Accurate and Efficient Prediction of NMR Parameters of Condensed-Phase Systems with the Generalized Energy-Based Fragmentation Method
Dongbo Zhao, Xiaoling Shen, Zheng Cheng, Wei Li, Hao Dong, Shuhua Li
Abstract
We have implemented the calculations of NMR parameters within the generalized energy-based fragmentation (GEBF) method for condensed-phase systems with periodic boundary conditions (PBC). In this PBC-GEBF approach, NMR parameters of molecules in a unit cell are assembled as a linear combination of the corresponding quantities from a series of small embedded subsystems. To treat condensed-phase systems containing large molecules, we propose a novel “fragment-based” strategy for building subsystems, while our previously reported “molecule-based” strategy for construction of subsystems is appropriate for periodic systems with small molecules. The “fragment-based” strategy in PBC-GEBF is demonstrated to be much more efficient than its “molecule-based” counterpart to treat crystals of large molecules. With the “molecule-based” PBC-GEBF method, we obtained consistently good NMR parameters of liquid water with B3LYP on top of neural-network-potential-based ab initio molecular dynamics (AIMD) snapshots. With the “fragment-based” PBC-GEBF approach, we predicted the 1H chemical shifts of a large macrocycle in solution based on a series of classical MD snapshots. The calculated results are in good accord with the experimental chemical shifts. Therefore, the PBC-GEBF method is expected to be a reliable and efficient tool for predicting NMR parameters of large complex systems in solutions.