Atomistic simulation of the kinetics of phase transformations
The research group focuses on the development and application of methods for long time-scale atomistic simulations. The two main research areas are the diffusion of impurities in the presence point and extended defects (e.g. diffusion of d-band elements in Ni-based superalloys), and the kinetics of phase transformations (e.g. formation of topologically close-packed phases, martensitic transformation in high-temperature shape memory alloys, nucleation during solidification).
Free energy landscape and optimal reaction coordinate for nucleation in Ni; the initial stage of the nucleation process is characterised by the formation of a precursor zone in the undercooled liquid before the crystal structure emerges from this preordered region; red spheres are fcc atoms, green hcp atoms, and light-brown are prestructured atoms.
Atomistic processes dominating the long-time dynamics of impurity diffusion, solid-solid phase transformations or nucleation belong to the class of so-called rare events. In this context, rare events comprise processes that require transitions between local minima of the potential energy surface that are separated by sizeable energy barriers. This leads to a separation of time scales between the short-time dynamics within each local minimum (e.g. lattice vibrations) and the long-time dynamics between the minima (e.g. diffusion, structural rearrangements), which makes it impossible to study such problems with classic molecular dynamics simulations. If the dynamics of the rare events can be described correctly based on the underlying atomistic processes, it is possible to follow the time evolution of a system over an extended time scale.
Within the group, various techniques such as accelerated molecular dynamics, kinetic Monte Carlo, or transition path sampling are utilised to investigate rare events.
- Dr. Yaojun Du
- Dr. Ari Harjunmaa
- Marco Rozgic
- Dr. Sergej Shuwalow
- nucleation and phase transformation
- (adaptive) kinetic Monte Carlo
- transition path sampling
- (accelerated) molecular dynamics
J. Rogal, E. Schneider, M. Tuckerman. Neural-network-based path collective variables for enhanced sampling of phase transformations Physical Review Letters, 123, 245701, (2019)
S. Menon, G. Díaz Leines, J. Rogal. pyscal: A python module for structural analysis of atomic environments Journal of Open Source Software, 4, 1824, (2019)
A. Ferrari, A. Paulsen, D. Langenkämper, D. Piorunek et al. Discovery of ω-free high-temperature Ti-Ta-X shape memory alloys from first-principles calculations Physical Review Materials, 3, 103605, (2019)
A. Ferrari, M. F. Schröder, Y. Lysogorskiy, J. Rogal et al. Phase transitions in titanium with an analytic bond-order potential Modelling and Simulation in Materials Science and Engineering, 27, 085008, (2019)
S. Gao, Z. Yang, M. Grabowski, J. Rogal et al. Influence of excess volumes induced by Re and W on dislocation motion and creep in Ni-base single crystal superalloys: a 3D discrete dislocation dynamics study Metals, 9, 637, (2019)
Dr. Jutta Rogal
Tel: +49 234 32 29317
Fax: +49 234 32 14977