Effet de l’aluminium

4.2 Effet de l’aluminium

4.2.1 Role of Al3+ on rheology and nano-structural changes of sodium silicate and aluminosilicate glasses and melts.

Charles Le Losq, Daniel R. Neuville, Pierre Florian, Grant Henderson et Dominique Massiot Manuscript soumis à la revue Géochimica et Cosmochimica Acta

Résumé :

Les alumonisilicates d’alcalins fondus sont des matériaux importants pour les domaines de recherche en science de la Terre et pour l’industrie verrière. L’aluminium influence les propriétés des verres et liquides, et ses effets dépendent fortement de sa concentration. Cet article présente une étude d’alumi-nosilicates fondus et vitreux compris dans le système Na2O-Al2O3-SiO2, contenant 75 mol% SiO2 et différents rapports Al/(Al+Na). La spectroscopie RMN MAS 1D du 23Na et la spectroscopie Raman indiquent toutes les deux que le rôle du Na+ change en fonction de la proportion d’Al2O3. Dans les compositions pauvres en aluminium, les distances interatomiques Na-O sont plus courtes, et le Na, en coordinence ∼ 6, joue un rôle de modificateur de réseau. Lorsque l’on remplace Na par Al, la spectro-scopie RMN MAS 1D du23Na et du29Si ainsi que la spectroscopie Raman montrent que les espèces Q3 se transforment en espèces Q4, et que les distances Na-O augmentent, en accord avec une augmentation de la coordinence du Na+. Ce dernier devient alors compensateur de charge de l’Al3+, qui est incor-poré en espèces Q4 dans les domaines les plus polymérisés du réseau (espèces Q4

(4Si)). Ces changements structuraux augmentent fortement la viscosité des aluminosilicates fondus, qui atteint un maximum lorsque Al/(Al+Na) = 0.5 (composition albite). En passant le joint tectosilicaté, où Al/(Al+Na) = 0.5, les spectres RMN 1D MAS de l’27Al montrent que de l’Al[5] est présent dans les verres. Les T g et les fragilité plus élevées des aluminosilicates peralumineux fondus par rapport à celles des tectosili-cates fondus indiquent que, proche de la T g, l’Al[5] favorise la connectivité du réseau, alors qu’à hautes températures, c’est une espèce transitoire permettant la diffusion des NBOs et BOs dans les liquides. Lorsque la température augmente, la formation d’Al[5] peut aussi permettre d’expliquer la dépendance à la température des capacités calorifiques des tectosilicates et aluminosilicates peralumineux fondus.

Role of Al3+ on rheology and nano-structural changes of sodium silicate

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and aluminosilicate glasses and melts.

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Charles Le Losq1, Daniel R. Neuville1*, Pierre Florian2,3, Grant Henderson4 and Dominique Massiot2,3

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1 Géochimie & Cosmochimie, CNRS-IPGP, Paris Sorbonne Cité, 1 rue Jussieu, 75005 Paris,

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neuville@ipgp.fr

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2 CNRS, UPR3079 CEMHTI, 1D avenue de la Recherche Scientifique, 45071 Orléans cedex2, France

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3 Université d'Orléans, Faculté des Sciences, Avenue du Parc Floral, BP 6749, 45067 Orléans

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cedex 2, France

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4 Geology department, University of Toronto, 22 Russel Street, Toronto, ON, Canada.

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Abstract:

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Alkali aluminosilicate melts are material of prime importance for both the geology research

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field and the glass making industry. Aluminium greatly influences glasses and melts properties, and

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its effect strongly depends on its concentration. This paper present a study of Na₂O-Al₂O₃-SiO₂

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glasses and melts, containing 75 mol% SiO₂ and different Al/(Al+Na) ratios. 23Na 1D MAS NMR and

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Raman spectroscopy both highlight the change of the role of Na+ with Al₂O₃ content. In

aluminium-20

poor composition, Na-O distances are short and Na is in coordinence ~6 and acts as a network

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modifier. When Al replaces Na, 29Si and 23Na 1D MAS NMR and Raman spectroscopies show that Q3

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species transform in Q4 species, and that Na-O distances increase, in agreement with an increase of

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the Na coordination number. Then Na+ becomes charge compensators of Al3+. Interestingly, NMR

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results show that the latter are incorporated in Q4 species in the most polymerized domains of the

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glass network (Q4

(4Si) species). These structural changes increase drastically the melt viscosity,

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which is maximum for Al/(Al+Na) = 0.5 (albite composition). When crossing the tectosilicate join,

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Al/(Al+Na)=0.5, 27Al 1D MAS NMR spectra display that Al[5] is present in glasses. The higher Tg and

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the lower fragility of peraluminous melts compared to the tectosilicate albite melt indicate that,

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near the Tg, Al[5] enhances the network connectivity while at high temperature, it is a transient and

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dynamic specie allowing the diffusion of NBO and BO in melts. Formation of Al[5] when increasing

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the temperature can also account for the temperature dependent heat capacity of tectosilicate and

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peraluminous melts.

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1. Introduction

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The structure and properties of glasses, melts and minerals in the ternary Na₂O-Al₂O₃-SiO₂

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system are important for both geological and industrial processes. These three oxide components

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constitute more than 80% of haplo-andesitic and -granitic magmatic systems, and are used in the

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glass (window glass) and glass ceramic (analogue of LAS glass ceramic) industries. The Na2

O-40

Al₂O₃-SiO₂ mineral phase diagram is well known (Shairer and Bowen, 1956), and the structure and

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properties of sodium silicate and aluminosilicate glasses and melts have been previously

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characterized using different tools: viscosity measurements (Riebling, 1966; Taylor and Rindone,

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1970; Toplis et al. 1997a,b); heat capacity measurements (Richet and Bottinga, 1984; Navrotsky

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et al. 1982; Roy and Navrotsky, 1984; Tangemann and Lange, 1998; Webb, 2008); NMR

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spectroscopy (Maekawa et al., 1991a; George and Stebbins, 1996; Stebbins and Xue, 1997; Lee

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and Stebbins, 2003, 2009); Raman spectroscopy (Seifert et al., 1982; Mysen et Frantz 1994a;

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Neuville and Mysen, 1996); XANES at the Na K-edge (Neuville et al., 2004b) and X-ray radial

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distribution analysis (Taylor and Brown, 1979a,b).

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At high temperature and at constant SiO₂ content, previous experiments have shown that

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viscosities increase when Al substitutes for Na (for the ratio Al/(Al+Na) =

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mol%Al₂0₃/(mol%Al₂0₃+mol%Na₂0) <0.5, in the peralkaline field), reach a maximum when

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Al/(Al+Na) is around 0.5 and decrease for Al/(Al+Na) higher than 0.5 (in the peraluminous field;

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Riebling, 1966; Toplis et al. 1997a,b). Near the glass transition temperature, viscosity variations

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still show a large increase when Al substitutes for Na for Al/(Al+Na) < 0.5. However, when

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Al/(Al+Na) ≥ 0.5 viscosities increase slightly (Taylor and Rindone, 1970). Several structural models

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have been proposed to interpret these observations. Day and Rindone (1962a,b,c) postulated that

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for Al/(Al+Na) ratios lower than – or equal to – 0.5, all Al₂O₃ ions are distributed in AlO₄ species.

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This has been confirmed by several studies (Day and Rindone, 1962c; Taylor and Brown, 1979b;

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Seifert et al., 1982; McMillan et al., 1982; McKeown et al., 1984; Merzbacher and White, 1988; Zirl

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and Garofalini, 1990; Neuville and Mysen, 1996; Lee, 2004; Lee et al., 2006). Day and Rindone

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(1962a,b,c) also assumed that for a Al/(Al+Na) ratio > 0.5, i.e. with excess aluminum, Al3+ and

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Na+ ions will go into a higher coordination state, probably 6 and 9 respectively. Recent XANES

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measurements at the Na K-edge made on minerals and glasses, as well as 23Na NMR observations

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have validated this statement (George and Stebbins, 1996; Neuville et al., 2004b). From other

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viscosity and density measurements, Riebling (1966) reached the same conclusions. In order to

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explain his observations, he suggested that some Al in five or six fold coordination may exist when

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Al/(Al+Na) > 0.5. On the other hand, Lacy (1963) proposed a different model. He assumed that,

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when Al/(Al+Na) > 0.5, all Al3+ ions are in a four-fold coordination state and three tetrahedra (2

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SiO₄ and 1 AlO₄ tetrahedra) share only one oxygen atom to form “triclusters”. Toplis et al. (1997b)

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followed Lacy’s idea in order to explain the viscosity maximum observed at high temperature near

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the tectosilicate join. Unfortunately, oxygen “triclusters” have not been observed experimentally

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except in calcium aluminates (Iuga et al., 2005).

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In the present communication, we have studied the effect of the Al/(Al+Na) ratio, at constant

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SiO₂ concentration, on the structure and properties of glasses and melts using viscosity

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measurements, NMR and Raman spectroscopy. We show that when Al substitutes for Na, it first

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results in an increase in the melt’s viscosity and polymerization. Observed structural changes are

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consistent with important thermodynamical and rheological changes depending on glass chemistry.

is added.

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2) Experimental methods

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2.1. Starting Materials

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Six samples (Table 1) were made by melting a mixture of Al₂O₃, Na₂CO₃ and SiO₂ powders

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previously dried at 1100°C (SiO₂ and Al₂O₃) and 350°C (Na₂CO₃), following the protocol already

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described in Schairer and Bowen (1956) and Neuville (2006). Approximately100g of powders were

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crushed in an agate mortar in ethanol for 1 hour. After that, decarbonation was performed in a

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platinum crucible by slowly heating the sample up to 1100-1500°C in a electric muffle furnace.

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When decarbonation was achieved, the melt was quenched by dipping the bottom of the crucible

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into pure water. Four successive melting, quenching and grindings operations were made to

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prepare homogeneous glasses. Finally, samples were maintained a few hours at high temperature

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(1100-1500 °C depending on the viscosity of the sample) to obtain bubble-free samples required

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for viscosity measurements. Densities of all samples have been measured with the Archimedes

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method using toluene as the immersion liquid (Table 1). Chemical compositions have been

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measured using a Cameca SX50 electron microprobe (Table 1), with a 30 nA current, U=30kV, and

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5s of counting. The values reported in Table 1 are the statistical mean of 10-20 individual

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measurements.

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Glasses are named NA75.XX, with XX the concentration in mol% of Al₂O₃. They contain 75

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mol% SiO₂ and the Na₂O concentration is given by 100 – (75+XX) mol%. NA75.15 data come from

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the literature (see Table 1 caption).

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2.2. High Viscosity Measurements

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Viscosity measurements on melts near their glass transition temperature have been performed

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in air using a creep apparatus (see Neuville et Richet, 1991 and Neuville, 2006 for further details).

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Samples used for measurements are small cylinders of approximately 5 mm diameter x 10 mm

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length. Their approximate weight is 0.5 g. The temperature gradient is the most critical part of

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such experiment and needs to be minimized. To limit these gradients, a silver cylinder was placed

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around the sample, creating a small chamber where the temperature is homogeneous.

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Furthermore, thermal gradients along the sample were checked using two Pt-PtRh₁₀ thermocouples

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(ITS90 type S thermocouples). The temperature difference between the top and the bottom of

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samples was always less than 0.2 K during viscosity measurements. To measure samples viscosity

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at one temperature, we performed 20 to 40 measurements at different stresses (between 6.6 and

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8.9 log Nm-2) to be sure that no non-Newtonian behaviour appeared; the reported viscosity value

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at a single temperature is the statistical mean of these measurements. Measurements carried out

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on the NBS 717 glass show that the viscosity uncertainty and reproducibility is less than 0.03 log

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units with this technique (see Neuville, 2006).

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2.3 Raman Spectroscopy at Room Temperature

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Raman spectra were recorded using a T64000 Jobin-Yvon® triple Raman spectrometer equipped

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with a confocal system, a 1024 CCD (Charge-Couple Detector) cooled by liquid nitrogen and an

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Olympus® microscope. The optimal spatial resolution allowed by the confocal system is 1-2 μm2

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with a x100 Olympus® objective, and the spectral resolution is 0.7 cm-1. A Coherent® laser 70-C5

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Ar+, having a wavelength of 514.532 nm, was used as the excitation line. Samples were excited

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with a laser power of 200 to 250 mW. No laser-induced damage was observed.

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Spectra were acquired on freshly exposed surfaces (fresh breaks) between 15-20 and 1500 cm

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1. Acquisition conditions such as time and repetition were adjusted to the signal emitted by the

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sample area. Typical values are 180 to 300 seconds and 3 repetitions. The analysed volume was

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adjusted close to the surface in the Raman optimum region, i.e on the first 10 µm of depth. All

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reported spectra are unpolarized.

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Before deconvolution, spectra were corrected for temperature and excitation line effects using a

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correction factor introduced by Long (1977)and given by Neuville and Mysen (1996):

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I = Iobs .[_o3 [1-exp(-hc/kT)]  / (_o-)4], (1)

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with h the Planck constant, h=6.626038.10-34 J.s, k the Boltzmann constant; k=1.38066.10-23

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J.K-1, c the speed of light, c=2.9979.1010 m.s-1, T is the absolute temperature, _{o the wavenumber}

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of the incident laser light (in the present study the 514.532nm 70-C5Ar+ line, _{o =19435.1cm}-1),

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and  the measured Raman shift in cm-1.

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In order to perform deconvolution of the 850-1300 cm-1 spectral range, representative of the Qn

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species distribution (see below), this spectral range was normalized to its intensity maximum.

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Spectral deconvolution was performed using the quasi-Newton algorithm given by Tarantola (2005)

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implemented in Matlab® (Le Losq and Neuville, 2012). This iterative algorithm is based on the

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method of non-linear least square minimization. Inputs for the software are:

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– Raman spectra, i.e raman shifts, intensities and their associated errors. Data errors were

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estimated as sqrt(n) on raw spectra with n the counts per second, and corrected also by the Long

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equation. We have then input the total error in the algorithm, which is the sum of the corrected

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counting error and of the standard deviation between spectra data points and an ideal line. This

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last contribution to the total error has been determined on a linear spectral region, devoid of any

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features, in corrected and normalized spectra (in our case between 1300 and 1400 cm-1). We

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assume that by doing so, all errors from data collection and processing are taken into account.

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Before deconvolution of the 850-1300 cm-1 spectra region, intensities and their associated errors

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were normalized in order to obtained an intensity maximum of 100;

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– The model, which is a simple sum of Gaussian bands, and the estimations of the initial

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parameters values and of their uncertainties. Initial values of Raman shifts, FWMH and intensity of

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bands, and their associated uncertainties were the same for all spectra. The input uncertainties

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were: i) = 15 cm-1 for the Raman shifts; ii) = 20 cm-1 for FWMH (depending of the initial peak

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FWMH) and iii) 100 for intensity, in order to have no constrains on this parameter.

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The quasi-Newton algorithm takes into account parameter uncertainties and data errors in order

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to minimize the least square criterion and to converge to an optimal point. In order to check if the

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output solutions were the global minimum (best solution), and not just a local minimum

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(intermediate solution), several sensitivity tests of input parameters were performed. Initial

other, allowing the highest degree of reproducibility to be achieved.

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2.4 Nuclear Magnetic Resonance Spectroscopy at Room Temperature

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27Al and 23Na NMR experiments were performed at the CEMHTI-CNRS Orléans on a high field

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NMR Bruker Avance III 750 (17.6 T) spectrometer working at a 27Al frequency of 195.5MHz and a

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23Na frequency of 198.4 MHz. Chemical shifts for the 27Al and 23Na are referenced to a 1M aqueous

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Al(NO3)3 or NaCl solution respectively. Magic Angle Spinning was performed at a speed of 30 kHz in

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aluminium free zirconia rotors of 2.5mm diameter. A small pulse angle (less than /18 for 27Al and

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 /12 for 23Na) was used with a radio-frequency of 50 kHz to ensure the quantitative character of

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the spectra (Lippmaa et al., 1986). Four thousand (resp. 2000) scans were accumulated for 27Al

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(resp. 23Na) with a recycling time of 0.5s (estimated spin-lattice relaxation times T₁ of less than

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100ms), using a spectral window of 1 MHz. The decomposition of the 1D spectra where obtained

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using the "dmfit" program (Massiot et al., 2002) which allows for retrieval of the mean isotropic

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chemical shift _iso (which does not coincide with the position of the peak maximum), the distribution

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of isotropic chemical shift _iso and the mean quadrupolar coupling constant, C_Q within the

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framework of the Gaussian Isotropic Model (also called “Czjzek”, Le Caer et al., 1998).

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29Si NMR was performed on a Bruker Avance I 200 spectrometer operating at a frequency of

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39.7 MHz. Samples were packed in 7mm diameter zirconia rotor and spun at a speed of 5 kHz. To

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avoid dead-time problems, a synchronized Hahn Echo sequence was used to record the spectra at

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a radio-frequency field of 25 kHz and an echo shift of 3 rotor periods. The spin-lattice relaxation

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time T₁ being estimated (using a saturation-recovery experiment) between 250s for alumina-poor

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and 150s for alumina-rich samples, the recycle delay has been adjusted accordingly between 250s

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and 150s. Between 800 and 1100 scans were accumulated for each composition (i.e. 3 days of

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acquisition time).

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3) Results

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3.1 Viscosity

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The measurements performed on supercooled melts and in the liquid state are listed in Table 2

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and plotted in figure 1a. They are in good agreement with previous measurements performed

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using the fibre elongation method (Taylor and Rindone, 1970) or micropenetration (Toplis et al.

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1997a). Figure 1a shows that at a given temperature, the viscosity of the NA75.00 melt is the

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lowest compared to other compositions. When Al substitutes for Na, and for Al/(Al+Na) < 0.36

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(NA75.00 to NA75.09 compositions), viscosity increases slightly while for Al/(Al+Na) between 0.36

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and 0.5 (NA75.09 and NA75.12 compositions), viscosity increases drastically. For Al/(Al+Na)

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higher than 0.5, in the peraluminous field, the viscosity increases very slightly. This behaviour is

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also observed in the dependence of the glass transition temperature (Tg, which correspond to a

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viscosity of 12 log Pa.s) on the Al/(Al+Na) ratio (Fig. 1b). Tg increases non-linearly, with a clear

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transition occurring when Al/(Al+Na) is between 0.36 and 0.5 (NA75.09 and NA75.12 melts). In

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this range, Tg increases by 240° in less than 3 mol% of substituted Na. The Tg of the glass of

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Albite composition (NA75.12) is of 1085.7K, in good agreement with the calorimetric

measurements of Richet and Bottinga (1984). When Al/(Al+Na) > 0.5, Tg increases very slowly, 206

reaching 1102.4 K for the NA75.16 glass. 207

The viscosity variations observed at low temperature are also visible at high temperature when 208

looking at the data of Riebling (1966) and Toplis et al. (1997a,b; Fig. 2a). However, they are less 209

pronounced in the high-temperature / low-viscosity range. Furthermore, the NA75.00 viscosity 210

versus 1/T curve shows strongly non-arrhenian behaviour, while the viscosity curves of the 211

tectosilicate (NA75.12) and peraluminous (NA75.15 and 16) melts display arrhenian behaviour (Fig 212

2a). The different non-arrhenian behaviours are linked to melt fragility: NA75.00, NA75.02, 213

NA75.06 and NA75.09 melts are more fragile than tectosilicate NA75.12 and peraluminous 214

NA75.15/NA75.16 melts (Fig. 2b, Angell, 1991). The NA75.00 is the most fragile. The NA75.12 215

melt is stronger than other peralkaline (Al/(Al+Na) < 0.5) and peraluminous (Al/(Al+Na) > 0.5) 216

melts (Fig. 2b). 217

Near the glass transition (viscosities between 109 and 1014 Pa.s), the relationship between 218

log η and 1/T is not linear and can be fitted using a Tamman-Vogel-Flucher (TVF) equation: 219

log 𝜂 =  𝐴 +   ^!

(!!!_!) , (2)

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where A, B, T1 are adjustable parameters given in Table 3, T the temperature in K and η the 221

viscosity in Pa.s. This equation was used in order to interpolate viscosity data to low temperature. 222

However, it is an empirical fit of viscosity data and does not provide pieces of information about 223

the thermodynamic state of the studied melt (Neuville and Richet, 1991). In order to model the 224

whole range of temperature and to be able to extract thermodynamic information, one can use the 225

Adam and Gibbs equation: 226

log 𝜂 =  𝐴 +   ^!"

!!!"#$(!) , (3)

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where Ae is a pre-exponential term, Be a constant proportional to the potential barrier 228

opposed to the cooperative rearrangement of the liquid structure, Sconf(T) the melt configurational

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entropy, η its viscosity in Pa.s and T its temperature in K (Richet, 1984; Neuville and Richet,

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1991). This model is based on the Adam and Gibbs’ theory of relaxation processes (Adam and

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Gibbs, 1965). It assumes that matter transport in a viscous melt implies the cooperative 232

rearrangement of subsystems having a configurational entropy Sc* and a size z*(T) at a 233

temperature T, separated by a Gibbs free-energy barrier Δµ opposed to their movements. 234

Considering one mole of particles in a melt, we can write the Be and Sconf(T) parameters of

235 equation 3 as: 236 𝐵𝑒 =  ^{!!  !}!^∗ !_! , (4) 237 and 238 𝑆!"#$ 𝑇 =   ^𝒩! !∗ (!")𝑆!^∗+ (^𝒩! !∗ ! − ^𝒩! !∗ !")𝑆!^∗, (5) 239

with k_B the Boltzmann constant and NA the Avogadro constant (Adam and Gibbs, 1965; Bottinga

240

and Richet, 1996). We deliberately wrote equation 5 in a developed form because it is linked from 241

a macroscopic point of view to the following equation (Richet, 1984): 242 𝑆!"#$(𝑇) = 𝑆!"#$(𝑇𝑔) + ^! 𝐶𝑝!"#$ !" /𝑇𝑑𝑡 , (6) 243 with 244 𝐶𝑝!"#$ 𝑇 = 𝐶𝑝! 𝑇 − 𝐶𝑝!(𝑇𝑔) . (7) 245

Cp_g(Tg) is the heat capacity of the glass at Tg. We thus directly see comparing equation 5 and 6

248

that Sconf(Tg) is linked to Sc* and z*(Tg), and to the variation of z* depending on

249

temperature.

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Be in equation 3 is not temperature dependent, implying through equation 4 that bothand

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S_c* have a negligible temperature dependence. This implies that the microscopic mechanism

252

controlling viscous flow in a melt does not change with the temperature (Toplis, 1998), at least on

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the applicable viscosity range of Eq. 3 (10-1012 Pa.s, Bottinga et al., 1995). Only the melt

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composition strongly influences non-linearly Be, hence andS_c*. Since S_c* influences Sconf(Tg) as

255

shown by equation 5, this explains why viscosity variations near Tg strongly depend on melt

256

chemistry. At high temperature, the z*(T) influence on Sconf(T) surpasses that of Sc*, and the

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configurational heat capacity of the melt will play a fundamental role on Sconf(T) and hence

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viscosity.

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From equations 5 and 6, it appears that the melt configurational entropy at Tg and hence the

260

residual entropy of glass, reflects the configurational entropy of melt subsystems. Sconf(Tg) has two

261

contributions: i) a topological part, which is mainly due to the various distributions of bond angles,

262

interatomic distances and coordination numbers, and ii) a chemical part, induced by the mixing of

263

different elements (Neuville and Richet, 1991). As a result, Sconf(Tg) reflects the melt

264

configurational state, providing an image of its atomic disorder, and variations of Sconf(Tg)

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dependent on melt chemistry bring insights about the influence of chemical and structural changes

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on thermodynamic properties.

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By combining equations 3 and 6, one can calculate the Sconf(Tg), Ae and Be parameters if

268

viscosity data and heat capacities values are available. Estimation of heat capacities are of great

269

importance because small errors on Cp_g and Cp_l estimations can lead to strong deviations of the

270

calculated Be and Sconf(Tg) parameters. The Cp_g of the studied glasses were computed according to

271

the model of Richet (1987), that considers Cp_g as additive functions of the composition.

272

For melts with Al/(Na+Al) < 0.5, liquid heat capacity, Cpl, is an additive function of the

Dans le document Rôle des éléments alcalins et de l'eau sur les propriétés et la structure des aluminosilicates fondus et vitreux : implications volcanologiques (Page 130-179)