Presolar SiC abundances in primitive meteorites by NanoSIMS raster ion imaging of insoluble organic matter

Abstract

Here we present results obtained with NanoSIMS raster ion imaging to determine the abundance of presolar SiC in the insoluble organic matter (IOM) extracted from a number of different classes of chondrites (both carbonaceous and ordinary). This builds on previous work [1] aimed at obtaining SiC abundances in primitive meteorites by SIMS and comparing them with noble gas analyses. Both IOM and presolar grains are found in similar CI-like relative abundances in the matrices of the most primitive chondrites [2, 3], indicating that a homogeneous mixture of grains was incorporated in the various parent bodies [3]. Both are then subjected to thermal and hydrothermal processing after parent body formation [4]. However, there are significant variations in the matrix-normalized abundances of SiC grains estimated from noble gases carried by presolar grains, which suggest that the primitive chondrites did not form from a well-mixed reservoir of presolar grains. Variations in the source material were attributed to the destruction of presolar grains by heating in the solar nebula (temperatures that may have exceeded 700°C) and were linked to the volatile element fractionations in chondrites [5]. The CR chondrites have amongst the lowest matrix-normalized SiC abundances, and largest volatile element ractionations, reported in the carbonaceous chondrites [5]. However, they contain the most primitive IOM of any chondrite class [6-7], which has experienced peak temperatures of <300°C [8]. These lowtemperatures could not have affected the SiC grains or their noble gas concentrations, indicating that either the IOM escaped heating (implying that it is not presolar)or SiC was degassed/destroyed at low temperatures, perhaps during parent body processing [3]. Thus, in order to resolve this contradiction, it is necessary to determine SiC abundances independently of noble gases. Ion imaging of SiC grains is a direct technique that has been shown to successfully identify presolar SiC grains amongst others