  The rapid rise of viscosity or relaxation time upon supercooling is universal
hallmark of glassy liquids. The temperature dependence of the viscosity,
however, is quite non universal for glassy liquids and is characterized by the
system's "fragility," with liquids with nearly Arrhenius temperature-dependent
relaxation times referred to as strong liquids and those with super-Arrhenius
behavior referred to as fragile liquids. What makes some liquids strong and
others fragile is still not well understood. Here we explore this question in a
family of glassy liquids that range from extremely strong to extremely fragile,
using "softness," a structural order parameter identified by machine learning
to be highly correlated with dynamical rearrangements. We use a support vector
machine to identify softness as the same linear combination of structural
quantities across the entire family of liquids studied. We then use softness to
identify the factors controlling fragility.

Soft Condensed Matter;Disordered Systems and Neural Networks;Statistical Mechanics