Search for: All records

The hybrid quantum mechanics/molecular mechanics (QM/MM) approach, which combines the accuracy of QM methods with the efficiency of MM methods, is widely used in the study of complex systems. However, past QM/MM implementations often neglect or face challenges in addressing nuclear quantum effects, despite their crucial role in many key chemical and biological processes. Recently, our group developed the constrained nuclear-electronic orbital (CNEO) theory, a cost-efficient approach that accurately addresses nuclear quantum effects, especially quantum nuclear delocalization effects. In this work, we integrate CNEO with the QM/MM approach through the electrostatic embedding scheme and apply the resulting CNEO QM/MM to two hydrogen-bonded complexes. We find that both solvation effects and nuclear quantum effects significantly impact hydrogen bond structures and dynamics. Notably, in the glutamic acid–glutamate complex, which mimics a common low barrier hydrogen bond in biological systems, CNEO QM/MM accurately predicts nearly equal proton sharing between the two residues. With an accurate description of both quantum nuclear delocalization effects and environmental effects, CNEO QM/MM is a promising new approach for simulating complex chemical and biological systems. 

The assignment of the hydrogen bonded O–H stretch vibration in the proline matrix IR spectrum has sparked controversy. Employing constrained nuclear electronic orbital methods, we provide a clear assignment that the vibrational frequency drops to near 3000 cm−1 as a result of the interplay between electronic effects, nuclear quantum effects, and matrix effects. 

Kohn–Sham density functional theory has been the most popular method in electronic structure calculations. To fulfill the increasing accuracy requirements, new approximate functionals are needed to address key issues in existing approximations. It is well known that nonlocal components are crucial. Current nonlocal functionals mostly require orbital dependence such as in Hartree–Fock exchange and many-body perturbation correlation energy, which, however, leads to higher computational costs. Deviating from this pathway, we describe functional nonlocality in a new approach. By partitioning the total density to atom-centered local densities, a many-body expansion is proposed. This many-body expansion can be truncated at one-body contributions, if a base functional is used and an energy correction is approximated. The contribution from each atom-centered local density is a single finite-range nonlocal functional that is universal for all atoms. We then use machine learning to develop this universal atom-centered functional. Parameters in this functional are determined by fitting to data that are produced by high-level theories. Extensive tests on several different test sets, which include reaction energies, reaction barrier heights, and non-covalent interaction energies, show that the new functional, with only the density as the basic variable, can produce results comparable to the best-performing double-hybrid functionals, (for example, for the thermochemistry test set selected from the GMTKN55 database, BLYP based machine learning functional gives a weighted total mean absolute deviations of 3.33 kcal/mol, while DSD-BLYP-D3(BJ) gives 3.28 kcal/mol) with a lower computational cost. This opens a new pathway to nonlocal functional development and applications.