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Frederik Zysk

Publications and source records attributed to Frederik Zysk.

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Predicting the hydrogen bond strength from water reorientation dynamics at short timescales

Path-integral molecular dynamics simulations and electronic structure-based energy decomposition analysis (EDA) are employed to connect hydrogen bond (H-bond) strength, its asymmetry, and the total delocalization energy at the water/air interface to experimentally measurable observables, such as the reorientation dynamics and the sum-frequency generation (SFG) spectrum. Using SFG spectra for distinct layers at the water/air interface, we validate the accuracy of our simulations and report a red-shift from the interface to bulk and a strongly bonded water peak at around 3250 cm$^{-1}$ in the layer closest to bulk. The reorientation dynamics of water molecules slow down from the interface to bulk, which correlates with the SFG results. From our EDA based on absolutely localized molecular orbitals, we observe a strong decline in total delocalization energy from bulk to the interface, as well as a decline in the strength of the strongest donor and acceptor interactions. The asymmetry between the two strongest interactions similarly rises towards the interface, while the importance of interactions from the outer solvation shells is greatly diminished and is lower than previously reported. Finally, we find that the strength of the strongest H-bond donor/acceptor is best correlated with the local minimum of the autocorrelation function resembling the L2 band librational motions. Following that, we propose a simple yet quantitative relationship between H-bond strength and the short-time reorientation dynamics at the water/air interface that could potentially be extended to predict H-bond strength in other hydrophobic systems from experimentally obtainable observables.

physics.chem-ph

Benchmarking semi-empirical quantum chemical methods on liquid water

Stimulated by the renewed interest and recent developments in semi-empirical quantum chemical (SQC) methods for noncovalent interactions, we examine the properties of liquid water at ambient conditions by means of molecular dynamics (MD) simulations, both with the conventional NDDO-type (neglect of diatomic differential overlap) methods, e.g. AM1 and PM6, and with DFTB-type (density-functional tight-binding) methods, e.g. DFTB2 and GFN-xTB. Besides the original parameter sets, some specifically reparametrized SQC methods (denoted as AM1-W, PM6-fm, and DFTB2-iBi) targeting various smaller water systems ranging from molecular clusters to bulk are considered as well. The quality of these different SQC methods for describing liquid water properties at ambient conditions are assessed by comparison to well-established experimental data and also to BLYP-D3 density functional theory-based ab initio MD simulations. Our analyses reveal that static and dynamics properties of bulk water are poorly described by all considered SQC methods with the original parameters, regardless of the underlying theoretical models, with most of the methods suffering from too weak hydrogen bonds and hence predicting a far too fluid water with highly distorted hydrogen bond kinetics. On the other hand, the reparametrized force-matchcd PM6-fm method is shown to be able to quantitatively reproduce the static and dynamic features of liquid water, and thus can be used as a computationally efficient alternative to electronic structure-based MD simulations for liquid water that requires extended length and time scales. DFTB2-iBi predicts a slightly overstructured water with reduced fluidity, whereas AM1-W gives an amorphous ice-like structure for water at ambient conditions.

physics.comp-ph

Simulations of Disordered Matter in 3D with the Morphological Autoregressive Protocol (MAP) and Convolutional Neural Networks

Disordered molecular systems such as amorphous catalysts, organic thin films, electrolyte solutions, and water are at the cutting edge of computational exploration today. Traditional simulations of such systems at length-scales relevant to experiments in practice require a compromise between model accuracy and quality of sampling. To remedy the situation, we have developed an approach based on generative machine learning called the Morphological Autoregressive Protocol (MAP) which provides computational access to mesoscale disordered molecular configurations at linear cost at generation for materials in which structural correlations decay sufficiently rapidly. The algorithm is implemented using an augmented PixelCNN deep learning architecture that we previously demonstrated produces excellent results in 2 dimensions (2D) for mono-elemental molecular systems. Here, we extend our implementation to multielemental 3D and demonstrate performance using water as our test system in two scenarios: 1. liquid water, and 2. a sample conditioned on the presence of a rare motif. We trained the model on small-scale samples of liquid water produced using path-integral molecular dynamics simulation including nuclear quantum effects under ambient conditions. MAP-generated water configurations are shown to accurately reproduce the properties of the training set and to produce stable trajectories when used as initial conditions in classical and quantum dynamical simulations. We expect our approach to perform equally well on other disordered molecular systems while offering unique advantages in situations when the disorder is quenched rather than equilibrated.

cond-mat.mes-hall

PECVD and PEALD on polymer substrates (Part II): Understanding and tuning of barrier and membrane properties of thin films

This feature article presents insights concerning the correlation of PECVD and PEALD thin film structures with their barrier or membrane properties. While in principle similar precursor gases and processes can be applied, the adjustment of deposition parameters for different polymer substrates can lead to either an effective diffusion barrier or selective permeabilities. In both cases the understanding of the film growth and the analysis of the pore size distribution and the pore surface chemistry is of utmost importance for the understanding of the related transport properties of small molecules. In this regard the article presents both concepts of thin film engineering and analytical as well as theoretical approaches leading to a comprehensive description of the state of the art in this field. Moreover, based on the presented correlation of film structure and molecular transport properties perspectives of future relevant research in this area is presented.

cond-mat.soft

PECVD and PEALD on polymer substrates (part I): Fundamentals and analysis of plasma activation and thin film growth

This feature article considers the analysis of the initial states of film growth on polymer substrates. The assembled results are based on the cooperation between research groups in the field of plasma physics, chemistry, electric as well as mechanical engineering over the last years, mostly within the frame of the transregional project SFB-TR 87 ("Pulsed high power plasmas for the synthesis of nanostructured functional layers"). This feature article aims at bridging the gap between the understanding of plasma processes in the gas phase and the resulting surface and interface processes of the polymer. The results show that interfacial adhesion and initial film growth can be well controlled and even predicted based on the combination of analytical approaches.

cond-mat.soft

Nuclear quantum effects on the vibrational dynamics of the water-air interface

We have applied path integral molecular dynamics simulations to investigate nuclear quantum effects on the vibrational dynamics of water molecules at the water-air interface. The instantaneous fluctuations in the frequencies of the O-H stretch modes are calculated using the wavelet method of time series analysis, while the time scales of vibrational spectral diffusion are determined from frequency-time correlation functions and joint probability distributions, as well as the hydrogen bond number correlation functions. We find that the inclusion of nuclear quantum effects leads not only to a redshift in the vibrational frequency distribution by about 120~cm$^{-1}$ for both the bulk and interfacial water molecules, but also to an acceleration of the vibrational dynamics on the water-air interface by as much as 60$\%$. In addition, a blueshift of about 30 ~cm$^{-1}$ is seen in the vibrational frequency distribution of interfacial water molecules compared to that of the bulk. Furthermore, the dynamics of water molecules beyond the topmost two molecular layers was found to be essentially similar to that of bulk water.

physics.chem-ph

Water structure near the surface of Weyl semimetals as catalysts in photocatalytic proton reduction

In this work, second-generation Car-Parrinello-based QM/MM molecular dynamics simulations of small nanoparticles of NbP, NbAs, TaAs and 1T-TaS$_2$ in water are presented. The first three materials are topological Weyl semimetals, which were recently discovered to be active catalysts in photocatalytic water splitting. The aim of this research was to correlate potential differences in the water structure in the vicinity of the nanoparticle surface with the photocatalytic activity of these materials in light induced proton reduction. The results presented herein allow to explain the catalytic activity of these Weyl semimetals: the most active material, NbP, exhibits a particularly low water coordination near the surface of the nanoparticle, whereas for 1T-TaS$_2$, with the lowest catalytic activity, the water structure at the surface is most ordered. In addition, the photocatalytic activity of several organic and metalorganic photosensitizers in the hydrogen evolution reaction was experimentally investigated with NbP as proton reduction catalyst. Unexpectedly, the charge of the photosensitizer plays a decisive role for the photocatalytic performance.

physics.chem-ph