FAU LMQ Research Spotlight: From Empirical Rules to Digital Predictions of ππ* Absorption Maxima

What happens when the wisdom of mid-20th-century chemists meets today’s digital tools? In their recent work, Connor Forster and Carolin Müller revisited and digitized the classical empirical rules of Woodward, Fieser, and Kuhn to predict ππ* absorption maxima directly from molecular structure. By translating their additive principles into a modern cheminformatics workflow, they provide a low-cost and interpretable alternative to computationally demanding quantum chemical or machine learning methods. The approach bridges historical chemical intuition with contemporary computational tools, offering a transparent and educationally valuable framework for early-stage molecular design.

For more information, see the publication in Digital Discovery:

From handbooks to high-throughput: rule-based prediction of electronic absorption maxima from SMILES with ChromoPredict
Connor Forster, Carolin Müller
Digital Discovery, 2026, 5, 98-107