Growing dust grains in protoplanetary discs - I. Radial drift with toy growth models

Abstract

In a series of papers, we present a comprehensive analytic study of the global motion of growing dust grains in protoplanetary discs, addressing both the radial drift and the vertical settling of the particles. Here we study how the radial drift of dust particles is affected by grain growth. In a first step, toy models in which grain growth can either be constant, accelerate or decelerate are introduced. The equations of motion are analytically integrable and therefore the grains dynamics is easy to understand. The radial motion of growing grains is governed by the relative efficiency of the growth and migration processes which is expressed by the dimensionless parameter Lambda, as well as the exponents for the gas surface density and temperature profiles, denoted p and q respectively. When Lambda is of order unity, growth and migration are strongly coupled, providing the most efficient radial drift. For the toy models considered, grains pile up when -p+q+1/2<0. Importantly, we show the existence of a second process which can help discs to retain their solid materials. For accelerating growth, grains end up their migration at a finite radius, thus avoiding being accreted onto the central star.

12 pages, 9 figures. Accepted for publication in MNRAS. v2: typos corrected

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Cited by in corpus (8)

• Self-induced dust traps: overcoming planet formation barriers
• Dust and gas mixtures with multiple grain species - a one-fluid approach
• Growing dust grains in protoplanetary discs - II. The Radial drift barrier problem
• Diversity in the outcome of dust radial drift in protoplanetary discs
• Size and density sorting of dust grains in SPH simulations of protoplanetary discs
• On the settling of small grains in dusty discs: analysis and formulas
• Size and density sorting of dust grains in SPH simulations of protoplanetary disc II: Fragmentation
• Imaging the Dusty Substructures due to Terrestrial Planets in Planet-forming Disks with ALMA and the Next Generation Very Large Array