We are excited to announce the publication of our latest work in The Journal of Physical Chemistry Letters: “Improved Description of Environment and Vibronic Effects with Electrostatically Embedded ML Potentials.”

In collaboration with Carles Curuthet from Universitat de Barcelona we introduce a multiscale strategy that combines electrostatically embedded machine learning potentials with the QM/MMPol polarizable embedding model. This approach accurately simulates optical spectra and excited state dynamics, as demonstrated on 3-methyl-indole in different environments. Our method paves the way for deeper insights into the relationship between biological motions and photophysics.