We have introduced a computational methodology to study vibrational spectroscopy in clusters inclusive of critical nuclear quantum effects. This approach is based on the recently developed quantum wavepacket ab initio molecular dynamics method that combines quantum wavepacket dynamics with ab initio molecular dynamics. The computational efficiency of the dynamical procedure is drastically improved (by several orders of magnitude) through the utilization of wavelet-based techniques combined with the previously introduced time-dependent deterministic sampling procedure measure to achieve stable, picosecond length, quantumclassical dynamics of electrons and nuclei in clusters. The dynamical information is employed to construct a novel cumulative flux/velocity correlation function, where the wavepacket flux from the quantized particle is combined with classical nuclear velocities to obtain the vibrational density of states. The approach is demonstrated by computing the vibrational density of states of [Cl-H-Cl] -, inclusive of critical quantum nuclear effects, and our results are in good agreement with experiment. A general hierarchical procedure is also provided, based on electronic structure harmonic frequencies, classical ab initio molecular dynamics, computation of nuclear quantum-mechanical eigenstates, and employing quantum wavepacket ab initio dynamics to understand vibrational spectroscopy in hydrogen-bonded clusters that display large degrees of anharmonicities.

We study the hydrogen tunneling problem in a model system that represents the active site of the biological enzyme, soybean lipoxygenase-1. Toward this, we utilize quantum wavepacket dynamics performed on potential surfaces obtained by using hybrid density functional theory under the influence of a dynamical active site. The kinetic isotope effect is computed by using the transmission amplitude of the wavepacket, and the experimental value is reproduced. By computing the hydrogen nuclear orbitals (eigenstates) along the reaction coordinate, we note that tunneling for both hydrogen and deuterium occurs through the existence of distorted, spherical s-type proton wave functions and p-type polarized proton wave functions for transfer along the donor-acceptor axis. In addition, there is also a significant population transfer through distorted p-type proton wave functions directed perpendicular to the donor-acceptor axis (via intervening π-type proton eigenstate interactions) which underlines the three-dimensional nature of the tunneling process. The quantum dynamical evolution indicates a significant contribution from tunneling processes both along the donor-acceptor axis and along directions perpendicular to the donor-acceptor axis. Furthermore, the tunneling process is facilitated by the occurrence of curve crossings and avoided crossings along the proton eigenstate adiabats.

Abstract:In a recent publication, we introduced a computational approach to treat the simultaneous dynamics of electrons and nuclei. The method is based on a synergy between quantum wave packet dynamics and ab initio molecular dynamics. Atom-centered density-matrix propagation or Born-Oppenheimer dynamics can be used to perform ab initio dynamics. In this paper, wave packet dynamics is conducted using a three-dimensional direct product implementation of the distributed approximating functional free-propagator. A fundamental computational difficulty in this approach is that the interaction potential between the two components of the methodology needs to be calculated frequently. Here, we overcome this problem through the use of a time-dependent deterministic sampling measure that predicts, at every step of the dynamics, regions of the potential which are important. The algorithm, when combined with an on-the-fly interpolation scheme, allows us to determine the quantum dynamical interaction potential and gradients at every dynamics step in an extremely efficient manner. Numerical demonstrations of our sampling algorithm are provided through several examples arranged in a cascading level of complexity. Starting from a simple one-dimensional quantum dynamical treatment of the shared proton in [Cl-H-Cl] -and [CH 3 -H-Cl] -along with simultaneous dynamical treatment of the electrons and classical nuclei, through a complete three-dimensional treatment of the shared proton in [Cl-H-Cl] -as well as treatment of a hydrogen atom undergoing donor-acceptor transitions in the biological enzyme, soybean lipoxygenase-1 (SLO-1), we benchmark the algorithm thoroughly. Apart from computing various error estimates, we also compare vibrational density of states, inclusive of full quantum effects from the shared proton, using a novel unified velocity-velocity, flux-flux autocorrelation function. In all cases, the potential-adapted, time-dependent sampling procedure is seen to improve the computational scheme tremendously (by orders of magnitude) with minimal loss of accuracy.

A new x-ray beamline has recently been built, and is now operational, on dipole magnet 2 of the Synchrotron Radiation Source (SRS) at Daresbury. This beamline takes 32 mrad of horizontal aperture from a central tangent point. The time-resolved x-ray diffraction (TRXD) Station 2.1, takes 17 mrad of horizontal aperture and is the central point of this paper. Beamline 2 has been realized as part of a SERC–MRC agreement.

Hydrogenases reversibly catalyze the production of molecular hydrogen. Current interest in these enzymes is focused on understanding the catalysis, since this may prove useful for hydrogen-based fuel cell and photosynthetic hydrogen production cell technologies. A key step in the hydrogenase catalytic cycle and the focus of this work is proton transport (PT) to and from the active site. The PT mechanism of the enzyme is studied using reactive molecular dynamics simulations of the full protein and the excess proton transfers via the multistate empirical valence bond (MS-EVB) method. Pathways connecting the bulk and the active site are located that suggest possible participation by several protonatable residues. PT free energy surfaces are calculated to differentiate the pathways.