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We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.
The elucidation of conformations and relative potential energies (rPEs) of small molecules has a long history across a diverse range of fields. Periodically, it is helpful to revisit what conformations have been investigated and to provide a consistent theoretical framework for which clear comparisons can be made. In this paper, we compute the minima, first- and second-order saddle points, and torsion-coupled surfaces for methanol, ethanol, propan-2-ol, and propanol using consistent high-level MP2 and CCSD(T) methods. While for certain molecules more rigorous methods were employed, the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pV5Z theory level was used throughout to provide relative energies of all minima and first-order saddle points. The rPE surfaces were uniformly computed at the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ level. To the best of our knowledge, this represents the most extensive study for alcohols of this kind, revealing some new aspects. Especially for propanol, we report several new conformations that were previously not investigated. Moreover, two metrics are included in our analysis that quantify how the selected surfaces are similar to one another and hence improve our understanding of the relationship between these alcohols.
Liquid–liquid equilibria of dipropylene glycol dimethyl ether and water by molecular dynamics
(2011)
A traditional way to teach bachelor students in electrical engineering is organized such that theoretical knowledge is predominant in the first year while applications and practical experiences are reserved for later stages of their education. In this contribution, we want to introduce a reverse approach: In a freshmen course at Bonn-Rhein-Sieg University of Applied Science, students gain hands-on experience with resistances, condensers and other active parts, like transistors or relays from the very first day. We present how the combination of practical experience directly linked with theoretical knowledge enhances students' learning. It promotes deeper understanding of the theory and a better transfer between theory and practice. This teaching approach is adapted to address two main goals: First, to give practical experience to first-semester students as a basis for further laboratory and working situations. Second, to create a deeper and more sustainable understanding of physics by directly observing the effects that are described in formulas. The key to success is to find an efficient solution to carry out this approach with the given spatial and financial resources-which means, to do it in the lecture hall with very few material resources. To show that this innovative teaching concept really enhances the competencies of the students, an innovative evaluation approach was used where the students have to reflect upon their competencies before and after the course.
Herein we report an update to ACPYPE, a Python3 tool that now properly converts AMBER to GROMACS topologies for force fields that utilize nondefault and nonuniform 1–4 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 1–4 scaling factors and positive dihedral force constants. We demonstrate that the updated ACPYPE accurately transfers the GLYCAM06 force field from AMBER to GROMACS topology files, which employs non-uniform 1–4 scaling factors as well as negative dihedral force constants. Validation was performed using β-d-GlcNAc through gas-phase analysis of dihedral energy curves and probability density functions. The updated ACPYPE retains all of its original functionality, but now allows the simulation of complex glycomolecular systems in GROMACS using AMBER-originated force fields. ACPYPE is available for download at https://github.com/alanwilter/acpype.
In this contribution we present the concept for creating an “International Chair” position at a German University of Applied Sciences and our experiences in its first implementation. Our primary goal was to increase the diversity of the university’s teaching personalities and enrich student education by including content, methods, examples and experiences from other cultures. This gives students an international and intercultural learning experience that is otherwise only acquired through studying abroad. We conclude that the International Chair is a valuable and powerful university tool for increasing international exposure to the departments, their staff and students.
Atomistic biomolecular simulations predominantly utilize additive force fields (FF), where the electrostatic potential is modeled by fixed point charges. Among other consequences, the lack of polarizability in these models undermines the balance of hydrophilic/hydrophobic non-bonded interactions. Simulations of water/alkane systems using the TIP3P water model and CHARMM36 parameters reveal a 1 kcal/mol over-estimate of the experimental transfer free energy of water to hexadecane; more recent optimized water models (SPC/E, TIP4P/2005, TIP4P-Ew, TIP3P-FB, TIP4P-FB, OPC, TIP4P-D) overestimate this transfer free energy by approximately 2 kcal/mol. In contrast, the polarizable SWM4-NDP and SWM6 water models reproduce experimental values to within statistical error. As an alternative to explicitly modeling polarizability, this paper develops an efficient automated workflow to optimize pair-specific Lennard-Jones parameters within an additive FF. Water/hexadecane is used as a prototype and the free energy of water transfer to hexadecane as a target. The optimized model yields quantitative agreement with the experimental transfer free energy and improves the water/hexadecane interfacial tension by 6%. Simulations of five different lipid bilayers show a strong increase of water permeabilities compared to the unmodified CHARMM36 lipid FF which consistently improves match with experiment: the order-of-magnitude underestimate for monounsaturated bilayers is rectified and the factor of 2.8 - 4 underestimate for saturated bilayers is turned into a factor of 1.5 - 3 overestimate. While agreement with experiment is decreased for the diffusion constant of water in hexadecane, alkane transfer free energies, and the bilayers' area per lipid, the method provides a permeant-specific route to achieve a wide range of heterogeneous observables via rapidly optimized pairwise parameters.
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
Automated parameterization of intermolecular pair potentials using global optimization techniques
(2014)
In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters’ influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.
Wo Laborexperimente zu aufwendig, zu teuer, zu langsam oder zu gefährlich oder Stoffeigenschaften gar nicht erst experimentell zugänglich sind, können Computersimulationen von Atomen und Molekülen diese ersetzen oder ergänzen. Sie ermöglichen dadurch Reduktion von Kosten, Entwicklungszeit und Materialeinsatz. Die für diese Simulationen benötigten Molekülmodelle beinhalten zahlreiche Parameter, die der Simulant einstellen oder auswählen muss. Eine passende Parametrierung ist nur bei entsprechenden Kenntnissen über die Auswirkungen der Parameter auf die zu berechnenden Größen und Eigenschaften möglich. Eine Gruppe von Standardparametern in molekularen Simulationen sind die Partialladungen der einzelnen Atome innerhalb eines Moleküls. Die räumliche Ladungsverteilung innerhalb des Moleküls wird durch Punktladungen auf den Atomzentren angenähert. Für diese Annäherung existieren diverse Ansätze für verschiedene Molekülklassen und Anwendungen. In diesem Teilprojekt des Promotionsvorhabens wurde systematisch der Einfluss der Wahl des Partialladungssatzes auf potentielle Energien und ausgewählte makroskopische Eigenschaften aus Molekulardynamik-Simulationen evaluiert. Es konnte gezeigt werden, dass insbesondere bei stark polaren Molekülen die Auswahl des geeigneten Partialladungssatzes entscheidenden Einfluss auf die Simulationsergebnisse hat und daher nicht naiv, sondern nur ganz gezielt getroffen werden darf.
The lattice Boltzmann method is a modern approach to simulate fluid flow. In its original formulation, it is restricted to regular grids, second-order discretizations, and a unity CFL number. This paper describes our new off-lattice Boltzmann solver NATriuM, an extensible and parallel C++ code to perform lattice Boltzmann simulations on irregular grids. NATriuM also allows high-order spatial discretizations and non-unity CFL numbers to be used. We demonstrate how these features can efficiently decrease the number of grid points required in a simulation and thus reduce the computational time, compared to the standard lattice Boltzmann method. We detail the implementation of a recently proposed semi-Lagrangian lattice Boltzmann method and prove its efficiency in comparisons to other state-of-the-art off-lattice Boltzmann schemes.
In light of emobility, the development of efficiency improved drivetrain components will also have a high priority. Whereas for conventional vehicle propulsion systems (i.e. combustion type engines) the avoidance of CO2 penalty was in strong focus, for electrified vehicles it is the impact on vehicle range. For GKN Driveline as the world's leading supplier of driveline components and systems, the prediction of energy savings is of particular importance in order to quantify the benefit of efficiency optimizations on the energy consumption of the vehicles. This paper gives an introduction to a simplified and transparent method of modelling to provide a basic understanding of the impact of efficiency improvements. Hereby it is shown, that with the increasing electrification of the drivetrain, the optimization of the efficiency in the mechanical path of power transmission will become even more important.
Gleichlaufgelenke als Teil der Antriebswellen (Seitenwellen und Längswellen) sind in allen maßgeblichen Triebstrangkonfigurationen im direkten Leistungsfluss angeordnet. Ihre Hauptfunktion ist die Übertragung einer Antriebsleistung unter Ermöglichung von Abbeugung und Axialverschiebung. Dieser Beitrag soll einen Überblick zu den wesentlichen, auf dem heutigen Markt verbreiteten Bauweisen und ihren jeweiligen Einsatzgebieten geben. Besonders berücksichtigt werden hierbei neue Gelenkkonzepte, die sich aufgrund ihrer besonderen Gestaltung durch deutlich höhere Wirkungsgrade auszeichnen. Der Einfluss auf den Energieverbrauch soll quantifiziert werden, hierzu wird ein neuartiger Berechnungsansatz vorgestellt, der eine einfache Abschätzung des Einflusses von Wirkungsgradverbesserungen auf den Energieverbrauch für verschiedener Antriebskonzepte (ICE / Hybrid / E-Fahrzeuge) erlaubt.
Molecular simulations are an important tool in the study of aqueous salt solutions. To predict the physical properties accurately and reliably, the molecular models must be tailored to reproduce experimental data. In this work, a combination of recent global and local optimization tools is used to derive force fields for MgCl2 (aq) and CaCl2 (aq). The molecular models for the ions are based on a Lennard-Jones (LJ) potential with a superimposed point charge. The LJ parameters are adjusted to reproduce the bulk density and shear viscosity of the different solutions at 1 bar and temperatures of 293.15, 303.15, and 318.15 K. It is shown that the σ-value of chloride consistently has the strongest influence on the system properties. The optimized force field for MgCl2 (aq) provides both properties in good agreement with the experimental data over a wide range of salt concentrations. For CaCl2 (aq), a compromise was made between the bulk density and shear viscosity, since reproducing the two properties requires two different choices of the LJ parameters. This is demonstrated by studying metamodels of the simulated data, which are generated to visualize the correlation between the parameters and observables by using projection plots. Consequently, in order to derive a transferable force field, an error of ∼3% on the bulk density has to be tolerated to yield the shear viscosity in satisfactory agreement with experimental data.
In this contribution, we examine how visualization on an ultra high-resolution display wall can augment force-field research in the field of molecular modeling. Accurate force fields are essential for producing reliable simulations, and subsequently important for several fields of applications (e.g. rational drug design and biomolecular modeling). We discuss how using HORNET, a recently constructed specific ultra high-resolution tiled display wall, enhances the visual analytics that are necessary for conformational-based interpretation of the raw data from molecular calculations. Simultaneously viewing multiple potential energy graphs and conformation overlays leads to an enhanced way of evaluating force fields and in their optimization. Consequently, we have integrated visual analytics into our existing Wolf2Pack workflow. We applied this workflow component to analyze how major AMBER force fields (Parm14SB, Gaff, Lipid14, Glycam06j) perform at reproducing the quantum mechanics relative energies and geometries of saturated hydrocarbons. Included in this comparison are the 1996 OPLS force field and our newly developed ExTrM force field. While we focus on atomistic force fields the ideas presented herein are generalizable to other research areas, particularly those that involve numerous representations of large data amounts and whose simultaneous visualization enhances the analysis.
Properties of 1,4-trans-poly(isoprene) at ambient conditions are determined by simulations on two length scales based on two different models:? a fully atomistic and a mesoscopic one. The models are linked via a mapping scheme such that one mesoscopic bead represents one chemical repeat unit. Melts as well as solutions of several chain lengths are investigated and mapped individually to the meso-scale. The resulting models are compared to each other. The meso-scale models could be simulated over a large variety of chain lengths and time scales relevant for experimental comparison. Concerning static properties, we determine the persistence length and the scaling behavior of the radius of gyration. The latter is compared to experiments, and the agreement is satisfactory. Furthermore, we find deviations from Rouse dynamics at all chain lengths at ambient conditions.
