Nanoscale Structure and Structural Relaxation in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>Zr</mml:mi><mml:mn>50</mml:mn></mml:msub><mml:msub><mml:mi>Cu</mml:mi><mml:mn>45</mml:mn></mml:msub><mml:msub><mml:mi>Al</mml:mi><mml:mn>5</mml:mn></mml:msub></mml:math>Bulk Metallic Glass

Hwang, Jinwoo; Melgarejo, Z. Humberto; Kalay, Yunus Eren; Kalay, I.; Kramer, M. J.; Stone, Donald S.; Voyles, Paul M.

doi:10.1103/physrevlett.108.195505

Cited by 187 publications

(101 citation statements)

References 42 publications

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“…Among them, the fraction of the Z16 cluster showed a remarkable growth (2.75 times higher) [22]. On the other hand, the fraction of crystal-like atoms has a little decreased and it indicates that the crystal-like clusters would transform into the icosahedral ones by annealing, which is consistent with a recent experimental observation in Zr50Cu45Al5 bulk metallic glasses [11]. In the same relaxed phase, 96.7% of the icosahedron-like clusters are the (smaller) B atom-centered, while 99.7% of the Z16 cluster-like clusters are the (larger) A atom-centered.…”

Section: Low Distortion 5-rings and Alloy Compositions Of Good Glass-supporting

confidence: 81%

“…The early works of computer simulation have shown that the icosahedral order would exist in both liquid and glassy phases [3,4]. After the discovery of good metallic glass-formers [5,6], experimental observations [7][8][9][10][11][12] has reported that the icosahedral short-range order does exist in metallic glasses and that some medium-range order may also exist beyond the icosahedral short-range order. However, it was little known how the icosahedral short-range order is arranged and extended to form a medium-range order in glassy phases.…”

Section: Introductionmentioning

confidence: 99%

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Dynamics and Geometry of Icosahedral Order in Liquid and Glassy Phases of Metallic Glasses

Shimono

Onodera

2015

Metals

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Abstract:The geometrical properties of the icosahedral ordered structure formed in liquid and glassy phases of metallic glasses are investigated by using molecular dynamics simulations. We investigate the Zr-Cu alloy system as well as a simple model for binary alloys, in which we can change the atomic size ratio between alloying components. In both cases, we found the same nature of icosahedral order in liquid and glassy phases. The icosahedral clusters are observed in liquid phases as well as in glassy phases. As the temperature approaches to the glass transition point Tg, the density of the clusters rapidly grows and the icosahedral clusters begin to connect to each other and form a medium-range network structure. By investigating the geometry of connection between clusters in the icosahedral network, we found that the dominant connecting pattern is the one sharing seven atoms which forms a pentagonal bicap with five-fold symmetry. From a geometrical point of view, we can understand the mechanism of the formation and growth of the icosahedral order by using the Regge calculus, which is originally employed to formulate a theory of gravity. The Regge calculus tells us that the distortion energy of the pentagonal bicap could be decreased by introducing an atomic size difference between alloying elements and that the icosahedral network would be stabilized by a considerably large atomic size difference.

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Section: Low Distortion 5-rings and Alloy Compositions Of Good Glass-supporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Dynamics and Geometry of Icosahedral Order in Liquid and Glassy Phases of Metallic Glasses

Shimono

Onodera

2015

Metals

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“…Hwang et al 38 observed nanoscale crystal-like superclusters in the Zr 50 Cu 45 Al 5 MGs, in their model based on reverse Monte Carlo modeling constrained at short range by an empirical interatomic potential and at medium range by fluctuation electron microscopy data (as shown in Fig. 8a).…”

Section: -100mentioning

confidence: 99%

“…Examples include a structural signature of dynamical slowdown as well as the liquid fragility in metallic glass-forming liquids, [26][27][28][29][30][31][32] anomalous thermal contraction of metallic melts in the nearest-neighbor shell, [33][34][35] possible crystallike order in MGs/liquids, [36][37][38][39] a fractal structure model of MGs, [40][41][42] advanced algorithms (such as machine learning methods) to efficiently characterize the structural basis of flow defects and dynamical slowdown in amorphous materials, 43,44 and a new structure parameter that incorporates dynamic (atomic vibration) information beyond the description of static structure/ configuration. [45][46][47][48][49] Computational research has played a key role in formulating these ideas.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling sheds light on structural evolution in metallic glasses and supercooled liquids

Ding

2017

npj Comput Mater

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This article presents an overview of three challenging issues that are currently being debated in the community researching on the evolution of amorphous structures in metallic glasses and their parent supercooled liquids. Our emphasis is on the valuable insights acquired in recent computational analyses that have supplemented experimental investigations. The first idea is to use the local structural order developed, and in particular its evolution during undercooling, as a signature indicator to rationalize the experimentally observed temperature-dependence of viscosity, hence suggesting a possible structural origin of liquid fragility. The second issue concerns with the claim that the average nearest-neighbor distance in metallic melts contracts rather than expands upon heating, concurrent with a reduced coordination number. This postulate is, however, based on the shift of the first peak maximum in the pair distribution function and an average bond length determined from nearest neighbors designated using a distance cutoff. These can instead be a result of increasing skewness of the broad first peak, upon thermally exacerbated asymmetric distribution of neighboring atoms activated to shorter and longer distances under the anharmonic interatomic interaction potential. The third topic deals with crystal-like peak positions in the pair distribution function of metallic glasses. These peak locations can be explained using various connection schemes of coordination polyhedra, and found to be present already in high-temperature liquids without hidden crystal order. We also present an outlook to invite more in-depth computational research to fully settle these issues in future, and to establish more robust structure-property relations in amorphous alloys.npj Computational Materials (2017) 3:9 ;

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“…In this state, although almost all the molecules are in locally crystalline environments, there is no long-range crystalline order, and so the S(k) is liquid-like. It is a fascinating open question as to whether this medium-rangecrystalline/paracrystalline/nanocrystalline order is also present in any of: amorphous silicon, [1][2][3] two-line ferrihydrite, 4-6 metallic glasses, 35 polymers, 36 ACC, 7-16 ACP 17 and ACS. [18][19][20] Whether or not these materials have this ordering has consequences.…”

mentioning

confidence: 99%

State between Liquid and Crystal: Locally Crystalline but with the Structure Factor of a Liquid

Mithen

Sear

2016

Crystal Growth & Design

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We are familiar with large highly-ordered single crystals, such as those used in the semiconductor industry. There the crystalline ordering in the silicon crystals extends for billions and more lattice spacings. As a result, X-ray diffraction (XRD) patterns of these crystals have sharp Bragg peaks. We are also familiar with liquids, where the molecules have a local structure that is very different to that in a crystal. In addition, in liquids there is only ordering over a few molecular diameters, and so they do not have Bragg peaks. But there are materials, where the situation is much less clear. Many of these materials are referred to as amorphous.For example, the structure of amorphous silicon is controversial. There is debate 1-3 over whether it possesses some crystalline ordering of the sort variously referred to as paracrystalline order, nanocrystalline order or medium-range crystalline order, or whether it has no crystalline ordering. We do not know if locally, silicon atoms are arranged in the structure of a liquid, or whether they are in tiny crystals only a few silicon atoms across. There are other systems at the borderline between liquid and crystal. The mineral ferrihydrite can be classified as crystalline (this is called six-line ferrihydrite), or as amorphous (this is called two-line ferrihydrite). [4][5][6] The structures of Amorphous Calcium Carbonate (ACC), 7-16 Amorphous Calcium Phosphate (ACP), 17 and Amorphous Calcium Sulphate (ACS) [18][19][20] are also poorly understood. The properties of ACC clearly depend on how it is prepared, 9,21-24 and Gebauer et al. 23 refer to 'protovaterite' and 'proto-calcite' forms of ACC, which * To whom correspondence should be addressed although amorphous have NMR and EXAFS spectra that have (broadened) features in common with vaterite, and with calcite, respectively. Vaterite and calcite are two of the crystal polymorphs of calcium carbonate.Experimental data such as XRD can clearly distinguish between large single crystals and liquids, but as we have known since Scherrer's work a hundred years ago, 25 as the size of crystallites decreases, the width of the Bragg peaks in the structure factor S(k) increases. Finite size effects give a peak width ∆k ≈ k/n, for a crystallite n lattice spacings across. For n 10, the peak is so broad that it is essentially as broad as features in the S(k)'s of liquids, and so XRD is not be able to distinguish between a liquid or glass, and a state made of very small crystallites. In computer simulations we can circumvent the problem this causes in identifying a state, as there we know the exact positions of all molecules, in real space, and so have much more information than is contained in an XRD pattern.Here we use computer simulation to study crystallisation in microscopic detail, in a simple model: the Gaussian Core Model (GCM). 26 In the GCM, molecules interact via the spherically symmetric potential v(r) = ε exp[−r 2 /σ 2 ], where the parameters ε and σ have dimensions of energy and length, respectively. This is a simple mod...

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Nanoscale Structure and Structural Relaxation inZr50Cu45Al5Bulk Metallic Glass

Cited by 187 publications

References 42 publications

Dynamics and Geometry of Icosahedral Order in Liquid and Glassy Phases of Metallic Glasses

Dynamics and Geometry of Icosahedral Order in Liquid and Glassy Phases of Metallic Glasses

Computational modeling sheds light on structural evolution in metallic glasses and supercooled liquids

State between Liquid and Crystal: Locally Crystalline but with the Structure Factor of a Liquid

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