Synopsis: Multi-scale quantum mechanical methods are instrumental to the analysis of condensed phase studies, especially those with strong connections to experimental efforts. These research areas generally span a wide range of energies, from covalent and metallic bonding to dispersion interactions, and can involve reactive events and/or electronically excited states. A number of state-of-the-art techniques have emerged in recent years, including linear-scaling quantum mechanical approaches, machine learning approaches for creating density functional tight binding and quantum-based reactive force fields, and a wide variety of coarse-grained models for both soft and hard matter. To help maximize the impact of these novel developments in the physics, chemistry, and materials science communities, we plan to bring together leading developers and practitioners of these methods to identify the grand challenges facing in applying current methods to large-scale condensed phase problems, as well as appropriate benchmarks for novel multi-scale QM methods. We also hope the workshop will foster collaborations that help tackle these challenges and lead to the next generation of multi-scale QM methods that are generally applicable to a broad range of chemical, materials, and biological problems.

We believe the scope of this workshop provides excellent synergy with the workshop entitled “Machine Learning and Informatics for Chemistry and Materials” (Olexandr Isvayev et al.) which is being held simultaneously.