Candidate Atomic Cluster Configurations in Metallic Glass Structures

Miracle, D.B.; Lord, Eric A.; Ranganathan, S.

doi:10.2320/matertrans.47.1737

Cited by 66 publications

(41 citation statements)

References 36 publications

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“…The most stable glasses represent 4 values of R, including 0.710 for CN = 9 structures; 0.799 for CN = 10 structures; 1.116 for CN = 15 structures; and 1.248 for CN = 17 structures [33,61]. Again various binary system alloys produced in the present work are not glassy.…”

Section: Discussionmentioning

confidence: 86%

Role of different factors in the glass-forming ability of binary alloys

et al. 2014

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International audienceIn the present work, we discuss the glass-forming ability of various binary alloys in which the glassy phase was not formed even by melt spinning technique with high cooling rate of the melt up to 1 MK/s (some consisted of partly glassy phase), though by commonly accepted guidelines, these alloys could be as good glass-formers as many other binary glasses. The alloys studied belong to binary systems with multiple eutectics; the constituent elements have a negative enthalpy of mixing, and a significant variability of atomic size differences is observed from system to system. The results indicate the necessity of taking into account simultaneously various factors influencing the glass-forming ability including melt fragility

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Section: Discussionmentioning

confidence: 86%

Role of different factors in the glass-forming ability of binary alloys

et al. 2014

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“…SRO features were thought to pivot on the existence of local icosahedral structures centered around solute atoms. Various idealized SRO configurations were presented in [46]. Schenk et al experimentally verified icosahedral short range order (ISRO) in undercooled liquids [9].…”

Section: Lightning Summary Of Numerous Current Approachesmentioning

confidence: 99%

Detecting hidden spatial and spatio-temporal structures in glasses and complex physical systems by multiresolution network clustering

Ronhovde

Chakrabarty

et al. 2011

Eur. Phys. J. E

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Abstract. We elaborate on a general method that we recently introduced for characterizing the "natural" structures in complex physical systems via a multi-scale network based approach for the data mining of such structures. The approach is based on "community detection" wherein interacting particles are partitioned into "an ideal gas" of optimally decoupled groups of particles. Specifically, we construct a set of network representations ("replicas") of the physical system based on interatomic potentials and apply a multiscale clustering ("multiresolution community detection") analysis using information-based correlations among the replicas. Replicas may be (i) different representations of an identical static system or (ii) embody dynamics by when considering replicas to be time separated snapshots of the system (with a tunable time separation) or (iii) encode general correlations when different replicas correspond to different representations of the entire history of the system as it evolves in space-time. Inputs for our method are the inter-particle potentials or experimentally measured two (or higher order) particle correlations. We apply our method to computer simulations of a binary Kob-Andersen Lennard-Jones system in a mixture ratio of A80B20, a ternary model system with components "A", "B", and "C" in ratios of A88B7C5 (as in Al88Y7Fe5), and to atomic coordinates in a Zr80Pt20 system as gleaned by reverse Monte Carlo analysis of experimentally determined structure factors. We identify the dominant structures (disjoint or overlapping) and general length scales by analyzing extrema of the information theory measures. We speculate on possible links between (i) physical transitions or crossovers and (ii) changes in structures found by this method as well as phase transitions associated with the computational complexity of the community detection problem. We briefly also consider continuum approaches and discuss the shear penetration depth in elastic media; this length scale increases as the system becomes increasingly rigid.

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“…The topology of these clusters has been analyzed. 17 These clusters are representative local structural elements, but to describe an atomic structure, we must also show how these clusters are arranged in space. …”

Section: Short-range Structure: Relative Atom Size and Cluster Formationmentioning

confidence: 99%

A Physical Model for Metallic Glass Structures: An Introduction and Update

Miracle

2012

JOM

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For many years, the atomic structure of metallic glasses eluded a simple physical description. Inspired by the efficient filling of space with atoms of different sizes, a model has been developed by constructing efficiently packed atomic clusters and then efficiently filling space with these clusters. This model gives a simple physical picture of the origin of short-range and mediumrange order in metallic glasses, and also gives quantitative agreement with measurements that span length scales from nearest-neighbor atoms to global properties. A brief outline of the development and application of the efficient cluster packing model is given. Recent modifications to this model and remaining questions that form the basis of continued work are described.

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Candidate Atomic Cluster Configurations in Metallic Glass Structures

Cited by 66 publications

References 36 publications

Role of different factors in the glass-forming ability of binary alloys

Role of different factors in the glass-forming ability of binary alloys

Detecting hidden spatial and spatio-temporal structures in glasses and complex physical systems by multiresolution network clustering

A Physical Model for Metallic Glass Structures: An Introduction and Update

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