Abstract
A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms, decompose it and retain only its positive definite part to construct a sparse preconditioner matrix. The construction requires only the computation of the gradient of the corresponding molecular mechanical terms that are already available in popular force field software packages. For molecular crystals, the preconditioner can be combined straightforwardly with the exponential preconditioner recently introduced for periodic systems. The efficiency is demonstrated on several systems using empirical, semiempirical and ab initio potential energy surfaces.
Highlights
Geometry optimisation and transition state search are fundamental procedures to identify important stationary points of molecules, molecular crystals and material systems in computational chemistry
We briefly review the methodology for preconditioning geometry optimisation and the dimer saddle point search method for material systems[3]
We investigated several organic molecules’ geometry optimisations with (FF) and without (ID) our new FF-based preconditioner on three potential energy surfaces
Summary
Geometry optimisation and transition state search are fundamental procedures to identify important stationary points of molecules, molecular crystals and material systems in computational chemistry. The update of the approximate Hessian can be achieved either by using quasi-Newton methods or other techniques such as DIIS10,11 Such strategies significantly improve the speed of convergence in either Cartesian or internal coordinates[6]. If the model Hessian is cheap to calculate (e.g., as obtained from a surrogate model) and provides a reasonable approximation of the quantum Hessian, it may be advantageous to recompute it at every optimisation step Such a scheme was introduced by Lindh et al.[12], where a model potential is constructed consisting of quadratic terms for all distances, angles and dihedrals in the molecule. This approach yields excellent performance, which led to its wide implementation in quantum chemistry program packages (e.g. in MOLPRO13, ORCA14, DALTON15, CRYSTAL16)
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