ANALISIS DE INFORMACION OBTENIDA DE LOS ENSAYOS CANAL

The lattice strain model of Blundy & Wood (1994) is based in the Brice model (1975) that postulates that the principal factor controlling the incorporation of a cation that is too large to fit into a lattice site is the elastic strain energy required to displace the surrounding atoms. The Blundy & Wood (1994) expression is:

Di= D_{0 *} exp (–4πEN_A((r₀/2)(r_i–r₀)2 _{+ 1/3 (r}

i–r0)3)/RT)

Where D₀ is the strain compensated partition coefficient, r₀ is the ionic radius of the cation of interest, r_i is the radius of the substituent cation, E is the Young’s modulus of the host site, N_A is the Avogadro’s number; R is the gas constant and T is temperature in Kelvin degrees.

The elastic strain energy is inversely correlated with the logarithm of the partition coefficient (log D), which for a specific lattice site follows a semi-parabola distribution as a function of the ionic radius (Onuma et al., 1968). The optimum radius, (i.e. that for which D is largest), is close to the ionic radius of the host cation.

The LSM suggests that because crystals are characterised by a regular arrangement of ions in relatively rigid lattices, they are less tolerant to accommodating misfit cations than silicate melts which have disordered and flexible structures. Thus no melt composition-related term appears in their equation.

Blundy & Wood (1994) and Wood & Blundy (2001) found that, in the case of homovalent substitution (i.e. where trace ion and host ion have the same charge) E_M2+ _{and E}

M1+ in plagioclase lie close to the bulk crystal Young’s moduli for anorthite and albite respectively, while E_M22+ in clinopyroxene was similar to the bulk crystal Young’s modulus of diopside. Blundy & Dalton (2000) found that for plagioclase and clinopyroxene the partitioning parabola becomes tighter (E_M n+ increases) and is displaced to lower r n+ _{as charge increases.}

Chapter 2 - Literature review

Blundy & Wood (1994) and Wood & Blundy (1997) also found that values for the optimum site radius, r_0(M)n+_{, are not the same as the radius of the cation normally resident at the site of interest.} For example, for clinopyroxene r_0(M2)2+ _{is slightly smaller than the radius of Ca}2+_{, the ion which} normally occupies that site. They proposed that r_0(M)n+ _{is closely related to the known metal-oxygen} bond lengths (dM-O) in the host minerals, taken to be 1.38Å (Shannon, 1976), i.e. dM-O = r_0(M) n+ _{+ 1.38 Å. Additionally, Blundy and Wood (2002) observed a decrease in r0}n+

(M) with charge and suggested that a highly charged cation (i.e. net positive charge at the site of interest) draws in the oxygen anions reducing the optimum radius, with r0n+

(M) being nearly constant at high charge of the site. Contrarily, a low-charged cation (with net negative charge) repels the oxygens, thus increasing the optimum radius of the site.

Blundy et al. (1996) concluded that D₀ (the strain-compensated partition coefficient) depends on activity-composition relationships in both crystal and melt phases, and might be sensitive to melt composition as well as to pressure and temperature. Similarly, Hill et al. (2011) found that partition coefficients for cations with charge greater than 2+ _{decrease as a result of increasing P and T.} These findings further corroborate a dependence of clinopyroxene-melt partitioning on pressure and temperature.

Blundy & Wood (1994, 2003a, b) and Wood & Blundy (1997, 2001, 2003) used the LSM to rationalise a large data set of lanthanide, yttrium and other elements partition coefficients for a range of minerals. They obtained values of D_0, r₀and E for several hundred experiments and then parameterised them as a function of chemical composition (of the melt and crystals), P and T. Their approach has been used to calculate Ds for REE, Y and when applicable for the metals of interest for this study.

For elements partitioning into clinopyroxene, the majority of the elements that we studied are 3+ _{ions (i.e. REE, Y, V and Sc) or 2}+ _{ions (Sr, Ba, Cu, Zn, Co and Pb), with the exception of copper} which could also be 1+_{. These elements are thought to partition mostly into the M2 clinopyroxene site} (Blundy & Wood 1994, 2003a, b; Wood & Blundy 1997, 2001, 2004; Hill et al., 2011). The equations used for D clinopyroxene/melt calculations can be found in Wood & Blundy (2003) and Hill et al., (2011).

Plagioclase has only one single large cation site (M) into which all the elements that we studied partition. This site is normally occupied by Ca and Na. Equations used for the calculation of D_Ba and D_Sr can be found in Blundy & Wood (1991). Equations to calculate Ds for REE and metals of interest can be found in Wood & Blundy (2003). However, because the parameters for 3+ _{cations (e.g. REE)} are difficult to derive due to r₀3+

(M) values being larger than La3+ (Wood & Blundy 2003 and references therein) we have not used the obtained values for our geochemical modelling. These authors also do not recommend using their equations for cations with lone pair of electrons (i.e. Pb).

Olivine has two octahedral sites (M1 and M2) but because they have a similar size and geometry, most authors refer to it simply as M site. The equations used to calculate Ds for 1+_{, 2}+ _{and 3}+ _cations can be found in Wood & Blundy (2004). While using the equations to calculate Ds for 1+ _{and 3}+ _D

Chapter 2 - Literature review 2.4.3 Parameterisation method of Bédard

The parameterisation method is a semi-empirical approach that provides mathematical expressions for changes in the D values for a range of elements (e.g. REE and HFSE)that partition into olivine (Bédard, 2005) and orthopyroxene (Bédard, 2007). The author compiled a large amount of published natural and experimental D values for olivine and orthopyroxene with the aim of examining covariations of D with pressure, temperature, and changes in melt and mineral compositions. An advantage of this method would be that it provides a large compilation of natural and experimental mineral/melt partitioning studies, which allows a wide range of intensive parameters to be taken into account. Nevertheless, it would also provide several sources of error and uncertainties.

Given that modelling for orthopyroxene is not necessary for this study, the following section will only review the work of Bédard (2005) which studies element partitioning between olivine and silicate melt.

Bédard (2005) found that titanium was the element with most reported D values and used this advantage to constrain the different effects that changes in temperature, pressure, H₂O, olivine Fo, MgO and SiO₂ content of the melt have on element partitioning. After calculating regressions for all the parameters mentioned above, Bédard (2005) found that regressions against both MgO content of the melt and temperature yielded reasonable trends. However, he suggested that MgO would provide more practical correlations as MgO contents can be calculated from microprobe mineral analyses whereas temperature is difficult to deduce in natural systems. Consequently, the MgO content of the melt was used to parameterise Ds for all trace elements.

Bédard (2005) also compares his Dolivine/liquid _{regressions to calculations using the lattice strain} model of Blundy and Wood (1994). He found that using a constant r₀ value of 0.807Å, MgO shows good correlation with D₀ and E_M3+_{. This suggests that it is possible to use the parameterisation equations} in conjunction with the LSM to calculate D for most 3+ _{cations (e.g. Sc and REE).}

The equations listed in Table 2 of Bédard (2005) have been used to calculate Ds for all the elements of interest for this study. Additionally, Jean Bédard provided us with a number of regression equations to calculate Ds for Cu and Zn partitioning into clinopyroxene, plagioclase and magnetite. The results of these calculations are presented in Table 2.1 along with the results obtained by using the lattice strain model of Blundy & Wood (1994).