Computational Methods for Ab Initio Molecular Dynamics

Abstract

Ab initio molecular dynamics is an irreplaceable technique for the realistic simulation of complex molecular systems and processes from first principles. This paper proposes a comprehensive and self-contained review of ab initio molecular dynamics from a computational perspective and from first principles. Quantum mechanics is presented from a molecular dynamics perspective. Various approximations and formulations are proposed, including the Ehrenfest, Born-Oppenheimer, and Hartree-Fock molecular dynamics. Subsequently, the Kohn-Sham formulation of molecular dynamics is introduced as well as the afferent concept of density functional. As a result, Car-Parrinello molecular dynamics is discussed, together with its extension to isothermal and isobaric processes. Car-Parrinello molecular dynamics is then reformulated in terms of path integrals. Finally, some implementation issues are analysed, namely, the pseudopotential, the orbital functional basis, and hybrid molecular dynamics.

A Review on Combination of Ab Initio Molecular Dynamics and NMR Parameters Calculations

“…Therefore, quantum MD combined with GIPAW NMR calculations were used to confirm the quality and correctness of the deposited crystal structure. The obtained computational results supported the presence of only one molecule in the asymmetric unit as the standard deviation of the values of the 13 C isotropic chemical shielding calculated for the four equivalent atoms were found to be negligible. Finally, the splitting was explained as resulting from exceptionally strong residual dipolar couplings between the 13 C and 14 N atoms.…”

“…aiMD simulations coupled to calculations of NMR parameters have been of great utility in predicting the effects of nuclear vibrations on NMR chemical shieldings and Jcouplings in each state of matter. Among the nuclei studied using this combined approach, popular ones such as 1 H, 13 C, or 15 N, but also more exotic, for example, 131 Xe, 195 Pt, and 207 Pb, can be found. It was also confirmed that with aiMD, it is possible to investigate relaxation phenomena as from a single or a set of computed aiMD trajectories, the relaxation times T 1 and T 2 can be determined.…”

“…In order to underline the importance of the vibrational motion inclusion, the already quite an old paper by Martin Dračınsky and Paul Hodgkinson should be brought up here [32]. After comparison with the experimental data, it was proven that for the most common nuclei such as 1 H, 13 C, 14 N, 17 O, and 35 Cl, aiMD significantly improves the accuracy of the post-simulation calculated quadrupolar couplings. This conclusion is even more appealing if one takes into account the diversity of the structures used in this particular study.…”

“…A good example is a study that focused on piracetam, a popular active pharmaceutical ingredient [54]. In the 13 C ssNMR spectrum of one of the studied forms, the splitting of some peaks suggested that there is more than one molecule in the asymmetric unit (Z > 1), although in the experimental crystal structure obtained from SCXRD measurements, only one molecule was present (Z = 1, Z = 4). Therefore, quantum MD combined with GIPAW NMR calculations were used to confirm the quality and correctness of the deposited crystal structure.…”

Boosting the Optimization of Lithium Metal Batteries by Molecular Dynamics Simulations: A Perspective

“…[20] CMD relies on semi-empirical effective potentials which is similar to quantum effects, while AIMD is based on the real physical potentials. [21] Various properties such as structure, electronic structure, ion solvation structure, ion diffusion, chemical reaction, thermal stability, intermolecular interactions and surface properties can be calculated by MD under different conditions which are called canonical ensemble (NVT), mocrocanonical ensemble (NVE), isothermal isobaric ensemble (NPT) and isenthalpy isobaric ensemble (NPH) in professional. [22] Beside the all-atom simulations mentioned above, large scale dynamic behavior can be simulated by CGMD and it can reflect more information on the micro level.…”