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Keywords
Ressourceneffiziente Optimierung von Hohlkörpern aus Kunststoff mittels Multiskalensimulation
(2017)
This study investigates the initial stage of the thermo-mechanical crystallization behavior for uni- and biaxially stretched polyethylene. The models are based on a mesoscale molecular dynamics approach. We take constraints that occur in real-life polymer processing into account, especially with respect to the blowing stage of the extrusion blow-molding process. For this purpose, we deform our systems using a wide range of stretching levels before they are quenched. We discuss the effects of the stretching procedures on the micro-mechanical state of the systems, characterized by entanglement behavior and nematic ordering of chain segments. For the cooling stage, we use two different approaches which allow for free or hindered shrinkage, respectively. During cooling, crystallization kinetics are monitored: We precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influence crystallization behavior. Our models reveal that the main stretching direction dominates microscopic states of the different systems. We are able to show that crystallization mainly depends on the (dis-)entanglement behavior. Nematic ordering plays a secondary role.
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.
In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.
Liquid–liquid equilibria of dipropylene glycol dimethyl ether and water by molecular dynamics
(2011)
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 dieser Dissertation stellen wir einen neuen Ansatz zur Modellierung von Polymersystemen vor. Es werden (von methodischer Seite her) zwei automatisierte Iterationschemata dazu eingeführt, Kraftfeldparameter mesoskopischer Polymersysteme systematisch zu optimieren: Das Simplex-Verfahren und das Struktur-Differenzen-Verfahren. So werden diejenigen Freiheitsgrade aus Polymersystemen eliminiert, die eine hohe Auflösung erfordern, was die Modellierung größerer Systeme ermöglicht. Nach Tests an einfachen Flüssigkeiten werden vergröberte Modelle von drei prototypischen Polymeren (Polyacrylsäure, Polyvinylalkohol und Polyisopren) in unterschiedlichen Umgebungen (gutes Lösungsmittel und Schmelze) entwickelt und ihr Verhalten auf der Mesoskala ausgiebig geprüft. Die zugehörige Abbildung (von physikalischer Seite her) so zu gestalten, daß sie die unverwechselbaren Charakteristiken jedes Systems auf die mesoskopische Längenskala überträgt, stellt eine entscheidende Anforderung an die automatisierten Verfahren dar.
Structural and Dynamical Properties of Polystyrene Determined by Coarse-Graining MD Simulations
(2007)
We present results from a detailed study of a new, optimized coarse-grained (CG) model of polystyrene (PS) and compare it with a recently published one (Harmandaris et al., Macromolecules 2006, 39, 6708). We will explain in detail, what led us to a different mapping scheme and put that into the general framework, with special emphasis on the aspect of time mapping. The new model is tested against the structural and dynamic properties of PS, resulting from atomistic simulations.
Comparison Between Coarse-Graining Models for Polymer Systems: Two Mapping Schemes for Polystyrene
(2007)
Computational chemistry began with the birth of computers in the mid 1900s, and its growth has been directly coupled to the technological advances made in computer science and high-performance computing. A popular goal within the field, be it Newtonian or quantum based methods, is the accurate modelling of physical forces and energetics through mathematics and algorithm design. Through reliable modelling of the underlying forces, molecular simulations frequently provide atomistic insights into macroscopic experimental observations.
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.