04 Fakultät Energie-, Verfahrens- und Biotechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/5
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Item Open Access On the use of side‐chain NMR relaxation data to derive structural and dynamical information on proteins : a case study using hen lysozyme(2020) Smith, Lorna J.; Gunsteren, Wilfred F. van; Hansen, NielsValues of S2CH and S2NH order parameters derived from NMR relaxation measurements on proteins cannot be used straightforwardly to determine protein structure because they cannot be related to a single protein structure, but are defined in terms of an average over a conformational ensemble. Molecular dynamics simulation can generate a conformational ensemble and thus can be used to restrain S2CH and S2NH order parameters towards experimentally derived target values S2CH(exp) and S2NH(exp). Application of S2CH and S2NH order‐parameter restraining MD simulation to bond vectors in 63 side chains of the protein hen egg white lysozyme using 51 S2CH(exp) target values and 28 S2NH(exp) target values shows that a conformational ensemble compatible with the experimentally derived data can be obtained by using this technique. It is observed that S2CH order‐parameter restraining of C-H bonds in methyl groups is less reliable than S2NH order‐parameter restraining because of the possibly less valid assumptions and approximations used to derive experimental S2CH(exp) values from NMR relaxation measurements and the necessity to adopt the assumption of uniform rotational motion of methyl C-H bonds around their symmetry axis and of the independence of these motions from each other. The restrained simulations demonstrate that side chains on the protein surface are highly dynamic. Any hydrogen bonds they form and that appear in any of four different crystal structures, are fluctuating with short lifetimes in solution.Item Open Access Predicting and rationalizing the Soret coefficient of binary Lennard‐Jones mixtures in the liquid state(2022) Zimmermann, Nils E. R.; Guevara‐Carrion, Gabriela; Vrabec, Jadran; Hansen, NielsThe thermodiffusion behavior of binary Lennard‐Jones mixtures in the liquid state is investigated by combining the individual strengths of non‐equilibrium molecular dynamics (NEMD) and equilibrium molecular dynamics (EMD) simulations. On the one hand, boundary‐driven NEMD simulations are useful to quickly predict Soret coefficients because they are easy to set up and straightforward to analyze. However, careful interpolation is required because the mean temperature in the measurement region does not exactly reach the target temperature. On the other hand, EMD simulations attain the target temperature precisely and yield a multitude of properties that clarify the microscopic origins of Soret coefficient trends. An analysis of the Soret coefficient suggests a straightforward dependence on the thermodynamic properties, whereas its dependence on dynamic properties is far more complex. Furthermore, a limit of applicability of a popular theoretical model, which mainly relies on thermodynamic data, was identified by virtue of an uncertainty analysis in conjunction with efficient empirical Soret coefficient predictions, which rely on model parameters instead of simulation output. Finally, the present study underscores that a combination of predictive models and EMD and NEMD simulations is a powerful approach to shed light onto the thermodiffusion behavior of liquid mixtures.Item Open Access Probing self-diffusion of guest molecules in a covalent organic framework : simulation and experiment(2024) Grunenberg, Lars; Keßler, Christopher; Teh, Tiong Wei; Schuldt, Robin; Heck, Fabian; Kästner, Johannes; Groß, Joachim; Hansen, Niels; Lotsch, Bettina V.Covalent organic frameworks (COFs) are a class of porous materials whose sorption properties have so far been studied primarily by physisorption. Quantifying the self-diffusion of guest molecules inside their nanometer-sized pores allows for a better understanding of confinement effects or transport limitations and is thus essential for various applications ranging from molecular separation to catalysis. Using a combination of pulsed field gradient nuclear magnetic resonance measurements and molecular dynamics simulations, we have studied the self-diffusion of acetonitrile and chloroform in the 1D pore channels of two imine-linked COFs (PI-3-COF) with different levels of crystallinity and porosity. The higher crystallinity and porosity sample exhibited anisotropic diffusion for MeCN parallel to the pore direction, with a diffusion coefficient of Dpar = 6.1(3) × 10-10 m2 s-1 at 300 K, indicating 1D transport and a 7.4-fold reduction in self-diffusion compared to the bulk liquid. This finding aligns with molecular dynamics simulations predicting 5.4-fold reduction, assuming an offset-stacked COF layer arrangement. In the low-porosity sample, more frequent diffusion barriers result in isotropic, yet significantly reduced diffusivities (DB = 1.4(1) × 10-11 m2 s-1). Diffusion coefficients for chloroform at 300 K in the pores of the high- (Dpar = 1.1(2) × 10-10 m2 s-1) and low-porosity (DB = 4.5(1) × 10-12 m2 s-1) samples reproduce these trends. Our multimodal study thus highlights the significant influence of real structure effects such as stacking faults and grain boundaries on the long-range diffusivity of molecular guest species while suggesting efficient intracrystalline transport at short diffusion times.Item Open Access Application of generalized (hyper-) dual numbers in equation of state modeling(2021) Rehner, Philipp; Bauer, GernotThe calculation of derivatives is ubiquitous in science and engineering. In thermodynamics, in particular, state properties can be expressed as derivatives of thermodynamic potentials. The manual differentiation of complex models can be tedious and error-prone. In this work, we revisit dual and hyper-dual numbers for the calculation of exact derivatives and show generalizations to higher order derivatives and derivatives with respect to vector quantities. The methods described in this paper are accompanied by an open source Rust implementation with Python bindings. Applications of the generalized (hyper-) dual numbers are given in the context of equation of state modeling and the calculation of critical points.Item Open Access Modeling subsurface hydrogen storage with transport properties from entropy scaling using the PC‐SAFT equation of state(2022) Eller, Johannes; Sauerborn, Tim; Becker, Beatrix; Buntic, Ivan; Gross, Joachim; Helmig, RainerHydrogen is a promising alternative to carbon based energy carriers and may be stored in large quantities in subsurface storage deposits. This work assesses the impact of static (density and phase equilibria) and dynamic (viscosity and diffusion coefficients) properties on the pressure field during the injection and extraction of hydrogen in the porous subsurface. In a first step, we derive transport properties for water, hydrogen and their mixture using the Perturbed‐Chain Statistical Associating Fluid Theory equation of state in combination with an entropy scaling approach and compare model predictions to alternative models from the literature. Our model compares excellently to experimental transport coefficients and models from literature with a higher number of adjustable parameters, such as GERG2008, and shows a clear improvement over empirical correlations for transport coefficients of hydrogen. In a second step, we determine the effect of further model reduction by comparing our against a much simpler model applying empirical transport coefficients from the literature. For this purpose, hydrogen is periodically injected into and extracted out of a dome‐shaped porous aquifer under a caprock. Our results show that density and viscosity of hydrogen have the highest impact on the pressure field, and that a thermodynamic model like the new model presented here is essential for modeling the storage aquifer, while keeping the number of coefficients at a minimum. In diffusion‐dominated settings such as the diffusion of hydrogen through the caprock, our developed diffusion coefficients show a much improved dependence on temperature and pressure, leading to a more accurate approximation of the diffusive fluxes.Item Open Access An atomistic view on the uptake of aromatic compounds by cyclodextrin immobilized on mesoporous silica(2022) Kraus, Hamzeh; Hansen, NielsThe effect of immobilized β-cyclodextrin (bCD) molecules inside a mesoporous silica support on the uptake of benzene and p -nitrophenol from aqueous solution was investigated using all-atom molecular dynamics (MD) simulations. The calculated adsorption isotherms are discussed with respect to the free energies of binding for a 1:1 complex of bCD and the aromatic guest molecule. The adsorption capacity of the bCD-containing material significantly exceeds the amount corresponding to a 1:1 binding scenario, in agreement with experimental observations. Beside the formation of 1:2 and, to a lesser extent, 1:3 host:guest complexes, also host-host interactions on the surface as well as more unspecific host-guest interactions govern the adsorption process. The demonstrated feasibility of classical all-atom MD simulations to calculate liquid phase adsorption isotherms paves the way to a molecular interpretation of experimental data that are too complex to be described by empirical models.Item Open Access Process-based screening of porous materials for vacuum swing adsorption based on 1D classical density functional theory and PC-SAFT(2025) Mayer, Fabian; Buhk, Benedikt; Schilling, Johannes; Rehner, Philipp; Gross, Joachim; Bardow, AndréAdsorption-based processes are showing substantial potential for carbon capture. Due to the vast space of potential solid adsorbents and their influence on the process performance, the choice of the material is not trivial but requires systematic approaches. In particular, the material choice should be based on the performance of the resulting process. In this work, we present a method for the process-based screening of porous materials for pressure and vacuum swing adsorption. The method is based on an equilibrium process model that incorporates one-dimensional classical density functional theory (1D-DFT) and the PC-SAFT equation of state. Thereby, the presented method can efficiently screen databases of potential adsorbents and identify the best-performing materials as well as the corresponding optimized process conditions for a specific carbon capture application. We apply our method to a point-source carbon capture application at a cement plant. The results show that the process model is crucial to evaluating the performance of adsorbents instead of relying solely on material heuristics. Furthermore, we enhance our approach through multi-objective optimization and demonstrate for materials with high performance that our method is able to capture the trade-offs between two process objectives, such as specific work and purity. The presented method thus provides an efficient screening tool for adsorbents to maximize process performance.Item Open Access On the use of 3J-coupling NMR data to derive structural information on proteins(2021) Smith, Lorna J.; Gunsteren, Wilfred F. van; Stankiewicz, Bartosz; Hansen, NielsValues of 3J-couplings as obtained from NMR experiments on proteins cannot easily be used to determine protein structure due to the difficulty of accounting for the high sensitivity of intermediate 3J-coupling values (4-8 Hz) to the averaging period that must cover the conformational variability of the torsional angle related to the 3J-coupling, and due to the difficulty of handling the multiple-valued character of the inverse Karplus relation between torsional angle and 3J-coupling. Both problems can be solved by using 3J-coupling time-averaging local-elevation restraining MD simulation. Application to the protein hen egg white lysozyme using 213 backbone and side-chain 3J-coupling restraints shows that a conformational ensemble compatible with the experimental data can be obtained using this technique, and that accounting for averaging and the ability of the algorithm to escape from local minima for the torsional angle induced by the Karplus relation, are essential for a comprehensive use of 3J-coupling data in protein structure determination.