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Unsupervised topological learning approach of crystal nucleation. Sci Rep 2022; 12:3195. [PMID: 35210485 PMCID: PMC8873400 DOI: 10.1038/s41598-022-06963-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 01/27/2022] [Indexed: 12/12/2022] Open
Abstract
Nucleation phenomena commonly observed in our every day life are of fundamental, technological and societal importance in many areas, but some of their most intimate mechanisms remain however to be unravelled. Crystal nucleation, the early stages where the liquid-to-solid transition occurs upon undercooling, initiates at the atomic level on nanometre length and sub-picoseconds time scales and involves complex multidimensional mechanisms with local symmetry breaking that can hardly be observed experimentally in the very details. To reveal their structural features in simulations without a priori, an unsupervised learning approach founded on topological descriptors loaned from persistent homology concepts is proposed. Applied here to monatomic metals, it shows that both translational and orientational ordering always come into play simultaneously as a result of the strong bonding when homogeneous nucleation starts in regions with low five-fold symmetry. It also reveals the specificity of the nucleation pathways depending on the element considered, with features beyond the hypothesis of Classical Nucleation Theory.
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Kirova EM, Pisarev VV. Morphological aspect of crystal nucleation in wall-confined supercooled metallic film. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2020; 33:034003. [PMID: 33078713 DOI: 10.1088/1361-648x/abba6b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 09/21/2020] [Indexed: 06/11/2023]
Abstract
In this paper, we simulate the nucleation and growth of crystalline nuclei in a molybdenum film cooled at different rates confined between two amorphous walls. We also compare the results for the wall-confined and wall-free systems. We apply the same methodology as in the work (Kirova and Pisarev 2019J. Cryst. Growth528125266) which is based on reconstructing the probability density function for the largest crystalline nucleus in the system. The size of the nucleus and the asphericity parameter are considered as the reaction coordinates. We demonstrate that in both the free and confined systems there are two mechanisms of crystal growth: the attachment of atoms to the biggest crystal from the amorphous phase and the merging of the biggest crystal cluster with small ones (coalescence). We show that the attachment mechanism is dominant in the melt cooled down at a slower rate, and the mechanism gradually shifts to coalescence as cooling rate increases. We also observe the formation of long-lived crystal clusters and demonstrate that amorphous walls do not affect their geometric characteristics. However, system confined between walls demonstrates higher glass-forming ability.
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Affiliation(s)
- E M Kirova
- National Research University Higher School of Economics, 20 Myasnitskaya str., 101000 Moscow, Russia
- Joint Institute for High Temperatures of RAS, 13/2 Izhorskaya str., 125412 Moscow, Russia
| | - V V Pisarev
- National Research University Higher School of Economics, 20 Myasnitskaya str., 101000 Moscow, Russia
- Joint Institute for High Temperatures of RAS, 13/2 Izhorskaya str., 125412 Moscow, Russia
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Wu Z, Mo Y, Lang L, Yu A, Xie Q, Liu R, Tian Z. Topologically close-packed characteristic of amorphous tantalum. Phys Chem Chem Phys 2018; 20:28088-28104. [PMID: 30383068 DOI: 10.1039/c8cp05897k] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The structural evolution of tantalum (Ta) during rapid cooling was investigated by molecular dynamics simulation, in terms of the system energy, the pair distribution function and the largest standard cluster analysis. It was found that the critical cooling rate for vitrification was about R ≥ 0.25 K ps-1, two orders lower than other metals (such as Au, Ag, Al, Zr and Zn) and that the meta-stable σ phase (β-Ta) not only appears on the pathway from liquid to the stable body-centred cubic crystal, but is also easily obtained at room temperature as a long-lived metastable phase with some probability. The most interesting point is that the liquid, amorphous and β-Ta phases share a nontrivial structural homology; the intrinsic topologically close-packed (TCP) structures in liquids are inherited and developed in different ways, resulting in amorphous or crystalline solids, respectively. With highly local packing fractions and geometrical incompatibility with the global close-packed (such as hcp, fcc and bcc) crystals, TCP structures inevitably result in structural heterogeneity and favour vitrification. As a superset of icosahedrons, TCP structures are ubiquitous in metallic melts, and just before the onset of crystallization reach their maximal number, which is much bigger in Ta than in other poor-GFA metals; so we argue that the strong forming ability of TCP local structures significantly enhances the glass forming ability of pure metals. These findings open up a new perspective that could have a profound impact on the research into metallic glasses.
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Affiliation(s)
- Zhizhou Wu
- College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
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Liang Y, Zhang Y, Yu B, Liu R, Xie Q, Tian Z. The deformation and transformation of icosahedron in Mg70Zn30 metallic glasses. Chem Phys Lett 2018. [DOI: 10.1016/j.cplett.2018.05.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Liang YC, Liu RS, Xie Q, Tian ZA, Mo YF, Zhang HT, Liu HR, Hou ZY, Zhou LL, Peng P. Structural evolutions and hereditary characteristics of icosahedral nano-clusters formed in Mg 70Zn 30 alloys during rapid solidification processes. Sci Rep 2017; 7:43111. [PMID: 28230068 PMCID: PMC5322369 DOI: 10.1038/srep43111] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 01/19/2017] [Indexed: 01/01/2023] Open
Abstract
To investigate the structural evolution and hereditary mechanism of icosahedral nano-clusters formed during rapid solidification, a molecular dynamics (MD) simulation study has been performed for a system consisting of 107 atoms of liquid Mg70Zn30 alloy. Adopting Honeycutt-Anderson (HA) bond-type index method and cluster type index method (CTIM-3) to analyse the microstructures in the system it is found that for all the nano-clusters including 2~8 icosahedral clusters in the system, there are 62 kinds of geometrical structures, and those can be classified, by the configurations of the central atoms of basic clusters they contained, into four types: chain-like, triangle-tailed, quadrilateral-tailed and pyramidal-tailed. The evolution of icosahedral nano-clusters can be conducted by perfect heredity and replacement heredity, and the perfect heredity emerges when temperature is slightly less than Tm then increase rapidly and far exceeds the replacement heredity at Tg; while for the replacement heredity, there are three major modes: replaced by triangle (3-atoms), quadrangle (4-atoms) and pentagonal pyramid (6-atoms), rather than by single atom step by step during rapid solidification processes.
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Affiliation(s)
- Yong-Chao Liang
- School of Physics and Microelectronics Science, Hunan University, Changsha, 410082, China.,College of Big Data and Information Engineering, Guizhou University, Huaxi District, Guiyang, 550025, China
| | - Rang-Su Liu
- School of Physics and Microelectronics Science, Hunan University, Changsha, 410082, China
| | - Quan Xie
- College of Big Data and Information Engineering, Guizhou University, Huaxi District, Guiyang, 550025, China
| | - Ze-An Tian
- School of Physics and Microelectronics Science, Hunan University, Changsha, 410082, China
| | - Yun-Fei Mo
- School of Physics and Microelectronics Science, Hunan University, Changsha, 410082, China
| | - Hai-Tao Zhang
- School of Physics and Microelectronics Science, Hunan University, Changsha, 410082, China.,Department of electronic and communication engineering, Changsha University, Changsha, 410003, China
| | - Hai-Rong Liu
- College of Materials Science and Engineering, Hunan University, Changsha, 410082, China
| | - Zhao-Yang Hou
- Department of Applied Physics, Changan University, Xi'an, 710064, China
| | - Li-Li Zhou
- Department of Information Engineering, Gannan Medical University, Ganzhou, 341000, China
| | - Ping Peng
- College of Materials Science and Engineering, Hunan University, Changsha, 410082, China
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