To adjust the distribution of target values for ML models, we chose the square root of the initial size and the intensity 𝑁 0 of the droplet as well as the natural logarithm of the lifetime 𝜏 as The currently used Gaussian Process models predict hydrogel properties based on monomer and cross-linker class labels and their respective concentration, which implies that they can only be used on a finite set of compounds. In principle, the input representation can be based on molecular features and structural information, rather than categorical compounds, and therefore enable predictions also on unseen monomers. While data requirements for this approach are higher, it would allow for virtual materials design and exploration of new monomers and crosslinkers, which is beyond the scope of this work.