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The polarizable density embedding (PDE) model is an advanced fragment‐based QM/QM embedding model closely related to the earlier polarizable embedding (PE) model. PDE features an improved description of permanent electrostatics and further includes non‐electrostatic repulsion. We present an implementation of analytic geometric gradients for the PDE model, which allows for partial geometry optimizations of QM regions embedded in large molecular environments. We benchmark the quality of structures from PE‐QM and PDE‐QM geometry optimizations on a diverse set of small organic molecules embedded in four solvents. The PDE model performs well when targeting Hartree–Fock calculations, but density functional theory (DFT) calculations prove more challenging. We suggest a hybrid PDE‐LJ model which produces solute–solvent structures of good quality for DFT. Finally, we apply the developed model to a theoretical estimation of the solvatochromic shift on the fluorescence emission energy of the environment‐sensitive 4‐aminophthalimide probe based on state‐specific multiconfigurational PDE‐QM calculations. [ABSTRACT FROM AUTHOR]

The polarizable embedding (PE) model is a fragment‐based quantum‐classical approach aimed at accurate inclusion of environment effects in quantum‐mechanical response property calculations. The aim of this tutorial review is to give insight into the practical use of the PE model. Starting from a set of molecular structures and until you arrive at the final property, there are many crucial details to consider in order to obtain trustworthy results in an efficient manner. To lower the threshold for new users wanting to explore the use of the PE model, we describe and discuss important aspects related to its practical use. This includes directions on how to generate input files and how to run a calculation. This tutorial review is an introduction to the practical use of the quantum‐classical polarizable embedding model for computing response properties of molecules embedded in complex atomistic environments. It includes a getting‐started guide that illustrates how input files are generated and how to run calculations. Aspects that are crucial for efficiently obtaining reliable results are described and discussed. [ABSTRACT FROM AUTHOR]