Metal-silicate Partitioning at High Pressure and Temperature: Experimental Methods and a Protocol to Suppress Highly Siderophile Element Inclusions

Abstract

Estimates of the primitive upper mantle (PUM) composition reveal a depletion in many of the siderophile (iron-loving) elements, thought to result from their extraction to the core during terrestrial accretion. Experiments to investigate the partitioning of these elements between metal and silicate melts suggest that the PUM composition is best matched if metal-silicate equilibrium occurred at high pressures and temperatures, in a deep magma ocean environment. The behavior of the most highly siderophile elements (HSEs) during this process however, has remained enigmatic. Silicate run-products from HSE solubility experiments are commonly contaminated by dispersed metal inclusions that hinder the measurement of element concentrations in the melt. The resulting uncertainty over the true solubility and metal-silicate partitioning of these elements has made it difficult to predict their expected depletion in PUM. Recently, several studies have employed changes to the experimental design used for high pressure and temperature solubility experiments in order to suppress the formation of metal inclusions. The addition of Au (Re, Os, Ir, Ru experiments) or elemental Si (Pt experiments) to the sample acts to alter either the geometry or rate of sample reduction respectively, in order to avoid transient metal oversaturation of the silicate melt. This contribution outlines procedures for using the piston-cylinder and multi-anvil apparatus to conduct solubility and metal-silicate partitioning experiments respectively. A protocol is also described for the synthesis of uncontaminated run-products from HSE solubility experiments in which the oxygen fugacity is similar to that during terrestrial core-formation. Time-resolved LA-ICP-MS spectra are presented as evidence for the absence of metal-inclusions in run-products from earlier studies, and also confirm that the technique may be extended to investigate Ru. Examples are also given of how these data may be applied.