Analytical Nuclear Gradients for Projection-based Wavefunction-in-Density Functional Theory Embedding

Projection-based wavefunction-in-density functional theory (WF-in-DFT) embedding provides a simple framework for embedding WF theories within DFT. It has been successfully used to retain the high accuracy of WF methods while still benefitting from the low cost of DFT. Even though this method has performed well for single-point energy calculations, it has lacked analytical nuclear gradients, preventing the efficient exploration of the potential energy surface. Here, we present recent work on the development of analytical nuclear gradients for the projection-based WF-in-DFT embedding method so we can perform tasks such as geometry optimizations and study reaction pathways. We illustrate the application of projection-based WF-in-DFT gradients on a number of simple systems with the aim to model conical intersections.