Publications Search Results

Now showing 1 - 10 of 38
  • Publication
    Optimizing Lennard-Jones parameters by coupling single molecule and ensemble target data
    ( 2022)
    Strickstrock, Robin
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    Huelsmann, Marco
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    Kirschner, Karl
    This contribution is a proof-of-concept that a diverse set of training observables leads to a meaningful force field even if a very limited number of thermodynamic state points (i.e. temperatures) is used. This approach generates optimized force-field parameters, enabling the user to extract additional information from MD simulations. The ultimate goal is to extend this approach and enable an increased amount of observables to be reproduced using a single force field for a series of chemically similar molecules (e.g. oligomer hydrocarbons). Specifically, we present a new optimization strategy to expand the limits of existing force fields and investigate how much added error is introduced to already reproducible observables. For this purpose, we optimized the Lennard-Jones parameters of n-octane using an isolated molecule's relative conformational energies and the liquid-phase density (293.15 K) for a molecular ensemble as optimization objectives. To test the impact on other observables, additional substances and temperatures that were not part of the training set were evaluated. This evaluation includes the surface tension, viscosity and density for n-hexane, n-heptane, n-octane and n-nonane at 293.15, 315.15 and 338.15 K. We show that it is possible to expand the limits of a force field, improving its overall accuracy at a small cost to its previously well-reproduced observables. Additionally, we propose approaches for further developments of the optimization strategy to increase the observables accuracies that suffer a loss in exchange for the capability of reproducing additional properties.
  • Publication
    3D-Printed Replica and Porcine Explants for Pre-Clinical Optimization of Endoscopic Tumor Treatment by Magnetic Targeting
    ( 2021)
    Roeth, Anjali A.
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    Garretson, Ian
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    Beltz, Maja
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    Herbold, Till
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    Schulze-Hagen, Maximilian
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    Quaisser, Sebastian
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    Georgens, Alex
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    Slabu, Ioana
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    Klink, Christian D.
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    Neumann, Ulf P.
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    Linke, Barbara S.
    Background: Animal models have limitations in cancer research, especially regarding anatomy-specific questions. An example is the exact endoscopic placement of magnetic field traps for the targeting of therapeutic nanoparticles. Three-dimensional-printed human replicas may be used to overcome these pitfalls. Methods: We developed a transparent method to fabricate a patient-specific replica, allowing for a broad scope of application. As an example, we then additively manufactured the relevant organs of a patient with locally advanced pancreatic ductal adenocarcinoma. We performed experimental design investigations for a magnetic field trap and explored the best fixation methods on an explanted porcine stomach wall. Results: We describe in detail the eight-step development of a 3D replica from CT data. To guide further users in their decisions, a morphologic box was created. Endoscopies were performed on the replica and the resulting magnetic field was investigated. The best fixation method to hold the magnetic field traps stably in place was the fixation of loops at the stomach wall with endoscopic single-use clips. Conclusions: Using only open access software, the developed method may be used for a variety of cancer-related research questions. A detailed description of the workflow allows one to produce a 3D replica for research or training purposes at low costs.
  • Publication
    Investigation of Crystallization and Relaxation Effects in Coarse-Grained Polyethylene Systems after Uniaxial Stretching
    ( 2021)
    Grommes, Dirk
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    Schenk, Martin R.
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    Bruch, Olaf
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    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.
  • Publication
    Lettuce: PyTorch-Based Lattice Boltzmann Framework
    ( 2021)
    Bedrunka, Mario Christopher
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    Wilde, Dominik
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    Kliemank, Martin
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    Foysi, Holger
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    Krämer, Andreas
    The lattice Boltzmann method (LBM) is an efficient simulation technique for computational fluid mechanics and beyond. It is based on a simple stream-and-collide algorithm on Cartesian grids, which is easily compatible with modern machine learning architectures. While it is becoming increasingly clear that deep learning can provide a decisive stimulus for classical simulation techniques, recent studies have not addressed possible connections between machine learning and LBM. Here, we introduce Lettuce, a PyTorch-based LBM code with a threefold aim. Lettuce enables GPU accelerated calculations with minimal source code, facilitates rapid prototyping of LBM models, and enables integrating LBM simulations with PyTorchs deep learning and automatic differentiation facility. As a proof of concept for combining machine learning with the LBM, a neural collision model is developed, trained on a doubly periodic shear layer and then transferred to a different flow, a decaying turbulence. We also exemplify the added benefit of PyTorchs automatic differentiation framework in flow control and optimization. To this end, the spectrum of a forced isotropic turbulence is maintained without further constraining the velocity field. The source code is freely available from https://github.com/lettucecfd/lettuce.
  • Publication
    The performance of Dunning, Jensen, and Karlsruhe basis sets on computing relative energies and geometries
    ( 2020)
    Kirschner, Karl N.
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    Heiden, Wolfgang
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    In an effort to assist researchers in choosing basis sets for quantum mechanical modeling of molecules (i.e. balancing calculation cost versus desired accuracy), we present a systematic study on the accuracy of computed conformational relative energies and their geometries in comparison to MP2/CBS and MP2/AV5Z data, respectively. In order to do so, we introduce a new nomenclature to unambiguously indicate how a CBS extrapolation was computed. Nineteen minima and transition states of buta-1,3-diene, propan-2-ol and the water dimer were optimized using 45 different basis sets. Specifically, this includes one Pople (i.e. 6-31G(d)), 8 Dunning (i.e. VXZ and AVXZ, X = 2-5), 25 Jensen (i.e. pc-n, pcseg-n, aug-pcseg-n, pcSseg-n, and aug-pcSseg-n, n = 0-4), and 9 Karlsruhe (e.g. def2-SV(P), def2-QZVPPD) basis sets. The molecules were chosen to represent both common and electronically diverse molecular systems. In comparison to MP2/CBS relative energies computed using the largest Jensen basis sets (i.e. n = 2,3,4), the use of smaller sizes (n = 0,1,2 and n = 1,2,3) provides results that are within 0.11-0.24 and 0.09-0.16 kcal⋅mol −1. To practically guide researchers in their basis set choice, an equation is introduced that ranks basis sets based on a user-defined balance between their accuracy and calculation cost. Furthermore, we explain why the aug-pcseg-2, def2-TZVPPD and def2-TZVP basis sets are very suitable choices to balance speed and accuracy.
  • Publication
    Editorial: Tailor-made approaches on use of multiscale modeling for research on soft materials - capabilities, restrictions and future possibilities
    ( 2020)
    Carbone, Paula
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    Faller, Roland
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    Qian, Hu-Jun
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    This editorial discusses the broad range and scope of this special issue of Soft Materials. All articles deal with the challenge to model and/or simulate various types of systems of soft matter. Depending on the microscopic insight deemed to understand macroscopic properties, different tailor-made approaches are needed to reliably explain such properties. In the past decades, this led to many approaches and techniques to cope with the limitations of atomistic modeling, due to limited computing resources to researchers. As an inventor of several such methods and techniques, this issue is honoring Florian Müller-Plathe, on the occasion of his 60th birthday.
  • Publication
    Lattice Boltzmann simulations on irregular grids
    ( 2020)
    Krämer, Andreas
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    Wilde, Dominik
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    Küllmer, Knut
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    Foysi, Holger
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    Joppich, Wolfgang
    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.
  • Publication
    ACPYPE update for nonuniform 1-4 scale factors: Conversion of the GLYCAM06 force field from AMBER to GROMACS
    ( 2019)
    Bernardi, Austen
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    Faller, Roland
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    Kirschner, Karl N.
    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 14 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 14 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 14 scaling factors as well as negative dihedral force constants. Validation was performed using-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.
  • Publication
    Deeper Theoretical Understanding by Means of Practical Experience in Electric and Electronic Circuits for Freshmen
    ( 2019)
    Groß, Ingo
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    Grein, Martina
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    Groß, Iris
    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 goal s: 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.
  • Publication
    Multistep Lattice Boltzmann Methods: Theory and Applications
    ( 2019)
    Wilde, Dominik
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    Krämer, Andreas
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    Küllmer, Knut
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    Foysi, Holger
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    This paper presents a framework for incorporating arbitrary implicit multistep schemes into the lattice Boltzmann method. While the temporal discretization of the lattice Boltzmann equation is usually derived using a second-order trapezoidal rule, it appears natural to augment the time discretization by using multistep methods. The effect of incorporating multistep methods into the lattice Boltzmann method is studied in terms of accuracy and stability. Numerical tests for the third-order accurate Adams-Moulton method and the second-order backward differentiation formula show that the temporal order of the method can be increased when the stability properties of multistep methods are considered in accordance with the second Dahlquist barrier.