Fidel Costa

Diffusion coupling between trace and major elements and a model for calculation of magma residence times using plagioclase

Residence times of plagioclase crystals in magma reservoirs can be determined by modeling the compositional zoning of trace elements in these crystals. We present a formulation to model diffusion of trace elements in plagioclase paying special attention to certain thermodynamic and kinetic aspects. In particular, we account for the compositional dependence on anorthite content of the chemical potential and diffusion coefficients of trace elements (e.g., Mg), the choice of suitable boundary conditions and potential effects of diffusion in more than one dimension. We show that contrary to intuition, diffusive fluxes of trace elements may be coupled to major element concentration gradients, and ignoring such coupling can lead to incorrect estimates of timescales. We illustrate application of the model using plagioclase crystals from a suite of gabbroic xenoliths from a Holocene dacitic lava flow of Volcan San Pedro (Chilean Andes, 36°S). The inferred timescale for metasomatism of the xenoliths by evolved liquids is on the order of 100 (30 to 148) yr and serves to illustrate how trace element zoning in plagioclase provides a window into timescales of magmatic processes inaccessible by isotopic or other methods.

Magmatic Na-rich phlogopite in a suite of gabbroic crustal xenoliths from Volcan San Pedro, Chilean Andes: Evidence for a solvus relation between phlogopite and aspidolite

Abstract Magmatic Na-rich phlogopite (1-5 wt% Na2O) is present as a late-crystallizing mineral in two groups of texturally and mineralogically distinct gabbroic xenoliths at Volcán San Pedro (36°S, Chile), an Andean arc volcano. Phlogopites are characterized by high 100·Mg/(Mg + Fe) (up to 83) and high Cr2O3 contents (up to 0.4 wt%), and they are always found surrounding variably resorbed olivine, pyroxenes, Cr-spinel, and in some cases, plagioclase. We interpret these micas as the result of open-system processes involving infiltration of water-rich evolved melts [with high Na/(Na + K)] and reaction with refractory minerals. The highest 100·Na/(Na + K) (~70) and Na2O concentrations (~5 wt%) in phlogopite appear to require reaction with liquids of unrealistically high Na/(Na + K) if no other factor is considered. This, together with the observation that phlogopites consist of alternating Na-rich and Na-poor cleavage-parallel bands, can be best interpreted by the presence of a solvus between the aspidolite (Na) and phlogopite (K) end-members. The high proportions (up to 15 vol%) of Na-rich phlogopite in two different groups of gabbroic xenoliths suggest that it might be a more common and abundant mineral than has been previously recognized, and that it may be used as an indicator of open-system processes.

CEmin: A MATLAB-Based Software for Computational Phenocryst Extraction and Statistical Petrology

It is nowadays common to collect large-area backscattered electron images and X-ray maps of entire standard petrographic thin sections. These images can be calibrated for compositions of some minerals (e.g., plagioclase) with a small number of electron microprobe analyses, and thus provide a wealth of quantitative data for hundreds of crystals. However, to effectively make use of the textures and compositions of large numbers of crystals we need to be able to efficiently outline and segregate the crystals of interest from the rest of the sample. Here we present CEmin, a set of MATLAB routines that are user-friendly and allow users to semiautomatically separate plagioclase crystals in grayscale images of volcanic rocks for further processing. These data can then be used for textural and chemical zoning studies. Efficiently extracting large amounts of crystal data allows for identification of plagioclase populations that are indicative of magmatic processes (e.g., closed versus open system) and statistical comparison to thermodynamic models. Plain Language Summary It is possible nowadays to acquire large data sets of crystal and chemical information of magmatic rocks in a quick and efficient manner. Here we present a new user-friendly software that allow the extraction of the size and compositions of hundreds of crystals from a single petrographic thin section. Such information opens the era of big data in petrological studies and allows to investigate volcanic and plutonic processes using statistical approaches.