• Ruesch, Jonas H.
• Hussong, Jeanette
• Tropea, Cameron
• Roisman, Ilia V.
• Stumpf, Bastian

Abstract

<jats:sec><jats:title>Abstract</jats:title><jats:p>Droplets within droplets occur in numerous situations in which two immiscible liquids interact, for instance, binary drop collisions or when a drop of one liquid impacts onto a film of a different liquid, ejecting secondary droplets containing both liquids. In the present study, an imaging technique for determining the volume fraction of each liquid component in such two-component droplets is introduced, in which multiple images of the same droplet at different times are used. The processing of these images is supported by a machine learning algorithm, which is taught using synthetically generated images and validated on droplets with known mixture fractions placed in an acoustic levitator. The application of the technique is demonstrated by measuring the volume fraction in splashed secondary droplets following the impact of a drop of one liquid onto a film of a different liquid.</jats:p></jats:sec><jats:sec><jats:title>Graphical abstract</jats:title></jats:sec>

Topics

• impedance spectroscopy
• size-exclusion chromatography
• machine learning