UV-Visible Absorption Spectra of Solvated Molecules by Quantum Chemical Machine Learning
Zekun Chen,
Fernanda C. Bononi,
Charles A. Sievers
et al.
Abstract:Predicting UV-visible absorption spectra is essential to understand photochemical processes and design energy materials. Quantum chemical methods can deliver accurate calculations of UV-visible absorption spectra, but they are computationally expensive, especially for large systems or when one computes line shapes from thermal averages.Here, we present an approach to predict UV-visible absorption spectra of solvated aromatic molecules by quantum chemistry (QC) and machine learning (ML). We show that a ML model… Show more
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