The development of materials is the driving force in the civilization, people have always committed to make new materials to meet the requirements of the human society. The fabrication, and the understanding of a material construct a positive two-step feedback loop, after thousands of years of continuous exploration, a large number of knowledge about the fabrication methods, structures, and properties of thermodynamically stable materials have been known. Meanwhile, meta-stable materials, and non-stoichiometric materials have drawn people’s attention in two perspectives: one is the application, some meta-stable non- stoichiometric materials possess unique, better properties; the other is the understanding, these materials often exhibit complex structures and complicated phase selections, whose driving mechanism is not clearly known. Take the Al-Sm system shown in Figure. 1.2 as an example again, we can see that for the same composition of metallic glass Al90Sm10, it
can undergoes such diverse and distinct phase selection paths depending on the fabrication processes, novel meta-stable phases can be generated accordingly. Our goal is to have a comprehensive understanding of the nature of these novel phases and the phase transitions, in order to predict and control them. Motivated by this goal, my thesis study uses high performance computing technology, together with theory and experiment, investigates the structural and dynamical properties during the phase selection in the Al-Sm alloy. We summarize the thesis study works as follows:
1. We have established a self-contained algorithm to rigorously evaluate the free energy for solid and liquid phases of an alloy system, based on thermodynamic integration, which has good agreements with experimental data. The significance of this work lies
in (1) it can be used to determine the driving force for nucleation in supercooled liquid, which is fundamental to achieving microscopic understandings of freezing and melting phenomena; (2) it is self-contained, the accuracy only depends on the accuracy of classical inter-atomic potential. This is the foundation of our understandings on phase selection.
2. We have elucidate the kinetic effect, especially the limited diffusivity of Sm atoms’ role in the meta-stable non-stoichiometric -Al60Sm11 phase forming. In Chapter.4, Monte
Carlo simulation with cluster expansion free energy model, and molecular dynamics simulation with “bootstrap” accumulation method make it possible to simulate sam- ples whose (effective) size can be comparable to experimental ones; In Chapter.5, the persistent-embryo method (PEM) opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation. These methods link the simulation and experiment, provide a convincing scheme to verify our under- standings of phase selection.
3. We have also developed GPU based, Pythonic molecular dynamics software package: the HOOMD-blue EAM/FS package. Our work is expected to significantly expand the scope of the HOOMD-blue software, which was traditionally used in the community of soft condensed matter physics. And its Python interface makes it more convenient to perform the simulation and analyze the results. This provide a powerful tool in understanding the phase selection.
The above works have yielded complete or preliminary achievements, the establish of various algorithms, models, methods and software packages lays foundations for future re- search. But of course, this thesis study is just one small step further to our goal, to have a deeper understanding of the phase selections in meta-stable metallic alloys, a lot of follow- up tasks need to be completed. These tasks include: (1) Use the free energy evaluation
data of our procedure as an descriptor, compared with experimental data, to refine the clas- sical EAM/FS potential. (2) Incorporate the structural and dynamical properties of Sm atoms we have found in Chapter. 4 and Chapter. 5 into the coarse-grain model or phase field model, to simulate the phase selection in macroscopic scale. (3) Investigate the effect of non-stoichiometric persistent-embryo, to identify all the very early nucleation pathways and their associated probabilities. (4) MPI parallel the HOOMD-blue EAM/FS package, to perform multi-GPU computing in order to simulate larger samples.
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