Ices in planet-forming disks: Self-consistent ice opacities in disk models

Abstract

Context. In cold and shielded environments, molecules freeze out on dust grain surfaces to form ices such as H2O, CO, CO2, CH4, CH3OH, and NH3. In protoplanetary disks, such conditions are present in the midplane regions beyond the snowline, but the exact radial and vertical extension depend on disk mass, geometry, and stellar ultra-violet irradiation. Aims. The goal of this work is to present a computationally efficient method to compute ice and bare-grain opacities in protoplanetary disk models consistently with the chemistry and to investigate the effect of ice opacities on the physico-chemical state and optical appearance of the disk. Methods. A matrix of Mie efficiencies is pre-calculated for different ice species and thicknesses, from which the position dependent opacities of icy grains are then interpolated. This is implemented in the PRODIMO code by a self-consistent solution of ice opacities and the local composition of ices, which are obtained from our chemical network. Results. Locally, the opacity can change significantly, for example, an increase by a factor of more than 200 in the midplane, especially at ultra-violet and optical wavelengths, due to ice formation. This is mainly due to changes in the size distribution of dust grains resulting from ice formation. However, since the opacity only changes in the optically thick regions of the disk, the thermal disk structure does not change significantly. For the same reason, the spectral energy distributions (SEDs) computed with our disk models with ice opacities generally show only faint ice emission features at far-IR wavelengths. The ice absorption features are only seen in the edge-on orientation. The assumption made on how the ice is distributed across the grain size distribution (ice power law) influences the far-infrared and millimeter slope of the SED. The ice features and their strengths are influenced by the ice power law and the type of chemistry. Our models predict stronger ice features for observations that can spatially resolve the disk, particularly in absorption.