Interactive Tool for Customizing Hydrogel Properties in Practical Applications

Soft materials represent an interdisciplinary frontier in modern science, combining theoretical and experimental knowledge from diverse fields in both fundamental research and cutting‐edge technological applications. Hydrogels have garnered significant interest due to their unique properties. Nevertheless, practitioners often lack sufficient information on how to synthesize hydrogels, and the final composition is traditionally determined through trial and error. This study introduces a novel methodology to identify the optimal composition prior to experimentation. An ordinal regression model for mixture experiments to simulate the synthesis process, an adaptation of the Particle Swarm Optimization algorithm to tackle the complex optimization problem, and an open‐access interactive app to facilitate the calculations are proposed. This work represents a milestone in the hydrogel synthesis field: first, because of the savings in human, economic, and material resources it entails, the latter being consistent with the commitment to environmental sustainability; second, because it aligns with the principles of open science, providing an accessible and reproducible tool for the entire scientific community; and finally, because it seeks to overcome the barrier of expert knowledge to generalize the use of hydrogels. It represents the first step toward the development of an AI system specialized in the design of novel smart materials.