Engineering melanin-based meta-material for broad UV-visible absorption

Designing materials with high intensity absorption of solar light across wide wavelength range is a primary goal in organic optoelectronics engineering. However, the potential application of most known biomolecules specifically in bio-optoelectronics is limited because they can only absorb light within specific wavelengths. Both experimental and computational approaches have investigated the potential of the skin pigment melanin, in this direction, but progress has been limited due to the complexity of its chemical space. In this work, we design a comprehensive virtual chemical space of melanin and develop machine learning-based approach to predict their complete optical and thermodynamical properties. These predictions help engineering melanin-based sustainable materials for tailored optoelectronic applications.