Force Field Parametrization of Metal Ions from Statistical Learning Techniques.

A novel statistical procedure has been developed to optimize the parameters of nonbonded force fields of metal ions in soft matter. The criterion for the optimization is the minimization of the deviations from ab initio forces and energies calculated for model systems. The method exploits the combination of the linear ridge regression and the cross-validation techniques with the differential evolution algorithm.

Assessment of multireference perturbation methods for chemical reaction barrier heights.

A few flavors of multireference perturbation theory, two variants of the n-electron valence state perturbation theory and two of the complete active space perturbation theory, are here tested for the calculation of barrier heights for the set of chemical reactions included in the DBH24/08 database, for which very accurate values are available. The comparison of the results obtained with these approaches with those already published for other theoretical models indicates that multireference perturbation theory is a valuable tool for the description of a chemical reaction. Moreover, limiting the comparison to the perturbation theory approaches, one observes that the bad behavior found for single reference methods (such as Møller-Plesset to second and fourth order in the energy) is markedly improved upon moving to the multireference generalizations.

Multi-level quantum Monte Carlo wave functions for complex reactions: the decomposition of α-hydroxy-dimethylnitrosamine.

We present here several novel features of our recently proposed Jastrow linear generalized valence bond (J-LGVB) wave functions, which allow a consistently accurate description of complex potential energy surfaces (PES) of medium-large systems within quantum Monte Carlo (QMC). In particular, we develop a multilevel scheme to treat different regions of the molecule at different levels of the theory. As prototypical study case, we investigate the decomposition of α-hydroxy-dimethylnitrosamine, a carcinogenic metabolite of dimethylnitrosamine (NDMA), through a two-step mechanism of isomerization followed by a retro-ene reaction.

Barrier Heights in Quantum Monte Carlo with Linear-Scaling Generalized-Valence-Bond Wave Functions.

We investigate here the performance of our recently developed linear-scaling Jastrow-generalized-valence-bond (J-LGVB) wave functions based on localized orbitals, for the quantum Monte Carlo (QMC) calculation of the barrier heights and reaction energies of five prototypical chemical reactions. Using the geometrical parameters from the Minnesota database collection, we consider three hydrogen-exchanges, one heavy-atom exchange, and one association reaction and compare our results with the best available experimental and theoretical data. For the three hydrogen-exchange reactions, we find that the J-LGVB wave functions yield excellent QMC results, with average deviations from the reference values below 0.

Size-Extensive Wave Functions for Quantum Monte Carlo: A Linear Scaling Generalized Valence Bond Approach.

We propose a new class of multideterminantal Jastrow-Slater wave functions constructed with localized orbitals and designed to describe complex potential energy surfaces of molecular systems for use in quantum Monte Carlo (QMC). Inspired by the generalized valence bond formalism, we elaborate a coupling scheme between electron pairs which progressively includes new classes of excitations in the determinantal component of the wave function. In this scheme, we exploit the local nature of the orbitals to construct wave functions which have increasing complexity but scale linearly.

Quantum Monte Carlo calculations of the dimerization energy of borane.

Accurate thermodynamic data are required to improve the performance of chemical hydrides that are potential hydrogen storage materials. Boron compounds are among the most interesting candidates. However, different experimental measurements of the borane dimerization energy resulted in a rather wide range (-34.