Despite decades of intense research, whether the transformation of supercooled liquids into glass is a kinetic phenomenon or a thermodynamic phase transition remains unknown. Here, we analyzed optical microscopy experiments on 2D binary colloidal glass-forming liquids and investigated the structural links of a prominent kinetic theory of glass transition. We examined a possible structural origin for localized excitations, which are building blocks of the dynamical facilitation theory-a purely kinetic approach for the glass transition. To accomplish this, we utilize machine learning methods to identify a structural order parameter termed "softness" that has been found to be correlated with reorganization events in supercooled liquids. Both excitations and softness qualitatively capture the dynamical slowdown on approaching the glass transition and motivated us to explore spatial and temporal correlations between them. Our results show that excitations predominantly occur in regions with high softness and the appearance of these high softness regions precedes excitations, thus suggesting a causal connection between them. Thus, unifying dynamical and thermodynamical theories into a single structure-based framework may provide a route to understand the glass transition.
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