Reconciling color purity and redox potential in electrochromic materials via electronic-state-informed molecular...

Reconciling vivid coloration and low oxidation potential in electrochromic materials-essential for functional devices such as displays, sensors, and energy systems-remains a key challenge due to intrinsic electronic trade-offs. Here we establish a generalizable design strategy based on electronic-state informatics, integrating quantum chemical calculations with machine learning, to identify and experimentally validate a triphenylamine-based compound that exhibits pure yellow color (h = 93.6°) and low oxidation potential (E_ox = 0.12 V). While demonstrated here for electrochromic materials, our interpretable, data-driven framework is broadly applicable to the multi-objective design of π-conjugated molecules, including emitters, absorbers, and charge-transporting materials. This approach moves beyond empirical trial-and-error, offering a rational and generalizable methodology for property-driven molecular engineering.