Dynamical and structural properties of liquid Cu-Ti melts: experimental and simulation studies
This is a collaborative project with the German Aerospace Center (DLR) (Institute for Material Physics in Space), Cologne, Germany, and the Université Grenoble (SIMAP), France.
Bulk metallic glasses (BMGs) based on Cu-Ti combine properties such as a good thermal and electric conductivity, high strength, large elastic limit, good resistance against corrosion, and biocompatibility, which can be applied in many industrial applications. However, it was found that the glass forming ability (GFA) is very limited for Ti-rich alloy compositions. Only alloying additional elements like Zr and Ni allows for bulk glass formation. Very recently, a new class of a quasi-ternary system (Ti-Zr)-(Ni-Cu)-S has been developed, where the existence of an icosahedral short-range order in the liquid state has been suggested to be responsible for an enhanced GFA. Besides the structural aspect, also its relationship with the dynamical properties on an atomistic scale plays an important role for an enhanced GFA. Therefore, the relevant microscopic mechanisms responsible for such good GFAs are still to be explored.
Within this project, we study the dynamical and structural properties of Cu-Ti melts. The binary Cu-Ti system serves as basis for many excellent multicomponent glass-forming alloys, while structural properties such as the structure factor can be relatively easy obtained experimentally. Therefore, it makes a good model system. Furthermore, it features a large, undercooled liquid region, which is relevant for glass formation. Especially, the interplay between the dynamics of the system (e.g., viscosity, inter-diffusion) and the structural properties (e.g., packing fraction, topological and chemical short-range order) is of fundamental interest. Moreover, the precise knowledge of these properties in the liquid may also serve as experimental input for simulations of complex processes, such as welding, casting, surface treatment, nucleation, and crystal growth.
All samples are processed containerlessly using an electrostatic levitator (ESL), which provides precise structure and dynamic data. Moreover, processing the samples without any crucible using electrostatic levitation allows to determine these quantities in the undercooled melt precisely. The density of the Cu-Ti system increases monotonously upon increasing the Ti content, from which an almost ideal mixing behavior of the molar volume has been identified. The melt viscosity features a non-monotonous trend with increasing Ti content, which is largest for intermediate Ti contents. On the microscopic scale, local contraction of the average interatomic distance has been observed upon alloying. However, the average packing fraction derived from the macroscopic melt density remains almost constant. Therefore, the slowdown of the melt dynamics is rather due to chemical interactions between Cu and Ti, which form preferred neighboring pairs. Nevertheless, the chemical short-range order in Ti-Cu melts is less pronounced than observed for Zr-Ni or Hf-Ni melts, which may explain the faster atomic dynamics in Ti-Cu as compared with Zr-Ni and Hf-Ni.
Figure 1: Picture of a liquid metal sample levitating in an electrostatic field. (A. Meyer, D. Holland-Moritz, F. Kargl from the German Aerospace Center (DLR))
This study demonstrates that by combining scattering techniques e.g., neutron and x-ray diffraction, with ESL a deep understanding of the structure-dynamic relationship in liquid metal alloys can be achieved. However, open questions remain, regarding the composition dependence of the diffusion coefficient, the local structure and next neighboring atoms, and nucleation phenomena, can be answered, which eventually contribute to a deeper understanding of the relationship between structure, dynamics, and GFA.
These questions we are currently addressing with ab-initio molecular dynamics simulations. A follow-up project that involves simulation based on a machine-learning approach is currently discussed and outlined.
If you are interested in performing ab-initio and machine-learning based simulations, please reach out to me via lucas.kreuzer@frm2.tum.de. Open positions for master theses are currently available.
Further reading:
Please see these papers for more information
