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

Fragility in Glassy Liquids: A Structural Approach Based on Machine Learning