We describe a chemical robotic discovery assistant equipped with a curiosity algorithm (CA) that can efficiently explore a complex chemical system in search of complex emergent phenomena exhibited by proto-cell droplets. The CA-robot is designed to explore proto-cell formulations in an open-ended way with no explicit discovery or optimization target. By applying the CA-robot to the study of multicomponent oil-in-water proto-cell droplets, we discovered an order of magnitude more instances of interesting behaviours than possible with a random parameter search. Among them, a formulation displaying a sudden and highly specific response to temperature was discovered. Six modes of proto-cell droplet motion were identified and classified using a time-temperature phase diagram and probed using a variety of techniques including NMR, which allowed the design of a payload release system triggered by temperature. This work shows how objective free search can lead to the discovery of useful and unexpected properties, with real-world applications in formulation chemistry.