DESC: An Automated Strategy to Efficiently Account for Dynamic Environment Effects in Solution

The properties and dynamic behavior of molecules in liquid solutions depend critically on the solvent and other species, or cosolutes, including electrolytes (if present), especially when molecular association or pairing occurs. In Quantum Mechanical (QM) calculations, the electronic structure of molecules in liquid solution is typically obtained with implicit solvent models (ISMs). However, ISMs cannot differentiate between, for example, cation types (e.g., Cs⁺ versus <i>n</i>Bu₄N⁺), leading to limited accuracy in capturing possible solute-specific interactions. Addressing this issue in QM calculations often requires an explicit treatment of the cosolute, typically a counterion, a challenging approach due to the definition of representative cosolute positions, numerical convergence, and high computational cost for bulky species. A new computational strategy called Dynamic Environment in Solution by Clustering (DESC) is herein presented, which leverages classical Molecular Dynamics (MD) data to feed QM calculations, enabling the inclusion of counterion-specific effects with greater detail and efficiency than ISMs. DESC is particularly advantageous in cases where ion pairing/aggregation is significant, offering chemically representative QM results at a small fraction of the computational cost associated with the explicit inclusion of counterions in the model. This work presents MD data on polyoxometalate-counterion-solvent systems, introduces the philosophy behind DESC and its operational details, and applies it to polyoxometalate solutions and other relevant systems, comparing outcomes with benchmark QM/ISM calculations.