We present an accurate adaptive multiscale molecular dynamics method that will enable the detailed study of large molecular systems that mimic experiment. The method treats the reactive regions at the quantum mechanical level and the inactive environment regions at lower levels of accuracy, while at the same time molecules are allowed to flow across the border between active and environment regions. Among many other things, this scheme affords accurate investigation of chemical reactions in solution. A scheme like this ideally fulfills the key criteria applicable to all molecular dynamics simulations: energy conservation and computational efficiency. Approaches that fulfill both criteria can, however, result in complicated potential energy surfaces, creating rapid energy changes when the border between regions is crossed. With the difference-based adaptive solvation potential, a simple approach is introduced that meets the above requirements and reduces fast fluctuations in the potential to a minimum. In cases where none of the current adaptive QM/MM potentials are able to properly describe the system under investigation, we use a continuous force scheme instead, which, while no longer energy conserving, still retains a related conserved quantity along the trajectory. We show that this scheme does not introduce a significant temperature drift on time scales feasible for QM/MM simulations.
A new approach for relativistic correlated electron structure calculations is proposed by which a transformation to a two-spinor basis is carried out after solving the four-component relativistic Hartree-Fock equations. The method is shown to be more accurate than approaches that apply an a priori transformation to a two-spinor basis. We also demonstrate how the two-component relativistic calculations with properly transformed two-electron interaction can be simulated at the four-component level by projection techniques, thus allowing an assessment of errors introduced by more approximate schemes.
Abstract:Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed PyAdf, a scripting framework for quantum chemistry. PyAdf handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of PyAdf and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications.
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