Abstract
Coexisting biotite and muscovite in ten metapelitic and quartzofeldspathic rocks from western Labrador have been analyzed by electron microprobe for major and minor elements and by a laser ablation microprobe coupled to ICP-MS (LAM-ICP-MS) for selected trace elements—Li, Sc, V, Cr, Mn, Co, Ni, Cu, Zn, Rb, Sr, Y, Zr, Nb, Cs, Ba, REE, Hf and Ta. The samples have experienced a single prograde Grenvillian metamorphism ranging from 490 to 680°C and from 7 to 12 kbar. The trace element compositions of coexisting micas in the metamorphic rocks are used to assess the effects of crystal structure, major element composition and temperature on the partitioning of each element between biotite and muscovite. Overall, trace element distributions are systematic across the range of metamorphic grade and bulk composition, suggesting that chemical equilibrium was approached. Most distribution coefficients (biotite/muscovite) show good agreement with published data. However, distribution coefficients for Co and Sr are significantly different from previous determinations, probably because of contamination associated with older data obtained by bulk analysis techniques. The sequence of distribution coefficients is governed mainly by the ionic radii and charges of substituting cations compared to the optimum ionic radius of each crystallographic site in the micas. In particular, distribution coefficients exhibit the sequence Cr 3+ (0.615 Å) > V 3+ (0.64 Å) > Sc 3+ (0.745 Å) in VI-sites, and Ba 2+ (1.61 Å) > Sr 2+ (1.44 Å) and Cs + (1.88 Å) > K + (1.64 Å) > Rb + (1.72 Å) > Na + (1.39 Å) in XII-sites. The distributions of Li, Sc, Sr and Ba appear to be thermally sensitive but are also controlled by major element compositions of micas. V and Zr partitioning is dependent on T and may be used to cross-check thermometry calculations where the latter suffer from retrograde re-equilibration and/or high concentrations of Fe 3+. The ranges and dependence of distribution coefficients on major element compositions provide important constraints on the values that can be used in geochemical modeling.
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