Is Olivine Speedometer a Reliable Tool to Constrain Thermal Story of SNC Meteorite?

Mathematics – Logic

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Minerals, Olivine, Snc Meteorites, Speed Indicators, Temperature Distribution, Approximation, Nakhlites, Finite Difference Theory, Diffusion Coefficient, Activation Energy, Cooling, Pyroxenes, Crystallization

Scientific paper

Several quantitative studies on thermal stories of SNC meteorites have been carried out to infer burial depth. Two approaches are generally used: (i) indirect estimation based on textural observation compared with products from controlled cooling crystallization experiment (ii) direct quantitative cooling rate calculation from diffusion zoning in mineral. The first method, applied on basaltic shergottite, is largely based on textures and compositions of pyroxene and/or maskelinite. The second one, performed on picritic shergottite (EET79001 and Dar al Gani 476) and the nakhlite NWA 817, uses zoning of olivine to extract cooling rate. At the onset of cooling, olivine was homogeneous and was then modified by atomic diffusion due to contact with Fe-rich surrounding melt when olivine was incorporated as a xenocryst. It had long been argued that olivine speedometer, giving absolute cooling rate, was the reliable method compared to the first one which bears large uncertainties. Unfortunately any contribution using olivine as a speedometer in meteorites are negligent (or at least optimistic) about the assignment of uncertainties to cooling rate estimate. In such studies numerical procedures, where diffusion equation is solved by finite difference approximation, are generally preferred to analytical one. However error propagation becomes obvious when using analytical methods in as much they allow the dependence of cooling rate results on input parameter to be clearly seen. For instance temperature To and diffusion data (E the activation energy and Do the preexponential term of diffusion coefficient D expressed through the Arrhenius law) are first order parameters in cooling rate equation. Small errors on temperature and diffusion data are magnified due to the logarithmic relation ship between input T and cooling rate S.

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