Leif Christian Kröger

Automated Discovery of Reaction Pathways, Rate Constants, and Transition States Using Reactive Molecular Dynamics Simulations

We provide a methodology for deducing quantitative reaction models from reactive molecular dynamics simulations by identifying, quantifying, and evaluating elementary reactions of classical trajectories. Simulations of the inception stage of methane oxidation are used to demonstrate our methodology. The agreement of pathways and rates with available literature data reveals the potential of reactive molecular dynamics studies for developing quantitative reaction models.

The furan microsolvation blind challenge for quantum chemical methods: First steps

Herein we present the results of a blind challenge to quantum chemical methods in the calculation of dimerization preferences in the low temperature gas phase. The target of study was the first step of the microsolvation of furan, 2-methylfuran and 2,5-dimethylfuran with methanol. The dimers were investigated through IR spectroscopy of a supersonic jet expansion. From the measured bands, it was possible to identify a persistent hydrogen bonding OH-O motif in the predominant species. From the presence of another band, which can be attributed to an OH-π interaction, we were able to assert that the energy gap between the two types of dimers should be less than or close to 1 kJ/mol across the series. These values served as a first evaluation ruler for the 12 entries featured in the challenge. A tentative stricter evaluation of the challenge results is also carried out, combining theoretical and experimental results in order to define a smaller error bar. The process was carried out in a double-blind fashion, with both theory and experimental groups unaware of the results on the other side, with the exception of the 2,5-dimethylfuran system which was featured in an earlier publication.

Round Robin Study: Molecular Simulation of Thermodynamic Properties from Models with Internal Degrees of Freedom

Thermodynamic properties are often modeled by classical force fields which describe the interactions on the atomistic scale. Molecular simulations are used for retrieving thermodynamic data from such models, and many simulation techniques and computer codes are available for that purpose. In the present round robin study, the following fundamental question is addressed: Will different user groups working with different simulation codes obtain coinciding results within the statistical uncertainty of their data? A set of 24 simple simulation tasks is defined and solved by five user groups working with eight molecular simulation codes: DL_POLY, GROMACS, IMC, LAMMPS, ms2, NAMD, Tinker, and TOWHEE. Each task consists of the definition of (1) a pure fluid that is described by a force field and (2) the conditions under which that property is to be determined. The fluids are four simple alkanes: ethane, propane, n-butane, and iso-butane. All force fields consider internal degrees of freedom: OPLS, TraPPE, and a modified OPLS version with bond stretching vibrations. Density and potential energy are determined as a function of temperature and pressure on a grid which is specified such that all states are liquid. The user groups worked independently and reported their results to a central instance. The full set of results was disclosed to all user groups only at the end of the study. During the study, the central instance gave only qualitative feedback. The results reveal the challenges of carrying out molecular simulations. Several iterations were needed to eliminate gross errors. For most simulation tasks, the remaining deviations between the results of the different groups are acceptable from a practical standpoint, but they are often outside of the statistical errors of the individual simulation data. However, there are also cases where the deviations are unacceptable. This study highlights similarities between computer experiments and laboratory experiments, which are both subject not only to statistical error but also to systematic error.

Automated Chemical Kinetic Modeling via Hybrid Reactive Molecular Dynamics and Quantum Chemistry Simulations

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable, and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready to use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodological advancement of chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Kinetic Modeling of Precipitation Terpolymerization for Functional Microgels

Abstract Microgels based on poly(N-isopropylacrylamide)- and poly(N-vinylcaprolactam) can be synthesized by precipitation polymerization. To get a better insight into the kinetics of the microgel synthesis, a model-based approach is pursued. Herein, the approach proposed by Janssen et al. (2017) is extended to the terpolymerization system. The kinetic model for a two-phase terpolymerization is combined with parameter values from quantum mechanical calculations. The remaining unknown parameter values are estimated from experimental data using reaction calorimetry and Raman spectroscopy. Acceptable agreement of simulation and experimental measurements is obtained. The prediction of the gel phase growth is combined with the consumption of comonomers and the cross-linker N,N’-methylenebis(acrylamide) to predict the average distribution of comonomers, thus giving insight into the microgel structure. The resulting particle structures indicate uniform N-vinylcaprolactam and N-isopropylacrylamide compositions in the core and an outer layer with a high N-vinylcaprolactam fraction, while the cross-linker distribution decreases from core to shell.

Assessing Statistical Uncertainties of Rare Events in Reactive Molecular Dynamics Simulations

Reactive molecular dynamics (MD) simulations are a versatile tool which allow for studying reaction pathways and rates simultaneously. However, most reactions will be observed only a few times in such a simulation due to computational limitations or slow kinetics, and it is unclear how this will influence the obtained rate constants. Therefore, we propose a method based on the Poisson distribution to assess the statistical uncertainty of reaction rate constants obtained from reactive MD simulations.