Figure 10.

Schematic illustration of the expected impact of using machine learning techniques in the DESs-assisted development of bioinspired hybrid materials synthesis. The potential data set includes results from laboratory experiments, developing synthetic data using molecular dynamics simulations, and a data set on structure–property relationships. The data set may span DESs, biominerals, biopolymers, and minerals. The use of generative models may provide the field with insights into novel material discovery for specific applications and material properties.