An Efficient and Accurate Formalism for the Treatment of Large Amplitude Intramolecular Motion

Abstract

We propose a general approach to describe large amplitude motions (LAM) with multiple degrees of freedom (DOF) in molecules or reaction intermediates, which is useful for the computation of thermochemical or kinetic data. The kinetic part of the LAM Lagrangian is derived using a Z-matrix internal coordinate representation within a new numerical procedure. This derivation is exact for a classical system, and the uncertainties on the prediction of observable quantities largely arise from uncertainties on the LAM potential energy surface (PES) itself. In order to rigorously account for these uncertainties, we present an approach based on Bayesian theory to infer a parametrized physical model of the PES using ab initio calculations. This framework allows for quantification of uncertainties associated with a PES model as well as the forward propagation of these uncertainties to the quantity of interest. A selection and generalization of some treatments accounting for the coupling of the LAM with other internal or external DOF are also presented. Finally, we discuss and validate the approach with two applications: the calculation of the partition function of 1,3-butadiene and the calculation of the high-pressure reaction rate of the CH3 + H → CH4 recombination.

The Effect of Alcohol and Carbonyl Functional Groups on the Competition between Unimolecular Decomposition and Isomerization in C4 and C5 Alkoxy Radicals

“…Thus, proper treatment of internal HRs is critical to more accurately compute rates for reactions that are the focus of this work. With this in mind, we recognize more advanced methods of treating contributions to H‐transfer rates from internal rotors, but such treatments were not attempted here .…”

Bayesian machine learning for quantum molecular dynamics

“…The approach discussed in this subsection bears similarity to the Bayesian calibration of force fields in molecular dynamics simulations (see, for example, Refs. [26][27][28][29][30][31][32]). The goal of this work is either to quantify the error of the molecular dynamics simulations due to the uncertainty of the molecular force fields or to obtain the force field parameters best suited for the simulations of particular properties.…”

“…Bayesian inference has already been used with much success in classical molecular dynamics, as exemplified by Refs. [26][27][28][29][30][31][32].…”

NIC-CAGE: An Open-Source Software Package for Predicting Optimal Control Fields in Photo-Excited Chemical Systems

“…For these reasons, we only focus on quantum control calculations along one-dimensional potentials since (1) two-or higher-dimensional intrinsic reaction paths (or their associated dipole moment surfaces, which are required for quantum control) are not readily computable and (2) much of the relevant dynamics can still be gleaned from the one-dimensional slices of the potential energy surface. To this end, prior work by us [21,30,31,32,33,34] and other researchers [26,35] have shown that an approximate path (which differs from the intrinsic/minimum path) can be parameterized with a single internal coordinate such as a bond length [21], valence bend angle [32,33,34], or dihedral angle [30,31] that can accurately describe reactions involving bond dissociation, isomerization, or internal rotation, respectively. Once a suitable reduced coordinate, x, is chosen, both V(x) and µ(x) can be readily computed in most quantum chemistry packages such as Gaussian [36], Q-Chem [37], GAMESS [38], or NWChem [39] by carrying out a relaxed potential energy scan.…”