Combined chemical and physical model for plutonic devolatilization: A non-Rayleigh fractionation algorithm

Abstract

Modeling of magmatic-hydrothermal processes requires the estimation of intensive parameters, the experimental determination of partition coefficients and other equilibria, and quantitative models of processes such as magmatic crystallization and devolatilization. In this paper, a new chemical model for magmatic devolatilization, based on a physical model for volatile release during second boiling, is presented. Models are presented for stable isotopes and nonchloride complexed elements. The release of volatiles during isobaric, plutonic crystallization (second boiling) has been modeled as either a batch (closed-system) or Rayleigh-fractional (open-system) process. However, when the chemical mass transfer, attendant to second boiling, is modeled in conjunction with a simple physical model involving critical percolation of the magmatic volatile phase, the mass transfer can be shown to occur as a transitional batch-fractionation process. Early devolatilization during second boiling follows a batch law as discrete bubbles grow. Depending on the depth (pressure) of intrusion, and the initial volatile content of the magma, the discrete volumes of the volatile phase will achieve a spanning cluster of volumes at some stage in devolatilization progress. When connectivity of volatile phase volumes is established, devolatilization will follow a modified fractionation law wherein a finite, rather than infinitesimal volume of the fractionating phase is in equilibrium with the melt. For devolatilization of melts of a given initial volatile concentration, increasing depth leads to later formation of a spanning cluster and increasing batch character. Extreme depletions of magmatic chlorine or deuterium, or enrichments of magmatic molybdenum or fluorine are made more probable by early establishment of spanning clusters of volatile volumes. A new algorithm for calculating the δD of hydrous phases in intrusive rocks as a function of whole rock water content predicts D depletions on the order of −100 (relative to SMOW).