On the effects of microphysical grain properties on the yields of carbonaceous dust from type II SNe

TL;DR

This study investigates how microphysical properties of carbonaceous dust grains influence their size distribution and survival in type II supernovae, highlighting the importance of detailed microphysics for accurate dust yield predictions.

Contribution

It introduces a parametrization of grain shape and sticking coefficient effects, showing their impact on dust size distribution and implications for extinction and grain survival.

Findings

Dust amount is largely independent of microphysical parameters within the considered range.

Condensation times and size distributions are sensitive to grain shape and sticking coefficient.

Larger grains form with higher sticking coefficients and more aspherical shapes, affecting extinction and survival.

Abstract

We study the role of the unknown microphysical properties of carbonaceous dust particles in determining the amount and size distribution of carbonaceous dust condensed in type II supernova explosions. We parametrize the microphysical properties in terms of the shape factor of the grain and the sticking coefficient of gas-phase carbon atoms onto the grain surfaces. We find that the amount of dust formed is fairly independent of these properties, within the parameter range considered, though limited by the available amount of carbon atoms not locked in CO molecules. However, we find that the condensation times and size distributions of dust grains depend sensitively on the microphysical parameters, with the mass distributions being weighted toward larger effective radii for conditions considering grains with higher sticking coefficients and/or more aspherical shapes. We discuss that this leads to important consequences on the predicted extinction law of SN dust and on the survival rate of the formed grains as they pass through the reverse shock of the SN. We conclude that a more detailed understanding of the dust formation process and of the microphysical properties of each dust species needs to be achieved before robust prediction on the SN dust yields can be performed.