A new grid of disk models with grain-surface CO chemistry plus an ML inference tool produces gas mass estimates from ALMA observations that match independent dynamical and HD values without requiring extreme elemental depletion.
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12 Pith papers cite this work. Polarity classification is still indexing.
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A semi-analytic model using elastoplastic contact mechanics and weakest-link fracture statistics reproduces the sticking-bouncing boundary from DEM simulations and places the bouncing barrier within ALMA-inferred size-velocity ranges for moderately porous aggregates.
Semi-analytical model links observed scattering-surface height to small-dust mass, yielding global mass fractions of order 10^{-3} consistent with modest grain growth in ten protoplanetary disks.
Presents and benchmarks an SPH code for the full one-fluid dusty gas with multiple species that conserves mass, momentum, angular momentum and energy while recovering analytic solutions where the terminal velocity approximation fails.
A 2D Monte Carlo dust evolution simulation shows that a planet-induced pressure bump reproduces the observed compositions and formation ages of carbonaceous chondrites, implying formation in a single long-lived dust trap outside Jupiter's orbit.
Azimuthal dust polarization at millimeter wavelengths traces high dust-to-gas ratio zones created by the streaming instability in protoplanetary disks.
2D radiation-hydrodynamical simulations find accretion outbursts unstable to Rossby-wave instability, forming vortices that suppress planetesimal formation until post-burst quiescence.
Halos in Elias 2-24, IM Lup, and DM Tau hold 20-30% of total dust mass with cm-sized grains, helping resolve the disk mass-budget problem even though drift and growth timescales are shorter than disk ages.
Numerical simulations of porous fractal and consolidated particles show stronger forward scattering, broader polarization peaks, and lower absorption per unit mass than compact spheres, implying larger dust masses from observed fluxes.
Two migrating super-Earths in low-viscosity disks trigger narrow and broad dust substructures with high dust-to-gas ratios favorable for planetesimal formation.
The paper proposes the iSEEDs project to integrate machine learning with astrochemistry for extracting physical conditions and molecular abundances from protostellar disk datasets.
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Full one-fluid dusty gas with multiple grain species in SPH
Presents and benchmarks an SPH code for the full one-fluid dusty gas with multiple species that conserves mass, momentum, angular momentum and energy while recovering analytic solutions where the terminal velocity approximation fails.