Printing Structural Color via AI-Guided Experimentation

Structural color, which arises from the interaction of light with micro- and nanostructured materials, has been recognized as an environmentally sustainable alternative to traditional dyes and pigments. In this study, Direct Ink Writing has been utilized as the additive manufacturing technique for fabricating structurally colored materials which here, are bottlebrush block copolymers. The experimental workflow has been integrated with an artificial intelligence-driven optimization process, enabling an efficient exploration of the printing parameter space. Image analysis techniques have been employed to characterize the resultant color profiles, with hue in the HSV color space serving as the primary objective function for optimization. The development of software architecture that facilitates real-time data collection and feedback has been undertaken in collaboration with the National Center for Supercomputing Applications (NCSA). Preliminary results have demonstrated the feasibility of the proposed approach in tuning structural coloration, while ongoing efforts aim to enhance automation capabilities and expand the scope of parameter optimization.