extracted from a clay block used for large-scale diffusion studies at laboratory scale (García-Gutiérrez et al., 2008). The core comes from the EST433 borehole, 604 m underground that comes from the clay rich section (C2b2) at the middle of the Callovo-Oxfordian formation and whose calcite content is 34%. The Callovo-Oxfordian clay dry density is about 2.2 g/cm3 and the humid density about 2.4 g/cm3. For RBS calculations a value of 2.3 g/cm3 was used. The FEBEX bentonite comes from the Cortijo de Archidona deposit (Almería, Spain). This swelling clay has smectite content greater than 90% (93 ± 2%), with quartz (2 ± 1%), plagioclase (3 ± 1%), cristobalite (2 ± 1%), potassic feldspar, calcite, and trydimite as accessory minerals (Huertas et al., 2000). For RBS analyses, bentonite cylindrical plugs of 1.2 cm diameter and a few millimeters thick were compacted at different dry densities, 1.2, 1.4 and 1.65 g/cm3. The samples are similar to those used for radionuclide diffusion experiments at laboratory scale, as described in (GarcíaGutiérrez et al., 2006b). The bulk density of the FEBEX clay is 2.7 g/cm3. The porosity of theses clays were studied by 3H-PMMA impregnation technique in the same samples used for RBS diffusion analyses (Siitari-Kauppi et al., 2008). The Opalinus clay structure consists of sheet like features with a mean porosity of 20%. In the case of Callovo-Oxfordian samples, PMMA measured porosity value was 17 ± 2%. Opalinus and Callovo-Oxfordian clays showed grain sizes of hundreds of micrometers at this scale. FEBEX samples were broken in the PMMA procedure and their porosities are estimated as function of their compaction density: 55.5% at 1.2 g/cm3, 48% for 1.4 g/cm3 and 39% for 1.65 g/cm3. Prior to diffusion studies, clay tablets were hydrated by introducing the samples into a closed system filled with the synthetic water representative of the different clays: FEBEX bentonite pore-water (Fernández et al., 2004), Opalinus clay pore water (Pearson, 2000) and Callovo-Oxfordian pore water (Melkior et al.,
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2004). The chemical composition and characteristics of the synthetic waters used are given in Table 1. To maintain the clay integrity, direct contact between tablets and water was always prevented. In the first RBS solute diffusion studies performed within Opalinus clay (Alonso et al., 2009) it was observed that direct contact between water and the clay promotes the disintegration of the clay surface, which would affect the RBS measurements. Commercial gold nanoparticles of 2, 20 and 40 nm (BBInternational) were selected. The concentration and main characteristics of the colloid suspensions are included in Table 2. Full details on these colloids can be found in (Alonso et al., 2007). For diffusion studies, the colloid suspensions were used without dilution.
2.2. RBS diffusion methodology Two sets of experiments were performed to study the colloid diffusion within consolidated or compacted clay. The FEBEX bentonite, Opalinus and Callovo-Oxfordian samples were analyzed by RBS to obtain the average clay composition required for RBS spectra simulation, as described in (Alonso et al., 2009). For diffusion experiments, clay samples previously saturated in the correspondent reference pore water (Table 1) were spiked with 40 ll of the selected colloid suspensions described below and sketched in Fig. 1a. In all cases, after colloid addition, clay tablets were placed in a closed box partially filled with the pore water, to prevent de-hydration of clay during diffusing time, but avoiding direct contact between the water and the clay. Experimental diffusion times ranged from 2 to 7 days. First in-diffusion experiments were carried out in the Opalinus consolidated clay with the smaller Au colloids (2 nm), with expected deeper diffusion than the 20 or 40 nm colloids, to test whether the methodology was sensitive enough to evaluate colloid diffusion under conditions equivalent to that used to measure solute diffusion coefficients within the same clay (Alonso et al., 2009). Once the diffusion of smaller colloids could be proven, the effects of colloid size were analyzed within the consolidated Callovo-Oxfordian clay from Bure site, France (Gaucher et al., 2004) by spiking the samples with 20 or 40 nm colloids. Thirdly, colloid diffusion was analyzed in compacted FEBEX bentonite, Spain (Huertas et al., 2000), at different compaction densities (1.2, 1.4 and 1.65 g/cm3). Experiments were carried out maintaining the geochemical conditions naturally imposed by the clays so that all processes affecting colloid mobility are accounted for in the most real possible conditions. Before RBS measurements, the sample surfaces were cleaned with ethyl alcohol, to eliminate colloids blocked at the outer clay surface which can bias the measurement of concentration profiles within the clay. All samples were covered with a carbon layer of about 100 Å to prevent electrostatic charge effects during RBS ion beam irradiation. Different surface areas of 1 mm2 were analyzed on the clay samples by RBS.
RBS is generally used to determine the concentration of trace elements heavier than the major constituents of the substrate in the samples near-surface region (several lms). A high energy ion beam (4He+, 2.2 MeV) is directed at the sample, parallel to the diffusion profile (as sketched in Fig. 1b). The energy of the backscattered particles depends on the masses of the scattering atoms and on their depth in the sample and are recorded in a RBS spectrum. For elastic collision, the amount of energy transferred to the sample atom and to the backscattered ion depends on the mass ratio of the incident ion and the sample atom. Therefore the measurement of the backscattered ion energy allows the elemental sample composition to be derived. If the incident ion does not hit the sample atom at the surface, but instead hits a deeper lying atom, the backscattered ion loses energy proportionally to its penetration depth and the samples stopping power (Chu et al., 1978). This means RBS can also be used to define a depth profile of the sample composition. Fig. 1c schematics an RBS spectrum of a clay sample where Au diffused. In the spectrum, the signals of all elements composing the material appear superimposed. If an element is homogenously distributed in depth its individual signal is steplike. The individual signal starts from a maximum energy corresponding to the backscattered energy of the incident particles interacting with the element located at the surface. If the collision takes place at depth, the backscattered particle has to travel through the material before and after the collision, and so the signal from this collision will have lower energy depending on the scattering event depth. The energies are higher for higher atomic mass elements, as expected for elastic collisions. Tracer diffusion is revealed by broad peaks with a decreasing tail at lower energies. By increasing the diffusion length, the peak tail size and length increases. In some cases the diffusion signal can be superimposed on signal from other elements composing the material. Signal overlapping hinders precise evaluation of diffusion lengths. Moreover, when Au signals attributed to presence of colloids deposited over the clay surface were detected in the RBS spectra, even after cleaning, this first surface layer was not accounted for diffusion calculations (Alonso et al., 2009). RBS measurements were performed at the Laboratori Nazionali di Legnaro (INFN-LNL, Italy) with a HVEC 2.5 MeV Van de Graaff accelerator with 4He+ particles at 2 MeV, 40 nA and with a scattering angle of 160°. Within the experimental conditions, it is in principle possible to detect heavy elements at depths around 5 lm with a depth resolution of 50 nm and with detection limits around 1012 atoms/cm2. RBS spectra were analyzed with the X-RUMP code (Doolittle, 1986; http://www.genplot.com/). This computational algorithm simulates the backscattering phenomenon and provides a highly effective tool for interpreting RBS data. Spectrum simulation is performed, in an iterative manner, by defining a theoretical sample substrate – obtained from the RBS analyses of the un-treated clays (without colloids), with a specific elemental composition and structure, to achieve an optimum set of parameters allowing a fit of a given spectrum. Impurities and diffusion profiles are simulated
Table 1 Chemical composition of the synthetic pore waters used in RBS diffusion experiments. Element +
Na K+ Mg2+ Ca2+ Sr2+ Cl SO@ 4 CO@ 3 =HCO3 Ionic strength (M) pH
Bentonite pore water (1.65 g/cm3) (mol/L)
Opalinus pore water (mol/L)
Callovo-Oxfordian pore water (mol/L)
1.29 101 1.11 103 1.71 102 1.54 102 – 9.27 102 4.52 102 9.20 104 0.66 7.50
2.40 101 1.61 103 1.69 102 2.58 102 5.05 104 3.00 101 1.41 102 4.76 104 0.39 7.8
7.39 103 2.56 103 6.58 103 8.73 103 – 3.47 102 1.77 103 1.64 103 0.40 7.2
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U. Alonso et al. / Physics and Chemistry of the Earth 36 (2011) 1700–1707 Table 2 Summary of the main characteristics of the ‘‘as-received’’ gold colloids. Colloids Au 2 nm Au 20 nm Au 40 nm
Particles (ml) 13
15 10 7 1011 9 1010
Concentration (ppm)
Conductivity (lS/cm)
Zeta potential (mV)
pH
12.1 ± 0.2 56.8 ± 0.2 58.2 ± 0.2
8.0 ± 0.2 8.0 ± 0.2 8.0 ± 0.2
31.3 ± 0.7 32.5 ± 1.2 34.1 ± 1.5
6.19 6.06 6.16
(a) Diffusion set-up (c) RBS spectrum
Au colloids
Energy (MeV) 8
1.0
1.5
2.0
2.5
3.0
3.5
O
Normalized Yield
Clay Closed vessel with water
(b) RBS measurements 4He2+,
6
Si K
4
Au Fe
2
E0 0 200
300
400
500
600
700
800
900
Channel Ei
The number of scattered ions and their energy provides an RBS spectrum.
Fig. 1. Sketch of the experimental set-up. (a) Clay samples placed previously saturated in the reference pore water in a closed box partially filled with the pore water are spiked with 40 ll of the selected colloid suspensions. (b) Once the experimental diffusion time lasted, for RBS measurements a high energy ion beam (4He+, 2.2 MeV) is directed at the sample, parallel to the diffusion profile. (c) The detection of the backscattered particles and their energies provides an RBS spectrum, that contains the information on the sample composition and tracer profiles.
by introducing a gold concentration profile defined by the following equation:
x C ¼ C B erfc pffiffiffiffiffiffiffiffiffi 2 ðDtÞ
ðE:1Þ
This equation is a solution of Fick’s second law, which satisfies the experimental boundary conditions for concentration C = CB, x = 0, t > 0 and the initial conditions C = 0, x > 0, t = 0 is (Crank, 1956). From the experimental conditions, we can assume that the colloid access is very limited and that the surface concentration is maintained practically constant. In RBS analysis, the natural distance units are given in atoms/ cm2 and to convert the RBS units to a distance scale the density of the solid must be considered: 2.3 g/cm3 for the Opalinus and Callovo-Oxfordian clays and a grain density of 2.7 g/cm3 for the FEBEX bentonite. Major sources of uncertainty in the apparent diffusion coefficient determination by RBS are related to the chemical heterogeneities of the clay sample (for example variations of Fe or K content) and the bulk density considered for the calculations. These uncertainties were analyzed elsewhere (Alonso et al., 2009) and it was shown that even considering extreme values, the apparent diffusion coefficients would vary only within a factor of 2. 3. Results and discussion 3.1. Clay characterization by RBS The FEBEX bentonite, Opalinus and Callovo-Oxfordian samples were first analyzed by RBS to obtain the average clay composition
required for RBS spectra simulation, as described in (Alonso et al., 2009). No appreciable signal was detected in any clay spectrum at energies corresponding to elements heavier than Ba (Z = 56) and no Au was detected in clays. Table 3 presents the mean elemental compositions (in atomic wt.%) obtained for the FEBEX bentonite, the Opalinus and the Callovo-Oxfordian clays from the simulated RBS spectra. The values are comparable to that obtained by chemical analyses for the clays (Fernandez, 2007; Fernández et al., 2004). Only elements with composition higher that 0.001 atomic % were considered in the simulation. The relative analytical error is below 5% for heavy elements, but errors can be higher for lighter elements that are present in low concentrations as, for example, carbon. The obtained compositions are used in all further simulations just allowing small variations of some higher elements content (Fe, K, ..) and introducing adequate Au profiles to fit a given spectrum.
3.2. Colloid diffusion within consolidated clay Fig. 2A shows, the RBS spectrum measured on Opalinus clay spiked with 2 nm Au colloids and kept in contact 2 days. In an RBS spectrum, the signals of all elements composing the material appear super-imposed but starting from a maximum energy correspondent to the element located at the surface. In Fig. 2A, the maximum energies of some elements are indicated. Details on the interpretation of a RBS spectrum of Opalinus clay can be found in Alonso et al. (2009). The higher mass element detected in the as-received Opalinus samples is Ba (channel 869). In the inset, the same spectra are presented limited to the region of interest for Au to better appreciate
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Table 3 Mean elemental compositions obtained by simulating the RBS spectra measured on the ‘‘as-received’’ FEBEX bentonite, Opalinus and Callovo-Oxfordian clays. Concentration values presented in atomic wt.%. Element
Composition in atomic wt.% measured by RBS
C O Na Mg Al Si S Cl K Ca Ti Mn Fe Sr Ba
Bentonite
Opalinus
Callovo-Oxfordian
– 64.5 1 1.9 15 14.9 – 5 101 5 101 5 101 1.2 101 8 101 3 101 1.8 102 5 103
4.4 65 6.1 101 2.1 7.9 16 1.0 101 1.4 102 2.2 1.7 1.2 101 1.2 102 1.4 1.6 102 1.8 102
4.7 102 63.6 6.5 101 1.1 11.2 12.7 1.1 1.5 4.5 1.9 1.2 101 1.3 102 1.5 1.7 102 1.9 102
Energy (MeV) 1.0
20
1.5
2.0
(a)
Opalinus clay "as recieved" Opalinus clay + Au colloids 20 nm 2 days Energy (MeV) 1.2
Normalized Yield
Normalized Yield
15
10
1.7
1.8
1.9
2.0
2.1
Opalinus clay "as recieved" Opalinus clay + Au colloids 2 nm 2 days Simulations
1.0 0.8
Au
0.6 0.4 0.2 Sr
0.0 700
750
5
Ba
Au
800
850
900
Channel
C
O
0 200
300
Mg Si
400
500
S
K
600
Fe
Sr
700
Ba Au
800
the Au signal (at channel 900, energy 2.03 MeV), that indicates Au colloids entered in the clay. Spectrum simulation is performed defining the Opalinus clay composition presented in Table 3 and introducing an Au concentration profiled defined by (E.1). The obtained simulation is plotted as continuous line in Fig. 2A. The profile required to simulate the spectrum is shown in Fig. 1B. From this profile the apparent diffusion coefficient obtained for the 2 nm Au colloids within Opalinus clay is Da(Au 2 nm) = (2.1 ± 0.5) 1018 m2/s. Experiments analyzing the diffusion of bigger colloids within consolidated clay were performed with Callovo-Oxfordian samples. Fig. 3 shows the RBS spectra obtained within Callovo-Oxfordian clay contacted to Au colloids of 20 nm and 40 nm during 7 days. A small Au peak where detected in the spectra but to facilitate the comparison it is necessary to expand the spectra limited to the region of energy of interest for Au (energies 1.5–1.9 MeV). Clear Au signals can be appreciated in both cases, which were not detected in the ‘‘as received’’ Callovo-Oxfordian clay (spectrum also included in Fig. 3). Both Au signals indicated that colloids with a size larger than 2 nm can accede within the consolidated clay but they present different behavior. The widen Au peak observed for the 20 nm Au colloids, with a pronounced tail going to lower energies, indicates colloid access. The thin but taller Au signal observed for the Au colloids of 40 nm, indicates that diffusion is limited and that colloids are being blocked at the outer surface. The observed differences (diffusion vs. surface retention) are confirmed by the simulations. Spectra were analyzed as previously described and fit with the concentration profiles of E.1 to obtain the apparent diffusion coefficients. Da values are: Da(Au 20 nm) = (1.7 ± 0.5) 1018 m2/s, Da(Au 40 nm) = (1.0 ± 0.5) 1019 m2/s. The obtained apparent colloid diffusion coefficients are clearly smaller than those of colloids in free water that can be calculated by Stokes–Einstein equation (from 9 1011 m2/s for 2 nm colloids to 1 1011 m2/s for 40 nm colloids). Da obtained for smaller 2 nm colloids is one order of magnitude lower than the one measured by RBS, under equivalent experimental conditions, for an anionic spe17 cie Da ðReO m2 =s (Alonso et al., 2009). This 4 Þ ¼ ð3:4 0:8Þ 10 indicates that, apart from charge exclusion, colloid diffusion is being hindered by pore size exclusion, being its accessible porosity substantially reduced. Colloid sorption within the clays cannot be
900
Energy (MeV)
Channel 4
-3
(b) 1.5x10
-3
1.0x10
5.0x10
Au colloids 2 nm 2 days in Opalinus clay Au 2 nm C (x,t) = Cs*erfc((x-0)/(2*sqrt(Da*t))
3
Normalized Yield
Concentration (atomic weight %)
2.0x10
-3
-4
1.5
1.6
4000
6000
8000
2
Au 20 nm Au
10000
2
Distance in RBS units (atoms/cm ) Fig. 2. (a) RBS spectrum measured on Opalinus clay kept in contact with 2 nm Au colloids during 2 days (w) and RBS spectrum of the ‘‘as received’’ Opalinus clay (j). In the inset, the same spectra are presented limited to the region of interest for Au. Spectra simulations are plotted as continuous lines and (b) Au concentration profile (E.1) introduced to simulate the RBS spectra of Opalinus sample contacted with Au colloids of 2 nm during 2 days.
1.9
Au 40 nm
0.0 2000
1.8
Callovo-Oxfordian "as recieved" Callovo-Oxfordian + Au colloids 20 nm 7 days Callovo-Oxfordian + Au colloids 40 nm 7 days Simulations
1
0
1.7
0 600
650
700
750
800
Channel Fig. 3. RBS spectra measured on Callovo-Oxfordian clay spiked with Au colloids of 20 nm (w) or 40 nm (d) during 7 days. The spectrum of the ‘‘as received’’ CallovoOxfordian (j) is also included for comparison. Spectra simulations are plotted as continuous lines.
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3.3. Colloid diffusion within compacted bentonite at different dry densities Fig. 4 shows the RBS spectra measured on bentonite clay compacted at 1.2 g/cm3, after contact with gold colloids of 20 nm during 2 or 7 days, limited to the region of interest for Au. A RBS spectrum of the as received bentonite is also included for comparison. Again the Au signal presents a peak shape that decreases within lower energies indicating that Au colloids acceded to the compacted bentonite at 1.2 g/cm3 but being mainly located at the near surface. Fig. 5A shows a comparison of RBS spectra measured for the same colloids (20 nm) and the same contact time (7 days) within compacted bentonite at different dry densities (1.2, 1.4 and 1.6 g/ cm3). In all cases the Au signal is detected, the peak is higher and wider at the lower compaction density, indicating higher concentration and longer diffusion.
Energy (MeV) 0.6
1.6
Normalized Yield
1.7
1.8
1.9
(a)
Bentonite "as recieved" Bentonite 1.2 g/cm3 + Au colloids 20 nm 7 days Bentonite 1.4 g/cm3 + Au colloids 20 nm 7 days Bentonite 1.6 g/cm3 + Au colloids 20 nm 7 days Simulations
0.5
0.4
Au 20 nm
0.3
0.2
0.1 Ba
Au
0.6 00
(b)
Bentonite "as recieved" Bentonite 1.2 g/cm3 + Au colloids 40 nm 7 days Bentonite 1.4 g/cm3 + Au colloids 40 nm 7 days Simulations
0.5
Normalized Yield
discarded and colloid mechanical trapping is also feasible, but it is difficult to separate the contribution of each mechanism. Accessible porosities measured in the Opalinus clay varies from a 15% for tritium (conservative element) to an 8% for chloride (Cl) that suffers anion exclusion (Garcia-Gutierrez et al., 2008), and similar values are measured within Callovo-Oxfordian (average accessible porosity for Cl 8.8% (Descostes et al., 2008). The mercury porosity for the Callovo-Oxfordian clay was measured by Boulin et al. (2008) to be a 14%, mainly made of mesopores lower than 2 lm (diameters around 100 nm) with a 25% above 50 nm, surrounded by smaller pores (around 20 nm). The existence of pores larger than 2 lm pores in the undamaged rock was not clearly proven. The pore size distribution of the Opalinus clay, presents a 20% pore of diameters bigger than 2 nm, a 55% of pores between 2 and 50 nm and a 25% of voids above 50 nm but lower than 20 lm. Voegelin and Kretzschmar (2002) model calculations predicted that colloids smaller than 10 nm could travel significant distances within Opalinus clay. However, the obtained diffusion coefficients (1018 to 1019 m2/s) are clearly smaller than those used by these authors for the calculations (in the range of 1011 m2/s).
0.4
0.3
Au 40 nm
0.2
0.1 Sr
0.0 650
Ba
700
Au
750
800
Channel Fig. 5. (a) RBS spectra measured on bentonite samples contacted to Au colloids of 20 nm during 7 days compacted at different dry densities 1.2 g/cm3 (j), 1.4 g/cm3 (w) and 1.6 g/cm3 (d). The spectrum of the ‘‘as received’’ bentonite (N) is also included for comparison and (b) RBS spectra obtained on compacted bentonite contacted to 40 nm Au colloids at 1.2 g/cm3 (j) and 1.4 g/cm3 (w) compaction densities. Spectra simulations are plotted as continuous lines.
Energy (MeV)
Normalized Yield
0.5
1.7
1.8
1.9
Gold colloid 20 nm - Profiles in compacted bentonite -3
Concentration (atomic weight %)
0.6
1.6
Bentonite "as recieved" Bentonite 1.2 g/cm3 + Au colloids 20 nm 2 days Bentonite 1.2 g/cm3 + Au colloids 20 nm 7 days Simulations
0.4
Au 20 nm
0.3
0.2
0.1
1.0x10
-4
9.0x10
3
Bentonite 1.2 g/cm 3 Bentonite 1.4 g/cm 3 Bentonite 1.6 g/cm
-4
8.0x10
-4
7.0x10
-4
6.0x10
-4
5.0x10
-4
4.0x10
C (x,t) = Cs*erfc((x-0)/(2*sqrt(Da*t))
-4
3.0x10
-4
2.0x10
-4
1.0x10
0.0 0
Au
0.0 650
700
750
1000
2000
3000
4000
Distance in RBS units (atoms/cm) 800
Channel Fig. 4. RBS spectra measured on bentonite clay compacted at 1.2 g/cm3, after contact with gold colloids of 20 nm during 2 days (j) or 7 days (w). The spectrum of the ‘‘as received’’ bentonite (N) is also included for comparison. Spectra simulations are plotted as continuous lines.
5000
2
Fig. 6. Au concentration profiles (E.1) introduced to simulate the RBS spectra of the bentonite samples contacted to Au colloids of 2 nm at three different compaction densities (RBS spectra presented in Fig. 4a).
Fig. 5B shows the RBS obtained in bentonite at different dry densities (1.2, 1.4 g/cm3) for bigger Au colloids (40 nm). It can be
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U. Alonso et al. / Physics and Chemistry of the Earth 36 (2011) 1700–1707 Table 4 Average diffusion coefficients measured by RBS (Da) for gold colloids of 20 and 40 nm within Opalinus and Callovo-Oxfordian Clays and in FEBEX bentonite compacted at different densities: 1.2, 1.4 and 1.65 g/cm3. n.m. = not measured. Clay Opalinus Callovo-Oxfordian Bentonite 1.2 g/cm3 Bentonite 1.4 g/cm3 Bentonite 1.6 g/cm3
Da m2/s (Au 2 nm) 18
(2.1 ± 0.5)10 n.m n.m n.m n.m
seen that no Au signal was detected in the samples compacted at density of 1.4 g/cm3. The same occurred for higher densities, being their spectra totally equivalent to that measured for the ‘‘asreceived’’ clay, indicating the Au colloids of 40 nm did not enter in the clay. Au signal was still clearly detected in the spectra of the bentonite at the 1.2 g/cm3 density even if the signal was lower than that observed for smaller colloids (Fig. 5A). Fig. 6 shows the Au concentration profiles (E.1) required to simulate the RBS spectra shown in Fig. 5 (plotted as continuous lines). The obtained diffusion coefficients, for the different colloids and the different compaction densities are presented in Table 4. The obtained Da values (1019 to 1020 m2/s) are glaringly smaller than those measured even for anions in compacted bentonite approximately 1011 m2/s for Cl and 1012 m2/s for SO@ 4 (see for example (García-Gutiérrez et al., 2006b). A dependence of colloids Da on the compaction density is observed (similar to that observed for anionic species in FEBEX bentonite) but, obviously the behavior cannot be directly compared due to steric exclusion in the case of bigger particles at higher densities. Indeed, the FEBEX bentonite is swelling clay whose porosity and size distribution depends on the compaction density. Mercury intrusion analyses were performed elsewhere in FEBEX bentonite with hygroscopic water content (Huertas et al., 2006). The measured pore size distribution was divided in interlamellar pores (0.1–1 nm), intra-aggregate pores lower than 2 nm and interaggregate pores from 2 to several micrometers in size. Measurements at different compaction densities indicated that the volume of pores smaller than 200 nm was equivalent at all bentonite compaction densities, the percentage of mesopores (6 nm–100 nm) increases while the percentage of large pores decreases increasing the compaction density (Huertas et al., 2006). The accessible porosities for negatively charged species are reduced because of anion exclusion. García-Gutiérrez et al. (2004) measured accessible porosities for Cl within bentonite, with deionised water previously equilibrated with the bentonite, and at different densities and obtained values changed from a 17% at 1.0 g/cm3 to 2.5% at 1.65 g/cm3. Considering that the percentage of larger pores decreases at higher densities, it is expected that colloids do not accede at higher densities. Comparatively, the obtained Da are higher in consolidated clays than in compacted bentonite, since there is not enough macropores in compacted clay and the pore network >20 nm is poorly connected. 4. Conclusions The methodology applied allowed evaluating diffusion coefficients for Au colloids (2, 20 and 40 nm) within compacted and consolidated clays. In all the cases, very low apparent diffusion coefficients could be measured within a range of 1 1018 to 1 1019 m2/s, and a dependence on both the colloid size and compaction density was observed. Within compacted bentonite, at density higher than 1.4 g/cm3, the access of colloids bigger than 20 nm was not detected, while colloids of 40 nm could be detected in the
Da m2/s (Au 20 nm)
Da m2/s (Au 40 nm)
n.m (1.7 ± 0.5)1018 (5.0 ± 0.5)1019 (7.6 ± 1.5)1020 (5.7 ± 1)1020
n.m (1.0 ± 0.5)1018 (1.6 ± 0.5)1019 No Au detected No Au detected
Callovo-Oxfordian clay). This confirms clays are efficient filters for colloids because the colloid size to clay pore size ratio hinders diffusion in addition to charge exclusion. The direct measurement of low gold colloid diffusion coefficients within the clay samples indicates that the methodology is appropriate to determine the contribution of colloidal transport to radionuclide migration. Acknowledgments This work was partially supported by the EU within the FUNMIG project (Ref. FP6-516514) and by the Spanish Ministry of Science and Innovation (MICINN) under the project CROKIS (Ref. CGL 2008-04721/BTE). The Laboratori Nazionali di Legnaro (LNL-INFN, Legnaro-Padova, Italy) is greatly acknowledged for providing access and support for the RBS measurements at the AN2000 accelerator. The authors are grateful to Dr. Coelho and Prof. Bruno and one anonymous referee for their helpful revision that significantly improved the final manuscript. References Alonso, U., Missana, T., Geckeis, H., García-Gutiérrez, M., Turrero, M.J., Möri, R., Schäfer, T., Patelli, A., Rigato, V., 2006. Role of inorganic colloids generated in a high-level deep geological repository in the migration of radionuclides: open questions. J. Iberian Geol. 32, 79–94. Alonso, U., Missana, T., Patelli, A., Rigato, V., Ravagnan, J., 2007. Colloid diffusion in crystalline rock: an experimental methodology to measure diffusion coefficients and evaluate colloid-size dependence. Earth Planet. Sci. Lett. 259, 372–383. Alonso, U., Missana, T., Gutiérrez, M.G., Patelli, A., Siitari-Kauppi, M., Rigato, V., 2009. Diffusion coefficient measurements in consolidated clays determined by RBS micro-scale profiling. Appl. Clay Sci. 43, 477–484. Boulin, P.F., Angulo-Jaramillo, R., Daian, J.-F., Talandier, J., Berne, P., 2008. Pore gas connectivity analysis in Callovo-Oxfordian argillite. Appl. Clay Sci. 42, 276–283. Chu, W.-K., Mayer, J.W., Nicolet, M.-A. (Eds.), 1978. Backscattering Spectrometry. Academic Press. Claret, F., Schäfer, T., Bauer, A., Buckau, G., 2003. Generation of humic and fulvic acid from Callovo-Oxfordian clay under high alkaline conditions. Sci. Total Environ. 317, 189–200. Courdouan, A., Christl, I., Meylan, S., Wersin, P., Kretzschmar, R., 2007a. Characterization of dissolved organic matter in anoxic rock extracts and in situ pore water of the Opalinus clay. Appl. Geochem. 22, 2926–2939. Courdouan, A., Christl, I., Meylan, S., Wersin, P., Kretzschmar, R., 2007b. Isolation and characterization of dissolved organic matter from the Callovo-Oxfordian formation. Appl. Geochem. 22, 1537–1548. Crank, J., 1956. The Mathematics of Diffusion. Claredon Press, Oxford, p. 14. Degueldre, C., Scholtis, A., Thomas, B., 1997. A sampling and analysis exercise at Mt. Terri (June/July 1997) Analytical results. Mt Terri Project Report TN 97-20. Switzerland. Descostes, M., Blin, V., Bazer-Bachi, F., Meier, P., Grenut, B., Radwan, J., Schlegel, M.L., Buschaert, S., Coelho, D., Tevissen, E., 2008. Diffusion of anionic species in Callovo-Oxfordian argillites and Oxfordian limestones (Meuse/Haute–Marne, France). Appl. Geochem. 23 (4), 655–677. Doolittle, L.R., 1986. A semiautomatic algorithm for Rutherford backscattering analysis. Nucl. Inst. Methods Phys. Res. B 15, 227–231. Fernandez, A.M., 2007. Physical, chemical and mineralogical characteristics of the Opalinus clay, Callovo-Oxfordian and Boom clay minerals. CIEMAT Technical Report P.I.D. 3.2.1B Madrid, Spain. Fernández, A.M., Baeyens, B., Bradbury, M., Rivas, P., 2004. Analysis of the porewater chemical composition of a Spanish compacted bentonite used in an engineered barrier. Phys. Chem. Earth, Parts A/B/C. 29, 105–118. García-Gutiérrez, M., Cormenzana, J.L., Missana, T., Mingarro, M., 2004. Diffusion coefficients and accessible porosity for HTO and 36Cl in compacted FEBEX bentonite. Appl. Clay Sci. 26, 65–73.
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