EmbASI: An extensible Pythonic framework for DFT-in-DFT and WF-in-DFT embedding

High-level quantum mechanical (QM) simulations are important for understanding chemical and physical systems, but these methods scale unfavorably with system size, and this limits calculations to model representations of the real systems. To simulate realistic systems, approaches such as hierarchical quantum mechanics in quantum mechanics embedding (QM/QM) can be used to localize the accurate electronic structure methods to a region of chemical interest, with the wider environment represented using a less expensive embedding potential. However, implementing embedding procedures into established QM software packages is often challenging due to their monolithic design and complex software structure. Here, we present a modular and open-source approach that enables QM/QM embedding using established electronic structure codes with reduced development overhead. We demonstrate the new software, EmbASI, using the projection-based embedding theory scheme. Calculations performed for pentanol and organic dimers demonstrate the efficacy of the hierarchical density functional theory (DFT) embedding approach with the charge localization and partitioning procedures implemented in the wrapper environment; when using a truncated local atomic orbital basis, wavefunction-in-DFT embedding calculations demonstrate speed-ups of 32× for a 70 atom system, evaluated with RPA@PBE-in-PBE relative to a full RPA@PBE calculation, while introducing minimal errors to the total energies of the embedding simulations (<1 kJ mol−1). We then demonstrate capabilities for realistic extended zeolite models, achieving similar minimal errors with significant compute speed-up and memory reductions. The results demonstrate the capabilities of EmbASI for immediate applied QM/QM modeling and provide a broader foundation for multiscale QM simulations using established electronic structure infrastructure.