UniversalQM/MMapproaches for general nanoscale applications

Abstract

Quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. Whereas this modeling approach can cope with a large system size at moderate computational costs, the models are often tedious to construct and require manual preprocessing and expertise. As a result, transferability to new application areas can be limited and the many parameters are not easy to adjust to reference data that are typically scarce. Therefore, it is desirable to devise automated procedures of controllable accuracy, which enables such modeling in a standardized and black‐box‐type manner. Although diverse best‐practice protocols have been set up for the construction of individual components of a QM/MM model (e.g., the MM potential, the type of embedding, the choice of the QM region), automated procedures that reconcile all steps of the QM/MM model construction are still rare. Here, we review the state of the art of QM/MM modeling with a focus on automation. We elaborate on MM model parametrization, on atom‐economical physically‐motivated QM region selection, and on embedding schemes that incorporate mutual polarization as critical components of the QM/MM model. In view of the broad scope of the field, we mostly restrict the discussion to methodologies that build de novo models based on first‐principles data, on uncertainty quantification, and on error mitigation with a high potential for automation. Ultimately, it is desirable to be able to set up reliable QM/MM models in a fast and efficient automated way without being constrained by specific chemical or technical limitations. This article is categorized under: Electronic Structure Theory > Combined QM/MM Methods

Efficient automatic construction of atom-economical QM regions with point-charge variation analysis

“…Therefore, systematic schemes for automating such decisions are desperately needed (for a recent review, see ref. 5). Most important is the choice of a suitable QM region.…”

Quantum Computing for Molecular Biology**

“…The determination of this quantum region can be automated (see, e. g., Refs. [41] and [42]). Numerous approaches have been devised for the embedding of a small active quantum part into an environment (see, e. g., Refs.…”

Efficient automatic construction of atom-economical QM regions with point-charge variation analysis

“…Therefore, systematic schemes for automating such decisions are desperately needed (for a recent review, see Ref. [5]).…”