Author
Listed:
- Dominic Roehm
(Institute for Computational Physics)
- Kai Kratzer
(Institute for Computational Physics)
- Axel Arnold
(Institute for Computational Physics)
Abstract
Nucleation, i.e., the onset of a phase transition like crystal growth, is a rare event with waiting times in the order of days. Yet, it is an event on the molecular scale, and therefore difficult to study, both experimentally and by computer simulations. Our interest is in the role of long range interactions in nucleation, in particular electrostatic and hydrodynamic interactions mediated by solvent molecules. In order to model the solvent, we use a lattice fluid that is propagated by the fluctuating Lattice Boltzmann (LB) method. Our implementation uses a graphics card (GPU) to propagate the solvent and is coupled to the Molecular Dynamics (MD) simulation package ESPResSo. Using this code, we study the heterogeneous crystallization in Yukawa-like colloidal systems. Our simulations allow to observe the growth of a crystal in a channel with and without hydrodynamic interactions, and indicate that hydrodynamic interactions slow down the crystallization. Additionally, we present results on the homogeneous crystallization of Yukawa particles. While heterogeneous nucleation can be observed directly in simulations, homogeneous nucleation requires special sampling techniques. We use our own Forward Flux Sampling implementation, the Flexible Rare Event Sampling Harness Systems (FRESHS). FRESHS can control popular MD simulation packages as back-end, making it a versatile tool to study rare events. Our simulations confirm previous results at higher supersaturations, which show that the nucleation mechanism involves two steps, namely the formation of a metastable bcc phase and the transformation to a stable fcc phase.
Suggested Citation
Dominic Roehm & Kai Kratzer & Axel Arnold, 2013.
"Heterogeneous and Homogeneous Crystallization of Soft Spheres in Suspension,"
Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering ‘13, edition 127, pages 33-52,
Springer.
Handle:
RePEc:spr:sprchp:978-3-319-02165-2_3
DOI: 10.1007/978-3-319-02165-2_3
Download full text from publisher
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
1. Check below whether another version of this item is available online.
2. Check on the provider's
web page
whether it is in fact available.
3. Perform a
for a similarly titled item that would be
available.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-319-02165-2_3. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.