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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.
This study reports the geometries and electronic energies of n-octane's unique conformations using perturbation methods that best mimic CCSD(T) results. In total, the fully optimised minima of n-butane (2 conformations), n-pentane (4 conformations), n-hexane (12 conformations) and n-octane (96 conformations) were investigated at several different theory levels and basis sets. We find that DF-MP2.5/aug-cc-pVTZ is in very good agreement with the more expensive CCSD(T) results. At this level, we can clearly confirm the 96 stable minima which were previously found using a reparameterised density functional theory (DFT). Excellent agreement was found between their DFT results and our DF-MP2.5 perturbation results. Subsequent Gibbs free energy calculations, using scaled MP2/aug-cc-pVTZ zero-point vibrational energy and frequencies, indicate a significant temperature dependency of the relative energies, with a change in the predicted global minimum. The results of this work will be important for future computational investigations of fuel-related octane reactions and for optimisation of molecular force fields (e.g. lipids).
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.
Aufgrund der weltweiten Bemühungen, den CO2- und Schadstoffausstoß zu reduzieren, sind die Automobilhersteller veranlasst, die Entwicklung effizienter Fahrzeuge verstärkt voranzutreiben. Die gestiegenen Anforderungen machen sich besonders an den Entwicklungstrends der letzten Jahre bemerkbar. Neben Maßnahmen, um den Kraftstoffverbrauch konventioneller Fahrzeuge zu reduzieren, wie z.B. Downsizing, Start/Stopp-Automatiken oder Disconnect-Systemen bei Allradfahrzeugen, gewannen elektrifizierte Fahrzeugkonzepte wie Hybrid- und Elektrofahrzeuge stark an Bedeutung.
On the basis of the worldwide efforts to reduce CO2 and pollutant emissions, automobile manufacturers are being induced to pursue the development of more efficient vehicles with greater vigour. It is precisely the increased requirements for high-efficiency power transmission components that will allow suppliers of drivetrain components and systems as GKN to achieve a better position on the market by offering a drive technology with optimized efficiency levels.
Aufgrund der weltweiten Bemühungen, den CO2- und Schadstoffausstoß zu reduzieren, sind die Automobilhersteller veranlasst, die Entwicklung effizienter Fahrzeuge verstärkt voranzutreiben. Die gestiegenen Wirkungsgradanforderungen leistungsübertragender Komponenten ermöglichen es gerade Zulieferern von Antriebsstrangkomponenten und -systemen wie GKN, sich durch wirkungsgradoptimierte Antriebstechnik besser auf dem Markt zu positionieren.
Der vorliegende Übersichtsartikel berichtet über Fortschritte in der molekularen Modellierung und Simulation mittels massiv-paralleler Hoch- und Höchstleistungsrechner (HPC). Im SkaSim-Projekt arbeiteten dazu Partner aus der HPC-Community mit Anwendern aus Wissenschaft und Industrie zusammen. Ziel dabei war es mittels HPC-Methoden die Vorhersage von thermodynamischen Stoffdaten in Bezug auf Effizienz, Qualität und Zuverlässigkeit weiter zu optimieren. In diesem Zusammenhang wurden verschiedene Themen bearbeitet: Atomistische Simulation der homogenen Gasblasenbildung, Oberflächenspannung klassischer Fluide und ionischer Flüssigkeiten, multikriterielle Optimierung molekularer Modelle, Weiterentwicklung der Simulationscodes ls1 mardyn und ms2, atomistische Simulation von Gastrennprozessen, molekulare Membran-Strukturgeneratoren, Transportwiderstände und gemischtypenspezifische Bewertung prädiktiver Stoffdatenmodelle.
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.
Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies
(2018)
Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995)] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012)], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.
Ressourceneffiziente Optimierung von Hohlkörpern aus Kunststoff mittels Multiskalensimulation
(2017)
Die mechanischen Eigenschaften von extrusionsblasgeformten Kunststoffhohlkörpern hängen wesentlich von den vom Verarbeitungsprozess beeinflussten Materialeigenschaften ab. Ziel der dargestellten Untersuchung ist, prozessabhängige Materialkennwerte in Simulationsprogrammen zu berücksichtigen und damit deren Vorhersagegenauigkeit zu erhöhen. Hierzu ist die Schaffung einer Schnittstelle zwischen Prozess- und Bauteilsimulation notwendig. Darüber hinaus wird vorgestellt, wie Simulationen auf Mikroebene (molekulardynamische Simulationen) genutzt werden können, um Materialkennwerte ohne die Durchführung eines Realexperiments zu ermitteln.
One way by which bacteria achieve antibiotics resistance is preventing drug access to its target molecule for example through an overproduction of multi-drug efflux pumps of the resistance nodulation division (RND) protein super family of which AcrAB-TolC in Escherichia coli is a prominent example. Although representing one of the best studied efflux systems, the question of how AcrB – TolC interact is still unclear as the available experimental data suggest that either both proteins interact in a tip to tip manner or do not interact at all but are instead connected by a hexamer of AcrA molecules. Addressing the question of TolC – AcrB interaction, we performed a series of 100 ns – 1 μs molecular dynamics simulations of membrane-embedded TolC in presence of the isolated AcrB docking domain (AcrBDD). In 5 / 6 simulations we observe direct TolC – AcrBDD interaction that is only stable on the simulated time scale when both proteins engage in a tip to tip manner. At the same time we find TolC opening and closing freely on extracellular side while remaining closed at the inner periplasmic bottleneck region, suggesting that either the simulated time is too short or additional components are required to unlock TolC.
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.
Pseudopotential-based Lattice Boltzmann models provide an efficient means to simulate multiphase flows. Although thoroughly analysed and extended, they still suffer from various numerical deficiencies, such as stability issues at large density and viscosity ratios as well as spurious velocities in interfacial regions. In this work, we show how to optimize the model numerically with regard to the latter. This optimized scheme is analysed in static as well as oscillating droplet simulations and is compared to different higher-order isotropic schemes. We found that the optimized scheme substantially lowers spurious velocities and competes well with comparable schemes in both test cases.
In the pursuit to study the parameterization problem of molecular models with a broad perspective, this paper is focused on an isolated aspect: It is investigated, by which algorithms parameters can be best optimized simultaneously to different types of target data (experimental or theoretical) over a range of temperatures with the lowest number of iteration steps. As an example, nitrogen is regarded, where the intermolecular interactions are well described by the quadrupolar two-center Lennard-Jones model that has four state-independent parameters. The target data comprise experimental values for saturated liquid density, enthalpy of vaporization, and vapor pressure. For the purpose of testing algorithms, molecular simulations are entirely replaced by fit functions of vapor–liquid equilibrium (VLE) properties from the literature to assess efficiently the diverse numerical optimization algorithms investigated, being state-of-the-art gradient-based methods with very good convergency qualities. Additionally, artificial noise was superimposed onto the VLE fit results to evaluate the numerical optimization algorithms so that the calculation of molecular simulation data was mimicked. Large differences in the behavior of the individual optimization algorithms are found and some are identified to be capable to handle noisy function values.
Automated force field optimisation of small molecules using a gradient-based workflow package
(2010)
In this study, the recently developed gradient-based optimisation workflow for the automated development of molecular models is for the first time applied to the parameterisation of force fields for molecular dynamics simulations. As a proof-of-concept, two small molecules (benzene and phosgene) are considered. In order to optimise the underlying intermolecular force field (described by the (12,6)-Lennard-Jones and the Coulomb potential), the energetic and diameter parameters ε and σ are fitted to experimental physical properties by gradient-based numerical optimisation techniques. Thereby, a quadratic loss function between experimental and simulated target properties is minimised with respect to the force field parameters. In this proof-of-concept, the considered physical target properties are chosen to be diverse: density, enthalpy of vapourisation and self-diffusion coefficient are optimised simultaneously at different temperatures. We found that in both cases, the optimisation could be successfully concluded by fulfillment of a pre-defined stopping criterion. Since a fairly small number of iterations were needed to do so, this study will serve as a good starting point for more complex systems and further improvements of the parametrisation task.
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.
The need for predicting physical compound properties supplementing experimental data is considerable. Nowadays a wide range of classical simulation techniques is available for computing a multitude of such properties with acceptable effort. We here give a field report about our approach, which was to fit an initial model to a single point in the phase diagram. By way of accessing commonly available experimental values we developed a compound-specific force field via simplex optimization. For predicting the desired properties of the novel model we did engage classical equilibrium as well as reverse non-equilibrium molecular dynamics in combination with Monte Carlo methods and report here the performance of these methods in detail for the example compound ethylene oxide. We find that the new model describes the experimentally observed behavior of the test compound ethylene oxide (EO) very well in the molecular dynamics section. However, when applying the simplex optimized model to the Monte Carlo section, the limits of transferability become apparent.
Ionic liquids are highly relevant for industrial applications as they stand out due to their special chemical and physical features, e.g. low vapor pressure, low melting point or extraordinary solution properties. The goal of this work is to study the capability of the three ionic liquids [C2MIM][NTf2], [C12MIM][NTf2] and [C2MIM][EtSO4] to diffuse through a POPC membrane (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine). To achieve this, we used molecular simulation techniques, which on the one hand give insight into specific domains of the membrane and on the other hand compute partition coefficients and free energy profiles of solutes in lipid membranes, which cannot be measured by labor experiments. To be as accurate as possible we parameterized a new united atom force field for the ionic liquid of type 1-alkyl-3-methylimidazoliumethylsulfate [CnMIM][EtSO4] with n = 1,2,4,6,8. Like the other IL force field for [CnMIM][NTf2] (see Köddermann et al., ChemPhysChem 14, 3368–3374, 2013) used in this work, the new one was derived to reproduce experimental densities and self-diffusion coefficients. The new force field reproduces the experimental data extremely well. Using this force field, the influences of cation and anion exchanges as well as the variation of the chain length on the free energy could be analyzed. We performed umbrella-sampling to characterize the free energy profile of one ion pair, accompanied by a second one, in solution, at the membrane interface, and inside the membrane. In the outlook we present our intention to parameterize force fields in a systematic and user-friendly way. We will use the combination of two optimization toolkits, developed at SCAI: The global optimization toolkit CoSMoS and the local optimization techniques implemented in the software package GROW.
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.
GROW: A gradient-based optimization workflow for the automated development of molecular models
(2010)
The concept, issues of implementation and file formats of the GRadient-based Optimization Workflow for the Automated Development of Molecular Models ‘GROW’ (version 1.0) software tool are described. It enables users to perform automated optimizations of force field parameters for atomistic molecular simulations by an iterative, gradient-based optimization workflow. The modularly constructed tool consists of a main control script, specific implementations and secondary control scripts for each numerical algorithm, as well as analysis scripts. Taken together, this machinery is able to automatically optimize force fields and it is extensible by developers with regard to further optimization algorithms and simulation tools. Results on nitrogen are briefly reported as a proof of concept.
The Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) has developed a software tool for the automated parameterization of force fields for molecular simulations using efficient gradient-based algorithms. This tool, combined with well-established simulation techniques, can quantitatively determine many physicochemical properties for given compounds.
