Division/Committee: [PHYS: Division of Physical Chemistry]

Embedding is a powerful approach for studying complex systems with electronic structure theory, reducing computational cost as system size increases. Early methods combined semi-empirical quantum mechanics for enzyme active sites with molecular mechanics or continuum models, and recent advancements in QM/QM, QM/MM, fragmentation, and PCM methods have enhanced their sophistication. Applications in electronic excitations and nonadiabatic dynamics, essential for photochemistry and photobiology, have driven innovations in coupling the QM region with its environment. Subsystem interactions, once treated classically, are increasingly captured explicitly with embedding operators. Modern software development, GPU hardware, machine learning, and enhanced sampling techniques enable simulations of larger QM regions and longer timescales. Embedding methods now span materials science, biomolecules, condensed-phase dynamics, spectroscopy, and catalysis. This symposium features embedding methods for diverse systems, with talks from experts advancing and applying these methods across chemistry, biochemistry, and materials science.

Marco Caricato

University of Kansas

Appearances