Publications by authors named "Kai Leonhard"

Accurate thermochemistry computations often require proper treatment of torsional modes. The one-dimensional hindered rotor model has proven to be a computationally efficient solution, given a sufficiently accurate potential energy surface. Methods that provide potential energies at various compromises of uncertainty and computational time demand can be optimally combined within a multifidelity treatment.

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Automatic potential energy surface (PES) exploration is important to a better understanding of reaction mechanisms. Existing automatic PES mapping tools usually rely on predefined knowledge or computationally expensive on-the-fly quantum-chemical calculations. In this work, we have developed the PESmapping algorithm for discovering novel reaction pathways and automatically mapping out the PES using merely one starting species is present.

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Accurately predicting partition coefficients log  is crucial for reducing costs and accelerating drug design as it provides valuable information about the bioavailability, pharmacokinetics, and toxicity of different drug candidates. However, the performance of the existing methods is ambiguous, making it unclear whether these methods can be effectively utilized in drug discovery. To assess the performance of these methods, a series of SAMPL challenges have been conducted over the past few years, aiming to enable the development and validation of predictive models.

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Vibrational spectroscopy in supersonic jet expansions is a powerful tool to assess molecular aggregates in close to ideal conditions for the benchmarking of quantum chemical approaches. The low temperatures achieved as well as the absence of environment effects allow for a direct comparison between computed and experimental spectra. This provides potential benchmarking data which can be revisited to hone different computational techniques, and it allows for the critical analysis of procedures under the setting of a blind challenge.

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Computational benchmark data for complexes requires accurate models of anharmonic torsional motion. State-of-the-art hindered rotor treatments come with a number of difficulties, regarding discontinuities from badly converged points or coupling, oscillations, or the consideration and correction of stationary points. Their manual handling introduces a level of arbitrariness not suitable for benchmark procedures.

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Biohybrid fuels are a promising solution for making the transportation sector more environmentally friendly. One such interesting fuel candidate is 1,3-dioxolane, which can be produced from inedible biomass. However, very little kinetics data are available for the low-temperature oxidation of this fuel molecule.

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This work presents a novel parametrization for the ReaxFF formalism as a means to investigate reaction processes of chlorinated organic compounds. Force field parameters cover the chemical elements C, H, O, Cl and were obtained using a novel optimization approach involving relaxed potential energy surface scans as training targets. The resulting ReaxFF parametrization shows good transferability, as demonstrated on two independent ab initio validation sets.

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Bio-hybrid fuels are a promising solution to accomplish a carbon-neutral and low-emission future for the transportation sector. Two potential candidates are the heterocyclic acetals 1,3-dioxane (CHO) and 1,3-dioxolane (CHO), which can be produced from the combination of biobased feedstocks, carbon dioxide, and renewable electricity. In this work, comprehensive experimental and numerical investigations of 1,3-dioxane and 1,3-dioxolane were performed to support their application in internal combustion engines.

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In our two-paper series, we first present the development of ReaxFF CHOCl parameters using the recently published ParAMS parametrization tool. In this second part, we update the reactive Molecular Dynamics - Quantum Mechanics coupling scheme ChemTraYzer and combine it with our new ReaxFF parameters from Part I to study formation and decomposition processes of chlorinated dibenzofurans. We introduce a self-learning method for recovering failed transition-state searches that improves the overall ChemTraYzer transition-state search success rate by 10 percentage points to a total of 48 %.

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Copper guanidine-quinoline complexes are an important class of bioinorganic complexes that find utilization in electron and atom transfer processes. By substitution of functional groups on the quinoline moiety the electron transfer abilities of these complexes can be tuned. In order to explore the full substitution space by simulations, the accurate theoretical description of the effect of functional groups is essential.

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The spectroscopic quantification of mixture compositions usually requires pure compounds and mixtures of known compositions for calibration. Since they are not always available, methods to fill such gaps have evolved, which are, however, not generally applicable. Therefore, calibration can be extremely challenging, especially when multiple unstable species, for example, intermediates, exist in a system.

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The development of a reaction model is often a time-consuming process, especially if unknown reactions have to be found and quantified. To alleviate the reaction modeling process, automated procedures for reaction space exploration are highly desired. We present ChemTraYzer-TAD, a new reactive molecular dynamics acceleration technique aimed at efficient reaction space exploration.

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This study presents configuration integral Monte Carlo integration (CIMCI), a new semiclassical method for handling fully coupled anharmonicity in gas-phase thermodynamics that promises to be black boxable, to be applicable to all kinds of anharmonicity, and to scale better at higher dimensionality than other methods for handling gas-phase molecular anharmonicity. The method does so using automatically and recursively stratified, simultaneous Monte Carlo (MC) integration of multiple functions, following a modified version of the standard MISER scheme that converges at a rate of about the square of naïve MC integration. For the small systems analyzed by this study where proper reference data is available (HO and HO), the method's anharmonic entropy corrections match reference data better than those of other black box anharmonic methods, e.

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Article Synopsis
  • The peptide LBF14 can transform vesicles into tubule networks and contains non-standard amino acids, but its exact interactions with membranes and structure remain to be fully understood.
  • Researchers used molecular dynamics simulations to study LBF14, focusing on its folding, interaction with lipid bilayers, and the impact of histidine protonation on its helical structure.
  • The simulations revealed that while LBF14 interacts with membranes and shows two distinct conformations, it does not significantly change the overall membrane structure or pressure; these findings align with previous studies on the peptide.
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The chemistry of urethanes plays a key role in important industrial processes. Although catalysts are often used, the study of the reactions without added catalysts provides the basis for a deeper understanding. For the non-catalytic urethane formation and cleavage reactions, the dominating reaction mechanism has long been debated.

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The site-specific first microsolvation step of furan and some of its derivatives with methanol is explored to benchmark the ability of quantum-chemical methods to describe the structure, energetics, and vibrational spectrum at low temperature. Infrared and microwave spectra in supersonic jet expansions are used to quantify the docking preference and some relevant quantum states of the model complexes. Microwave spectroscopy strictly rules out in-plane docking of methanol as opposed to the top coordination of the aromatic ring.

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The prediction of solvation free energies is essential for a variety of applications. Solvation free energies of neutral systems can be predicted quite accurately. The accuracy of predictions for solvation free energies of ionic solutes dissolved in neutral solvents, however, has been reported to be worse by at least 1 order of magnitude.

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Anharmonicity can greatly affect rate constants. One or even several orders of magnitude of deviation are found for obtaining rate constants using the standard rigid-rotor harmonic-oscillator model. In turn, reactive molecular dynamics (MD) simulations are a powerful way to explore chemical reaction networks and calculate rate constants from the fully anharmonic potential energy surface.

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() can be calculated either from the Rice-Ramsperger-Kassel-Marcus theory or by inverting macroscopic rate constants (). Here, we elaborate the inverse Laplace transform approach for () reconstruction by examining the impact of () data fitting accuracy. For this approach, any inaccuracy in the reconstructed () results from inaccurate/incomplete () description.

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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.

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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.

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The polymer poly(N-isopropylacrylamide) (PNIPAM) is studied using a novel combination of multiscale modeling methodologies. We develop an iterative Boltzmann inversion potential of concentrated PNIPAM solutions and combine it with lattice Boltzmann as a Navier-Stokes equation solver for the solvent. We study in detail the influence of the methodology on statics and dynamics of the system.

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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.

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